Dec

26

With direct application to speculation (featuring VC's):

You've (Likely) Been Playing The Game of Life Wrong

The world is not Normal.

Dec

19

Often when I listen to specs I hear "off-topic" book recommendations. Examples:

"The most important book to do with trading is Secrets of Professional Turf Betting by Robert Bacon" — The Chair. A book about parimutuel horse betting.

"The most important book to do with the stock market is Horse Trading by Ben Green" — A game theorist & friend of The Chair. A book about selling horses

"I can find new trading strategies on almost every new page (Thinking Fast and Slow by Daniel Khaneman)" — The Chair's Brother (Mr. Roy Niederhoffer). A psychology book

"Our entire investment philosophy is based off this book (Snow Crash by Neal Stephenson) — Fred Wilson of Union Square Ventures, a Tier 1 VC firm. Its a sci-fi book.

"One of the most important things you can learn todo with investing is creative writing" — Jeffrey Hirsch. Not a book but still an off-topic research recommendation.

I have never regretted reading an "off-topic" book. Any more of such recommendations?

Nils Poertner responds:

Coaching Plain & Simple, by P. Szabo, D. Meier (book about learning - how to coach oneself in a way)

Asindu - what books to get rid off, to burn, what is an obstacle in your life is also relevant. Early 2008, I visited a French friend on Lehman trading floor in London. V nice guy, senior analyst for their credit models, high IQ 130 plus, bit gullible though. He was surrounded by over 20 books of advanced math on either side of his desk. I had the urge to get a huge sledgehammer and whack down the books…you know.

Larry Williams suggests:

Zurich axioms. A must read.

Peter Ringel agrees with Larry:

I have them on my wall. Besides some of the lists by Vic, Larry, Adam Grimes and some other. Valuable.

And did you find the Daily Speculations booklist?

Asindu Drileba writes:

Yes. I forgot about Zurich Axioms. Thanks. This Daily Speculations list is good, I actually wasn't aware of it.

Nov

28

Anyone have any favorite good luck charms/rituals to help with trading results?

Peter Ringel writes:

some of the old floor traders, we had on this list, reported how superstitious some of the traders were. Cloths, bathroom time…

Asindu Drileba comments:

Lucky charms may sound delusional but they are actually more common than we think. They are more like placebos. I take pill X, my headache goes away. (But pill X is made from wheat flour and a bitter "filler" and has exactly zero pharmaceutical contents, yet it works).

Have you ever pushed the button that opens the door of an elevator? Well, those buttons are completely fake! Elevator doors are pre-programmed to open and close at hard coded intervals. Pushing the button does nothing. They simply exist to give people a sense of control.

Nils Poertner writes:

To have a strong belief one can learn (from mkts or others) is a good start.
ie allowing for mistakes to happen, not fretting them. (many cultures are guilt-ridden, like the German culture on so many fronts. All it takes is sometimes to muster up enough courage and learn from mistakes and don't judge).

Zubin Al Genubi offers:

I'm reading Kidding Ourselves, Hidden Power of Self Deception, by Hallinan, in which he describes real physical and psychological effects of psychosomatic causes such as death, hallucinations. You see what you want to see. You are and become what you believe yourself to be. It affects health, performance, money. He also describes how a feeling of lack of control can be debilitating and even deadly. Some feel a lack of control in that they don't control the market, but one can easily (physically at least) click the keys to buy and sell any time.

From scientific studies: Our results suggest that the activation of a superstition can indeed yield performance-improving effects.

Nov

21

Yesterday's range in VIX was one of the widest & wildest one I have seen in a very long time that happened without any major news. Wednesday close to Thursday low 18% decline followed by 46% rally to the day's high. Is there anyone who can check the occurrences in the past and how SPX traded in the following days of such a massive range explosion?

Asindu Drileba responds:

The Chairman's book, Practical Speculation, has a detailed analysis of the multivariate relationship between the VIX and the SPY. Unfortunately I forgot the page, and I am currently not close to my copy. [see pages 107-110] But it has something to do with how the fluctuations around the average of the VIX affects the SPY.

Paolo Pezzutti does some counting:

#VIX +11.71% at 26.43
Highest close since 24 April
Since 2020 VIX>26 has occurred 290 times.
After 4 days the Emini S&P Futures:
+27.01 pts Mean, 63.4% Wins, 1.63 Profit Factor

Larry Williams cuts to the chase:

Vix goes up when stocks go down they are inverse of each other—no magic there are all.

Nov

10

The more goods cost, the more money visa makes since the fees they charge Issuing banks & acquiring banks are based on a percentage basis. So, higher prices (inflation) –> better predicted revenues for Visa? Inspired by a nice documentary on the history of VISA.

I wonder what the best indicator for inflation would be for testing this? CPI? Oil?

Cagdas Tuna writes:

I was thinking as to find a similar indicator for economic slow turn, spending cuts. It came to my mind to follow sales slips. I live in Malta which is a very tech friendly country for spending habits such as Apple/Google Pay availabilities, many digital banks access etc. I often asked if I need a receipt that I usually don’t. It depends for every country but if there is a rule for stores/restaurants to keep at least a copy for each transaction then it might be the indicator to follow. It might be used for inflation as well but of course needs detailed information.

Pamela Van Giessen comments:

To the best of my knowledge, merchants are not required to keep receipts. We track each sale but it will be the credit card processor or platform such as Square that holds the credit card or Apple or Google pay receipts. I can’t imagine that merchants would be willing to share their sales data. I know I wouldn’t.

Visa doesn’t care how much goods cost. They get their nearly 3% processing fee (+ .10 or .15 per transaction) whether there are 20 transactions for $100/ea or 40 transactions for $50/ea. In fact, they make more $ on a higher volume of transactions.

I don’t think tracking Visa or MC, etc could be a meaningful prediction of inflation as all the credit card companies continuously fight for market share. Note that they all send out multiple credit card offers to everyone all the time. Then, you have a store like Costco that only accepts their credit card (Citibank).

Additionally, there are people who use primarily cash. Those $ would be left out. You may say that cash use is low, and maybe it is. What I can tell you is that today at a market 80% of my sales were cash and that was likely the case for all the other merchants at this market. Older people especially use cash a lot. Just like drug dealers.

I have a theory that the cash economy is much bigger than everyone thinks. Insight into that might be more interesting.

Carder Dimitroff responds:

After considering Panela's cash sales point, I remembered that several companies required customers to switch from credit card payments to bank transfers. Additionally, several small establishments offer incentives for customers to pay in cash. They may be attempting to simplify their accounting and tax reporting. I do know that the federal government has immediate access to individual credit card transactions.

Pamela Van Giessen adds:

I thought it was the Fed that used to report on aggregated credit card data.

The other challenge with using credit card financials is that the credit card processors raise their % cut all the time. This is not due to actual inflation; it is due to them having a government protected moat that allows them to take more and more whenever they want because merchants are stuck with the whole system and consumers don’t realize that they will pay for the service — in increased prices. Every time Square, PayPal, etc., send me notices that they will be increasing fees, I increase my prices. I guess that is a kind of proxy for inflation but it’s a lousy sort of financial market induced inflation not based on anything more than their desire for more profits. I am all about free markets but the credit card processing biz is not even close to a free market.

The government using credit card processing to surveil us may be one reason I see more and more people using cash.

Larry Williams suggests:

Stock market is good predictor of inflation.

Nov

9

Came to our financial firm 2007 and gave a 100 page presentation full of bullet points and cartesian logic (why housing boom will last). Either 3,5, or 9 bullet points per page.

At the end of the presentation I was tempted to go over to the presenter and ask him "why do you love your wife? (I didn't). The answer might have been bullet points.

Pamela Van Giessen writes:

Michael Korda tells in his memoir, Another Life, of the time that Simon & Schuster hired probably the same prestigious consulting firm to study how to improve revenues/profitability. Prestigious consulting firm (after taking the prestigious consulting firm fee) told the publishing company that they should publish more bestsellers.

Laurel Kenner comments:

I bet the prestigious firm concluded with ‘Key Takeaways’ as a final insult to the intelligence of the client.

Asindu Drileba writes:

I heard that people pay consultancy firms not for their knowledge, but for the fact that executives use them as a scape goat. If an executive wants to pursue policy X. They simply hire a consultancy to recommend policy X. If policy X ends up as a disaster (legally, morally or financially). They can simply say "Policy X was an idea from XYZ consultancy", we had nothing to do with it.

Peter Ringel adds:

a variation of this are fighting owners/ partners about policy. If decision pipelines are blocked, external council is used. Like a neutral arbitrator. I think, these are the main situations externals are used. Usually a good reason to short the entity, especially outside of markets. If they don't have the capability to decide and act on strategy in-house, it‘s a red flag.

Henry Gifford responds:

Even better is hiring a licensed engineer to instruct everyone to do something stupid that they know won’t work, so everyone who did as the engineer decided is blameless.

Jeff Watson offers:

A consultant is a person who knows 1000 ways to make love to a woman…..but he doesn’t know any women.

Oct

21

AV1 is a new video compression format that may reduce the size of a video file by up to 50%. The big advantage is that videos will be up to half the size, with the exact same image and audio quality.

Two big consequences may ensue (when AV1 is fully adopted):

- Internet bills for streaming Netflix will reduce.
A 2 GB movie will only cost 1 GB from the perspective of a customer paying their Internet Service Provider. So more frequent subscriptions?

- Netflix will cut its bandwidth costs by 50%. So the profit margin (respective to bandwidth costs) will go up by 50% if users fully adopt AV1?

Currently, AV1 is only available on select hardware chips (listed table on Wikipedia) Maybe as users get new devices, use of AV1 will grow. This will likely happen gradually over several years (maybe half a decade). But an obvious winner would be Netflix & YouTube (Google Stock). Maybe bandwidth is so cheap it won't make a dent in the business revenues? But all major companies seem very enthusiastic about implementing AV1. Maybe bandwidth has it's (less talked about) variant of Moore's law. Where after a few years it gets easier to move stuff around the internet.

Cagdas Tuna wonders:

How many nuclear plants we need to feed that endless “technology”?

Nils Poertner asks:

How would you express this into a trade idea, Asindu? I find it easy to put ideas into a trade - it encourages deeper thinking and gives a feedback when wrong. eg, I was bullish housing London property 2007, but short-term it didn't really work out at all! longerterm yes. it was fuzzy thinking of my behalf.

Asindu Drileba answers:

Going long $NFLX since the business is largely about streaming video. The same pattern occurred in Tesla when the cost of efficient batteries dropped by like 90%. So margins automatically go up. (in theory) Tesla could have still gone under due to debt or something else. So, of course it may may fail (most likely)

Another big draw back is that such "qualitative" insights cannot be tested in the past. Maybe a good analogy would be to go long Starbucks $SBUX if you think the price of coffee wil drop the next 5 years by 50%.

So the ideas may be generalized to:

- Find key Ingredient company X uses in thier products

- Find out if the drop in key ingredient's price over 5 years improves profit margin over X years -> positively impacts stock prices.

This general idea, may then be tested across several industries for example:

- MacDonalds (drop in price of beef)

- TSMC, ASML, INTEL, NVDA (drop price of silver) as silver is very essential in chip manufacturing.

Hopefully testing this across multiple industries on different historical accounts may yield some consistent patterns.

Nils Poertner responds:

Good to write it down in a trading journal and look in a few months what happened. Started writing hand-written letters to friends now. In our digital age, everyone incl me, is going for speed, but deeper thinking - also quality in thinking /research is underrated. Intuitively speaking - we are prob getting some unexpected moves coming, as well.

Oct

19

In Casino Royal (2006) there is a speculator called Le Chiffre. He would manage money for war lords & other "underground" clients. He would take positions in markets, and then "manipulate them". For example in this clip, he takes a short position in an airlines company, then later bombs a plane belonging to it.

This year, I am starting to think that Le Chiffre is real. Someone opened a crypto account on Hyperliquid (decentralized exchange) and made an $88m profit from short positions that very day.

Cagdas Tuna responds:

Good catch! I have been reading these whales news since March-April 2025 mostly tied to Trump’s policy shifts. It is not difficult to guess who those Le Chiffres might be related to!

Peter Ringel writes:

I wanted to place 1 Nov in my calendar - as a new Mkt Risk date based on Trumps post. Only to realize, I placed this date regarding tariffs before. This makes this old news to some degree. And all of this is potentially an overreaction / a play.

Ed. - lagniappe: Forget Sean Connery, Watch James Bond Make His Real Debut on TV

Before Connery registered his license to kill in the 1962 hit Dr. No, millions of viewers were introduced to Barry Nelson’s “Bond, Jimmy Bond” in a 1954 episode of the CBS anthology series Climax! The show’s producers secured the rights to adapt Ian Fleming’s just-published debut Bond novel, Casino Royale, during their first season.

Since the Climax! version of Casino Royale is only 50 minutes, the plot has obviously been shortened considerably. And yet, if you’ve read the book or, more likely, seen the 2006 movie version that launched Craig’s Bond career, you’ll recognize the basic narrative, even though none of the familiar 007 flourishes are in place. In fact, Nelson doesn’t enjoy “00” status at all — he’s merely identified as a “Combined Intelligence” agent who is tasked with competing head-to-head against the mysterious Le Chiffre (Peter Lorre) in a rousing game of baccarat.

Jeff Watson does some research:

James Bond, the complete list…there are more than you think:

Please list every James Bond on film, TV, and radio. Grok: Alright, here goes-starting with the big-screen Bonds: Sean Connery, George Lazenby, Roger Moore, Timothy Dalton, Pierce Brosnan, Daniel Craig. Then David Niven in the 1967 spoof Casino Royale. On TV, there's Barry Nelson from a 1954 Climax! episode of Casino Royale. Radio Bonds? Bob Holness in a 1956 BBC Casino Royale adaptation, Tom Hiddleston in a 2014 Heart of the Matter series, and Toby Stephens in various BBC radio dramas.

Oct

12

We use quantitative tools - "counting" - to measure and analyze markets, and I enjoy coming across scientific measurements that are new to me and also amazing in scope, such as the sverdrup. The sverdrup is a unit describing the volume of water transport in ocean currents. One sverdrup is a volume flux of one million cubic meters per second (1 Sv = 10^6 m^3 per second). Named after Harald Sverdrup.

From the web:

The strongest ocean current measured in sverdrups is the Antarctic Circumpolar Current (ACC), the largest and most powerful current system on Earth. The ACC is a wind-driven current that flows clockwise around Antarctica, uninterrupted by landmasses.

Measurements of the ACC's volume transport vary, but all figures show it is in a class of its own:
Estimates of the ACC's mean transport range from 100 to over 170 sverdrups (Sv). One study found an average transport of 173.3 Sv through the Drake Passage, the current's narrowest choke point. To put this in perspective, this is over 100 times the combined flow of all the world's rivers.

The graphic shows how relatively narrow the Drake Passage is.

We certainly measure volume in markets. Are there specific flows and currents? Choke points?

Asindu Drileba writes:

In a book recommended by The Chair, This is the Road to Stock Market Success, the author mentions that (paraphrased), "When the trading volume of a stock changes by a large amount, yet the price doesn't move by much, it is time to get out of the market."

Oct

7

Miscellany

October 7, 2025 | Leave a Comment

Asindu Drileba has been watching the Daily Spec calendar:

After being hammered in Aug, Orange did well in Sept. It transitioned to a positive day in the S&P 5/6 times.

Nils Poertner is getting wisdom from the classics:

The most certain sign of wisdom is cheerfulness.
- Michel de Montaigne

some type of cheerfulness def relevant for us in markets /trading - in particular when social moods go south / ppl fall for chatboxes (overuse it !) and confuse with reality etc.

Big Al is going for history:

This is the audio version:

The History of the United States Navy

but I am also watching the video version for free on Amazon Prime. The author:

Craig L. Symonds

Craig Lee Symonds (born 31 December 1946, in Long Beach, California) was the Distinguished Visiting Ernest J. King Professor of Maritime History for the academic years 2017–2020 at the U.S. Naval War College in Newport, Rhode Island. He is also Professor Emeritus at the U. S. Naval Academy, where he served as chairman of the history department. He is a distinguished historian of the American Civil War, World War II, and maritime history. His book Lincoln and His Admirals won the Lincoln Prize. His book Neptune: The Allied Invasion of Europe and the D-Day Landings was the 2015 recipient of the Samuel Eliot Morison Award for Naval Literature, and his book Nimitz at War: Command Leadership from Pearl Harbor to Tokyo Bay won the Gilder-Lehrman Military History prize.

Sep

11

Gappy (Giuseppe Paleologo) posted this on X, and it prompted me to wonder if a power law would apply to the skill differences and win rates of tennis players viz their rankings. Need to find some easily accessible data for that. And of course, how PLs apply to the distribution of returns with the S&P 500 in a given time period. But could it be predictive?

