Daily Speculations The Web Site of Victor Niederhoffer and Laurel Kenner


Feb. 16-28, 2006


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Cycles, by Victor Niederhoffer

A letter from a man with a bearish position reached this desk recently, pointing out that in 2002, the market was down 23%. That's four years before 2006. In the year 1974, 32 years before 2006, the market was down 30%. Similarly, 40 years before, in 1966, the market was down 13%. The question emerges if there is anything inordinately bearish about these years that are two away from an even multiple of four.

Much additional commentary was contained in the letter concerning highs and lows during such years. However, since it is impossible to tell a high or low during the year until after it has transpired, and it is possible to define a high and low in many different ways depending on its severity, isolation, and duration, and the indexes themselves without dividends have a drift of 6% a year, and many other cycles of 3, 5, and 2 might just as easily have been hypothesized, leading directly to a situation where thousands of implicit hypotheses were in play, I focused on the main contention.

After all, if there's nothing unusually bearish about the 2002 plus four years to start with, then any ideas that one should look for special times to sell, thereby going against that 6% drift in normal years, would seem especially dysfunctional, regardless of how much the letter writer obviously wished for validation from my colleagues and myself, as well as the salubrious activities of any self fulfilling selling that presumably would be induced by our belief in the cycles posited.

Put another way, if someone tells you that he's bearish, the main decision that would be appropriate would be to sell. However, since there is a 10% drift to the market (including dividends), one would wish to have a fairly high degree of belief in the regularity or qualitative insights that engendered the bearishness to sway one rationally from the current level of stocks held long on which you presumably expect to make 10% a year from random selection. If the main thrust of that regularity doesn't hold water, then looking up a tree with 100 branches, twigs, and leaves for the one node that does support a bearish view would seem dysfunctional.

In order to shed some light on the basic contention I worked with Tom Downing to put some statistics on the table on this important matter. We started with the actual % price changes in the index to see if the terrible second years, of what others used to refer to as the good second year in the presidential cycle, was so terrible.

The results are as follows:

   t      r(t)    r(t+1)   r(t+2)   r(t+3)
 1950     23%      16%      12%      -7%
 1954     45%      26%       3%     -14%
 1958     38%       8%      -3%      23%
 1962    -12%      19%      13%       9%
 1966    -13%      20%       8%     -11%
 1970      0%      11%      16%     -17%
 1974    -30%      32%      19%     -12%
 1978      1%      12%      26%     -10%
 1982     15%      17%       1%      26%
 1986     15%       2%      12%      27%
 1990     -7%      26%       4%       7%
 1994     -2%      34%      20%      31%
 1998     27%      20%     -10%     -13%
 2002    -23%      26%       9%       3%
 2006      ?

Expected Returns as a function of Year Mod 4

Here are the means for the data above:

             t      t+1      t+2      t+3
average     5.5%   19.3%     9.3%     3.1%
stdev      22.4%    9.1%     9.7%    17.6%
max        45.0%   34.1%    25.8%    31.0%
min       -29.7%    2.0%   -10.1%   -17.4%

Note that the 2002, 2006 (mod 4) years go up about 59% of the norm. Even worse are the 2005 type years where the average was just 33% of the norm. Best yet, but apparently not of interest to a bear are the 2007, 2003, type years coming one away where the average is 205% as great as the norm.

Now what are the chances that we would find one of these four years  has a mere 5.5% average change versus the norm of 9.3%. Mr. Downing re-sampled the data above with replacement to get a bootstrap mean 9.3% and bootstrap standard error of 4.3%. Given these estimates,18% of such realizations of yearly performance figures would give a return of 5.5% or less (corresponding to a z of -0.90). But remember that there are four years we could choose from to find a low z. For one of them not to have an 18% chance of an event of that negativity to occur, four events with a chance of 82% would have to show a z of greater than -0.90. That chance is 0.82 to the fourth, or 40%. Thus, it's 60% that in looking for four-year cycles that we would find at least one of the years with a z of that low, or a low change of 5.5 % or less.

Regrettably, the situation is even less favorable than 4 in 10 that the result is not in accord with chance, as one could just as well have looked at three-year cycles, five-year cycles etc. None of these as Mr. Downing calculated have even a semblance of non-randomness about them. Indeed, they cluster much closer to randomness with no numbers sticking out.

I presume that the author of the letter would not be interested in the analysis of whether the 2007-type years are inordinately bullish, because that might upset the tenacity with which he holds to his short position in 2006, knowing that he is staring in the face of a rise of twice the usual in 2007 corresponding to a z of 2.3.and a probability of 0.01 of this large a change by chance factors alone on this one instantiation. Below are some statistics that Mr. Downing created from his simulation.

Implied t-statistics for the four groups are:

           t      t+1     t+2     t+3
Implied  -0.90    2.33   -0.01   -1.47

For example, for the first group, the mean
was 5.5 percent; implied t-stat is calculated
as (5.5 - 9.3)/4.3 = -0.90.

Performing same exercise for 2,3, and 5 year intervals:
2 Year Cycles:
mean      7.4%   11.2%
implied  -0.66    0.57

3 Year Cycles:
mean      7.7%    5.4%   15.1%
implied  -0.43   -1.02    1.45
5 Year Cycles:
mean     14.2%    8.9%    3.5%   12.0%    8.5%
implied   1.00   -0.09   -1.17    0.54   -0.16

As the artful simulator states, in general, there is less evidence for two-, three- and five-year cycles than for four-year.

One use of this study, aside from providing a rudder for any open-minded readers who are trying to see the plain natural state of affairs, would be to test whether there are any moves from year one to any other years that might be consistent with any non-random regularities that would be sufficient to change the basic belief of a steady 6% drift. Another use would be for those positing yearly cycles of any other kinds, for example, the oft-repeated four-year presidential cycle that so many believe in as an article of faith would be to use the benchmark simulation mean and s.d. figures above as a guideline for proper levels of confidence in hypotheses relating to other regularities.

I would hope that these statistics on the table would prevent many others from being snatched by any who would appeal to them based on very special bifurcations of the data, multiple hypotheses, selective reporting of results, withholding of evidence against the hypothesis, non-falsifiable assertions, slippery obfuscations, et al.

On another front, the hypothesis advanced was very fruitful in eliciting considerable creative work that should be a model for those who in the future wish to have a solid foundation in considering yearly moves and or a barrier for those not wishing to be snatched.

Every day for 40 years, Darwin walked a half-mile or so through the tangled bank of a cleared sand walk on his estate at Down, frequently stopping to examine the insect and plant life surrounding the garden. Doubtless he generated many hypotheses related to the study of corals, barnacles, finches, worms, and man on these walks. On those occasions when I am not on strike out of disgust with how wrong and how harmful the columns of their resident chronic pessimist is, I get the same pleasure from reading Barron's each week that Darwin did on his sand walks. It is a source of never ending hypotheses about influences on markets, corrections to shibboleths being unloaded on the public, and constant amazement at how off key all their articles are.

Let's take the Feb 20, 2006 issue as an example. Alan Ab#lson is on vacation this week, but there is a big feature on Technical Analysis in his stead entitled, "Is this market set to stumble". There they feature Walt Deemer, a friend of Frank Cross, who is Loaded for Bear. He's bearish about the yield curve, the chances of a recession, the optimism of investor sentiment ("The Psychology seems to be one of predicting another drifting-up year"), the concentration of the Fidelity sector funds investments in energy, the break in energy indicating a top on a cyclical bull market, the attractive alternatives of a 4.7% return on cash, a top pattern since mid-November, the concentration in Rydex funds, the number of days from a four-year cycle low, the vulnerability of emerging markets, and the vulnerability of Nasdaq. The market is due to show a four-year cycle decline "I'm surprised because in a normal four-year cycle, (that) has worked since the end of World War II, and when something works as long as that, you have got to believe in it, the market goes up for little more than two years, and then goes sideways as it forms a top." Let's stop there. While Deemer says that history says that he's right, I say that all his observations that are quantifiable are completely consistent with chance, and the rest are card stacking .

Let's take the Nasdaq. Here are year-end prices for Nasdaq since its start in February 1985 at 125:

    1985  132      1986  141     1987  156      1988  177
    1989  224      1990  200     1991  331      1992  360
    1993  398      1994  404     1995  576      1996  821
    1997  991      1998 1836     1999 3708      2000 2341
    2001 1577      2002  984     2003 1468      2004 1621
    2005 1645

During the period, Nasdaq 100 has shown a 12-fold increase with 4 declines out of 21 moves. A run of 5 rises was followed by a run of 1 decline which was followed by a run of 8 rises which was followed by a run of 3 declines, which has been followed by a run of 3 rises. Now, I ask "Where is the four-year cycle?" Similar objections, and the query "Have you tested this?" can be made to at least 40 other shibboleths in the current issue of that paper.

