Aug

13

Hey friends. This has been a hard week and difficult to fully accept. So many things to write about Victor, but I'll pick just one small part to bring some levity and that is his sense of humor. Vic had a wicked sense of humor. It comes across particularly is his coded language and his voice that always carried a 40s Brooklyn accent. Here are a few that tickle me: "pretty kettle of fish", "gentlemen and ladies heal thyself", "haaaaaave" (for half), "fish dinner", "brisket at the petroleum club", "not bad for a poor speculator", "Ha!" (as a trade fills), "Mr. Coke", the tennis balls raining down on the roof, "Let's go for a walk". This last one really hits, I'll forever be taking walks with Victor and listening.

Steve Ellison responds:

The Chair’s invitation in 2004 to “join our group of scholars” changed the trajectory of my life. I treasure the many friendships I have from this List and have numerous anecdotes about Victor, but for the sake of brevity, I will confine myself to two instances from the economically depressed year of 2009.

In May that year, I went to a West Coast mini-Spec Party in honor of Kenny Sogi’s graduation from USC. The event was held at a beach house in Los Angeles County where James Tar was living. At some point, we decided to call the Chair in New York. For some reason, the most suitable phone for a conference call was in Mr. Tar’s car, so 12 of us jammed into the car to talk with the Chair. After we all identified ourselves, Victor asked, “What do you think of the market?”

One person after another in the car outlined his reasons for being bearish. After 5 or 6 people had had their say, maybe Victor was getting tired of the bearishness because he called on me by name. “Steve, you’re bullish, right?” I said that I was and cited a few findings from my counting studies.

In August that year, I went to New York for the smallest Spec Party I ever attended, I think between 20 and 30 people. While we were gathered in Victor’s living room, he asked us whether using stops was good practice. The conversation that followed, with everybody participating, was pure gold, a meal for multiple lifetimes.

Jul

15

I have always wondered to what extent a random walk with normally distributed steps would differ from a Pareto distribution with comparable means and third moments. I have never believed that stock prices are fractals or infinitely variance, or any way different from a shifting normal distribution or a mixture of same. The hazard rates of fall off for both distributions could be compared, and one would hypothesize that there would not be a observable difference.

Ralph Vince writes: 

Vic,

I have always agreed with precisely what you are saying. The "Pereto Explanation," does NOT explain market conditions changing; it is stationary. Clearly, those who posited that were naive when such might be better modelled by moving distributions (maybe even Cauchy distributions, where variance issues still persist).

However, when we speak of variance in returns, we must consider that the ntion of "infinite variance" is equally naive(!) as follows: What is varying is returns, specifically, today's price divided by some price in the past (e.g. yesterday for daily returns). Everyone seems to (conveniently) discount that these cannot go below zero. Thus, if returns were equivalently bound on the upside (at 200%) we could be certain that variance in returns was NOT infinite. Sine we cannot makes this assumption, we can only assume that variance can be infinite ONLY by upside moves of ever increasing maximum magnitude as we increase the window of time into the future.

We should be so lucky!

p.s. my own take on it is that we are dealing with moving distributions, likely Normal or at least where the variance is measurable and finite. The shape of the distribution, it;s moments, however, can move rapidly and without any warning whatsoever. price change, is just the single data point selected at that moment from such chrono-dynamic distributions, the real question pertaining to price change — and challenge — is to discern what that distributions is at the moment. THAT is the real price change, the solitary point witnessed, just a random manifestation of it.

Steve Stigler writes: 

On stock models: Some aspects of these models are driven by a wish for internal consistency, that the step distribution is the same (rescaled) for steps in minutes or hours, etc. And the steps are independent. These imply that the steps are "stable distributed", a class that includes normal and some heavy tail distributions. The reason is the central limit theorem (clt) - if the step for a minute was pareto with finite variance then the step for an hour would be the sum of 60 such and by the CLT approximately normal. If the step for a second is pareto, even more like a normal for an hour. So if you don't want a very complicated analysis the only choice with finite variance in normal, and if you take any other step dist for small steps the dist for large steps will be approx normal.

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