Power Laws in Economics and Finance
Xavier Gabaix, Stern School, NYU

A power law (PL) is the form taken by a large number of surprising empirical regularities in economics and finance. This review surveys well-documented empirical PLs regarding income and wealth, the size of cities and firms, stock market returns, trading volume, international trade, and executive pay. It reviews detail-independent theoretical motivations that make sharp predictions concerning the existence and coefficients of PLs, without requiring delicate tuning of model parameters. These theoretical mechanisms include random growth, optimization, and the economics of superstars, coupled with extreme value theory. Some empirical regularities currently lack an appropriate explanation. This article highlights these open areas for future research.

Asindu Drileba writes:

One of the funniest commodities traded in Uganda (my country) is Vanilla. The price fell from, $156 per kilo, to $1.14 per kilo. A -99% drop during the 2020 covid lock down.

Vanilla cultivation is special in that it can't be farmed mechanically.

- It only flowers once a year
- The flower is only open for 24 hours in one year
- It can only be hand pollinated
- If you miss those 24 hours in one year, your done, wait for the next season.

So a lot of the cultivation is by small "artisanal" farmers.

Madagascar produces close to 80% of the world's vanilla. All other countries produce the rest. So its a power law distribution. The smallest hiccup in Madagascar can cause the vanilla price to skyrocket or drop.

I think power laws outside prices (like supply chains of vanilla) can be used to predict what asset, commodity or instrument will be volatile (large moves both up & down). I think these underlying setups in assets are what echo as power law distributions into prices.

Sep

8

Dutch scientist Christiaan Huygens found in the 17th century that larger pendulum clocks will sync smaller ones.

Video by Veritasium: The Surprising Secret of Synchronization

Pendulums in the human world = our various belief systems (which are sometimes in competition to each other and go deep). Two examples perhaps: in finance: a trader has religious reasons why he /she does not think he deserves the STELLAR gains. Ways are found to turn accumulated gains into a loss! in health: why do some ppl stay sick and others recover miraculously against all odds?

Zubin Al Genubi writes:

The Kuramoto mathematical model describes synchrony in networks. The line between order and randomness occurs at the phase transition when the network nodes synchronize.

Building on Kuramoto's model, the Watts and Strogatz model makes testable predictions about interventions most likely to trigger cascades.

In small world network terms there are "vulnerable clusters" in the market. In market terms the vulnerable clusters are weak hands, funds faced with margin calls, or fund hitting a stop losses. Obvious 2d points or tipping points are stop points at prior lows. If a vulnerable cluster is close to the second tipping point, it can ignite a cascade.

Nils Poertner responds:

Mathematicians often find something which ordinary people know intuitively. 2 more examples:

1. Five teenagers bully a victim. Knock-out the strongest in the group and the rest will fall too (big bully was the dominant pendulum, trumping the small ones).

2. When the most valuable firm(s) in an index suddenly struggle (NVDA?), it often means bad things for wider index.

Asindu Drileba adds:

I found the same pattern in the "Complex Systems" community. An example in Secrets of Professional Turf Betting: The idea of "copper the public opinion" & "principle of ever changing cycles" are an intuitive description of the minority game & El farol Bar problem in complex systems. Statistical arbitrage is almost exactly what Robert Bacon describes as a "dutch book."

In Neil Johnson's Simply Complexity, he derives an insight that currency traders have (knowing what currency is "in play") using graph theory.

I think Simply Complexity is a very good book for speculators, since it uses accessible analogies and no complicated math. The book has a lot of analogies regarding the market. The most relevant section for Specs would be, Chapter 4: Mob Mentality (I however enjoyed the entire book).

A Few excerpts:

The bar-goers who tend to shift opinions about whether to go with history or against it, tend to lose more and hence eventually change their p value.

This reminded me of people that both go short & long in the market (I am long only). P is the probability of an event happening.

Figure 4.3 from the book and its caption:

We are naturally divided. The final arrangement of a collection of people, in the case of a bar where the comfort limit is around half the number of potential attendees. This shows the emergent phenomenon of a crowd who think that history repeats itself, and an anticrowd who think that the opposite will happen. Hence the population polarizes itself into two opposing groups. This polarization of the population represents a universal emergent phenomenon. It will arise to a greater or lesser extent in any Complex System involving collections of decision-making objects such as people, which are competing for some form of limited resource.

The figure is similar to the Arc Sin law of PnL. Something that appears in Ralph Vince's book The Mathematics of Money Management and Nassim Taleb's Dynamic Hedging. Unfortunately, I don't have a good intuition on the Arc Sin law of PnL.

Sep

3

I post these wondering what Carder D thinks:

Big Tech’s A.I. Data Centers Are Driving Up Electricity Bills for Everyone
Electricity rates for individuals and small businesses could rise
sharply as Amazon, Google, Microsoft and other technology companies
build data centers and expand into the energy business.
14 August, 2025

AI Boom Reshapes Power Landscape as Data Centers Drive Historic Demand Growth
Monday, March 3, 2025

The power industry was once considered slow-moving and perhaps even boring. That is no longer the case as technology has expanded and power demand projections skyrocket. New reports released by analysts at Enverus and Deloitte are examined to provide insight on what’s likely to evolve in the power industry over the coming year and beyond.

Carder Dimitroff responds:

I believe these articles present several issues that could benefit investors:

1) Transformers (not pole transformers). The queue for new transformers is long, and about half are manufactured offshore. Data centers need transformers as do new power sources.

2) Gas turbines. Same situation as transformers. For efficient turbines, the queue is about 5 years.

3) Solar panels. Those who previously invested in solar will see their ROIs grow faster than they expected.

4) Retail consumers. They will see their gas and electric utility bills grow as they pay for higher costs of energy and subsidize infrastructure costs to support new loads.

5) New manufacturing. Several geographical options will present better opportunities than others, as the cost of power is regional and seasonal.

6) Forget new nuclear as a near-term solution.

Asindu Drileba asks:

What do you think about nuclear fusion? Is it really close? The joke is that nuclear fusion has always been ready in 5 years for many decades. But I recently heard Chris Sacca (one of the best VCs ever, made over 250x for his entire fund), mention it is genuinely close and that his new fund, Lower Carbon existing partly to capture the incoming advancements in nuclear fusion.

Carder Dimitroff replies:

Today, nuclear fusion is a science project. Keep in mind that fusion requires operating temperatures of over 100 million degrees (at this level, the distinction between Fahrenheit and Celsius is irrelevant). Producing bulk power from this technology is more than ten years away. At these temperatures, it's unlikely they will be operating near population centers.

Aug

31

George Pólya came up with the term Inventor Paradox.

Basically, if one thinks about a problem more deeply, something else may open up. And one can achieve extraordinary results! Plenty of examples in finance, engineering, medicine.

Steve Ellison writes:

From the Wikipedia link about the inventor's paradox:

When solving a problem, the natural inclination typically is to remove as much excessive variability and produce limitations on the subject at hand as possible. Doing this can create unforeseen and intrinsically awkward parameters.

Very interesting idea with applications in many fields. As one example, I recently told my daughter, who is a partner at Boston Consulting, that I was reading a book about strategy by a professor at Harvard Business School. She told me, "Boston Consulting literally wrote the book on strategy": Your Strategy Needs a Strategy.

I ordered that book and so far have read the first chapter. One of the key questions is how predictable the business environment is. Another is, how much can you influence the environment? "Classical strategy" as taught in business schools generally assumes that the environment can be forecast and that the company has very limited influence over it. A case study was the Mars candy bar company.

But if you cannot forecast the environment, a very different approach is called for, with heavy emphasis on learning and iterating. And if you can in fact shape the business environment, you might want to find some partners and create an ecosystem.

As a footnote, the book I was originally reading, which I also found informative, was by Richard Rumelt: Good Strategy, Bad Strategy.

Asindu Drileba offers:

Optimize the Overall System Not the Individual Components, interview given by Edwards Deming. Excerpts:

The results of a system must be managed by paying attention to the entire system. When we optimize sub-components of the system we don’t necessarily optimize the overall system.

Optimizing the results for one process is not the same as operating that process in the way that leads to the most benefit for the overall system.

Applied to markets:

- It's easier to do well on the S&P 500 index (the general market), than do well in a single stock (picking).

- Attributed Mark Spitznagel, we should judge the buying of far OTM puts based on how they help the entire portfolio. Not the individual PnLs of buying the far OTM puts.

- Attributed to Roy Niederhoffer, many traders turn off trading strategies once they start loosing money, but different trading strategies make money at different times.

Aug

17

Concerning the transitions of colour, on the daily spec website. The chair recommended The Punnett square as a research topic. This was the best video I could find. It's amazing how he broke down the essentials in just 6 minutes:

Genotype, Phenotype and Punnet Squares Made EASY!

Big Al offers:

Great vid on Markov, and Markov chains leading to LLMs:

The Strange Math That Predicts (Almost) Anything - Markov Chains

Aug

7

The best data science course I have ever watched. In fact, probably the best data science course ever made is Prof. Yaser Abu-Mostafa's "Learning from Data" at Caltech. I am not exaggerating, and if you think I am, just read the comments section from the first video of the course The Learning Problem — its almost exclusively high praise.

This course is really old, as its from 2012. I watched it probably in 2017 or 2018. But its still very relevant today. Why its relevant today? Most courses focused on describing techniques that were popular then, but later became irrelevant. For example, GANs were replaced by Diffusion Models and core ML Architectures have shifted to Transformers.

Prof. Yaser's course is different because he covers Theory, Techniques and Concepts (most books/courses only describe ML algorithms/Techniques or how to use features in python libraries).

- Theory, refers to mathematical descriptions of ideas like "Is learning feasible" for your problem or dataset?, "Training vs Testing", "The theory of generalization" and the "Bias-Variance trade off".

- Techniques, refers to actual ML algorithms like Neural Networks, SVMs.

- Concepts, describes auxiliary things that are not really Machines Learning but useful to understand well. Like how to interpret/deal with Error & Noise, Sampling of data.

The full course is free.

I also recently came across a comment about a book he wrote to accompany the course which made me remember him: Learning From Data.

Aug

1

I interpret the "Vig" as the collective term for:

1) bid-ask spread (difference in prices between buying & selling) due to market makers
2) transaction fees (for limit & market orders) charged by the exchange
3) slippage (an instrument is more expensive the deeper in the order book you go) due to how liquid an asset is.

Possible solutions for each?
1) Can be fought with the exclusive use of limit orders instead of market orders.
"Be patient and you will have the edge", The Chair in, Practical Speculation — The fine art of bargaining for an edge
2) I noticed (at least in crypto markets) that the more volume you trade, the less fees you pay (on a percentage basis)
3) Restrict yourself to deep and very liquid markets.

Also, one technique is to trade as less often as you can (buy & hold). That way you will automatically pay less of all the three sources of Vig. I think this is so important as I often found many "edges", then accounted for the vig and they often became loosing strategies.

Big Al writes:

I would also add "opportunity cost" as part of the "Meta Vig" (MV), i.e., the total costs associated with trying to trade the markets. The MV would also include the negative effects of cortisol on the human body.

Henry Gifford suggests:

I think two good steps are to ask others what the big is, and to try to calculate it yourself. Both exercises will no doubt be educational. A few times over the years I have asked horse bettors what the big is, but none seemed to know. As for calculating yourself, one hopefully will learn how much it varies by, and maybe also gain insight into hidden vig.

Steve Ellison responds:

There is no free lunch with limit orders because of adverse selection. Sooner or later, you will place a limit order on a security that simply moves up and never looks back. It would have been your best trade ever, had you actually been filled. In the opposite scenario, for example when I bought Coca-Cola in 1998, and it was already down 25 percent by the T + 3 settlement date, you will of course be filled.

Studies of retail investing accounts have shown a negative correlation between number of transactions and investment returns. In one study, accounts that had been inactive for 18 months because their owners had died, and their estates had not been settled, outperformed the vast majority of their retail account peers.

Peter Ringel writes:

Generally, the lower you go ( smaller time frame - smaller scope of the trade ) the larger the relative Vig costs. a subclass of opportunity costs is spent time of (daily) preparation. my required prep is nearly the same over many time-frames - but the scope of a trade is way lower for lower time-frames. in cash equities, the resale of your order-flow by your broker to some HF shop can be counted as Vig too. is this a common practice in option markets too? Yes, the Vig greases the fin-industry, but it is mostly unavoidable paying / avoiding the Vig does not lead to success or failure in mkts IMHO.

Vic simplifies:

just trade once a quarterfrom long side

Zubin Al Genubi comments:

The biggest vig is capital gain taxes. The richest people in the world hold their single company stock 10000x and realize no gain. Its very hard to beat a long term hold.

Jul

22

Big Al offers:

Very nice Veritasium vid on randomness and information:

What is NOT Random?

Asindu Drileba likes a new interview:

I learned about Gappy Paleologo from this list. He has a new interview on a Bloomberg podcast. In it, he talks about:

- Why he suspects Astrophysicists make good quants
- Why AI can't fully take over trader's jobs (in principle)
- What makes a "good quant"

Jeff Watson is following the floor traders last stand:

Old-School Floor Traders Finally Get Their Day in Court Against CME
Trial opens in the Chicago plaintiffs’ long-running lawsuit claiming harm from the launch of electronic markets

The plaintiffs, who estimate that they are owed about $2 billion in damages plus interest, say the company broke its promises to them when it opened a data center for electronic trading that effectively doomed the old trading floors. CME has called the lawsuit baseless.

A spokeswoman for CME declined to comment. The company repeatedly tried to get the suit thrown out, but failed each time.

The lawsuit, filed in 2014, has dragged on so long that one of the original plaintiffs has died. Hundreds of former floor traders could be affected by the outcome. The trial, being held at a county courthouse in downtown Chicago, kicked off Monday with jury selection. It is expected to last several weeks.

Jul

2

I recently came to the conclusion that a lot of quants come from the field of Operations Research. I noticed a paper of MFM Osbourne was also published in an Operations Research Journal. After a bit of research with in this space I came across an approach called "Metaheuristics."

I think its very relevant to this list. Mr. Jim Sogi once described The Chair's approach to thinking as "Neiderhoffian thought." E. O Wilson called it "Consilience." "Metaheuristics", "Neiderhoffian Thought" and "Consilience" are all related, in that, they champion the idea that we can come across novel solutions via thinking in analogies & metaphors.

There is a table of curated Metaheuristics. It has algorithms inspired by Ants, Buffaloes, Rivers, Art (yes, like paintings), Squirrels, Wasps and Korean TV Shows (Squid Game Optimizer).

The gem I am talking about is a book called Advanced Optimization by Nature-Inspired Algorithms, by Omid Bozorg-Haddad. The book has 15 Algorithms. Notable mentions are:

- League Championship Algorithm (Inspired by sports)
- Shark Smell Optimisation (Inspired by how sharks use their sense of smell to find prey)
- Ant Lion Optimizer (Inspired by how larvae of Antlions entrap prey)

I consider the book well written. Each of the 15 algorithms are described in 4 ways. For example, the Ant Lion Optimiser algorithm:

1) It's done in plain English to give you a verbal understanding of what the algorithm does.

2) It's done in mathematics so you can know how to better understand the algorithm in math notation.

Example of math description of ant-lion algorithm

3) It's described using flow charts.

4) It's described in pseudocode so you can better know how to code the algorithms up.

All the 15 algorithms are described in this way. This was something I appreciated so much.

Jun

30

sp and bonds 1-day changes similar to Mendel's independent moves to next generation. when an event occurs that throws one of pair of bond or sp off, treat it as a mutation.

Punnett square

The Punnett square is a square diagram that is used to predict the genotypes of a particular cross or breeding experiment. It is named after Reginald C. Punnett, who devised the approach in 1905. The diagram is used by biologists to determine the probability of an offspring having a particular genotype. The Punnett square is a tabular summary of possible combinations of maternal alleles with paternal alleles. These tables can be used to examine the genotypical outcome probabilities of the offspring of a single trait (allele), or when crossing multiple traits from the parents.

Asindu Drileba writes:

Orange (S&P Up, Bonds Down) and Green (S&P Up, Bonds Up)

Orange appeared 4 times. In 3/4 times, Orange transitioned to Green with an average point gain of 35.4 in the SPY.How long will this continue? I noticed the pattern last month, unfortunately I didn't "count" it. Was it around for longer periods of time?

Vic's X/twitter feed

Jun

23

Jarisch-Herxheimer reaction in medicine: A sudden and typically transient reaction (eg fever) that may occur within 24 hours of being administered antibiotics for an infection such as syphilis.

Application in financial markets? eg when a troubled stock sells off briefly after a new strategy or management is announced but the stock recovers after some 24-48 h carnage.

Asindu Drileba writes:

In The Education of a Speculator, Chapter 14, "Music & Counting":

Another frequent work I hear in the market is Haydn's Symphony No. 94 ("The Surprise"). The surprise is a simple fortissimo chord in the second movement, designed "to make the women jump." In a contemporaneous review of the work, a lyrical critic wrote:

The surprise might be likened to the situation of a beautiful Shepherdess who, lulled to sleep by the murmur of a distant Waterfall, starts alarmed by the unexpected firing of a fowling-piece.'