Many thanks to Tom Downing, the artful simulator, for performing the simulations and sharpening the tests.

Derek Gard comments:

To test Mr. Deemer's claim that there is a 4 year cycle, a test was conducted looking at the 48 month correlation. Basically the idea is that if such a cycle exists then this month's net change will be correlated to the net change from 48 months ago.

This is not what the 4-year cycle claims and the test devised is erroneous because it tests a premise that is never claimed by the theory of a 4-year cycle. One cannot discredit a theory by testing against criteria that are not the basis of the criteria.

Now, to look at what the 4-year cycle actually claims: there was a significant market bottom in the fall of 2002, 1998, 1994, and 1990. Also, the start of another rally began in 1986. Oh yes, 1982 was also a significant bottom for the market. There was a small opportunity to invest in stocks in 1978. 1974 marked a major bottom, and so did 1970. Let us see; there was a multi-year low in 1966 and also in 1962. In 1958 the low point was in the spring, not the fall, but it was still in that 4th year.

So during the investing careers of most of the people on the List, the 4-year cycle appears to have been pretty accurate. Only 1986 was not a major bottom for the market, and only 1958 saw that bottom not occur in the fall.

The Search for an N Period Cycle, by Victor Niederhoffer

We have received an unusually high volume of varied opinions regarding the assertion posted by Derek Gard and the general topic of cycles. While we don’t condone or approve all of the methods, comments and tools mentioned, the myriad of viewpoints adds to the richness of the discussion.

Let us not forget that anyone who considers an important question like this must:

  1. Define his terms.
  2. Report the variability of his results.
  3. State his theory in a testable fashion.
  4. Consider the accord of the theory with randomness or in this case a random walk with a drift of 6% a year.
  5. Report specific results of the theory that can be tested with statistical methods and make specific predictions for the future that can be refuted or confirmed.

Lastly, one would have to determine some sort of significance level that would change one's decisions and report the number of theories that were implicitly or explicitly thrown out before settling on this specific permutation of the years and starting and ending points. The acceptance of authority on faith is a road to ruin.

GM Nigel Davies replies:

There was an attempt by a Brian Millard to calculate cycles by subtracting moving averages of the number of days in proposed cycle lengths. I understand that he didn't become rich from this method, though I do like the Britishness of the thing. It reminds me of the days of the Empire, the stiff upper lip and the chess of players like Harold Bird, Sir George Thomas and Sir Stuart Milner Barry. Damn it Sir, I wish those cycles would behave!

Dr. Phil McDonnell cautions:

Subtracting a moving average is a bad idea when looking for cycles. The technique can create an artificial oscillatory effect even when no cycle is present in the data via the Slutzky-Yule effect. So this technique cannot be used to prove the existence of a cycle.

The other thing that can happen is that the artificial oscillations can cancel out any natural cycle in the data causing it to disappear even if it was present in the original data. So this technique cannot be used to prove the non-existence of a cycle because of the cancellation issue. It is simply a flawed technique and should be avoided when doing any work involving cycles.

Having said that I still agree with the conclusion - there is no 48 month cycle. However that assertion has to be demonstrated by a different technique.

Alston Mabry contributes his study results:

Looking at S&P daily from 1950, I calculated the return for the next 250 trading days. Then I pulled out the days that were 250 trading-day lows, i.e., close<(lowest close previous 250 trading days). That gave me 248 days out of 13,623. To reduce overlap and try to create a practical ex-ante system, I dropped those 250-day low days that followed other 250-day low days within a 1-month period. So, you'd buy a 250-day low, but then not buy any other such lows that occurred within the next 20 trading days.

All days- count: 13623, mean return next 250 days: +8.80%, stdev: 15.77%

250-day lows (reduced overlap)- count: 40, mean return next 250 days: +9.47%, stdev: 20.21%, z: +0.27

But what about eliminating the overlap restriction and just buying all 250-day Lows?

250-day Lows (overlap allowed)- count: 248, mean return next 250 days: +12.54%, stdev: 18.93%, z: +3.74

Which brings up the question of solitary 250-day lows: How many 250-day lows were there, that were neither preceded nor followed by another 250-day low within 20 trading days?

solitary 250-day lows- count: 4, mean return next 250 days: +8.12%, stdev: 17.44%, z: -0.09

Which inevitably makes one ask: After encountering a fresh 250-day low (i.e., no other 250-day low in the preceding 20 trading days), what is the average density of 250-day lows in the following 20-day period?

250-day lows in 20 t-days after fresh 250-day low- mean: 3.825, stdev: 2.881

And just for kicks: What about buying only 1000-day lows?

1000-day Lows (overlap allowed)- count: 33, mean return next 250 days: +22.80%, stdev: 11.04%, z: +5.10

Unfortunately, these are the only dates you would have bought in (but they are 4-year cycle years):

21-May-70	23-Aug-74	1-Oct-74	23-Jul-02
25-May-70	27-Aug-74	2-Oct-74	7-Oct-02
26-May-70	28-Aug-74	3-Oct-74	9-Oct-02
13-Aug-74	29-Aug-74	2-Jul-02	
14-Aug-74	4-Sep-74	10-Jul-02	
15-Aug-74	11-Sep-74	15-Jul-02	
16-Aug-74	12-Sep-74	16-Jul-02	
19-Aug-74	13-Sep-74	18-Jul-02	
21-Aug-74	27-Sep-74	19-Jul-02	
22-Aug-74	30-Sep-74	22-Jul-02	

John Bollinger comments:

Perhaps I can pose the situation this way. Derek asserts that there is an exploitable four-year cycle. The chairman asserts that there is not. The hypothesis is thus that there is a four-year cycle and the null hypothesis is that there is not. Professor Pennington showed that such a cycle can be very roughly modeled using a model that is extremely sensitive to permutations in its parameters. (Small changes in the length of the countdown sequence and/or the count up sequence produce large linear changes in model output.) To me, all that is proven is that a model can be constructed that produces 253 25-month centered minima in a 10,000-year sample. Those more learned than I will undoubtedly understand the implications of the fact that the model output is almost a perfect artifact of the twice the window length.

Bruno argues for a MESA spectrum analysis. I assume that he is using John Ehler's MESA program. Unless I am mistaken, MESA is very sensitive to wave form and would have trouble spotting a cycle that is not at least roughly sinusoidal in wave form. As the alleged four-year cycle does not fit that description I wonder if the output relates to the question.

James Sogi opines:

The question statistically is whether the putative four-year cycle is a random occurrence. To reject that, there would need to be a sufficient number of occurrences in which the four year cycle predicted the subsequent return. The mean and distribution of those sample occurrences based on the four-year predictions would need to be distributed 2 standard deviations away from the population. The analysis can be done using a sample distribution or linear regression. Regression allows some additional analysis to be done on the fit.

Professor Pennington's example that a random drawing results in three- or four-year cycles is saying that if it happens at random in a random sequence, it is not likely to be significantly distributed. Thus the null hypothesis would not likely be rejected. Unfortunately the problem is that there are not enough four-year periods in modern data to make a good statistical test from the actual data. So the researcher must resort to Monte Carlo modeling to get a probability distribution and do the random sampling 10,000 times using the same mean and variance as the actual data. The central limit theory says that as N approaches infinity, the mean and variance of the proposed 4 year cycle will converge on the true mean and variance. This will give a larger population from which to calculate one’s test statistics and calculate whether the 4 year cycle is random or a significant anomaly that justifies rejection of the null hypothesis. Professor Carmona provides some leads on how to do this using S&P data and R.

While there may be fundamental arguments favoring a four-year cycle, statistically the null hypothesis cannot yet be rejected.

David Wren-Harden clarifies:

I think one source of confusion is to use words like "significant market bottom." To the statistician, this word, "significant", implies that tests can be applied to the statement to test for statistical, well, significance. If 1982 was a better year to invest than say, 1981, then the return from 1982-1986 should correlate better than 1981-1985; the four year cycle-low should be a better predictor of investment success than other years.

I think it would help if one would define the numerical steps to assess that a bottom is "significant." Also, how much larger is a "major" bottom than a "minor" one.

Steve Ellison adds:

My approach to this question was to evaluate the average value of the S&P 500 index relative to a four--year centered moving average. I have three major concerns with this question:

  1. Sample size: must necessarily be small
  2. Relevance: to get a sample size of even 10 requires going back 40 years. The behavior of the stock market 40 years ago, even 20 years ago, has very limited relevance today
  3. Drift: does the upward drift negate any demonstrable down cycle?

I began by calculating the yearly average of the S&P 500 index from 1950 to 1985, which allowed me to construct 4-year centered moving averages from 1952 to 1983, a period encompassing eight 4-year periods. I then divided each yearly average by the centered 4-year average and grouped the results by the remainder of the year divided by 4.