Two examples from currency markets:

1) Asia Currency crisis: When the Asian currency crisis of the 1990s was starting to manifest, IMF provided a loan to "stabilize" the economy. The currencies were stable for some time (the lull to sleep), then dropped by up to 80% in some Asian countries (the jump).

2) The Lebanese pound: The Lebanese pound remained very stable. Close to a flat line for 13 years (the lull to sleep), Then in Jan 2023 it dropped by 90% (the jump).

Equity Markets: "The best predictor that a company will go bankrupt, is stable income" — Nassim Taleb. Unfortunately its hard for me to get data on delisted (bankrupt) stocks so I can't test this. But the logic behind this reasoning is that, to provide stable income, corporations often optimise via unhealthy accumulation of debt, relying on a single supply chain (Apple & China), relying on a few big enterprise customers (Palantir & US Government).

While this optimisation makes it easier to milk profits that make a corporation look "stable" (the lull to sleep), it makes them more prone to catastrophic failure (the jump). A single customer canceling your service, trump tariffs on a single supply chain partner or debt unable to be paid may lead serious issues.

Jun

18

What exactly means this quote? I read of it years ago on a book about Medallion Fund but never understood if I got the meaning correctly.

We're right 50.75% of the time…but we're 100 % right 50.75% of the time. You can make billions that way.

- Robert Mercer

Peter Ringel responds:

my guess: trend following systems can have 40% win rate and lower. Yet via expectancy these sys can be very profitable. Medallion though, would do HF stuff, less MoMo.

Michael Chekalin comments:

Mercer refers to the consistency of Medallion. In other words, they are “consistently” profitable in the 50% area, which through proper money management, risk/reward, etc, can be extremely profitable.

Asindu Drileba writes:

I think its a reference to the "law of large numbers." Suppose you noticed the market goes up 51% of the time on Thursday. (for the 100 Thursdays in your sample dataset) This means that you will also loose 49% of the time. If you decide for example to only place bets for the first 20 days, you might have a win rate of 0%. All bets of the first 20 days can fail.

But the model will still be correct since you can make money for the subsequent 51 days and the lose money for the next 29 days — thus playing the market for all the 100 days (20 + 51 + 29). So your win rate will converge to 51/100 which is the same 51% you identified in your sample. You have therefore acquired 100% of the edge. I think that is what he means when he says "we are 100% right 50.75% of the time."

Nils Poertner adds:

Some specs have a 10pc win rate and do really well. Friend of mine was early investor in ETH in size- but all other of his ideas didn't work out. His nick name was "Harbinger of Failure." Kind of like the joke: "I told my friends I want to become a comedian - and they all laughed. And then I became a comedian and no-one laughed anymore." I often think about him now.

Jun

11

One must admire the first guy to introduce Brownian Motion into a theory about speculation.

Louis Bachelier's Theory of Speculation: The Origins of Modern Finance

Asindu Drileba wrires:

If you like that, you may find Louis Bachelier's other book Sketches in Quantitative Finance interesting. It's very accessible as it has no complex math and describes many concepts in probability/statistics in a very straightforward way. In it, he say's for example that despite Martingale strategies looking lucrative, "no one has gotten rich by using this method."

Jun

3

I can't find any books from the 1700s. Big events like the Mississippi Scheme and the South Sea Bubble happened in that period. But I can't find literature from the 1700s of people describing markets then. Maybe they had PTSD from having their fingers burnt? I heard Newton never wanted anyone to mention "South Sea" around him. (he lost his pile in the investment)

Stefan Jovanovich responds:

Essai sur la Nature du Commerce en Général, by Richard Cantillon (1680s–1734)

During 1719 Cantillon sold Mississippi Company shares in Amsterdam and used the proceeds to buy them in Paris. Mississippi Company shares surged from 500 livres in January 1719 to 10,000 livres by December 1719; during the same period the prices in Amsterdam went from 400 to 7,000. The daily average spread is calculated to have been between 20% and 40%.

Carder Dimitroff suggests:

Empire Incorporated — The Corporations that Built British Colonialism, by Philip J. Stern

The book provides historical perspectives about British markets and corporate financing. It's not an easy read, but it is fascinating.

William Huggins writes:

there is a collection of "things written afterwards" about 1720 called The Great Mirror of Folly but its mostly moralizing tracts than a steely-eyed review of what went down. keep in mind the experience (a bubble in uk-fr-nl, all at the same time) had profound effects on the market for almost a century afterwards with the fr retreating from paper money and the british passing the bubble act which made it waaaay harder for anyone to raise capital. trading stock largely returned to being an insiders game until the 1800s. GMoF was recently published along with a pile of other primary docs by Yale U press:

The Great Mirror of Folly: Finance, Culture, and the Crash of 1720

I like the goetzmann treatment of 1720 from Money Changes Everything personally. He's got a couple of good recorded talks on it too. for those interested in institutional developments around markets and financial institutions in north america, I strongly recommend Kobrak and Martin's "Wall Street to Bay Street."

Steve Ellison offers:

Extraordinary Popular Delusions and the Madness of Crowds was written in 1841 by Charles Mackay. The first three chapters are devoted to the Tulip Mania, the South Sea Bubble, and the Mississippi scheme. The remainder of the book is about non-financial episodes of irrationality, including a chapter about plagues that I re-read closely in March 2020.

May

31

I was browsing the Daily Speculations archive and found this:

10 Things I’ve Learned About Markets, from Victor Niederhoffer

No. 11 is, "All higher forms of math and statistics are useless in uncovering regularities."

Define "higher form". To someone that has just learned basic arithmetic, basic algebra seems "higher form". Does The Chair maybe mean "PhD level" math? Or does he mean that basic "counting" is the only proper way to uncover regularities?

Fazil Ahmed responds:

I think Ralph Vince has explained well, copying from the post:

Certainly in a post-'08 world, quants are out of favor, and for good reason. Most anyone I know who DOES make money in the markets, does so with very simple, robust techniques. Having considered going to quant school, and studied a good deal of it, I finally came to the conclusion that they are simply working with "models." Models of how the world behaves. unlike hard sciences like Physics and such where you can perform a test, come back a year from now, perform it again and get the same results, you don't have this in financial modeling. And I think this is where the quants have fallen short. Models are NOT reality, and they never got down to the bedrock, the reality of what his game is about. Of course it had to fail, and in a large way, at some point. A good rule of thumb is that if I need a computer, if it isn't simple enough to do in my head on the fly in the foxhole after I have been awake for over 100 hours, I can't use it.

Larry Williams comments:

This gets down to there are hard questions: What is the capitol of Montana? Only one answer: Helena.

And soft questions: How many people are in Montana? Varies from hour to hour.

May

30

Perplexity says it best:

The U.S. population is projected to keep growing through the end of the century, mainly due to immigration, even as deaths begin to outnumber births after 203325. By 2055, the U.S. is expected to reach 372 million people, with net immigration as the primary driver of growth. In contrast, China faces a rapidly aging population: by 2050, about one-third of its population will be over 65, and the number of elderly will vastly outnumber children, creating an “inverted pyramid” demographic structure. This aging trend is expected to slow China’s growth and strain its social systems, leading some to describe China as “becoming a nursing home” by century’s end. Meanwhile, the U.S., thanks to sustained immigration, will remain younger and larger than it would be from natural increase alone.

Asindu Drileba writes:

Professor Bejan's constructal law guarantee's that China will go bust on a long enough time horizon. I attribute this to China's rigid political system. Like Daenerys Targaryen said, "Those that don't bend, will break." Professor Bejan's TED Talk.

William Huggins responds:

for entirely different reasons, both Daron Acemoglu (econ Nobel 24) and Peter Zeihan are also in the China-bear camp long term - the former due to hitting the limits of "growth under extractive institutions", the latter due largely to demography (even if his tone is alarmist). Dalio's indicators suggest the opposite but all his data comes from a demographic regime of pyramids, not chimneys or inverted pyramids so i'm not sure his forecast will play out.

May

28

Street smarts: how a hawk learned to use traffic signals to hunt more successfully

But what was really interesting, and took me much longer to figure out, was that the hawk always attacked when the car queue was long enough to provide cover all the way to the small tree, and that only happened after someone had pressed the pedestrian crossing button. As soon as the sound signal was activated, the raptor would fly from somewhere into the small tree, wait for the cars to line up, and then strike.

Easan Katir predicts:

Next iteration: the hawk will be pressing the pedestrian crossing button!

Michael Brush quips:

Pavlov’s birds.

Henry Gifford writes:

When I was hiking down The Grand Canyon I sat on a rock at the edge of the trail and took out a sandwich and started to eat. A bird came flying from my left side, toward the sandwich in my right hand. I reacted by pulling the sandwich back, to the right side of my head. Another bird came from behind and grabbed it.

Later I heard the birds’ favorite food is tuna fish, which they steal cans of from hikers. They open the can by grabbing it in their beak and flying above the one of the three cabins at the bottom of the canyon where the park rangers live and dropping it on the roof. The rangers have been trained to comply by opening the can and placing it on a convenient rock.

Pamela Van Giessen responds:

Was it a raven? They are particularly smart birds when it comes to getting food out of visitors to the national parks we have visited.

Asindu Drileba writes:

Crows & ravens would make good scientists. Here for example a video of a crow showing that it understands water displacement in different scenarios.

Bo Keely, from the desert:

Yesterday at the meteor crater in Death Valley two crows perched on the rim. They had grown feather sunglasses and asked for food. I went to the car & they followed and I gave them whole wheat bread. Then I got in & drove a couple miles down the road, pulled over to check directions, and they landed outside the driver's door asking for more bread.

May

27

Drawdowns and Recoveries: Base Rates for Bottoms and Bounces
Michael J. Mauboussin
Dan Callahan, CFA

Long-term wealth creation for companies is also heavily skewed.
Hendrik Bessembinder, a professor of finance at Arizona State
University, studied the roughly 28,600 public companies that have been
listed in the U.S. from 1926 to 2024. Key to his definition of wealth
creation is that a stock produce returns in excess of one-month
Treasury bills.

His data show that just under 60 percent of the sample failed to match
the returns of Treasury bills, destroying $10.1 trillion in value
through December 2024. The other 40 percent or so created $89.5
trillion in value. Just 2 percent of the companies produced 90 percent
of the aggregate wealth creation of $79.4 trillion, and the top 6
(Apple, Microsoft, NVIDIA, Alphabet, Amazon, and ExxonMobil) alone
added $17.1 trillion.

Had you been astute enough to buy and hold any of these super wealth
creators you would have suffered meaningful drawdowns. For example,
the lifetime wealth creation of Amazon, a technology company known for
e-commerce and cloud computing, was $2.1 trillion from its initial
public offering in 1997 to year-end 2024. Yet Amazon shares dropped 95
percent from December 1999 to October 2001. The average maximum
drawdown for the stocks of the top 6 companies was 80.3 percent,
similar to the average of the full sample.

Asindu Drileba responds:

This is fairly consistent with the findings of Robert J Frey (former Managing Director of Rentech). He gave a talk titled 180 years of Market Drawdowns. The main point of the talk is that since the 1830s to present, the structure of the market has changed a lot.

- Different political regimes
- Different sets of stocks
- The creation of a central bank (in 1913)
- The advent of electronic trading
- The rise of high frequency trading
- The creation of the SEC (1934)
- Many new regulations
- Different people trading the markets in those 180 years.

But one thing has remained constant in those 180 years: The S&P is in a drawdown 75% of the time. He defines draw downs as a period between the decline from an all time high [where somebody bought] to the point that they break even. So psychologically speaking, 75% of the time, [some] investors in the S&P are in a state of regret. I am thinking that if you can find a way of trading this, the edge will probably last forever.

May

26

I believe every trade I enter will be a loser–that is my most powerful trading belief. That concept keep me on guard and alert. Emotions are strictly Money Management. If/when you are too emotional, it just means your position size is too big for your emotions.

H. Humbert responds:

The attitude will tend to put you in contrarian positions at the best times, the times of maximum fear in the market or towards a stock. What you said is the same as saying "your best purchases are the ones that are the hardest to make." Of course if you recognize that you are a contrarian, at the same time on some level you have faith that the position will work out. It just depends on what level you want to think about it, emotionally. First derivative second derivative stuff.

The point is, with money in the market based on who is, or who is not, playing tennis (times 10,000 investors with their own 10,000 irrational superstitions), there are bound to be mispriced securities somewhere. Our job is to find them. Despite all their spreadsheets, NPVs, TA, back testing and “counting,” investors remain among the most irrational and emotional creatures on the planet. That is a good thing. That has always created mispricing, and opportunities. In essence, trading is about betting against human nature.

Galen Cawley writes:

I would say that thinking in advance that every trade will be a loser does not provide a positive edge so much as it prevents behavioral errors.

1) If you are a completely algorithmic trader, then the question is largely moot.
2) On the discretionary side, focusing on potential losses prevents unforced errors such as overconfidence manifested in the form of both overtrading (size and frequency).
3) Visualizing worst-case outcomes can prevent you from going on tilt during a crisis or during a string of losses.

Asindu Drileba agrees:

I have this attitude too. I assume every position will be a loss. So practically it helps me size my positions modestly. When I am placing a trade. A position is only in two states: a) I am over betting, in which case I may blow up. b) I am under betting, in which case I won't blow up. The only way to make sure that you are on the side of b) is to: 1) over estimate your losses; and then 2) under estimate your wins.

Another reason for assuming that your position is going to be a loosing one is that you are proactive to your trades, not reactive. Reactive means that you improvise when surprised by how things have gone. Of which you may not be in the right head space to make a decision. Proactive means you already assumed the trade was going to loose, so you had a plan ahead of time (when you were clear headed). I, for example know exactly the maximum I can loose on each trade, and it is always an amount that doesn't make me panic. Do I get Annoyed? Disappointed? Yes. But I never panic.

May

25

This morning I finished rereading the classic Atlas Shrugged of Ayn Rand and every time I learn something new; her thought is monumental. I don’t agree with a lot of her ideas and I fully agree with others, but I’ve always found this book to be an impressive catalyst for thought; this is in my opinion her power: the ability in sparking debate.

Rich Bubb comments:

Atlas Shrugged is also available as a 3-part movie. I think the book was better.

Adam Grimes writes:

My opinion on her work has shifted over the years, in a strongly negative direction. Too much of my experience contradicts her metaphysics and epistemology, particularly the rigidity of her rational materialism, and, as someone who treasures the craft of writing, much of her prose lands as clunky and overly didactic. I'm also now unconvinced on the primacy and sufficiency of rational self-interest… but, as you said, perhaps her greatest value is in creating discussion.

Asindu Drileba adds:

Ayn Rand had a reading group called the "Ayn Rand Collective" — Which Alan Greenspan was part of. They [Greenspan, Rand and a "professor"] would meet at Rand's apartment to read every new chapter of her new book. She (Ayn Rand) then fell in love with the professor and they started dating.

After sometime, the "professor" encountered a pretty young student in his own class and he "fell in love with her". The professor told Rand about the affair, but Rand begged the professor to cancel it. The professor then said that he would dump Ayn Rand, and then exclusively date the young pretty student. He said that this was the right thing to do since he was following his "rational self-interest". Ayn Rand got angry, slapped the professor in the face twice and kicked him out of her reading group.

This was a good illustration of cognitive dissonance. Rand thought her readers should practice "rational-self interest" towards everyone else, except her.

Francesco Sabella met a girl:

I was very fascinated to meet a girl times ago who I knew for her philanthropic activities and for her ideas being the exact opposite of Rand; and I was surprised to see her carrying an Ayn Rand book and she told me she didn’t like at all her; it made me think of her ability in creating debates.

Victor Niederhoffer responds:

i would always marry a girl who admired the book. susan introduced me to it and i knew then i had to marry her. it was very good choice.

Read the full conversation.

May

22

I noticed that I know of very few books on the stock market before 1900. I only know of:

Confusion of Confusions, by Joseph De La Vega (1688)

The Art of Investing, by John F Hume (1888)

Are there any books about the market before 1900 that can help me grow this list?

Big Al replies:

Lombard Street: A Description of the Money Market, by Walter Bagehot

Fifty Years in Wall street, Henry Clews

Francesco Sabella suggests:

The Stock Exchange: A Short Study of Investment and Speculation, by Francis W. Hirst

Stefan Jovanovich offers:

The Stock Exchange from Within, by Van Antwerp, William Clarkson

Martin’s Boston Stock Market, by Joseph Gregory Martin

Wall Street in History, by Martha J. Lamb

May

16

The chair recently made a tweet about a Galton book he was reading. I could read the text on the image but had to squint. I later took a copy of the image as asked Grok to extract for me the text so I can read it comfortably. Grok could only extract the text "Natural Inheritance."

After that, it didn't tell me it failed to extract the rest. it just made up its own fictional text that sounded plausible. I quickly learned it was just slop since I had already read some of the actual text in the picture.

My worry is that some people are using these LLM tools for medical records, creating legal documents. The latest AI gimmick is the so called "Agents" that will supposedly be used to file tax returns, book flights and do actual tasks on behalf of humans. My opinion would be to completely cut out all AI tools for critical tools.

Steve Ellison responds:

I am very, very careful about what I enter at an AI prompt, especially when doing proprietary or confidential work, lest my ideas become part of the cloud.

Laurence Glazier comments:

For this sort of thing use NotebookLM. Choose your sources for it, it will give you citation and preview.

May

15

I went to China recently. What I saw and nearly all the people I talked to were not happy about the economic situation there and almost everyone thinks Xi is stupid.

Humbert A. responds:

This has been the status quo since pre-Covid times imo.

David Lillienfeld writes:

Peter Drucker observed that the problem with totalitarian regimes is that with only one person in charge and no one in a position to offer alternatives/challenge that individual, there is no means of identifying and developing managerial talent in a society and the society inherently slows until the person in charge dies and there is a contest/market for new leadership. There will be problems showing in China soon enough–it has a demographic hurdle coming and it shows no signs of having any idea how to deal with it. It has lots of domestic health issues that will likely cost it considerably within the next decade. Maybe Xi will demonstrate Drucker as being wrong, but I doubt it. Barely three decades ago, the concern in the US was that Japan was about to walk all over the US. It didn't. I'm not sure that China is going to do any better.

Asindu Drileba writes:

This is my exact suspicion.
1950s to Soviet collapse — US Vs Russia (Narrative is Russians will take over USA)
1980s to Asia Currency Crisis — USA Vs Japan (Narrative is Japan will take over USA)
Early 2000s to Present — USA Vs China (Narrative is China will take over USA)

Peter Ringel adds:

There is a perverse stickiness to it. I grew up in one of these shit-holes ( not Japan ! ) - East Germany in my case. All the models and all the data point to implosion. And then it takes decades and centuries and more. And finally, when it collapses everyone is surprised, and no one was expecting it.

May

13

I am putting together a list of the Best Investments Books of the Year. I am not seeing many great books on trading, investing, finance, markets, crypto, options, futures, cycles, etc. I would love to hear if you folks know of any great books out in the past 6 months or so or coming soon.

Matthew Gasda is justifiably proud:

The Sleepers: A Novel

Big Al offers:

This is high-level quant stuff - ie, over my head, and despite "Elements" in the title - but a fun stretch:

The Elements of Quantitative Investing (Wiley Finance) 1st Edition, by Giuseppe A. Paleologo

His more basic 2021 book is "Advanced":

Advanced Portfolio Management: A Quant's Guide for Fundamental Investors, by Giuseppe A. Paleologo

Carder Dimitroff suggests:

This book is about historical finance and may not be a direct response to the question.

Empire, Incorporated: The Corporations That Built British Colonialism, by Philip J. Stern

William Huggins responds:

on a similar (historical) note, one of my students just recommended this title to me. looking forward to cracking it later this month:

Ages of American Capitalism: A History of the United States, by Jonathan Levy

Asindu Drileba adds:

If you would regard a speculator/investor as someone who also builds businesses:

Never Enough: From Barista to Billionaire, by Andrew Wilkinson

Andrew is building Tiny. His intention is to build the Berkshire Hathaway of Tech and software. He is inspired by Monish Pabrai (The Dhando Investor). So he is more in the "Value investing" camp not really quantitative.

May

11

I have heard every single one of these more than once on the floor. This is the G version; the X version would be very inappropriate for this venue.

You’re long hope and short reality.
He couldn’t trade his way out of a wet paper straddle.
You’re bidding like it’s your wife’s money.
His stops have stops.
He buys the high, sells the low, and thinks he’s range trading.
If brains were dynamite, he couldn’t blow his nose.
He's so underwater, Aquaman just waved.
Tighter than a bull’s ass in fly season.
Your size is what we use for toilet paper.
He’s a momentum trader—in reverse.
He couldn’t fill a corn order, let alone an order ticket.
That guy trades like he’s reading Braille.
He thinks ‘limit down’ means he hit the jackpot.
He trades like he’s got a rearview mirror taped to his glasses.
He’s scalping—his own account.
Nice fade. If I ever need a contrary indicator, I’ll call you.
He went from hero to sandwich in one tick.
I’ve seen better risk management at a toddler’s birthday party.
Market’s moving—better go ask your horoscope.
You trading or just making donations today?
He’s got a 30-lot mouth and a 1-lot account.
That guy’s P&L looks like an EKG flatline.
You're not trading—you're gambling, but slower.
He’s so unlucky, he’d lose money in a rigged market where he’s the rigger.
The guy’s charts look like modern art—ugly, meaningless, and overpriced.
He averages losers like he’s building a position in failure.
Don’t worry, he’ll blow up before lunch.
His fills are like Bigfoot—plenty of stories, no proof.
That trade had more slippage than a greased pig at a county fair.
He went full margin—and full stupid.

Asindu Drileba writes:

I watched the documentary "Floored" that was about the extinction of pit traders due to the advent of computer driven traders. A lot of the traders seemed to have their edge in bullying and intimidation that was both physical and psychological.

I made a pit trading playlist that I binged on, and this seemed consistent even to pit traders in the currency pits of London.

One of the pit traders called the computer "The most vile invention ever made." I think he was just sad that his bullying was no longer an advantage. You can't insult a computer, or use your big body to push it away so you can have the edge, or seduce it with good looks.

Michael Brush responds:

Behind every computer, there is a person.

“The offer is $25.”
“But my computer says $45.”
“So sell it to your computer.”

Pamela Van Giessen adds:

For those interested in a biography of a once famous and beloved pit trader, I recommend Charlie D: The Story of the Legendary Bond Trader by William Falloon.

Francesco Sabella adds:

It's an incredible book! I read it years ago, I even saw a 2 hour video of Charlie D. when i was in high school where he gave a lecture on trading on 1989.

Larry Williams writes:

Charly D was one stand up guy. He loved the Bears and suggested a bet with a young lady trader for a nickel on the weekend's game. She said sure…and won. Monday morning Charley D gave her 5 grand (a nickel in betting parlance). She was astounded, told him she meant 5 cents not 5G's. No way could she risk that or take the money. He left it in her hand and walked away.

I was fortunate, thanks to T Demark, to be part of his Vegas support group - he was just amazing to hang with.

May

6

Shtetl (full documentary) | FRONTLINE

This is a very depressing video about envy and how bad things can become. I think it also adds to previous discussions about madness of crowds (how ordinary people start participating in senseless murder) and illustrates that there is really no limit to how primal humans can become as long as they are given the green light.

Two take aways:

a) Don't hang around envious people.

b) Always make sure you have as little as possible that people can envy you over.

May

3

Some in these areas of science (genetics, animal development and behavior) have proposed that humans have essentially domesticated ourselves during the Holocene.

Domesticated silver fox

The domesticated silver fox (Vulpes vulpes forma amicus) is a form of the silver fox that has been to some extent domesticated under laboratory conditions. The silver fox is a melanistic form of the wild red fox. Domesticated silver foxes are the result of an experiment designed to demonstrate the power of selective breeding to transform species, as described by Charles Darwin in On the Origin of Species. The experiment at the Institute of Cytology and Genetics in Novosibirsk, Russia, explored whether selection for behaviour rather than morphology may have been the process that had produced dogs from wolves, by recording the changes in foxes when in each generation only the most tame foxes were allowed to breed. Many of the descendant foxes became both tamer and more dog-like in morphology, including displaying mottled- or spotted-coloured fur.

But there has been criticism of the breeding experiment and conclusions.

Asindu Drileba responds:

My definition of "domestication" used to be that of "Animals simply living under the care of other animals". When I watched a PBS Eons video some years back, I learned that Paleontologist's had a very different definition of "domestication". They define it as "the dependence on the care of other living things, to the extent that they cannot no longer live in their natural environment (the wild) anymore."

In the animal context, humans domesticated dogs and stray dogs (dogs with no owner) are riddled with wounds and in general don't do well. They would probably die if left in a forest. Foxes however look good in the wild.

In the human context, a human being with no owner (a government, a parent or an employer) usually does as badly in the manner of the stray dog. This human would perfectly fit the paleontological definition of what would be a "domestic human". The same applies for the ownership class/ruling class. They have used the working classes to domesticate themselves so they too, also can't survive with out them either. An undomesticated human would be people that can survive in an environment urban dwellers can't, the natural environment.

Like how the Khoisan do well in the desert, or tribes in the deep Amazon also do well. If you dumped a random urban dweller in the Amazon rain forest or the Kahalari desert (under same circumstances as the natives) 99% of them would die within weeks.

May

2

I wanted to ask Carder's opinion on this article that I came across titled:

China builds world’s first working thorium reactor using declassified US documents

It uses molten salt to carry the fuel and manage heat, while thorium serves as the radioactive fuel source. Experts have long viewed thorium reactors as the next leap in energy innovation. Some scientists estimate that a single thorium-rich mine in Inner Mongolia could theoretically supply China’s energy needs for tens of thousands of years with far less radioactive waste than current uranium-based reactors.

Carder Dimitroff responds:

Thorium is a fuel that is currently used in some commercial reactors. Canadian reactors can accept thorium and other nuclear materials in their CANDU reactors. (Read more: We can use thorium.)

One reason that the US, EU, and other reactors do not use thorium is that their reactors and related supply lines were not designed to accept that type of fuel. In US PWRs and BWRs, the reactor relies on precise fuel physics to achieve optimal performance. Changing the type of fuel would present a tough, if not impossible, outcome in terms of performance, let alone capital and operating costs.

When compared to a plant's production costs, nuclear fuel is surprisingly inexpensive, including the cost of disposal. Most of its energy is wasted. Consequently, there is little motivation to change the nuclear fuel's value chain.

Molten salt reactors are not new. In 1959, the US built the "Sodium Reactor Experiment" in California. Since then, several other countries have improved the design. Today, it is a viable technology, particularly in the Small Module Reactor (SMR) market. One example is TerraPower's Natrium Project (Bill Gates). They are currently testing the liquid sodium fuels for their Small Modular Reactor (SMR) product. (Read more: Terrapower: Natrium)

Apr

24

Planck's principle:

A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die and a new generation grows up that is familiar with it…

An important scientific innovation rarely makes its way by gradually winning over and converting its opponents: it rarely happens that Saul becomes Paul. What does happen is that its opponents gradually die out, and that the growing generation is familiarized with the ideas from the beginning: another instance of the fact that the future lies with the youth.

— Max Planck, Scientific autobiography, 1950, p. 33, 97

relevance of how new ideas are being adopted in science, markets, everywhere.

Jeff Watson responds:

Science by consensus is not science. Just ask Galileo.

Pamela Van Giessen writes:

John McPhee wrote extensively about this and how the science of geology advanced over a few centuries in Annals of the Former World. Scientific community consensus is pernicious, and it is clear that there is mostly no convincing it.

William Huggins comments:

the foundation of science rests of replicability - anyone with the same data should be able to replicate results (even if they disagree about the mechanism). once replication is established, the difficult questions come from "is this data sufficient and representative?"; "is the data generating process stable or dynamic?"; "did i gather data in support of my hypothesis or to try to disprove it?". the fun stuff.

philosophy of science ensures we ask good questions and have good tools to tackle them with. this is why the Ph in PhD is short for "philosophy."

correction: "same data" is the wrong phrase - "equivalent, out-of-sample" would be a better choice of words.

Asindu Drileba writes:

The problem with the human mind is that it has too many glitches. You can verify data successfully and still be wrong. Here are two examples from Astronomy. First, The Mayans had models that would accurately predict eclipses. So, your data of when eclipses occur would replicate really well with their model. However the model of the solar system the Mayans used, had the Earth at the centre and the Sun revolved around it. The assumptions of the model were completely wrong, but the data (predictions) were accurate.

Second, is Newton's models, that predicted the movement of a comet accurately. Then you often here people say that Einstein proved Newton wrong with Relativity.

I think when it comes to science, explanations are very flimsy. What should matter is if the idea useful or not.

Francesco Sabella responds:

I think it’s a very good exercise to start from the point of view that our mind is bound to make mistakes, have glitches and start to work from that assumption; even if it’s not always true but it can be good as working hypothesis.

Big Al recalls:

Years ago, doing simple quantitative analyses to post to this list, I learned that one of the biggest pitfalls was my own desire to get a nice result.

Apr

20

An interesting article that is making me think its mostly IP theft:

An image of an archeologist adventurer who wears a hat and uses a bullwhip

One of the internet-est things to come out of the most recent update to GPT image generation is the Studio Ghibli-zation of everything - another reminder of how OpenAI (and everyone else) trains on images that are very obviously someone else’s work.

Carder Dimitroff adds:

It's also an energy thief. Some data center owners are trying to get ratepayers to cover infrastructure costs through the state ratemaking process. On top of the capital costs, ratepayers are also expected to pay elevated marginal power costs. It's not just power. It's also natural gas:

This proposed gas plant to power a data center campus is massive

The soaring power needs of data centers continue to raise eyebrows, and nowhere is this more evident than at one Pennsylvania project, where a massive proposed natural gas plant would replace a legacy coal facility.

Pamela Van Giessen responds:

Thanks for sharing this. Every publishing/media legal department should read this, along with all artist guilds. And then they should do their own tests. AI was always theft.

Asindu Drileba offers:

There is a developing case NYT vs OpenAI:

Judge explains order for New York Times in OpenAI copyright case

April 4 (Reuters) - The New York Times made its case, for now, that OpenAI and its most prominent financial backer, Microsoft, were responsible for inducing users to infringe its copyrights, a New York federal judge said in a court opinion on Friday explaining an order from March 26.

Ars Technica did a more comprehensive article about it a year ago.

Apr

18

I know The Chair uses linear regression and so do some hedge funds. But what are you people using it for? Predicting earnings? Stock Returns? Stock Prices?

What kind of inputs make sense to insert into a linear regression model? What mistakes do you think people make when using linear regression?

Big Al responds:

A book the Chair has recommended:

Applying Regression and Correlation: A Guide for Students and Researchers

I've used correlation for exploring lots of simple questions like, "Does the move on Monday predict the move on Tuesday?" The basic model is just "does A predict B?"

One mistake often made when looking at time series like stock prices is to use absolute dollar/point changes rather than % changes. Always use % changes.

Apr

17

An interesting analysis of the options market on April 9th Trump Tariff fiasco. It seems the options market was aware of incoming policies before they were enacted.

$70 Million in 60 Seconds: How Insider Information Helped Someone 28x Their Money

On April 9, 2025, someone risked $2.5 million on SPY call options—and walked away with $70+ million in under an hour. The trade was placed at 1:01 pm. At 1:30 pm, Trump announced tariff pauses. The market exploded upward. These options that cost 85 cents were suddenly worth more than $25.

It wasn’t just the profit. It was the precision. The market moved before the news. The options were bought before the rally. The volume spiked in contracts that almost never see this kind of interest unless something is expected. And the pattern wasn’t visible on previous trading days. This wasn’t a trend. It was a singular event. — $70m in 60 Seconds.

Apr

16

That is the creature Hugh Hendry - the Acid Capitalist - says we have to find in order to profit from our speculations.

The events in Ukraine are that gorilla. They are predicting the likelihood that Trump, Putin and the Muslim oil producers will establish a Drill, Baby, Drill world of orderly energy production and supply priced in U.S. $. The effects on the European and Asian consumers will be comparable to what happened to the German-speaking world and its silver standard when the French fulfilled the terms of the Treaty of Frankfurt by paying their reparations in gold.

Big Al needs some help:

Perplexity answers the question, "What happened to the German-speaking world and its silver standard when the French fulfilled the terms of the Treaty of Frankfurt by paying their reparations in gold?"

Stefan Jovanovich answers:

They = "events, dear boy". The prediction is that the new cartel of oil and gas exporters will establish "orderly production" that manages the risks of overproduction in the same artful manner that OPEC once operated before the invention of fracking.

William Huggins responds:

So you are suggesting us producers will submit to directives from moscow or Riyadh to limit their production? No evidence of anything but predation among those players but somehow trump purs them all on the same page? I have a bridge for sale….

Read the full conversation.

Apr

15

The president seems to believe that trade deficits are evil and must be stamped out. If he ever actually succeeded at meaningfully reducing the trade deficit (so far the reverse is happening), what would be the implications for capital flows into and out of the US, and how might those changes affect markets?

Humbert L. responds:

Finance professor Jeremy Siegal wrote a piece decades ago about how the trade deficit is driven in part to demographics. Currently, the US is consuming more than it can produce, due to baby boomers retiring, no longer working, while still consuming. China is on the other side of the coin, with a younger workforce that is producing more than it's consuming.

Eventually the demographics will reverse, along with the trade deficit. The old folks in the US pass away, along with their consumption, and the US will start producing more than it's consuming, while China's young ones become old, retire, and they start consuming more than they are producing.

Asindu Drileba writes:

This sounds like a very plausible explanation for the phenomenon of "cycles" in the stock market, as described by the senator.

Mar

27

Spec roundup

March 27, 2025 | Leave a Comment


Jeff Watson has been watching the CME:
Anyone else notice the increase in seat prices (trading rights) recently?