Average this yr/ mod ctrd avg stdev t score 0 1.0498 0.0477 2.95 1 1.0180 0.0653 0.78 2 0.9104 0.0364 -6.97 3 1.0062 0.0588 0.30

There appears to have been a highly non-random tendency for year 0 to be above the centered 4-year average and for year 2 to be below the centered 4-year average. All eight 2-year average prices were below the 4-year centered averages. However, because of drift, the average price change from year 0 to year 2 was approximately zero.

Next, I reviewed average prices from 1982 to 2005 to evaluate whether the earlier results held up. This second sample includes five 4-year periods.

Year in Average this year/ Cycle ctrd avg stdev t score 0 0.9895 0.0942 -0.25 1 0.9899 0.0401 -0.56 2 0.9637 0.0532 -1.52 3 1.0021 0.0910 0.05

The year 2 relative weakness is much reduced, but still present at about a .20 significance level. However, in the more recent period, the weakness was only relative and could not overcome the upward drift. Indeed, the average prices in 1986, 1990, 1994, and 1998 were all higher than those in the previous year; only 2002 was lower. The year 0 relative strength has disappeared entirely.

Dr. Phil McDonnell provides an extensive teach-in:

Hypotheses and Near Periodic functions- There are a number of assertions made in our current discussion on cycles which merit scrutiny. First I would like to offer one definition of what a classical cycle is. The formula can be written:

y = a * sin( wt + p )

where: a = amplitude w = period (usually denoted omega) p = phase y = output function (for markets usually price or price change)

Amplitude measures how high the waves get and can be thought of as the strength of the signal. Period is how long it takes a cycle to complete. Note that frequency is the reciprocal of period. So a cycle with a period of 5 months has a frequency of: 1/5 = .2

The phase is a constant which shifts the entire cycle to the left or right by a fixed amount. It can be thought of as "where a cycle starts". The above is not the only way to write a periodic formula or even to express Fourier terms but it is preferred because each parameter has a nice physical meaning which can be seen on a graph of the sine function. A remarkable result of mathematics is that you can represent a Fourier series as a sum of sines and cosines, OR as a sum of exp(t) to a complex power OR as sums of autocovariances. All three forms look completely different and yet are all the same. For me the simplest sniff test for a given cycle length is to look at the autocorrelation at that lag. If there is no positive correlation then the cycle is almost certainly bogus.

FALLACY. A common fallacy is that Fourier transforms can only be used to describe periodic functions. That is not true. They can describe any function over an interval to an arbitrary accuracy. The reason is they are orthogonal functions.

REGRESSION. You do not hear much about trigonometric least squares regression. There is a good reason for this. After you have done a Fast Fourier Transform (FFT) in order to turn it into a regression all you need to do is truncate. That bears repeating - just lop off some terms of the FFT sum and what is left will be a least squares solution. Once again it is guaranteed by orthogonality.

STRICTLY PERIODIC. One thing missing from our discussion of cycles was a proper definition of a periodic function. Here is mine:

f( t ) ~ f( t + n * p )

where: f( ) is some arbitrary function or set of data points t can be thought of as time or simply the x axis p is the period of the cycle n is some integer number of cycle periods of displacement from t ~ can mean equality or it can simply mean "is related or correlated"

The above strictly periodic definition was assumed in my earlier post and I believe in the minister's first posts on the subject. Believers in cycles often claim that they exist but do not follow exact periods. Lack of strict periodicity does cause problems for FFT and autocorrelation analysis. To this end one might propose a definition of a near periodic function.

NEAR PERIODIC. The following are some possible definitions of a near periodic function:

f( t ) ~ f( t + n * p + e(t) ) Phase shifted near periodic function

f( t ) ~ f( t + n * p * m(t) ) Period varying near periodic function

where: e(t) is a presumed small phase shift constant varying with t m(t) is a period dilating multiplier varying with t

Note that m(t) is presumed to be a number quite close to 1 which acts as a multiplier to stretch or shrink the period.

One problem with near periodic functions is that there is no well developed theory to analyze them. As Dr. Ryan pointed out the entire function should be analyzed to be considered true cycle. Ad hoc methods such as counting from salient bottoms or tops do not cut it either mathematically or statistically.

This begs an even greater question. What good is a cycle which varies in period? If you cannot rely on the cycle to follow its supposed course, how can you trade it? If the autocorrelation is negative then why would one wish to invest real money in a strategy which on its face would apparently lose money? The answers to these questions are the answers to the parable of the thermometer.

HYPOTHESIS TESTING. Defining a good hypothesis is at the heart of any statistical endeavor. As applied to markets the null hypothesis should ALWAYS be some variation of the random walk or the "no one can predict the market" hypothesis. This choice is inextricably linked to the issue of burden of proof.

AN ASSERTION DOES NOT A HYPOTHESIS MAKE. Suppose I make the assertion that every day I see crows on my lawn, the market goes up. In everyday parlance someone might call my assertion regarding crows an hypothesis. But statistically speaking it is not a good null hypothesis. Just because I made a claim or have a theory does not make it a good null hypothesis. My novel claim should be the alternative hypothesis.

Suppose I (erroneously) took the crow hypothesis as my null hypothesis and the random walk as the alternative. I gather some data and find that the results are quite random so the "alternative" hypothesis of the random walk cannot be rejected. Now I am in the silly position of accepting the claim that crows predict the market because their predictions appear to be random!

The clear way out of this logical dilemma is that the null hypothesis should always be the random walk and any claim of predictability must be the alternative. This shifts the burden of proof to the claim that somehow we can beat the market.

John Bollinger adds:

A perfect four-period cycle would spend two periods rising and two falling. In the presence of a trend 'translation' may occur. For example in the presence of a strong up trend, the cycle might translate to three periods rising and one period falling. Edward R. Dewey, among others, has written about this. This is important, as most cycles analysis tools--Fourier, MESA, etc., work best with roughly sinusoidal wave forms, which we rarely encounter in finance.

Dr. Phil McDonnell continues:

Fourier analysis can fit ANY set of data points to arbitrary precision. The underlying data need not be sinusoidal at all. Nor is there any need for symmetry in the sense of spending equal amounts of time above and below the zero line. Remember two of the common ways of dong Fourier analysis involve no trig functions at all - the auto-covariance way and the exp() way.

If you do not wish to use the Fourier terms to fit the supposed trend then the data should be de-trended first preferably by differencing (net change instead of price levels). Alternatively a linear regression can be performed and the residuals fed to the Fourier analysis.

John Bollinger comments:

A perfect four-period cycle would spend two periods rising and two falling. In the presence of a trend "translation" may occur. For example in the presence of a strong up trend, the cycle might translate to three periods rising and one period falling. Edward R. Dewey, among others, has written about this. This is important, as most cycles analysis tools--Fourier, MESA, etc., work best with roughly sinusoidal wave forms, which we rarely encounter in finance.

Dr. Phil McDonnell adds:

To test Mr. Deemer's claim that there is a four-year cycle, a test was conducted looking at the 48-month correlation. Basically the idea is that if such a cycle exists then this month's net change will be correlated to the net change from 48 months ago. The test was done for the most recent 300 full months. If such a cycle exists then we would expect the correlation coefficient to show a statistically significant positive correlation.

However when the test was conducted the correlation was found to be -2.92%. The number is not significant but more to the point it is the wrong sign!

The recent rise in GOOG coincided with the delivery of the latest issue of Time magazine into millions of mail boxes. The issue features a flattering cover story and interview with the Google triumvirate.

The Minister stresses:

I don't really understand why Dr. Phil's correlation study didn't settle all this; not only was the correlation between the returns of month N and N+48 small in magnitude, but it even had the wrong sign.

Still, attached is a gif file showing the magnitude of the Fourier transform of the last 512 monthly S&P returns. (I have subtracted a constant drift of 0.72% from all the returns.)

If you thought that the graph was the Fourier transform of an electrical signal, you'd assume that you were just seeing noise. There is a peak around 48 months, but also peaks of similar magnitude at 25, 13, and 5 months.

Here I took the last 512 actual S&P monthly returns and added an artificial sine-wave variation that would correspond to a + or - 30% variation in the S&P level with a period of 48 months.

You'll see that an artificially added term of this magnitude results in a very big peak in the Fourier spectrum.

The fact that we see nothing anywhere nearly that big in the Fourier transform of the actual S&P data tells us that if there are any coherent oscillations at period 48 months, then they must be correspond to an S&P level fluctuation of much less than 30%.