Big Al found a history lagniappe:

BabelColour
@StuartHumphryes
Travel back in time 117 years to the Russia of 1908. I have enhanced for you this rare colour photo of the Russian writer Leon Tolstoy, regarded as one of the greatest and most influential authors of all time. It was taken in the grounds of his house at Yasnaya Polyana, near Tula, Russia. It is original colour, not colourised.

Steve Ellison provided his own:

Since one might be well advised to beware the Ides of March, here is a picture I took in 2017 of the ruins of the Theater of Pompey.

Asindu Drileba has been reading:

The importance of contrarianism emphasized by Jeff Bezos, from the Amazon 2020 Letter to Shareholders:

Differentiation is Survival and the Universe Wants You to be Typical

Our bodies, for instance, are usually hotter than our surroundings, and in cold climates they have to work hard to maintain the differential. When we die the work stops, the temperature differential starts to disappear, and we end up the same temperature as our surroundings….While the passage is not intended as a metaphor, it’s nevertheless a fantastic one, and very relevant to Amazon. I would argue that it’s relevant to all companies and all institutions and to each of our individual lives too. In what ways does the world pull at you in an attempt to make you normal? How much work does it take to maintain your distinctiveness? To keep alive the thing or things that make you special?…This phenomenon happens at all scale levels. Democracies are not normal. Tyranny is the historical norm. If we stopped doing all of the continuous hard work that is needed to maintain our distinctiveness in that regard, we would quickly come into equilibrium with tyranny….We all know that distinctiveness – originality – is valuable. We are all taught to “be yourself.” What I’m really asking you to do is to embrace and be realistic about how much energy it takes to maintain that distinctiveness. The world wants you to be typical – in a thousand ways, it pulls at you. Don’t let it happen.

Mar

15

Maybe the most fundamental thread on Spec List has been counting/data/figuring things out, so here is a marvelous two-part video by 3Blue1Brown, with Terrence Tao, about how we determined various cosmic distances.

The Cosmic Distance Ladder, Part 1

The Cosmic Distance Ladder, Part 2

Additional commentary and corrections from Prof Tau

Gyve Bones writes:

This was a fascinating lunch lecture. Thank you. I first became fascinated with the story of how science and technology developed with the 1977 PBS series by James Burke "Connections" which told the story, without the aid of CGI graphics in my high school years. I was given the companion book for the series that Christmas by my very thoughtful mom. (It's also the story that launched my falling away from the Catholic faith in which I was raised, my teenage rebellion.)

Here's the episode which details how the Babylonian star tables by Ptolemy used by Copernicus were preserved from the destruction of the Library of Alexandria, found on papyrus scrolls in a cave backup library:

James Burke Connections, Ep. 2 "Death in the Morning"

Asindu Drileba responds:

Connections is so good. I really wish there was a remastered version (in HD at least). One of the things I still don't understand is how government funded broadcast corporations like PBS, BBC and DW make such high quality non-fiction films. I would go to say the have the best non-fiction documentaries. Capitalism doesn't apparently do well when it comes to making non-fiction. What makes them so good? Are they just structured properly?

Gyve Bones replies:

Here is a very well mastered set of the videos for Connections (1978).

Peter Ringel adds:

there is a Conjecture, that astronomers are the more happy and humble people. I guess, this is because, it is all so vast and relative.

Mar

11

I think a lot about how attention, like a searchlight, moves around the markets. I like, too, the simple logic that when retail investors are deciding what to buy, they have a huge array of choices, but when deciding what to sell, they are limited to what they own. (Leaving out the idea of looking at thousands of options to try to decide what to short.) Maybe index ETFs simplify this process, but then, before index ETFs we had mutual funds, so maybe not.

All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors
Brad M. Barber, Graduate School of Management, University of California, Davis
Terrance Odean, Haas School of Business, University of California, Berkeley
Advance Access publication December 24, 2007

We test and confirm the hypothesis that individual investors are net buyers of attention-grabbing stocks, e.g., stocks in the news, stocks experiencing high abnormal trading volume, and stocks with extreme one-day returns. Attention-driven buying results from the difficulty that investors have searching the thousands of stocks they can potentially buy. Individual investors do not face the same search problem when selling because they tend to sell only stocks they already own. We hypothesize that many investors consider purchasing only stocks that have first caught their attention. Thus, preferences determine choices after attention has determined the choice set.

Asindu Drileba writes:

Laslo Barabasi has a model called preferential attachment. His model can simply be defined as "people usually prefer to bet on a horse that is already winning". I hear night club promoters also do this. To pull in customers, you create artificially fake long lines. These long lines make a night club appear popular, and thus make people interested in going in.

For the S&P index for example, index rebalancing algorithms are at times market cap weighted. That is, stocks with a larger cap, get more money than those with smaller market caps. Which will increase their future allocations, as their market caps grow. Retailers and others seeking "Blue chips" cannot invest in the top 500 stocks. They may focus on the top 20, which further distorts the market caps. Barabasi claims that this is partly why stock market caps have a pareto-like distribution. 20% for stocks may hold 80% of the index value market cap. (I am not saying this so what is exhibited it's just an illustration).

Peter Ringel comments:

I hear night club promoters also do this. To pull in customers, you create artificially fake long lines. These long lines make a night club appear popular, and thus make people interested in going in.

This is one of the many cognitive biases of humans. Any group over 5 attracts attention by by-passers. It even works with cutouts of >5 humans. The research papers above immediately bring my thoughts to manipulation. The searchlight is a daily reality in markets to me. But someone is holding it and is pointing it. Wyckoff style manipulation games on and on. For hundred years. I do disagree a little with the paper about retail trader as the main victim. Institutional smart money today - in one corner of the market - is tomorrows dump money in another corner. They are easily also susceptible to the manipulation games.

Mar

10

A few years ago, I read Brig. General Smedley Darlington Butler's War is a Racket (full text). Sample passages:

In the World War a mere handful garnered the profits of the conflict. At least 21,000 new millionaires and billionaires were made in the United States during the World War. That many admitted their huge blood gains in their income tax returns. How many other war millionaires falsified their income tax returns no one knows.

The Nye Committee uncovered some astounding information about the munitions industry, including a confession to profits as high as 800 percent.

Inspired by the book, I looked up publicly listed defense companies and marked out dates for conflicts like the Gulf War, Iraq invasion, Assassinations, Ukraine Vs Russia, Palestine Vs Gaza. While there were some blips on defense stocks, they were not that impressive. So if people say the US defense "complex" is fleecing the government, where exactly is this money going? What doesn't it reflect on stock prices?

Gold on the other hand frighteningly has so many coincidents, when it actually "predicts" aggression. The price of Gold for example went up for a moment before Qasem Soleimani was killed in a drone strike by the Trump regime. Not to mention how it behaved during the previous "Gaza - Israel" & "Ukraine - Russia" conflicts. I also found a similar observation in The Education of a Speculator:

Then, out of the clear blue, from 2 P.M. to 3 P.M., gold jumped $7. No reason for the rise, just technical buying by the funds, we were told. But that weekend, around 4 A.M. on Sunday, U.S. Navy fighter planes shot down a Libyan jet flying over the Mediterranean. This caused tremendous tension, always good in those days for at least a good run in gold. After all, nuclear war in the Mideast was now possible.

— Chapter 4, Subsection (Practical Losses)

Why is Gold way better at predicting political aggression than defense stocks?

Big Al responds:

I find the tricky thing with macro events is being precise enough with dates. Some events, like Fed announcements or other econ data releases, can be timed more precisely. With bigger, geopolitical events, it's less definite. With defense stocks, I would look at their performance in the months before the event, on the assumption that the market would be anticipating rather than reacting. As for strong reactions, look at the chart of Rheinmetall since the start of the Ukraine war and also since the US election.

As for gold, here's an interesting approach, looking at market sectors:

Navigating crises: Gold's role as a safe haven for U.S. sectors

This paper investigates the correlation between U.S. sectors and gold, and whether gold can serve as a safe haven for investors in specific U.S. sectors during the global financial crisis, COVID-19, and the Russia-Ukraine war. We use data from the Standard & Poor's Depository Receipts (SPDR) Select Sector Exchange Traded Fund (ETF) to capture the performance of the respective sectors. Our findings document that gold is a weak safe haven for most U.S. sectors. Gold is not a safe investment for energy, materials, utilities, and consumer staples. Gold does provide vital protection for financial, consumer discretionary, industrial, technology, and healthcare.

Asindu Drileba comments:

Thanks for pointing me to RHM.DE. I didn't even know the company existed. It is exactly how I expected US defense stocks to behave during the Ukraine-Russia & Gaza-Palestine conflicts.

Mar

1

Sampler

March 1, 2025 | Leave a Comment

Carder Dimitroff points to:

Michigan’s Palisades nuclear plant nearing reopening

Michigan’s Palisades Nuclear Generating Station is one step closer to becoming the first nuclear power plant in the United States to reopen. After closing in 2022, the company that was set to decommission the plant has changed course, aided by a $1.5 billion loan from the U.S. Department of Energy to restart operations.

And a new SMR will be added on the same property in about 2030:

Michigan: First nuclear re-start is scheduled for this August

FWIW, the federal regulator (NRC) may be immune from budget cuts. Their licensing and regulatory activities are funded by the industry, not taxpayers.

Asindu Drileba suggests:

Great podcast on LLMs:

What kind of Intelligence is an LLM

[Part 3 of a 6-part series on intelligence in the Complexity podcast series by the Santa Fe Institute.]

Stefan Jovanovich finds:

The best underdog story in professional baseball in US:

The Best Underdog Story of 2025

Payton Eeles #11
St. Paul Saints
Minnesota Twins
Triple-A Affiliate
2BB/T: L/R5' 5"/180Age: 25

Feb

25

Lots of them! And with AI-generated explanations.

Asindu Drileba responds:

Wow. As much as the explanations may be wrong, they logically make sense. LLMs are really getting good. I didn't know they could do this.

Gyve Bones writes:

You can do similar things with astrological cycles and events, I came to realize when I built an ephemeris for the Market Information Machine and coded macros for ways to use the data. You can curve-fit any data to some combination of sinusoidal cycloids and get a 99% correlation, which then falls apart going forward because it was indeed a spurious back-fit with no reasonable causal linkage.

M. Humbert suggests:

If you track which countries where I’ve lived, those markets always experienced a bear market. I’m currently in the US. Advise strongly that you bet the farm, take out a 2nd mortgage, and buy out of the money put options the Magnificent 7.

Feb

21

Spec sampler

February 21, 2025 | Leave a Comment

Asindu Drileba recommends:

The Count of Monte Cristo was my favourite movie of 2024. I would recommend it to specs as it has a very interesting stock market trading segment. The stock trading segment was brilliant in that it incorporated ideas from poker (previously discussed in this list). It's also a good demonstration Howard Mark's "Second level thinking", and the use of deception in the market.

Also, the best description of the Fourier transform I have seen so far.

Jeffrey Hirsch is on IBD:

How To Trade Trump 2.0 And Why DeepSeek Is Not The End Of The AI World | Investing With IBD

Big Al offers:

Humorous and with many lessons:

How I Helped to Make Fischer Black Wealthier
Jay R. Ritter, Cordell Professor of Finance at the University of Florida

Hillary Clinton wasn't the only person who made money speculating in the futures market during the late 1970s and early 1980s. A lot of finance professors did, including me. However, I used a different strategy than Hillary. Following the advent of stock index futures trading in 1982, many finance professors started playing the turn-of-the-year effect. The most popular approach was to buy the Value Line futures and short the S&P 500 futures. This is what I did. Of course, if there is easy money to be made, prices should adjust as the market learns, and a perpetual money machine will cease to exist. But I figured out a way to still make money. Or so I thought. Unfortunately, there was an unexpected danger in my strategy. In 1986, Fischer Black of Goldman Sachs figured it out and took me to the cleaners.

Feb

19

We sent my 2025 annual forecast to the Copyright office. They would not copyright it saying, “it was AI generated so could not be copyrighted.” We replied it was not AI, showing why so were finally approved. This raises an unraised question about AI protection. What is/will be the law??

Asindu Drileba comments:

The purpose of AI regulation is just so the big players can build a cartel and lock in the market. This is why people like Sam Altman say they "welcome it".

Big Al gets conspiratorial:

Not to be too conspiratorial, but…

OpenAI whistleblower found dead at 26 in San Francisco apartment

A former OpenAI employee, Suchir Balaji, was recently found dead in his San Francisco apartment, according to the San Francisco Office of the Chief Medical Examiner. In October, the 26-year-old AI researcher raised concerns about OpenAI breaking copyright law when he was interviewed by The New York Times.

Peter Ringel writes:

I always suspected, that the senator is a robot. His performance is inhuman!

Your work is obviously your work. But, what if one uses AI for ones work, creations and everything? It should be still your IP. We have musicians on this list, who use AI for inspirations and research. I constantly lookup code via AI, b/c I am not a good coder. But the final script is mine. I even run AI models locally. The opensource models like Facebook's LAMA. (for an easy install, i can recommend: msty.app)

There is creativity in asking questions, to squeeze the right results out of AI. Prompt engineering is a thing.

Pamela Van Giessen prompts:

No doubt every single publishers’ lawyers are fighting the ability for AI generated anything to be copyrighted because so much AI is taking from existing copyrighted works, usually without permission or payment. Some publishers are feeding into AI programs with permission/payment (I think my previous employer, Wiley, is feeding at least some content into AI, for instance). This is a lousy deal for the authors and artists. The publishers will make vast sums, much like Spotify, and the content creators (I really hate that phrase) will get less than pennies on the dollar.

Liberals have done a great job of deflecting the real problem with platforms (omg, no content moderation or fact checking, TikTok is spying on Americans, the world will end!). The real problem with platforms is that they steal content, outright theft. And where is your government protecting you from this theft? NOWHERE.

Easan Katir relates:

I sent an unpublished manuscript to an Oxford-educated editor, asking her to edit. She asked if any of it was AI. I replied truthfully that I wrote most of it but I asked AI to add some. She declined the job, I guess making a stand: humans vs. AI. Fortunately or not, we know which is going to win.

Peter Ringel offers:

U.S. Copyright Office says AI generated content can be copyrighted — if a human contributes to or edits it

Pamela Van Giessen comments:

I imagine that the courts are going to get involved at some point. Since much AI is from existing copyrighted material, some (most?) used without permission, someone is going to challenge copyrighted AI that is really someone else’s material.

Jordan Low agrees:

precisely. i have been seeing a lot of content creators complain that their work is just automatically reworded into another article without attribution.

Update: Big Al offers an historical lagniappe:

The battle of Cúl Dreimhne (also known as the Battle of the Book) took place in the 6th century in the túath of Cairbre Drom Cliabh (now County Sligo) in northwest Ireland. The exact date for the battle varies from 555 AD to 561 AD. 560 AD is regarded as the most likely by modern scholars. The battle is notable for being possibly one of the earliest conflicts over copyright in the world.

Stefan Jovanovich writes:

The first written mention of the Battle of the Book occurs in the Life of Saint Columba composed by Manus O'Donnell in 1532. Britain did not have a formal copyright law until the passage of the Statute of Anne in 1710; that gave authors their first ownership claim to their writings. Until then the Stationers' Company had an exclusive right to all printing and publishing in Britain. The term "copyright" comes from the right a member of the Stationers' Company had to copy a written manuscript into print after the text had been registered with the Stationers' Company. The charter for the Stationers' Company was granted in 1557 by Queen Mary and King Philip, then confirmed in 1559 by Queen Elizabeth. The Company had the authority to seize "offending books".

Carder Dimitroff adds:

From March's Library: Early printed books were customized with hand-painted illumination for the wealthy.

Feb

10

Gambler: Secrets from a Life at Risk, by Billy Walters. A spectacle of compulsive gambling in every field by a very flawed individual with a template of ever changing factors that influence football betting.

Andrew Moe agrees:

Would also recommend Gambler, by Walters - in particular for the two chapters where he details his method of handicapping NFL games. He uses a variety of factors to build his own line and compares that to the public line. The bigger the difference, the bigger the bet. Lots of quantitative factors, for example being the home team on a Thursday night game is worth 0.4 spread points. If home and away have different playing surfaces (grass/turf), it's worth 0.2 spread points. A great team coming off a bye and away is worth 1.6 points - if they are home off a bye, it's worth 1.4 pts.

Big Al writes:

I have read various pieces re online sports betting recently. I also have been listening to season 4 of Michael Lewis's podcast, Against the Rules, which is all about sports betting.

The podcast reinforces points made by others, the main one being that Draft Kings and Fan Duel weed out the winners and allow only losers to make bets. Pros try to find ways around this, but amateurs are just suckers. Also, thanks to software, the system is largely automatic.

When I compare this to markets, I think of market makers on one side, and retail traders on the other, along with the whole ecology of touts that try to get retail's attention and make you think you should be buying this or selling that.