Tom Ryan replies:

The problem with all of these studies, including the minister's, is that you are using statistics that are geared to studying processes which have an absolute frequency, that is, you are assuming an absolute frequency and then testing for the null hypothesis for that particular frequency. However, there are many processes in nature that do produce definable cycles which have variable frequency and amplitude (non-periodic cycles). Non-periodic cycles have an average frequency rather than an absolute frequency. Glaciation is a good example as well as sun spots, volcanic eruptions, varves in lake sediments, fossil counts in many sedimentary beds. The best way to test for non-periodic cycles in a time series is the use of rescaled range or R/S to find deviation from the pure Hurst process. As discussed by Mandelbrot, cycles can occur in a pure Hurst process due to random exogenous events. This is what Hurst called the joker in the pack of cards effect; just because it might appear that there is a repeating pattern of cycle highs or lows (however you define them) when you plot the data series over time, that does not mean that a cycle exists. For cycles to exist the entire cycle (not just arbitrarily selected lows or highs) must show some dependency to previous data.

If you have enough data, even if there are jokers in the deck that give you the appearance of cycles, the data set can still scale in time indefinitely and the log(R/S) plotted against Log(n) will scale at some Hurst coefficient indicating that no real cycles exist. If however, there is true memory in the series, there will be deviations in the scaling at the average non-periodic cycle length. This is discussed in papers and books by E. Peters, A. Lo and others and has been a subject on the list before.

Peters published some interesting work on non-periodic cycles in the early 1990's where he tested the daily Dow Jones industrials for the period of 1888-1990. In this analysis, he tested 1, 5 and 20 day return data sets and found deviations from the fractal scalings at n=1250 for the 1 day returns, n=208 for the 5 day returns and n=52 for the 20 day returns. This consistency (1250, 1040, 1040) suggests that there is indeed some evidence for a non-periodic cycle with an average cycle length of 1040-1250 trading days in that particular data set of the Dow. However, the same methods applied to the S&P500 for the time period of 1960-2000 by me did not show any consistent evidence for a similar cycle. And the tick data Peters analyzed for the S&P500 scaled indefinitely (Fractal with H=0.6) when he looked at 3, 15, 30 minute data for the period of 1989-1992.

The problem is that if the average non-periodic cycle length is highly variable, it can take a very large data set to find the average non-periodic cycle length and with economic data we are always faced with the Baconian principle of ever changing cycles at work. Hence we have a catch-22 when applying this type of analysis to stock market data.

Also there is this which I sent to the list two years ago - the Renyi entropy is another way to look at autoregressive processes especially where there might be non stable oscillations like with tick data. We have been using Renyi entropy in rock structure problems.

Bruno Ombreux posits:

When it comes to identifying cycles, shouldn't we be using the same spectral analysis tools as the scientists that study cycles? We don't need to be specialists of the underlying theories. Just as we don't need PhDs in thermodynamics to drive cars with combustion engines. Scientists are using FFT, MEM...I don't see why we should use any other method than the ones that are widespread in the scientific community.

The Numerical Recipes book also provides C sources for the MEM. According to it, the particularity of MEM over FFT is that it detects very sharp spectral features. It also needs less data to give usable results.

The book also mentions the Wiener-Khinchin theorem. The Fourier transform of the autocorrelation is equal to the power spectrum. This emphasizes the very tight links between spectral analysis and time-series analysis. They are more or less the same thing, but one operates in frequency space and the other in time space. Therefore, a classical autocorrelogram should do the job too. This considered, I looked at the autocorrelation function plot of Monthly SP500 since inception.

There is nothing showing around the 48 month period. There are two interesting coefficients at lags 5 and 39.

Ljung-Box p-value at lag 5: 0.15 Ljung-Box p-value at lag 39: 0.72

Unfortunately, the first result is not very significant. The second one is at a far lag at which such tests results are dubious (loss of power). They are also unexplainable. One cannot trade those things which are probably artifacts and not significant enough.

I think the MESA software is pretty good at detecting cycles. Bias is taken care of in all these methods since they always start by de-trending the series to make it stationary. Is the variable slowly changing periodicity? If so, the answer is that the software is good at detecting this through color coding of cycle energy at each time t. This is a very nice representation of changing cycles. Seismic software uses the same type.

However, this software is TOO good at detecting cycles. It will find a lot of spurious cycles. This is due to the maximum entropy method, and explained in the Numerical Recipes chapter I referred to. As they suggest, it is best to use a second, less brutal method, as a check against spuriousness.

Allen Gillespie draws parallels:

A musical equivalent to a cycle would be the round, however, some interesting music grew out the physics of tape. If two identical tapes are played, they will eventually become out of phase. This led to the writing of some interesting phase music which starts as unison, becomes dissonant, harmonizes, dissonant, and then resolves back to unison. If a cycle is a circle there is no beginning or end. Philip Carret wrote it best, "There never was a time when every possible circumstance favored a rise in security prices nor, on the other hand, a time when every possible circumstance favored a bear market. The most that can ever be said is that the balance of factors favors an upward or a downward movement."

That said if there is a cycle to the market, and if the NBER is correct, then a forward estimate for a peak would be sometime this year at 63 months from March '01 in Jun '06 and 67 months would be Oct '06.

Derek Gard observes:

Looking at a chart of the DJIA shows the 4-year cycle rather plainly. Are there other opportunities to invest in the Market at bargain prices? Yes, 1987 comes to mind immediately. However, the fact that there are other years with marked bottoms does not negate the fact that the 4-year cycles delineated in my previous post were not also excellent opportunities.

The 4-year cycle lows examined are preceded by an average decline of 23.7%. Remember, the average gain off those lows has been 58%. I think it is interesting the 4-year cycle lows preceded by the smallest declines were followed by the largest rallies.

Have there been other equally profitable opportunities in the market during the time period in question? Yes, the aforementioned 1987 was one. But I see no others that appear "with the regularity of the seasons."

Perhaps, instead of trying to show how statistically insignificant these cycles are, we would be better served to remember the KISS principle and try to discover a way to recognize the low point opportunities during these 4-year cycle targets. No one has been able to foresee the opportunities presented by years like 1960, 1987, 1997, or 2003. The fact these other buying opportunities exist does not negate the existence of the buying opportunities presented on the 4-year cycle target dates. But we do seem able to rely on the regularity of the 4-year cycle, so perhaps that is where we would best be served to focus our attentions.

GM Nigel Davies follows up:

Addressing the prior post, how does one know what the 'target dates' are within the proposed methodology? As far as I can see the buying and selling points (i.e. the highs and lows) were only decided in retrospect.

OK, here's a live challenge. Let's say that one sold in 2004 or 2005 in preparation for the cycle low, and let's give one the benefit of picking the absolute top from these two years on December 14th 2005. How exactly will one be making the decision to buy in 2006?

The Minister states:

Now we have a more quantitative statement of what the phenomenon under discussion is supposed to be. I will state it as concisely as I can:

"The moves to the retrospectively known lows in years 2002, 1998, 1994, 1990, etc., from the retrospectively known highs at any time within the two prior calendar years, is anomalously large and negative."

Going back to 1952, and looking at ALL years, the statistics for the move from the previous two years' high to this year's low, are given by:

ALL Years- average -10.6%, std dev 12.6%, count 54, standard error 1.7%.

Now, for the years 2002, 1998, 1994, 1990, etc, the stats are: average -19.1%, std dev 15.6, count 13, standard error 4.3%.

So yes, the 2002, 1998, 1994 etc. series displayed somewhat bigger than average declines.

How likely is this to have happened by chance? Well, the difference in the two averages is 8.5%. The standard error for that difference is sqrt(4.3^2+1.7^2)=4.7%. And so 8.5/4.7 is equal to 1.8, and that can be interpreted as a t-score for our confidence that these two numbers are different with statistical significance. That t-score corresponds to something like a 1 in 10 chance that the numbers would be different due to randomness alone. At first, that sounds pretty good.

BUT, consider how many hypotheses we've considered. At least 4, because we could have hypothesized that instead the series 2001, 1997, 1993, 1989... was the one, or 2000, 1996, 1992, etc. If we test all four, there's a very high probability that at least ONE of them will differ from average with a t-score of something like 1.8 or more.

But there are more possible hypotheses. We could have tested 3-year cycles or 5 year cycles, and I haven't heard any a priori reason why 4 years is special.

Considering all the other equally valid hypotheses that one could have made, an effect of the magnitude that we see here was bound to happen from randomness alone.

I would say that the finding amounts to nothing more or less than the observation that there were big declines in 2002 and 1974.

The maxim "KISS" doesn't absolve one from doing some kind of basic analysis of the possibility that one's effect arise from randomness alone. Einstein said something like "Keep it as simple as possible, but not simpler!"

Denis Vako adds numerical data to the discussion:

If there is any regularity ACF shall catch it; ln diff. monthly DJIA since 1930 or ln diff. monthly S&P500 since 1950 indicate that ACF & PACF are significant at lag 5 only; any other lag is not significant; it proves that we do not have 48 months regularity in either of the above.

Estimated Autocorrelation for DJIA monthly since 1930s

                        Lower95% Upper95%
Lag     Autocorr   StdEr    Prob     Prob
       1     5.6     3.3    -6.5      6.5
       2    -0.5     3.3    -6.5      6.5
       3    -7.7     3.3    -6.5      6.5
       4     4.7     3.3    -6.5      6.5
       5    10.1     3.3    -6.6      6.6
       6     0.3     3.4    -6.6      6.6
       7     2.5     3.4    -6.6      6.6
       8     2.6     3.4    -6.6      6.6
       9     5.8     3.4    -6.6      6.6
      10     1.3     3.4    -6.7      6.7
      11    -0.4     3.4    -6.7      6.7
      12     1.5     3.4    -6.7      6.7
      13    -1.8     3.4    -6.7      6.7
      14    -6.2     3.4    -6.7      6.7
      15     1.8     3.4    -6.7      6.7

Dr. Kim Zussman reminisces:

As a bookend for this fine shelf, one recalls younger days as a gonzo mountain biker. Here in California there are many wonderful trails with beautiful oak canyons filled with delicate fawns, elderly Sierra Clubbers, and others eager to bowl with jolting man and machine at 20 mph.

The best trails are single track, in that they are narrow and twisty, and require technical skill (foresight, balance, composure, testosterone) to navigate at speed. When rolling rapidly down these paths, especially for the first time, it plays out as a series of obstacles and rapid adjustments. Some of it can be anticipated, like that boulder up there or this tree across the stream. Others you don't see until you are right on top of them; drop-offs, ruts, and dead mountain bikers.

The best riders know how to anticipate terrain and adjust speed for the probability of risk ahead, and when inevitable surprises arise adjust accordingly. They get to the bottom first with little blood.

Which leads one to wonder how is it possible that all the FFT and MESA analysis missed a very regular, predictable, cyclic drop. Not at 4-years, but yearly; when the monthly series that usually increases monotonically drops at the same time every year, always around the holidays.

Derek Gard clarifies his position:

How exactly will you be making the decision to buy in 2006?

The term "target date" refers to the year, not a specific date. I have not stated that I know how to tell when the bottom is. In fact, I indicated I believe this is a good place to place our focus; i.e. trying to determine when an entry should be made. But my inability to discern that entry point does not negate the fact an entry point still existed. Ignorance of how gravity works does not mean gravity does not exist.

First we should clear up a point or two. The 4-year cycle does not state when a top should occur. It simply states that every 4 years an opportunity to enter the market on the long side is presented to make above average gains in the market. The average gain in the DJIA is reportedly about 10.6%. So in two years, one could expect, on average, to be up 22.3%. Yet, we have seen the entry points on the 4-year cycle bottoms has yielded an average gain of 58% in 18-24 months. Returns that are more than double what the average year has yielded are worth taking note of. The average decline going into the 4-year cycle low was 23%. I do not think anyone would say this is not an opportunity. Is the average decline going into any year 23% on average? Actually it has not been, so once again the years labeled as the 4-year cycle lows present themselves with an opportunity that is not presented in most years in general.

Now to look at the reality of using other years, let us see what happens if, for example, we shift one year from the 4-year cycle. I do not know what the results will be as I write this, but I am willing to take the egg on the face if it proves to offer better returns.

Examining the years from 1957 onwards, the average return is 45%. That is less than using the 4-year cycle method by 13 percentage points. If that is a significant difference or not, I will leave each person to decide on their own. I think it is, and this would show that one cannot just use any year's low and project out 2 years later and achieve the same type of returns the 4-year cycle has achieved from a historical perspective. Also note that, while buying at the low of the 4-year cycle bottoms given in the previous postings, during none of them would one have had to wait out a decline that many times took the market to a point lower than the entry points. So this mock 4-year cycle would require conviction to hold on no matter what in order to reap the gains. The other program does not require such faith in the system.

To the point that we are looking at the past which is known; that is true. But all patterns are discerned after they have been active for a time. It is not a pattern until it is recognized in retrospect. Since we can see this pattern working in the past, and working on the premise those who ignore history are doomed to repeat it, we can make an assumption the pattern will continue until it does not. Winter comes about the same time every year. Sometimes it begins snowing in October, sometimes November, sometimes as late as early December, but we can still make a pretty safe bet that next winter there will be snow. The inability to predict exactly when snow will fall does not invalidate the pattern that snow will fall.

From the Ministry of Non-Predictive Studies: Unchanging Cycles, from Dr. Kim Zussman

At the end of every SP500 monthly close since 1950, one asks if it is the low for a period stretching 12 months back and 12 months ahead. In this case, the low centered on a 25-month interval, the year was noted and the distance between them calculated:

Yr. of low   Yrs between

2002            8
1994            4
1990            3
1987            3
1984            2
1982            4
1978            4
1974            4
1970            4
1966            4
1962            2
1960            3
1957            4

The mode is 4, though it would have been hard to know it ex-ante. This is completely retrospective in that it describes minima including periods in the future, and also does not specify what month within each year the trough occurred.

Now we have a debate since Mr. Moe said the number is three (and so did Monty Python).

The Minister speaks:

Dr. Z has a well-defined method for deciding whether, in retrospect, a market low occurred. A low has occurred if the month-end price is less than that of all the prior 12 months and all the forward 12 months.

I used Excel's random number generator to generate 10,000 monthly returns with mean 0.5% and standard deviation 4%. Using these returns and Dr. Z's definition, there were 253 lows over the 10,000 months, with the average time interval between them equal to 38.3 months, with standard deviation of 23.4 months. So it's not too surprising that 3 or 4 years is a typical number that pops up.

If you use an 18 month instead of 12 month window (i.e. you compare with the prior 18 months and the forward 18 months), then the average time interval between lows jumps to 62.7 months.

Bruno Ombreux adds:

I used a very old technical analysis program (shame on me) to look at cycles in monthly S&P500.

It is based on maximum entropy, not Fourier. This is a very powerful method that is used for instance in seismic exploration by the oil industry. If there are cycles, it will find them. Actually, it is so powerful that it will even find cycles that don't exist. The output is in the chart below. The yellow areas show cycling content in the data. The green line is the dominant cycle at any given time since S&P inception.

The conclusion is that there is no stable cycle in S&P monthly returns, and absolutely nothing cyclic in the 48 month region.

I am not a mathematician, so I am asking a question: Can Fourier fit any set of data points or does it need the series to be square-integrable? I have only seen the results derived for the L2 space. Are they generalizable to any Hilbert space or something even bigger like Banachs?

Anyway, your explanation of Fourier is the clearest I have ever read and made me cogitate. The fact that one can fit any series with any combination of orthogonal functions should elicit extreme cautiousness when using such methods, particularly when the fit is achieved with complicated functions. This is like time-domain statistics with too few degrees of freedom.

There is a good fit because of the mathematical properties of the series, but it only fits the past. For instance, one could probably use a combination of planetary angles, and all the other stuff astrologers look at, like houses or nodes, to get a very good fit of past S&P moves. Of course, it would only fit the past. The only way to make money with it would be to publish a book based on the findings: "Planetary Trading", which should be a bestseller.

I think to avoid this pitfall, the only solution is to use simple functions, that means the sines and cosines of Fourier, and to only consider a cycle for further study, if it makes physical sense. For example, if it existed, the four-year cycle would make sense, because there is an explanation in the US election cycle. Monthly or quarterly cycles linked to contract expiration or company reporting would make sense too. But a 5 month cycle in the S&P500 doesn't make sense. What on earth could cause it?

James Sogi adds:

Use bootstrapping methods, following along with Chair and the Artful Simulator, to derive a mean and standard error statistic in the situation (4-year returns) where there was not enough existing data to get a robust result . The re-sampled data with replacement using the sampled variance of yield converges to the true mean and variance as n approaches infinity under the central limit theory. The distributions of the multiple samples is used as a simulated population to get the p and t scores for the sample. They converted the p and t scores to odds. Collett describes the process. "It is sometimes helpful to describe the chance that a binary response variable leads to a success in terms of the odds of that event. The odds of success is defined to be the ratio of the probability of a success to the probability of a failure. thus if p is the true success probability, the odds of a success is p/(1-p)."The odds ratio is the ratio of the odds for two sets of binary data. The odds ratio can be set in a 2x2 contingency table and confidence levels can be computed.

R Cran has a library 'boot' to perform bootstrapping. Several of the other stat library functions have bootstrapping built in such as the chisq. test. The advent of modern statistical computing has changed statistical analysis and the theory by allowing robust and exact p scores in situations where it was not possible before.

R gives references explaining the bootstrap and its variations.

Time, Space and Material, by GM Nigel Davies

One of the more difficult aspects of chess is in understanding the relationship between time, space and material. There are many who are good at one, or able to work with two of these factors in their thoughts. But to find someone who is able to synthesize all three is unusual.