One specific bit from the Lewis podcast I thought was interesting: A pro was talking about prop bets on individual player performance and he said that people like to see things happen as opposed to not happen, so usually betting the under is advantageous because the over is over bet.

Asindu Drileba comments:

I think the days of the bookies are numbered. I am confident the future of sports betting rests in prediction markets like Khalshi, Poly Market, Smarkets etc. The odds will be better, will change in real time, and best of all, there will be no need to kick out winners. It will be like the futures market.

Only two reasons why bookies still exist: 1. The infrastructure for these "Event Derivatives" has not yet been built. 2. Regulatory hurdles.

Big Al offers:

A very interesting deep read:

Why prediction markets aren’t popular, by Nick Whitaker & J. Zachary Mazlish:

Rather than regulation, our explanation for the absence of widespread prediction markets is a straightforward demand-side story: there is little natural demand for prediction market contracts, as we observe in practice. We think that you can classify people who trade on markets into three groups, but each is largely uninterested in prediction markets.

Savers: who enter markets to build wealth. Prediction markets are not a natural savings device. They don’t attract money from pensions, 401(k)s, bank deposits, or brokerage accounts.

Gamblers: who enter markets for thrills. Prediction markets are not a natural gambling device, due to various factors including their long time horizons and often esoteric topics. They rarely attract sports bettors, day traders, or r/WallStreetBets users.

Sharps: who enter markets to profit from superior analysis. Without savers or gamblers, sharps who might enter the market to profit off superior analysis are not interested in participating. They also largely don’t need prediction markets to hedge their other positions.

Update: Asindu Drileba remains confident:

I see the article was written in May 2024. Towards the US presidential election, close to $2B in real money was placed on Polymarket. Polymarket is extremely difficult to use (you need to buy the right crypto, install the proper wallet, just to get it working). Last year Americans spent $100+ Billion on sports betting.

Sports betting books can simply be restructured to work by having their odds computed by a prediction market and not bookies. It would also be the best way to buy insurance. On say hurricanes, earthquakes, fires. I see a lot of catastrophe insurance gravitating towards prediction markets.

If someone asked me. "What trillion dollar business is no one building?" I would respond, "A well done prediction market." Trust me, the demand is there.

Vic's X/twitter feed

Feb

3

What causes inflation? Suppose we define inflation simply as the rise in prices of commodities, stocks, real estate etc. What causes it?

1) A generic explanation people offer (acolytes of Milton Friedman & Margaret Thatcher for example) is to blame monetary policy. Simplified as, inflation is caused by "too much money chasing too few goods."

Many people blamed President Trump's COVID stimulus packages for the rise of prices during that period. It seems specs in this list agree upon this when it comes to stock prices, i.e., lower interest rates (higher money supply) -> Higher stock prices (inflated stock prices).

2) An alternative explanation is that higher prices are caused by supply chain issues.

So they would claim that higher commodity prices were so because it was extremely difficult to move them around during lockdowns, let alone processing them in factories. A member also described that egg prices may be going up because of disease (a chink in the supply chain) not necessarily monetary policy. I am thinking that supply chain issues are more important to look at, than monetary policy.

Larry Williams predicts:

Inflation is very, very cyclical so maybe the real cause resides in the human condition and emotions. It will continue to edge lower until 2026.

Yelena Sennett asks:

Larry, can you please elaborate? Do you mean that when people are optimistic about the future, they spend more, demand increases, and prices go up? And then the reverse happens when they’re pessimistic?

Larry Williams responds:

Just that it is very cyclical— as to what drives the cycles I am not wise enough to know…though I suspect…some emotional pattern dwells in the heart and souls of as all that creates human activity—along the lines of Edgar Lawrence Smiths work.

Read the complete thread.

Jan

26

First, Prof. Tau on the Philippines Grand Lotto.

An unusual lottery result made the news recently: on October 1, 2022, the PCSO Grand Lotto in the Philippines, which draws six numbers from {1} to {55} at random, managed to draw the numbers {9, 18, 27, 36, 45, 54} (though the balls were actually drawn in the order {9, 45,36, 27, 18, 54}). In other words, they drew exactly six multiples of nine from {1} to {55}.

Then, Prof. Tau on Bayes.

The Bayesian updating makes me think of predictions for the S&P for 2024 and how one would have updated these as the year progressed.

Asindu Drileba wonders:

Suppose the S&P can only return two values +1% and -1%. If it has returned +1% for day one and -1% for day two. The dataset would day the s&p returns are +1%, -1% so:

- Probability of going up (+1%) is 0.5
- Probability of going down (-1%) is also 0.5

Given the 2 day dataset of +1%, -1%. Now, suppose it is day 3 and the market goes up (+1%). How do we use Bayesian techniques to update the probability? In the ordinary way. The dataset would be (+1%, -1%, +1%). So update probability:

- Probability of going up, 2/3 (0.666..)
- Probability of going down, 1/3 (0.3)

I am not saying this is how Bayesian updates work. I am trying to ask members how it work's given the above toy dataset. There is a related video by Julia Galef called Bayesian thinking.

Khilav Majmudar writes:

I've learnt more about Bayesian probability from these two Tao posts than anything else I've encountered online. Thank you.

George McPherson responds:

I think this falls into the category of the law of small numbers. Relatedly, I just finished reading The Hot Hand by Ben Cohen and enjoyed it very much.

Jan

24

Anonymity, Signaling, and Collusion in Limit Order Books
Álvaro Cartea, University of Oxford; University of Oxford - Oxford-Man Institute of Quantitative Finance
Patrick Chang, University of Oxford - Oxford-Man Institute of Quantitative Finance
Rob Graumans, University of Oxford - Oxford-Man Institute of Quantitative Finance; Autoriteit Financiële Markten (AFM)
Date Written: January 03, 2025

A key feature in the design of a limit order book is the anonymity of limit orders. However, we analyze data with trader identification and find that market makers break the anonymity of limit orders. Market makers use limit orders with large volumes to signal themselves to other market makers to avoid trading with each other and to snipe retail limit orders. We explain the behavior of market makers with a model that considers competitive and collusive equilibria. The model shows that the behavior of market makers we observe in the data is consistent with that in a collusive equilibrium where market makers use signals to avoid sniping each other's limit orders. Signaling enables market makers to share the benign flow from retail limit orders, and to share the additional benign flow from impatient investors who otherwise would have traded with a retail investor’s limit order.

Asindu Drileba writes:

I wonder how the markets would change if order books were opaque.

Jan

19

Here is the original thread.

All of the agents show their reasoning so you can see how they work.

1 • Market Data Agent: gathers market data like stock prices, fundamentals, etc.
2 • Quant Agent: calculates signals like MACD, RSI, Bollinger Bands, etc.
3 • Fundamentals Agent: analyzes profitability, growth, financial health, and valuation.
4 • Sentiment Agent: looks at insider trades to determine insider sentiment.
5 • Risk Manager: determines risk metrics like volatility, drawdown, and more.
6 • Portfolio Manager: makes final trading decisions and generates orders.

Here is the GitHub repository.

Why would this work or be good at? Why would it not work? I don't think it will work since the same model will be used my many if successful and the gains will be cancelled out.

Larry Williams comments:

Ultimate curve fit - wait a year to know.

Hernan Avella writes:

This is absolutely the way to go, but there’s a bit more to what we get to call “Agent”. Also his quant module is looking at dumb shit.

Julian Rowberry responds:

horses had a good track record before cars. AI is making key opinion leaders redundant too.

Jan

9

The Money Masters by Bill Still

Documentary about the creation and history of the modern central banking system. I learned so much from it. So many interesting reading recommendations, historical insights. It's my exact kind of documentary. Very long (3 hrs +), almost no cliché information & made before the year 2000. It checked all my boxes.

Dec

17

In a few books I have noticed a pattern of the author insinuating people not to conform to the herd. Here are some examples:

"My resistance to conformity has been the bedrock of my speculative persona." — Education of a Speculator, The Chair

"Copper the public opinion" — Secrets of Professional Turf Betting, Robert Bacon

"The most contrarian thing of all is not to oppose the crowd but to think for yourself." — Zero To One, Peter Thiel

"Whoso would be a man must be a nonconformist. " — Self Reliance, Ralph Emerson

"If you suggest a doubt as to the morality of these institutions, it is boldly said that “You are a dangerous innovator, a utopian, a theorist, a subversive; you would shatter the foundation upon which society rests.” " — The Law, Frederic Bastiat

Are there any other books you know of that advise their readers not to be conformists?

Vinh Tu adds:

A connected concept is the minority game.

Humbert H. writes:

In markets, simply being contrarian is a recipe for losing money because "the herd" is often correct and markets are almost always efficient. Unlike the El Farol Bar problem, to be successfully contrarian one has to have insight into either something fundamental "the herd" doesn't see or anticipate a change in direction for whatever reason while having a correct insight into the timing. Game theory in its basic form doesn't seem to be very useful.

Asindu Drileba responds:

Yes, the minority game (El Farol Bar Problem) is just a toy model. So it may seem to be detached from reality at times. There is an ecological model that zoologists have come up with. I don't know it's exact name but it is described as follows.

Environment 1: If you're a buffalo and feed on the same grass plains with 1,000 other buffalos (herd members). The quality of grass you will feed on will be lower, since your competing with 1,000 herd members. Fortunately the odds of being eaten by a predator are lower. If a lion/cheetah attacks, your individual odds of being eaten are 1/1000.

Environment 2: If you're a "contrarian" buffalo, i.e move alone without your 1,000 friends. The quality of grass your eating will be higher since you don't need to share with anyone. But the odds that you are eaten, on the condition that the predator is successful are 100% i.e 1 in 1, cause you're the only target and possible victim.

So to the prey: The contrarian buffalo should figure out a way to not be eaten if it is to enjoy higher quality grass. To the predator: Education of a Speculator, describes retail people like me (the public) as the primary food for superior predators. Remember the more buffalos that join a herd the bigger it becomes and the higher the probability of a predator catching a meal.

Hernan Avella offers:

Conformity in Large Language Models

The conformity effect describes the tendency of individuals to align their responses with the majority….In this paper, we adapt psychological experiments to examine the extent of conformity in state-of-the-art LLMs. Our findings reveal that all models tested exhibit varying levels of conformity toward the majority, regardless of their initial choice or correctness, across different knowledge domains.

Humbert H. comments:

There are a couple of reasons why I like my own version of buy-and-hold, but really buy-and-hold in general: whatever happens you're not food for any predators in the market. You can be a victim of financial shenanigans, but when diversified that's not a big problem. The other is the drift. Same reason I never became a physicist: I always found physics really easy, and was always good from my high schools in the USSR and the US where I was the physics teachers' "pet" to college. But early on I figured out that to really make it in physics you needed to be a genius, and I was not, so there was not point in going that way. I don't feel I can beat the predators in the market because the top ones are both smarter and have more resources, so I don't even want to try. I admire those on the list who are trying, but to quote Dirty Harry "a man's got to know his limitations". I do have a couple of strengths for my version of buy-and-hold: I like to buy falling knives, which very few people like, so that's contrarian, and I can lose (or gain) value without any emotions other than "this is fun to watch".

Nov

30

When do we start seeing the effects of AI show up in national economic data? If you had invested $5K in a laptop and a word processing program, you could replace a secretary at multiples of the cost. When the web came in, there was Amazon squeezing out the costs of the middlemen.

But I don't see the savings for AI. I see lots of talk, some free programs, but in terms of real productivity, not so much. I'm also told that it's early days and I'm asking for too much in posing such a question, but I think we're now getting far enough into AI that it's not an unreasonable matter to bring up.

One thing that's clear is that AI isn't going to generate employment the way the last tech push did. But if it's going to really change the world as its advocates suggest that it will, those productivity gains should be apparent by now.

M. Humbert writes:

However AI productivity gains are measured, it’ll have to account for the productivity loss due to its high energy consumption. For the Austrian economics fans here. I’ve found Copilot to be a helpful time saving tool, so others probably do as well, so time savings definitely are occurring from AI use today.

Laurence Glazier responds:

Using it all the time, huge experiential benefit. Chatting to GPT every morning while reading Thoreau. Instant context. The other big breakthrough is spatial computing. All in the service of art.

Asindu Drileba comments:

From my experience, co-pilot and other LLMs, have not solved anything that could not already be done via ordinary Googling. Looking up solutions to code issues on stack overflow is no different from LLMs. And stack overflow is still better for some tasks (fringe computer languages like APL for example). LLMs are impressive, but are mostly just gimmicks. The only thing it has actually saved me time on is generating copyrighter material and filler text.

Jeffrey Hirsch adds:

Just had that discussion today about ordinary google still being even better than LLM Ais in finding info. Had some fun with AI editing and embellishing copy.

Asindu Drileba adds:

I suspect that the bad SWE job market is due to high interest rates, no AI. The SWE job market is enriched mostly by VC money. And VC money dried up when LPs withdraw to earn risk free money in treasuries instead of betting on start-ups whose success is on probability. I expect it to recover if interest rates come down to previous levels.

I think the LLM narrative was just something that tech executives parroted to show they had an LLM strategy. It's, Like how in 2018/2017 every executive had a "Blockchain" strategy. A lot of businesses assumed that LLMs would replace simple customer support jobs but they just saw their tickets pile up. Even the $2B valued, Peter Thiel financed, code assistant that would make you money on Up work as you sleep turned out to be a blatant scam.

Steve Ellison writes:

I don't have an answer for Dr. Lilienfeld's question about when AI effects will show up in productivity statistics. But I do hear anecdotally through my professional networks that AI projects are adding real value.

At the same time, Asindu is correct that the bad job market for techies, myself included, is more a consequence of rising interest rates–and I would add overhiring during the pandemic–than positions being replaced by AI. As Phyl Terry put it, "But this company [that announced layoffs] wants to go public so the better story is 'we are smart leaders using AI to become more efficient and profitable' vs 'we were idiots during the pandemic and have to lay off some people because we messed up.'"

Gyve Bones writes:

I find that the AI's ability to interpret my request and put together a coherent synthesis of several sources to be very helpful. Grok is nice because it provides a set of links to sources relevant to the prompt, and to related ??-posts and threads.

Laurence Glazier asks:

I usually have audio conversations with GPT rather than the older typed-in input/output. I just subscribed to X Premium to get access to Grok. Any good links for learning good usage? How nice Musk names it from the Heinlein novel.

Gyve Bones responds:

Check out the sample prompts Grok supplies on the [ / ] section in ??. The news analysis prompts for trending items is pretty cool.

Bill Rafter writes:

My business partner and I are in the process of marketing a new software application. Although we are rather literate, we have been running all of our marketing materials through Copilot, and we are amazed at the improvements Copilot makes to our text. It results not only in improved communication, but is a real time-saver. We even asked it to write a business plan, and it came back with a better one than our original.

Peter Penha offers:

I have not (yet) been on Grok but have found that the prompts do not differ very much across LLMs:

A Primer on Prompting Techniques, June 2024.

Prompt engineering is an increasingly important skill set needed to converse effectively with large language models (LLMs), such as ChatGPT. Prompts are instructions given to an LLM to enforce rules, automate processes, and ensure specific qualities (and quantities) of generated output. Prompts are also a form of programming that can customize the outputs and interactions with an LLM. This paper describes a catalog of prompt engineering techniques presented in pattern form that have been applied to solve common problems when conversing with LLMs. Prompt patterns are a knowledge transfer method analogous to software patterns since they provide reusable solutions to common problems faced in a particular context, i.e., output generation and interaction when working with LLMs. This paper provides the following contributions to research on prompt engineering that apply LLMs to automate software development tasks. First, it provides a framework for documenting patterns for structuring prompts to solve a range of problems so that they can be adapted to different domains. Second, it presents a catalog of patterns that have been applied successfully to improve the outputs of LLM conversations. Third, it explains how prompts can be built from multiple patterns and illustrates prompt patterns that benefit from combination with other prompt patterns.

This is earlier/shorter February 2023 paper - I am also a fan/follower of Prof. Jules White’s classes on Coursera why I flag the shorter/earlier paper as well.

Separate on the subject of AI - Eric Schmidt has a new book Genesis with Dr. Kissinger as a co-author (his last work before his passing) but Schmidt did a Prof G Pod Conversation released Nov 21st - in the podcast Schmidt goes over the threat from LLMs that are unleashed and noted that China in his view has open sourced an LLM equal to Llama 3 and that China instead of a being three years behind the USA on LLMs is a year behind. That China comment can be found here at 26:30.

Finally if anyone wants a great book I have read, on the history of the race to AGI going back to 2009: the Parmy Olsen book Supremacy on the histories of Sam Altman and Demis Hassabis is a wonderful read. Also breaks the world down between the AI accelerationists and the AI armaggedonists.

Big Al adds:

I do use Bard to learn or refresh my memory with R. For example, I am trying to use the "tidyverse" set of packages, and Bard is very useful when asked to write code for some task specifically using, say, tidyquant. The code almost never works first time cut & paste, but I can see how things are done differently and figure out what needs fixing. And I get answers to simpler problems faster than on Stack Exchange which is better for more complicated issues.