Thus we have gambiteers who can balance time against material but are unable to combine this with the spatial issues associated with pawn structure. On the other hand there are lofty structural thinkers who can create deep and subtle plans but  who often get defeated when the position explodes in their face.

Both in chess and in life the oft-coined phrase is 'balance', but to me this has a patronizing ring to it, almost as if it's saying that if we dull our remarkable imbalances we'll be acceptable company for the crowd. Come join us in our mediocrity.

In my view the chess player should not be aiming for any wishy-washy balance, but rather mastery. And to do this, he must look into the eye of the primeval forces  which confront him, until he starts to understand them and can sense the meeting point.

An Update on Henry "Take Out the Canes" Clews, by way of James Sogi

Marie Clews wrote a book called Once Upon a Time at La Napoule about her life in a castle on the Cote D'Azur in France. The name caught my eye, and it turned out to be none other than the granddaughter of our Henry Clews Sr. (author of "Fifty Years on Wall Street").

Marie tells the rest of the story that Mr. Clews did not detail in his autobiography -- the story of his blowup. After the Civil War of 1861-1865, Mr. Clews's firm, Livermore, Clews & Co. in a desire to help with the Reconstruction of the ruined South, invested in bonds issued by the state of Georgia and Alabama. Georgia repudiated the bonds and refused to pay the interest on the coupons. Mr. Clews's firm was ruined, and he lost his previous fortune. He was forced to live in a two modest rooms in Hotel Brevcourt after selling virtually everything he owned.

In his thirties he began anew. He took about 10 years to recover, but he achieved tremendous success -- though not the prior dizzying heights.

Clews wrote Twenty-Eight Years in Wall Street in 1886 and updated it as Fifty Years in Wall Street in 1908. John Wiley & Sons recently issued an abridged version of the latter, with a foreword by Victor Niederhoffer.

My favorite excerpt from Clews:

But few gain sufficient experience in Wall Street to command success until they reach that period of life in which they have one foot in the grave. When this time comes, these old veterans of the Street usually spend long intervals of repose at their comfortable homes, and in times of panic, which recur sometimes oftener than once a year, these old fellows will be seen in Wall Street, hobbling down on their canes to their brokers’ offices.
Then they always buy good stocks to the extent of their bank balances, which they have been permitted to accumulate for just such an emergency. The panic usually rages until enough of these cash purchases of stock is made to afford a big “rake in.” When the panic has spent its force, these old fellows, who have been resting judiciously on their oars in expectation of the inevitable event, which usually returns with the regularity of the seasons, quickly realize, deposit their profits with their bankers, or the overplus thereof, after purchasing more real estate that is on the up grade, for permanent investment, and retire for another season to the quietude of their splendid homes and the bosoms of their happy families.

A Perspicacious Spec Surfs the Web, a Continuing Feature

It gets cold early in the Adirondacks.

And the Hamptons!... and they always swing through Aspen during the summer, and it does drop down into the 40s at night...

A Speculator's Story: Margaret Mitchell's Gone With the Wind

"Cheer up," he said, as she tied the bonnet strings. "You can come to my hanging and it will make you feel lots better. It'll even up all your old scores with me -- even this one. And I'll mention you in my will."
"Thank you, but they may not hang you till it's too late to pay the taxes," she said.
More "Gone With the Wind" excerpts of speculative interest collected by the Webmeistress.

A Counterintuitive Idea, by Dr. Mark Goulston

I have a counterintuitive idea for you. A paper/book or something else entitled:

"Beyond the Deal: Overcoming Transaction Myopia"

Transaction myopia is my term for: "get the deal, do the deal, next deal." After having spent 25+ years doing house calls to dying patients, I have seen how time and time again, it is true that "no dying man wishes he had spent more time at the office." I talked about a couple of examples of that in a piece I sent out to the open group in response to the Asperger's post.

If any of this speaks to you, and you seem to like some of my ideas, you might want to check out the short chapter I wrote for the book "Psychiatric House Calls" entitled: Living Through Wanting to Die.

The Assistant Webmaster replies:

I've heard "no dying man wishes he had spent more time at the office" 1,000 times; it's always struck me as a canard. I'm suspicious of deathbed conversions, and tend to think that what people do is more important that what they say (c.f. my recent review of "Do As I Say"). Is someone more cogent at age 90 then at age 30, 40, 50, when he's actually making daily decisions about how to spend his time? For many, spending "more time at the office" is completely rational. At the office (if they're authority figures of any sort) they're accorded respect and admiration, and enjoy the stimulating company of intelligent adults and the gratification of concrete achievements. At home, perhaps they're treated scornfully by contumelious spouses or surly teenagers.

Art Cooper adds:

I couldn't agree more with your response. In the field for which I was formally trained, the law, the best people love their work, and derive enormous satisfaction from it. This is obviously true of many professions, e.g., a research scientist who's completely devoted to his field of study. See Viktor Frankl's concept of logotherapy, articulated in "Man's Quest For Meaning" and elsewhere.

I'm sure there are many people working "9 to 5" drudge jobs who may look back on their deathbeds with regret over the amount of time they spent working, but for many people who derive satisfaction from their work, the sentiment is simply untrue.

Dr. Goulston responds:

These are cogent points, on the other hand I am highly sensitized to how easily and frequently people kid themselves into believing whatever they choose to and then finding a way of justifying it.

For example, I asked a former prosecutor turned criminal attorney how he dealt with clients he knows are guilty. He took umbrage and said, "Guilty" is a legal term and has little to do with whether they did it or not. The fact is that in our system, everyone has the right to a vigorous and rigorous defense for their alleged crimes.

I asked him, "So it doesn't matter to you if they did it or not?"

He responded, "No, that is the role of judge and jury."

"So it's okay with you to rip a witness to shreds on their sexual history, if you're defending a serial rapist," I asked.

"It's irrelevant and as I said, everyone has a right to a vigorous defense," he replied.

"But five years ago when you were a prosecutor, people acting the way you are acting now were scum," I reminded him.

Needing to have the last word, he reiterated: "As I said, everyone has a right to a vigorous defense."

Still another of my favorite examples of "self-justification" is large law firms whose labor group does a pedestrian, pro forma (CYA) job of warning companies about risk and exposure, but actually hope the company doesn't follow the advice, because if it crosses over to litigation, the fees are dramatically increased.

I believe that the measure of integrity of a law firm that deals with big paying companies is how vigorous they are about protecting those companies from themselves vs. defending those companies in litigation. The more vigorous they are doing the former, the higher their integrity. Unfortunately, it's too easy for many firms to be seduced into hoping cases go to litigation, because they "speculate" that if they win the case or it results in a small settlement, they get big fees and get to be champions (and are kept as counsel for that company); if they lose the case, they still get big fees, and when they're fired, they get to go to another company to play the "bait and switch" game again.

Kevin Depew responds:

What if one works out of a home office? In which case maybe it should be, "No dying man wishes he had spent more time at the office except the man who works out of the home office and couldn't seem to focus or concentrate because he was always daydreaming about working in a quieter, more professional office environment without so many distractions."

A couple of (older?) Irish sayings come to mind:

  1. "A trade not properly learned is an enemy."
  2. "It is sweet to drink but bitter to pay for."

Charles Pennington mentions:

It's often true though that work that was done decades earlier looks less and less relevant, because it becomes obsolete.


  • Sorting punch cards to go into the mainframe to do an overnight number-crunching calculation that could be done within 30 seconds at home in the year 2006.
  • Testing for a more durable filament to go into vacuum tubes, so people won't have to call the TV repairman so often to fix the RCA.
  • Working years in the 80's or 90's to get the genome of some primitive bacteria, knowing that in 2006 one could get the entire human genome in an hour.
  • A la "Dr. Evil", holding the world hostage for a ransom of 1 MILLION dollars.
  • But this obsolescence effect can also be viewed as an incentive NOT to leave the office, lab, or lair. If you quit, your past work's importance will dwindle to zero, but if you stay, you remain fresh and continue to contribute at a level that has relevance today.

    Dr. Goulston adds:

    Kevin Depew's post reminded me of a syndrome I named five years ago called "pseudo ADD" which is not to be confused with real ADD.

    Real ADD is about having your concentration interrupted from inside your brain/mind, because the resting "idle" of your brain cells is too slow. When the resting "RPMs" of your brain are too slow, your mind does not become engaged and you're left functioning as a brainstem, reacting in a reflex way to stimuli.

    Adrenaline (which excitement and risk triggers) raises the resting RPMs of your brain enough to engage your mind. When your mind is engaged, it doesn't think faster as much as it thinks more clearly because it is able to tune out extraneous stimuli. The problem is that although this makes you more goal directed, it causes you to be less empathic to others. That's why people with natural ADD (especially young children with it) often have trouble being empathic and sensitive to others. They are not generally insensitive (i.e. intentionally and purposefully that way), rather they are just "not" sensitive. So it is not meant personally to others, even though most of them take it personally. Giving such people Ritaline or Adderall, lessens the need to seek out excitement and adrenaline rush type activities and when it works, enables people with ADD to listen better in their personal relationships.

    Pseudo ADD occurs when your mind is not interrupted from inside your brain, but when it is interrupted by the emotional needs and demands from outside you. Rather than being unempathic, you are too empathic and will drop what you're concentrating on to attend to the needs of others (what the word "co-dependent" means). You have trouble tuning out the outside world with pseudo ADD. You suffer from what I call, "concentration interruptus." The treatment for Pseudo ADD is not medication, it's learning to set clearer boundaries between you and others and internalizing this so that you don't feel guilty when you say, "no" to others.

    The Efficient Market Hypothesis, by Stefan Lewellen

    Jeremy Grantham and Seth Klarman recently came to Yale to speak to my Endowment Management class. Grantham provided a memorable quote related to the topic of market efficiency: "Markets are shockingly inefficient. All you have to do is wait for the fat pitch and place your bet. Fama, Malkiel, and the EMH are just horribly wrong."

    I couldn't agree more. Limits to arbitrage, short sale constraints, mean reversion, and models of short-term and long-term investor sentiment all fly in the face of Gene Fama's arguments. Fama's own HML and SMB factor portfolios clearly show that segments of the market are systematically mispriced over long time horizons (and his explanation that value stocks are 'riskier' than growth stocks is somewhat suspect, in my opinion). The simple fact is that scaled price ratios show a clear, highly predictable long-term trend which cannot be refuted by Fama or anyone else. His notion of "temporary" market mispricings is correct, but highly misleading - empirical evidence clearly shows that markets can be mispriced both temporarily and over a long-term basis.

    With regards to fund performance, it is a mathematical certainty that the "average" investor cannot beat the market. If the market consists of two stocks and investors' holdings total 100% of each stock, then the "average" investor return must be the same as the market return because the sum of investor holdings is equivalent to the market. To me, this argument doesn't say anything about market mispricings or the skill of individual fund managers. It just says that investing is indeed a zero-sum game.

    That said, DFA is an interesting case study. The firm outperforms their benchmark by providing liquidity to illiquid markets, not due of the philosophy of its founders. There's nothing inherently wrong with their strategy; it just has very little to do with market efficiency. If you hold highly illiquid stocks and have positive trading costs, you will almost certainly outperform. You're simply being compensated for liquidity risk, which - since they almost never sell - DFA doesn't care about.

    What's on the Menu? by GM Nigel Davies

    It's almost 20 years since I sat in a restaurant in Albena, Bulgaria, attempting to order from an expansive menu only to find that everything I asked for was "off". Finally I asked what was "on" and discovered that my choice had been a binary one all along (schnitzel/no schnitzel). I resisted the temptation for irony in case they gave my schnitzel to the dog to play with before it finally arrived on the table. I lost 20 Elo points during that event, finishing second to bottom.

    Was this simply a matter of shortages? Actually I suspect there was a black market at work for all the items apart from the schnitzel. At an unofficial restaurant that wasn't part of the "tourist industry", there was a terrific choice and the food was excellent. There was also no evidence of shortage when I attended a privately held dinner at the home of the tournament organizer, a well-connected politician.

    Could the percentage of items available on restaurant menus be a good way of assessing a country's economic health? Probably. But recently I've been considering another application for menus in speculation.

    Having wrestled with a number of different methods of organizing tradable patterns, I got sudden inspiration whilst considering a Chinese takeaway menu. The different types of food are beautifully categorized according to recipe, each dish is given a simple number on the left with prices to the right. The customer can put a cross by the relevant dishes, and when he phones up place his order by reciting the numbers required. The takeaway will quickly tell him the effect on his wallet by totting up the prices.

    This same system is perfect for a trader; one would mark off the different pattern elements on a "trading menu" and then call up a database to discover the likely effect on one's wallet. If it looks good then you place your order.

    I think there are a number of advantages to this kind of menu approach which reminiscent of having an "opening repertoire" in chess. The menu presents you with all the dishes so you don't forget about their availability, and you will also be unable to improvise off menu items at the last minute. I'm of the opinion that improvising patterns at the last minute is very dangerous because one's search is likely to be influenced by emotional factors.

    Well there you have it, a takeaway approach to trading. I'm in the process of developing my own menu at the moment, hopefully I'll do better than in Albena.

    Cultural Fear, by Russell Sears

    Cultural fear, I believe is the fear of success. The Olympics are filled with stories of disaster at the last moment, due to the mind's/body's being betrayed by the fear of success. GM Nigel writes elegantly on how he prevents this fear from gripping him in a tournament.

    We have had 230 years of America's three grand ideas. Success has spewed like a fountain from these great ideas. Richard Bailey states basically these three ideas bring this fear into many, but I see only a fear of success. The three grand ideas are:

    1. Free Trade -- Or stated another way the spoils belong to those that take the risk. Wealth belongs to the business man, the pioneer, the inventor, the speculator not the king or the government. "Give me Liberty or give me Death", shows that there is no peace in a soul without this right.
    2. Democracy -- Or the Government is the servant of the people, not the reverse. The government owns nothing that the people don't give it.
    3. Freedom of Religion -- Or only the individual is responsible for his own soul.

    It has been within the last century that the US fought two World Wars, Korean, Vietnam and Gulf War, and now Afghanistan and Iraq II to strengthen and solidify these grand ideas. We are not afraid to fight for them. Perhaps we prefer fighting for them.

    The reason we are afraid of these things is the revolutionary success they have brought. How many businesses, life saving drugs, investors' fortunes are dropped in the last moments as spectacularly as the Olympic skier, Bode Miller straddling the gate or speed skater, Apolo Ono slipping on the last turn?

    Perhaps, this is why the Chair prefers the S&P futures over individual stocks. The whole will not give into this fear, making the cane strategy a winner. However, the same cannot, as consistently, be said about the individual company.

    Bruce Lee comments:

    I would like to look at it another way. Perhaps Bode Miller's straddling a gate, or the skaters' falling on their routines is not a reflection of the fear to succeed, but maybe the courage to fail. That is, more than anyone, they have the courage to take that extra ounce of risk to reach a level very few have achieved. And because of that risk, they are more susceptible to disaster.

    Steve Leslie asserts:

    Three quick points pertaining to Russell's comments:

    1. In 230 years, I doubt one can postulate three grand ideas for America's success. I am quite positive that sufficiently challenged more than three could be listed.
    2. I would hardly call The Korean War and the Vietnam undeclared war marvelous successes.
    3. The whole gives into fear with impunity on many ephemeral and longer lasting occasions just like stocks do. 1987 and 1998 are two that come to mind.

    Such Schadenfreude and misrepresentations obfuscate the truth.

    Russell Sears responds:

    In reply to Bruce Lee:

    It was my hope that my reputation as a competitive marathon runner would suffice to imply that I am clearly for the individual willing to risk much for slim hopes of glory. But, I can see how you and Mr. Leslie could also see me as an "over-the-hill, never-was wanta' be" cheering when the young champ falls or gets caught in a drug bust. Let me assure you that the Olympics can be heart-breaking for me to watch, crying real tears. But, I must admit that I was not too engaged in this Olympics, as this last weekend I made a poor attempt to race 42k in the freezing rain, in Austin TX.

    Further, we all have our own moments of doubts. Much of coaching and training to reach the top is not letting those doubts become excuses. Sympathy is reserved for those whose misfortunes are not self-inflicted. It is clear that these athletes could have been winners. They had what it takes to win, and you are right that this should be praised. If someone with as strong  a mind as GM Nigel and his cohorts have, can have doubts and lose focus, then I suspect we all fight these battles.

    These athletes clearly have outdone me and my feeble attempt to appear on the same stage as them. So the harshness in my criticism should be viewed from an envious admirer, not an aloof superior chastising. But may I suggest that the Olympics are at their Grecian ideal when athletes, rather than simply being idolized, are held up to the same moral spotlight as the Greek's mythology. Apollo bounced back and picked up a bronze, I will be cheering for him in the 500 and the relay.