Laurence Glazier comments:

It's an inverted Turing test situation. The things that AI can't do help identify our humanity, our birthright.

Nov

24

Contrary to what has often been repeated on this esteemed list over the years, the art and process of trading is fundamentally the art and process of setting the right stops. Simpletons may claim that adding stops to a system (trading ES) reduces profitability, but that's only because the system itself is flawed, with laziness baked into its design. Setting the right stop is an integral process—it involves gauging current and expected volatility, weighing potential paths, and accounting for the bias.

Steve Ellison writes:

One of my best experiences with this list was that at the sparsely attended Spec Party in summer 2009, the 20 or so of us who were there had a very spirited discussion in Victor's living room about whether it was advisable to use stops or not. Many excellent points were made both pro and con.

Speaking for myself, I usually don't enter stop orders because they become part of the market, but I have mental stops. On the rare occasions when I actually have a profit, I am determined to not let it turn into a loss. And if a trade goes against me (by a nontrivial amount), that's new information that apparently my original analysis missed; in that case I am determined not to let a small loss turn into a big loss.

To put it another way, I entered a trade because I thought I had an edge, but the market moved in the wrong direction. Maybe something bigger is going on than, say, my analysis of the last 10 post-options-expiration weeks.

Big Al offers:

Stop Orders in Select Futures Markets
Nicholas Fett and Lihong McPhail
Office of the Chief Economist
Commodity Futures Trading Commission
August 29, 2017

This paper analyzes trade and order book audit trail data to provide a detailed summary of the use of stop orders in select futures markets; specifically E-mini S&P 500 Futures, Ten Year Treasury Note Futures, and WTI Crude Oil Futures. Recent flash rallies and the ever increasing speed of futures markets have called into question the appropriateness of traditional stop order strategies. By utilizing metrics related to both placement of and execution of stop orders, we show that stop orders are being used in these futures contracts with varying frequency and the strategy of stop order placement varies greatly by participant. As expected, trades involving stop orders are found to be highly correlated with intraday price volatility. Existence of stop orders is generally unknown to market participants as stop orders are not visible in the orderbook but must be triggered by a trade in the market at the corresponding price. More importantly, our analysis indicates that many traders are not only using stop orders for hedging purposes but also using them for latency reduction strategies. We provide a background on the usage and depth associated with stop orders in selected futures markets.

Larry Williams responds:

THANKS FOR THE POST. This should dispel the notion "they are going after my stops."

Asindu Drileba writes:

I don't actually use stops at all. My position size is my stop. I only bet a maximum of 3% of my bankroll. I really only get out of the market when I am liquidated. I sleep knowing that if I am to loose, my maximum loss is capped at 3%. I don't even respond to margin call emails. I often want to capture the moves between the daily open and the close. So what happens in between is something I usually ignore.

Nov

2

And the law won

November 2, 2024 | Leave a Comment

From Big Al:

Campbell's law

The more any quantitative social indicator is used for social decision-making, the more subject it will be to corruption pressures and the more apt it will be to distort and corrupt the social processes it is intended to monitor.

Variation:

Goodhart's law

When a measure becomes a target, it ceases to be a good measure.

Nils Poertner writes:

if one could find a way to increase the odds of Sod's law happening to oneself (trading or otherwise, outside trading). one could find a way to be less exposed to that law. don't have an exact formula here it is just a question.

This book The Improbability Principle: Why Coincidences, Miracles, and Rare Events Happen Every Day, by David Hand, did flip a lever in my brain many yrs back. in this book he described that we have an inadequate idea of probabilities and nature is far more dynamic than we think and that perhaps our own actions and belief systems play a much larger role…(btw, am not saying fate never plays a role)

Rich Bubb writes:

Having witnessed (pre-retirement in 2020) multiple project, engineering & quality failures related to Murphy and/or SOD variants, the engineering & technicians [and often-times myself] that had to deal with the 'Magic Wand' mgmt insane dreams-up are/is best avoided by 'stepping away from the problem, asap'. In some areas, this 'stepping-away' is also known as the "Do NOTHING Rule". Corollary: "Ain't My Job Rule."

Or, knowing that everything rarely goes according to plan (Unknown Unknowns), & expect something-to-hit-the-proverbial-fan. One method I used (more often than I should admit), is a Reverse Fishbone/Ishikawa Diagram. The method has the "Result" of anything going wrong replacing the assumed desired effect , aka the 'Fish-head', then working backwards trying to determine Man, Method, Environment, Measurement, Machine, etc., possible snafu's, & mitigate or pre-fix problems.

Sometimes the Reverse Fishbone is done after the problem is revealed. And the $$$ Cost of mitigation are sometimes 'argued-away' by the cost-benefit folks controlling the situation's budget. This is one reason many engineers fear &/or loathe accountants (but not out loud).

Asindu Drileba adds:

Sods law seems related to a set of precepts used in computer science called the Fallacies of distributed computing.

When building a trading system assume that;
- The market's returns will arrive at the worst possible sequence.
- Your orders will not get filled exactly the way you want.
- Transaction fees are going to eat all your gains
- Your broker is going to scam you (a là FTX)
- You trading system might go offline for arbitrary reasons
- Regulations might change against your favour. (up tick rule, no shorting stocks)

Building a trading system based on such pessimistic assumptions will actually result it a system that will go through alot of muck and still be reliable.

Oct

31

There is a lot of talk about how precarious US Debt situation is. Two questions:

1. What possible disaster may come out of this? I am thinking Zimbabwe type hyper inflation. What other kind of disaster can happen?

2. What can retail level people do to protect themselves from this? Buy Swiss Francs? Gold & Silver? Bitcoin? What?

Larry Williams responds:

Gloom and doomers here is the chart to look at:

Bud Conrad writes:

Gold 1 year is up 24%. Silver 1 year is up 50%. The circumstances today are still very bad for the dollar. (Which is what is actually declining.)

The BRICS+ are meeting in Russia tomorrow Putin, Xi, Modi, Iran, Saudi Arabia (observer only), UAE etc.) to continue de-dollarization with non-dollar-denominated trade through non-SWIFT transactions for international Central Bank settlement. NO body is talking about this, being focused on how much the candidates will print up to bribe us for votes. The $1.1 T for interest on the $35 T of official Government Debt could rise, as the 10 year Treasury rate hit 4.2% while the Fed CUT short-term rate. Including unfunded liabilities for Social Security and Medicare would say the debt obligations are more like $200 T.

This is 10 year Treasury. Red pointer is when Fed Cut short term rate:

There is no way around avoiding the money printing required. Inflation and price rises are inevitable, as foreigners divest their $8 T of Treasury holdings, to avoid US asserting sanctions or seizing assets like the $300B of Russia holdings. They want out of US Hegemony fast, because of 14 rounds of sanctions on Russia.

Read the full conversation.

Oct

22

There is this new tool from Google called Notebook LM. It converts text into an audio of podcast format, two people conversing about the topic (a man & a woman). It's so good, I would say it's impossible for me to differentiate between a fake Notebook LM podcast and a real one. The AI's call him a "Renaissance Finance Man" and honestly speaking, I really enjoyed the fake podcast.

It's just 10 minutes long, if you want to listen to it, here it is. (You need to be signed into Gmail or a Google account to listen.)

Laurence Glazier responds:

Extraordinary. Will take a look at this. We need to be circumspect about everything we thought was real. Certainly any photos or new articles we see in the media.

Gyve Bones asks:

Very well done. What sources did you supply the LM?

Asindu Drileba explains:

The text was simply the About page of Daily Speculations. That's all I used. But I suspect it also added content else where from the internet and they mention stuff that isn't present in the about page.

Oct

14

This year is the 100th anniversary of the Johnson-Reed Immigration Act signed into law in 1924 by President Coolidge. It was a modification of the 1917 Immigration Act which was the first law to establish quotas for entry into the United States.

Before 1917 the only numerical restrictions on entry to the United States was the Chinese Exclusion Act of 1882, which excluded EVERYONE Chinese. Immigration acts had placed restrictions on individuals (1882 - no convicts, indigents, prostitutes, lunatics, idiots; 1903 - no anarchists, epileptics, crazies; 1907 - no infected, mentally or physically handicapped who could not work), but there had been no quotas. The 1917 Immigration Act continued the exclusion of the Chinese but extended it to everyone else in East Asia except the Japanese and the Filipinos. The law also imposed a literacy test for anyone over 16, but the test was for the person's own language, not just English.

The 1924 Act extended the outright exclusion to the Japanese and can reasonably be identified as the triggering event that allowed Fascists to take control over the government of Japan and spend the next decade and a half convincing the people who had embraced representative democracy, American jazz and baseball that they should choose their own race as the one to come first.

Humbert H. comments:

It’s interesting how some reasons for excluding specific groups from being able to immigrate have changed over time. “Strong economic competitor” has completely disappeared, whereas it was one of two main reasons for excluding the Japanese. There must be some sort of widespread recognition that importing groups that demonstrate great achievement in some economic areas is good for the country even though there is certainly some collateral damage to the established population.

Stefan Jovanovich rejoins:

GR and I have different readings about the exclusion for the Japanese. It was not economic competition; the U.S. had a healthy positive trade balance with Japan between the two world wars. We sent them oil and wheat; they sent us toys and trinkets.

The political pressures for exclusion came from
(1) Teddy Roosevelt's complete hatred of the Japanese AND the Russians (Give a President the Nobel Peace prize and bad things always happen). That made disdain for the Nips into a bedrock belief of all progressive Republicans (Thank you Earl Warren)
(2) The continuing negotiations after the signing of the Washington Naval Treaty of 1922

Humbert H. clarifies:

I didn’t mean economic competition with Japan, but with Japanese immigrants, mainly in California

Asindu Drileba writes:

I heard from somewhere, that before World War 1, passports & visas where not enforced that seriously. You could just show up to any place you wanted to go to without many formal requirements. I just imagine if the world was like that? Anyone can show up anywhere anytime without any legal hurdles?

Noam Chomsky (MIT linguist) says that there are two kinds of globalization.
Globalization 1: Is the free movement of people (labour) around the world with less restrictions.
Globalization 2: Is the free movement of capital & goods (products) with little legal restrictions.

He says that as we we're entering the 21st century, there has been a sharp decrease in Globalization 1 and a sharp increase in Globalization 2. It has been described that Globalization 2 has benefited corporations a lot (some even claim it has benefited the economy as a whole).

Can a country benefit economically (can corporations & markets see gains?) by making immigration as easy as it is to send money around the world? That is, people (labour) moving around with very little restrictions?

Jeff Watson offers:

It would be better this way:

A world of free movement would be $78 trillion richer
Yes, it would be disruptive. But the potential gains are so vast that objectors could be bribed to let it happen.

Humbert H. responds:

Of course anyone with a minimal economic education would realize that free movement of “labor” or entrepreneurs would result in creation of enormous wealth. In the real world though, new immigrants going on the dole has become a feature and not a bug in many wealthy countries. You read anything from England, and that seems like an accepted fact there. The list of various culture-clash and crime issues is long and only irritates people who are for unrestricted immigration. So this not a pure economics problem but more multifaceted. My point was that something, perhaps better knowledge of economics or personal experience, or maybe less dog-eats-dog competition for survival, taught the populace that importing highly capable people usually leads to good outcomes.

Jordan Low adds:

Do you enjoy Bing Cherries? He lost his farm in the act.

Ah Bing

Ah Bing was a 19th century horticulturalist and credited as the cultivator and namesake of the popular Bing cherry. Bing migrated to the U.S. around 1855 and worked as foreman in the Lewelling family fruit orchards in Milwaukie, Oregon.

Oct

12

Recommendations for an intro to multivariate statistics?

Bill Egan replies:

Here are four excellent multivariate statistics books I have used for many years. I suggest tackling them in this order.
1. Jerrold Zar - Biostatistical Analysis, 5th ed. (this is half univariate and half multivariate)
2. Neter, Kutner, Wasserman, Nachtsheim - Applied Linear Statistical Models, 4th ed (there is now a 5th ed and you can find the pdf by googling)
3. Alvin Rencher - Methods of Multivariate Analysis (there is now a 3rd ed.)
4. Mardia, Kent, Bibby - Multivariate Analysis (there is now a 2nd ed.)

You need to understand linear algebra to do this, e.g., at the level of Strang's Introduction to Linear Algebra, 6th ed. (his lectures are on MIT's opencourse website). Rencher, Neter, and Mardia all use that notation extensively. You also need to understand and be able to do univariate stats at the level of:
• Snedecor and Cochran - Statistical Methods, 8th ed.
• Riffenburgh and Gillen - Statistics in Medicine, 4th ed.

You will really learn multivariate methods only if you code them. Matlab is the best (Matlab Home is cheap), and yes, I coded everything in these books and a lot more work of my own invention in Matlab.

David Lillienfeld adds:

Snedecor and Cochran is the grand old lady of texts. Neter et al is still pretty popular on campuses.

Asindu Drileba asks:

Concerning statistical packages. I often hear some data science communities complain about how there are simply too many bugs & wrong implementations in the Python space. Maybe this is why you are recommending MATLAB? What do think of R or Julia?

Bill Egan responds:

I have used Matlab since 1993 for many things - research, papers, patents, commercial scientific software products. Matlab stands for matrix laboratory. The original data structure was scalar, vector, matrix. If you like to work in matrix/linear algebra notation, or need to, Matlab is the program to use. Other data structures have been added on, such as tables for mixed data types, but like al ladd-ons, this does not always work well. Quality control of the software is great. Very widely used by engineers. Very high level language, so you can see the algorithm without getting lost in the details like you do in C++.

R is not so good for linear algebra because the original data structure is a table for mixed data types. Matrix work is more difficult. Quality control of core R and major packages is good despite R being open source (although it has license restrictions) because it is used by many academic statisticians. I used R for analysis for a couple of years. Fairly high level language. Better for classical stats work where you make a table out of the data and have mixed data types.

Python is completely open source and the people who created and use it most have no knowledge of statistics and that shows. We used it primarily as a scripting/control language inside one of my software products. Available packages do have bugs/errors or are missing methods for stats. We tested them and could not use them; I had my guys code any stats related stuff from scratch. It is not as high level a language as R or Matlab, so you have to do more work. Do not recommend it.

I have no experience with Julia.

Oct

9

I feel so lucky to have come across this book. And I think it's so relevant to the market. The book is titled Programming Collective Intelligence and markets can be thought of as a form of collective intelligence. Like some people may suggest, a market can be described as a single brain made up of other brains.

The book is very practical and gives examples on how to make predictions amongst collective entities participating in E-commerce sites, Dating websites, Social Networks, Real Estate and so on. It has no mathematics (that I have seen so far). Everything is written is very clean readable Python code (no use of obscure Python features or keywords).

Here is the book's own description of Chapter 8:

Introduces decision trees as a method not only of making predictions, but also of modeling the way the decisions are made. The first decision tree is built with hypothetical data from server logs and
is used to predict whether or not a user is likely to become a premium subscriber. The other examples use data from real web sites to model real estate prices and "hotness."

And Chapter 11:

Introduces genetic programming, a very sophisticated set of techniques that goes beyond optimization and actually builds algorithms using evolutionary ideas to solve a particular problem. This is demonstrated by a simple game in which the computer is initially a poor player that improves its skill by improving its own code the more the game is played.

Table of contents & book description

Oct

7

From Carder Dimitroff:

Note: 1 GW = about 1 nuclear power plant.

US DOE/EIA: Batteries are a fast-growing secondary electricity source for the grid.

Utility-scale battery energy storage systems have been growing quickly as a source of electric power capacity in the United States in recent years. In the first seven months of 2024, operators added 5 gigawatts (GW) of capacity to the U.S. electric power grid, according to data in our July 2024 electric generator inventory. In 2010, only 4 megawatts (MW) of utility-scale battery energy storage was added in the United States. In July 2024, more than 20.7 GW of battery energy storage capacity was available in the United States.

From Kim Zussman:

Argentina Scrapped Its Rent Controls. Now the Market Is Thriving.

For years, Argentina imposed one of the world’s strictest rent-control laws. It was meant to keep homes such as the stately belle epoque apartments of Buenos Aires affordable, but instead, officials here say, rents soared.

Now, the country’s new president, Javier Milei, has scrapped the rental law, along with most government price controls, in a fiscal experiment that he is conducting to revive South America’s second-biggest economy.

The result: The Argentine capital is undergoing a rental-market boom. Landlords are rushing to put their properties back on the market, with Buenos Aires rental supplies increasing by over 170%. While rents are still up in nominal terms, many renters are getting better deals than ever, with a 40% decline in the real price of rental properties when adjusted for inflation since last October, said Federico González Rouco, an economist at Buenos Aires-based Empiria Consultores.

From Asindu Drileba:

Fraud, So Much Fraud

Charles Piller and the team here at Science dropped a big story yesterday morning, and if you haven't read it yet, you should. It's about Eliezer Masliah, who since 2016 has been the head of the Division of Neuroscience in the National Institute on Aging (NIA), and whose scientific publication record over at least the past 25 years shows multiple, widespread, blatant instances of fraud. There it is in about as few words as possible.

It turns out that alot of FDA drug approvals where based on this guy's research (a few listed in the article). I wonder what effect it may have on pharmaceutical businesses based off his research. Imagine spending decades & billions on a drug whose prior research turn's out to be completely forged (photoshopped images). This looks really bad for the Alzheimer's drug focused pharmaceutical industry.

From David Lillienfeld:

This is a comparison of international drug prices. U.S. gross prices are higher than those in comparison countries for all drugs and for brand-name originator drugs but lower for unbranded generic drugs.

Oct

2

Anyone else sick of the idea that gamblers are best at financial markets? Why aren't the champion players the richest in the world? Would you hire a gambler to manage your life savings? Don't gamblers (Livermore, etc) die broke?

Why This Wall Street Firm Wants Its Traders to Play Poker

Young traders who join the trading giant Susquehanna International spend at least 100 hours playing cards during a 10-week training program. When the stock market closes at 4 p.m., they often head straight from the trading floor to a dedicated poker room at the firm’s headquarters in the Philadelphia suburbs.

Jeff Yass, Susquehanna’s co-founder, sometimes joins in, scrutinizing hands new hires play and gauging how effectively they bluff. Thousands of employees, from traders to technologists, participate in the firm’s annual poker tournament. At least three have notched wins at the World Series of Poker in Las Vegas.

Big Al offers:

Trading Is a Lot Like Poker

Peter Ringel writes:

I agree to all the points from the trading side. I know the basics of poker, but not a skilled player. Not even a novice. It makes sense to use the filter "skilled poker player" for manager selection. But how to become a skilled player ? Is it easier to become skilled in poker vs a skilled trader? I suspect it is a similar hard battle.

Asindu Drileba comments:

The problem with "skill level" is that they kind of translate differently. Warren Buffet for example is a Bridge addict. (Bridge is also a game of chance like poker) He (Buffet) is definitely an "above average skill player", but nit amongst the top 20 in the world. In investing however, Buffet may be regarded as part of the top 5.

The same goes for other financiers. Sam Altman (top VC in Silicon Valley), Jason Calcanis (Top VC in Silicon Valley), Charlie Munger were probably above average poker players but their edges were stronger in the finance & investing world — but all these attribute poker to their success.

Big Al writes:

1. Poker is very different from other casino games. There is a lot of skill involved, a lot of math (at the higher levels), a deep understanding of game theory (at the very high levels), and there are many more decisions to be made in poker compared to, say, roulette. Most poker pros probably wouldn't call poker "gambling", though some are degen gamblers when they walk away from the poker table.

2. Poker is a lot like the other casino games in that, for most people, the best decision is not to play. Like in markets, where the best decision for most is not to trade but just buy a diversified portfolio and hold it for a long time.

3. But firms like Susquehanna are not advising "most people" and they're not buying and holding SPY. For them, poker is a good way to assess and develop various skills that are relevant to hacking the market and making big bets. Poker is a great laboratory for testing "risk tolerance".

4. The poker "ecosystem" is a lot like the trading market in that there is a need to keep getting new suckers to enter at the bottom level and convince them they can win.

Sep

28

Lana Del Rey — My boyfriends really cool, but he is not as cool as me. Cause I'm a Brooklyn Baby. An interview recently posted here with The Chair — "I attribute your being humble to being from Brooklyn" (interviewer referring to The Chair). Another person I listen to - Such mistakes can only be made by people who have not spent a lot of time in Brooklyn. Brooklyn comes up so many times. What's is there to know about it? Of course I have heard of people talking about other cities.

But people that talk about Brooklyn always say it like there is something they know which others don't know. What is in Brooklyn? What does it do to people?

David Lillienfeld adds:

In the epidemiology world, when one of the organizations meets in Manhattan, inevitably someone will suggest to the younger members to go across the Brooklyn Bridge and experience Brooklyn. There is definitely something about Brooklyn that focuses one's thoughts.

Steve Ellison offers:

The Chair wrote a whole chapter on this topic, the first chapter of Education of a Speculator, titled Brighton Beach Training.

Laurel Kenner suggests:

Survivors go there when they get to America.

Alex Castaldo responds:

Agreed, immigrants from Central and Eastern Europe often arrived in Brooklyn as a first step towards success and acceptance in America.

H. Humbert writes:

There is a hierarchy among the real estate developers of New York. Those who develop real estate (especially large commercial buildings) in the central area (the island of Manhattan, also known as New York County) consider themselves socially above the multimillionaires who develop property in the boroughs of Brooklyn, Queens, Bronx and Staten Island. They refer to Manhattan as simply "the City" and seldom go to the other boroughs (other than to take an airplane at LGA or JFK airports, which are in Queens).

Donald Trump's father was a developer of large number of properties all of which were in Queens and Brooklyn and he considered Manhattan development too financially risky. He was quite wealthy but in view of the above was not considered a "major New York developer", like Roth, Reichmann and other well known names.

His son Donald was very ambitious and wanted to move up in society. Contrary to his father's policy he took a gamble and decided to put up a large building, the Grand Hyatt Hotel on 42d street in Manhattan. The project was completed in 1978 and Donald Trump joined the ranks of major NY real estate developers. (What the other developers thought of his operation is another subject and requires a separate article). Even if he wasn't fully accepted by all, when his daughter married a member of the Kushner family, another prominent Manhattan developer, a few years later, it confirmed that the Trump family had reached the first rank among New York's wealthy families. But Donald Trump, having overcome his Queens handicap and shown that he could do better than his father, was not quite satisfied and he decided to enter national politics.

In summary, there is a slight prejudice against people from Queens and Brooklyn, which sometimes causes people to be even more motivated to succeed and be accepted.

In addition Brooklyn has its own distinct accent, which causes the prejudice to be slightly greater. If you would like to know what a Brooklyn accent sounds like you can listen to any speech by Janet Yellen. When she was in line for a top job in Washington, a previous Treasury secretary (probably hoping to get the job himself) mentioned her accent as a reason she should not be appointed. She got the job anyway. Another success for Brooklyn.

Jeff Watson gets musical:

Steely Dan nailed it.

Sep

22

Ever choke during a big event?

The Brain Really Does Choke Under Pressure
Study links choking under pressure to the brain region that controls movement

Have you ever been in a high-stakes situation in which you needed to perform but completely bombed? You’re not alone. Experiments in monkeys reveal that ‘choking’ under pressure is linked to a drop in activity in the neurons that prepare for movement.

The researchers found that, in jackpot scenarios, the activity of neurons associated with motor preparation decreased. Motor preparation is the brain’s way of making calculations about how to complete a movement — similar to lining up an arrow on a target before unleashing it. The drop in motor preparation meant that the monkey’s brains were underprepared, and so they underperformed. To a certain extent, “you just don't perform better as the reward increases”, Moghaddam says.

Asindu Drileba writes:

This seems related something psychologists call habituation (defined as the diminishing of an innate response to a frequently repeated stimulus). I leaned about it from Daniel Cohen, the first economist I actually enjoyed reading (I recommend the books Prosperity of Vice, Homo Economics). Daniel Cohen mentioned that "habituation" is the reason why in some instances adding financial incentives makes people perform worse at a task.

He gives an example of a Kindergarten School experiment. The school had a problem with parents coming late. So the school said that for every time a parent comes late to pick their child they will be fined a certain amount (lest say $10 every time you come late to pick up your child). The result was that more parents actually came late to pick their kids.

The psychological interpretation might be that parents eventually valued money less than that coming late. So paying a fine made them feel like they have "paid off their sin" that is, the monetary fine erased their guilt.

Daniel Cohen also thinks we are all going to be immortal some day. Here is a nice podcast where he talk about his ideas.

Sep

12

Book Review by Victor Niederhoffer: The Math Behind the Music (25 Sept, 2006)

The Math Behind the Music (Cambridge University Press, 2006) by Leon Harkleroad, will be of interest to musicians, mathematicians and marketicians. In a form that is accessible to every layman, the author describes the elementary mathematical principles behind sounds, instruments, compositions and visual aspects of scores in just 135 pages with a nice section of references and an included CD that covers examples of music that used math. No background is required as even such simple lower-school concepts as the factorial are developed by counting.

The first chapter is about the connections, history, common abstract patterns, and the composers and compositions that used math. The second chapter is about the physical basis of harmony, pitch and timbre that make up music. Considerable attention is paid to the frequency relations of various harmonies, and it's a good refresher for those who don't remember off the top that a fourth comes from any note by raising its frequency by 4/3, a fifth by raising its frequency by 1/2 and an octave by doubling. Sine curves are introduced to encapsulate the frequency patterns of various notes produced at different pitches by different instruments. Overtones are explained simply as the ratios of higher frequencies that a note produces that don't block out the original frequencies and the relation between harmonies and overtones is shown.

The third chapter discusses instrument tuning systems consistent with all the overtones and frequency relations between the notes of a scale.

The fourth chapter is the most interesting in that it shows how themes and melodies can be varied with simple rules such as opposition, inversion, and transposition. The relation between these simple rules and group theory are examined, and various ways of notating and combining the rules are covered.

The fifth chapter is about bell music, which is merely a variation of permutation and combination theory.

The sixth chapter is about randomization in music, with many of the same methods used to construct music as we use for simple simulations in markets.

The seventh chapter is about an attempt by one student to find the common basis, the patterns of harmony that make up the most popular songs. The eighth chapter is about how scores of music can be developed from visual cues, with rules to go from visual to music.

The ninth and final chapter is about failed efforts to combine music and math, with particular reference to George Birkhoff's efforts to develop a complete theory of aesthetics by developing a scale of beauty based on the simplicity-to-complexity ratio of a composition.

I found myself thinking many times of the relations between music and markets as I read the book. The combinations of opposites and inversions (where the intervals above a note and played the same intervals below, and transpositions (where the same theme is repeated a given number of intervals up) happens every day in the markets. The notation that musicians have developed to grapple with these techniques, including the summary of horizontal and vertical movements in visual sightings that the composer Villa-Lobos used to construct symphonies that depict buildings in a city, seems like a very fruitful field to augment technical analysis of markets.

The book is full of anecdotes and charts and methods that will be right on the top of the page for market practitioners, and will spark many a fruitful extension by those who wish to take the pencil to paper, and systematize what they have been doing in markets or charting with the work of some great composers and mathematicians in this related field.

Laurence Glazier offers:

This sounds a fine book. Abstract shapes indeed can be used for thematic material, in my chess days I considered using the outline of pawn structures like black's in the Dragon Variation. My mentor uses the letters in his friends' names. Music is developed by changing patterns in various - ever-changing! - ways, whether transposition, inversion, speed-changing, and I would add to the list in the book the use of rotation, a technique Chris Sansom and I used in the Fractal Music software. All this (except presumably rotation) applies in trading. The issue is whether it is predictive for traders, and that is akin to trying to predict what a Bach would do, the patterns are especially evident once they have happened.

Asindu Drileba adds:

The work of Dmitri Tymoczko might also be interesting for those that want to understand the relationship between randomness and music.

Sep

2

Counting: Seasonality

September 2, 2024 | 1 Comment

A lesson from the archives: Seasonality and changing cycles, by Victor Niederhoffer and Laurel Kenner, (04/26/2004)

A good part of the anomaly literature is devoted to studies of seasonality. A basic problem with these studies is that merely picking a season to study involves making guesses as to when and where the seasonality is. For example, is it in January or December, on Monday or Friday, in the United States or the Ukraine? (Yes, our Google search turned up a study of anomalies in the Ukraine.) Thus, the very choice of a subject might involve random luck.


Another aspect of seasonality studies that must be considered is whether the effects noted are sufficient to cover transaction costs. A retrospective study showing that you can make 2 cents more on Friday trades than Monday trades in your typical $50 stock would not be sufficient in practice to leave anyone but the broker and the market-maker richer.

Thus, it's essential to temper the conclusions of such studies with out-of-sample testing — in other words, with real trading.

[ … ]

Comment by Philip J. McDonnell, a former student of the Chairman at UC Berkeley: Dr. Niederhoffer points out that there is no a priori reason to believe that any one day of the week is stronger than any other. Thus when Y— collected the data (thank you!), presumably the reason was to find out if any days of the week behaved differently. Only after peeking at the data was it possible to say that Monday was the best and Tuesday the worst.

There are 10 such pairwise comparisons:
Mon with other 4 days 4
Tues with 3 last days 3
Wed with Thu & Fri 2
Thu with Fri 1
Total 10

In other words it is also possible that Tuesday could have been the best day and Monday the worst or any other pairwise comparison by chance alone. So when the one best and the one worst day shown by the data are compared and shown to have say a 5% significance we need to remember that we implicitly ruled out the other nine cases which weren't the best or worst. So we need to take our 5% number and multiply by 10 to get the correct significance of 50%. 50% is exactly consistent with randomness.

The problem is multiple comparisons are often subtle and remain unrecognized. Multiple comparisons are insidious because they dramatically reduce the power of the statistical tests we employ.

[ … ]

[More reading: Multiple comparisons problem]

William Huggins offers:

Bonferonni method suggests raising the confidence level proportional to the number of tested hypotheses. To get 95% confidence despite ten tests, he suggests 99.5 as a threshold.  It's a huge problem when testing which variables to include in a regression model.

Asindu Drileba writes:

The right way to do this type of thing is to form a specific hypothesis based on a single comparison and then to test it on the data. It is even possible to use data from a prior period to formulate our hypothesis. We then test our hypothesis on the subsequent period which excludes the period where we formed our hypothesis.

This is an approach used in machine learning. Datasets are always split into "training" and "test" datasets. "Training" datasets are exclusively used to build the components of the model. "Test" datasets are not used to build the model at all. They are excluded when building the model. The model built using the "training" dataset is then asked to make predictions on the "test" dataset. The accuracy on predictions made on the "test" datasets is then used to determine how accurate the model is (so it can be tuned for improvement or thrown away).

I found this particular statement from the full post so insightful because I didn't think of applying this approach to building models using other statistical methods (I thought it was something limited to machine learning).

Aug

24

I remember an interview by Vic where he said he did a lot of "counting". Does he mean combinatorics? Or something else. What are some resources where he has talked about this "counting" in more detail?

William Huggins replies:

he literally meant count the data/do the math. at its most basic, statistics is about counting and comparing to the results we would have expected from randomness. too many people form their beliefs because they were told something, or were presented with cherry-picked "supporting" data so the chair's injunction has been to actually check before committing capital.

Zubin Al Genubi adds:

Count the number of: Private Jets, pretty girls, closed businesses, for lease signs, big market drops, increase in vix, number of down days, number of days since last high/low, volume of trades, bids, offers, crashes, all time highs, stocks at new highs/ lows, crosses of round numbers, cigarette butt length, change in price, etc etc.

Test: is number above or below mean/ median? How many standard deviations away from mean? What happened after the time of count?

Penny Brown adds more:

I'll add to the list: the price of thoroughbred horses sold at auction and the length of women's dresses. (long hem below knee is bearish as was style in 70s, short hem in mini skirts is bullish)

Asindu Drileba responds:

Thank you. "Test Everything" is definitely something that keeps coming up whenever I listen to the chair.

Humbert H. asks:

In all these years I could never understand how this approach can coexist with affirming the reality of the ever-changing cycles. Like how do you know when to trust this counting and when the cycles changed on you?

Laurence Glazier offers:

Music is the pleasure the human mind experiences from counting without being aware that it is counting.

- Gottfried Leibniz

Aug

5

From Cellular bet-hedging:

Today, we seek to gain some insight into how bacteria bet hedge. We will imagine that we are designing the stress response system for a custom, designer super-bacterium. Our goal is to maximize its survival and proliferation. To help it out, we provide it with an array of sensors, information processing circuits, and responses—exactly the sorts of circuits we have been studying.

A poor little bacterium doesn’t stand a chance of accurately predicting future temperature, salt, toxins, antibiotics, and attacking immune cells all by itself. Instead, it uses a form of biological bet hedging, in which the shared genome of a clonal cell population effectively spreads its bets, in the form of individual cells, across multiple physiological states, each adapted to a different possible future.

It is part of a larger course called Biological Circuit Design. I really don't like reading maths as I don't understand most of it. But fortunately, this course also has Python implementations for a lot of the concepts they outline.

Big Al adds:

You might also call this a good example of portfolio diversification.

The portfolio concept in ecology and evolution

Biological systems have similarities to efficient financial portfolios; the emergent properties of aggregate systems are often less volatile than their components. These portfolio effects derive from statistical averaging across the dynamics of system components, which often correlate weakly or negatively with each other through time and space. The “portfolio” concept when applied to ecological research provides important insights into how ecosystems are organized, how species interact, and how evolutionary strategies develop. It also helps identify appropriate scales for developing robust management and conservation schemes, and offers an approach that does not rely on prescriptive predictions about threats in an uncertain future. Rather, it presents a framework for managing risk from inevitable perturbations, many of which we will not be able to understand or anticipate.

— keep looking »

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