    In reply to Steve Leslie:

    1. The "230 years" was a reference to the Revolutionary War, which I maintain was fought mainly for those three reasons. I am sure other reasons could be found. I will not even try to do justice to defending why those three great ideas are so critical and uniquely singled out; I will leave this to much better informed writers than myself. But I would be pleased to hear of other reasons that were foundationally instrumental and were/are held with such depth.
    2. The listing of the wars in the past century was meant to convey the depth of which we still hold these ideas. Perhaps such a sharp swing in thinking did not convey my thoughts. The three reasons are still holding strong 230 years later, which, in my opinion, is self evident of their well of success. Yet, War is always tragic. And, War is always a disaster, especially for the defeated. Yet, when done for these reasons, it can be creative destruction. Of course, Vietnam has emboldened the culture of fear. But Korea's severe contrast is a somber testimony of this truth.
    3. I take this to mean show me the numbers. Your examples of 1987 and 1998 fail to persuade me, in fact they encourage me . The subtle difference in fear I was trying to make between the whole and part was not the whole's total immunity to fear. Rather, that cultural fear, will bring catastrophic failure to the individual, and individual company, but the whole will withstand this attack.

    The Chair has taught us how to count, to tell when this reversal is most likely to occur. The cane strategy relies on fear attacking the whole, damaging it, but not destroying it. I will defer to his counting and success to prove that cultural fear on the whole is somewhat predictable.

    As for proving that individual companies do not display this predictability as well--this is a much taller order, which I don't have the resources or talent to undertake sufficiently. So I will differ to diversification theory and, clearly, non-systemic risk can be greatly reduced. This variance being unique to the individual stock, (here is my leap of faith) "probably" is not as predictable.

    I certainly have not had luck, and it may be me souring the grapes. And I may simply be displaying my own inept analytical abilities, but my yearly "one big loss" that destroys my return is consistently the individual stock, bought at  great discount to its one-time high, only to be brought down to catastrophic levels. Sometimes this stock's failure is clearly self-inflicted, other times it is the helpless victim of stampeding cultural fears.

    I am suggesting that while cultural fear is on the rise, these attacks will increase and will be harder. More and more individual companies will be attacked and fail. However, the resolve of those believing in these ideals is also increasing, is battle hardened, and is, in general, winning. The soldier fallen will be replaced by two others.

    Briefly Speaking: Stocks, Commodities & Anatevka, by Victor Niederhoffer

    Making the Rounds. There were some notable moves in markets on Monday. The S&P futures moved to 1299.75 at 3:30 PM EST before falling to 1294 at the end of the day -- the highest close since the 31-day high of 1299.70 on Jan. 11.

    The cash index closed at 1294.12, just missing the five-year high of 1294.18 set Jan. 11. The index has not closed above the round number since May 22, 2001.

    In summary:

    event                             date          futures          index
    close                             27-Feb-06      1294.0         1294.12
    prev closing high                 11-Jan-06      1299.7         1294.18
    most recent close above 1300      22-May-01      1312.8         1309.38 

    What does it mean? Well, I hypothesize that the second time a round number is breached, it is more bullish than the first time if the first time led to a failure. Also, with the Minister's permission, I report the tested result that a close within a certain distance of a round is quite bullish.

    A Bad Day for Commodities. There was yet another 3% decline in the GS Commodity futures index, from 423.8 to 411.50. But it was not what one has called a healthy day, in that stocks were up, so just the commodity longs suffered a disaster. I am reminded of the first time that I met a certain personage at the good offices of her then employer where they made the mistake of putting me on a televised panel with a representative of a white-shoe brokerage firm who was hawking the idea that commodities perform just as well as stocks over the long term, if you take account of maneuvering near the rollover dates. I could not help blurting out that the last time they came up with that argument, shortly thereafter Metallgesellschaft went bankrupt and apparently they hadn't learned their lesson, nor had they read the work of Julian Simon, nor should my relative silence be taken as acceptance.

    It was at that time that I realized that I was not fit to be on any panel, ever again, and that I was a superfluous man, especially since I had the results that I reported in my highly favorable review of the Adventurer's work showing that a buck invested in a reasonable prospective basket of commodities in 1900 would have grown to some 1/10th to 1/100th of an investment in stocks at that time.

    Someone's going to remind me here that since the time of such review commodities are up 50% or some such, and that I am always bullish on stocks, and that had something to do with my 1997 debacle. I hear the sounds of "Anatevka" from Fiddler in the Roof in the background as I write this and that is my answer.

    A little bit of this, a little bit of that.
    A pot, a pan, a broom, a hat.
    Someone should have set a match to this place years ago.
    A bench, a tree.
    So, what's a stove? Or a house?
    People who pass through Anatevka don't even know they've been here.
    A stick of wood. A piece of cloth.
    What do we leave? Nothing much.
    Only Anatevka.
    Anatevka, Anatevka.
    Underfed, overworked Anatevka.
    Where else could Sabbath be so sweet?
    Anatevka, Anatevka.
    Intimate, obstinate Anatevka,
    Where I know everyone I meet.
    Soon I'll be a stranger in a strange new place,
    Searching for an old familiar face
    From Anatevka.
    I belong in Anatevka,
    Tumble-down, work-a-day Anatevka.
    Dear little village, little town of mine

    Sushil Kedia comments:

    The single-handed benefit of compounding the growth through re-investment that equities have been achieving over a 100 years and more is but not possible to be replicated by any commodity known so far in the universe or knowable in the future. The commodity investment hypothesis is based merely on scarcity and a growing consumption of the same. This hypothesis often misses out the simple economics of supplementary and complementary goods in case there is a spike of excess demand over supply threatening to become a prolonged feature.

    On the other hand, stock selection which operates otherwise also in the passive investment of an equities index captures not only the compounding effect but also the scarcity side of the hypothesis since consistent compounding and re-investment led growth is clearly one parameter that one would use to select opportunities even when restricted to the universe of only stocks.

    For a simple illustration: if one were to say hoard a ton of aluminum or any other commodity over a period of 10 or 20 or 30 years all one could hope to capture is the inflation in the value of aluminum or such other commodity. Whereas an equity investor who would have purchased stock of a sound aluminum-producing company would have captured the benefits of the reinvestment of the profits in a business activity that continues to produce profits in excess of the cost of capital, compounded.

    The Smell of Health, by Victor Niederhoffer

    A most interesting scientific article, "Diagnostic Accuracy of Canine Scent Detection in Early and Late Stage Lung and Breast Cancers," by McCulloch, Michael et al. appears in Vol. 5, No. 1 of Integrative Cancer studies. The gist is that you can train any group of dogs to distinguish the afflicted from the healthy for those two diseases with 99% accuracy. Alternate hypotheses relating to foods eaten, age, smoking and previous sicknesses are tested and ruled out. A typical two-by-two table:

           healthy          sick
    no       708             10
    yes        4            664

    Thus, a "yes" increases the odds by a factor of 166 to 1 that you have the disease.

    Several thoughts emerge:

    1. It would be good for investors to find a dog that could ferret out the smell of a good stock as well as it can the diseased.
    2. What an incredible number of lives would be saved if tests based on breath, scent, urine and blood were used to diagnose rather than the invasive and immensely insensitive physical tests that are now given.
    3. What would be the net increase in human longevity if people still paid for their own health and doctors and others were free to purvey their panaceas the same way they hawk computers and communication devices?

    Tom Larsen adds:

    I remembered reading about an asian medicine group here in Marin County California, that was trying to train dogs to smell cancer. I recall they were using apricot poodles, almost three years ago.

    Kim Zussman on the New Recent High on SPY

    In case you were wondering, yesterday the S&P 500 closed at another new (post '01) high. To briefly recap, the thing bottomed in early '03 and went up sharply to the end of that year. Subsequently, stocks have risen less rapidly and with more give-and-take.

    Glancing at the chart it seems like new 4 to 5 year highs were followed by declines. To test this I used SPY since 01/'04 and non-overlapping 20 day periods. If a period had a high close, higher than any of the prior 200 closes, what is the return of the next 20 days (compared to all 20 day periods since 01/'04)?

    t-Test: Two-Sample Assuming Equal Variances

    20D ret                                         after hi     all
    Mean            1.00150      1.0068
    Variance        0.000276696  0.000500743
    Observations    11           27

    Pooled Variance 0.000438508
    Hypothesized Mean Difference 0
    df 36
    t Stat -0.710617919
    P(T<=t) one-tail 0.24094985
    t Critical one-tail 1.688297694
    P(T<=t) two-tail 0.481899699
    t Critical two-tail 2.028093987

    The 20 days following those containing 200 day highs were slightly lower than all 20 day returns for the period, but the difference was not significant (0.15% vs 0.68%). Perhaps there are technically better ways to show such a pattern?

    Steve Ellison on Hubris Management

    France's fending off of a takeover attempt by Italy`s Enel on "their" Compagnie Suez reminds me of the uproar over CNOOC's bid for Unocal last year, and the current Dubai Ports World's bid. One wonders if the nationalistic feelings aroused are compatible with self-interest, as studies have shown that acquiring firms generally overpay. An example from a unique perspective is the paper Hubris Amongst U.K. Bidders and Losses to Shareholders by Raj and Forsyth, who imputed hubris to acquisitions with above-average takeover premia by acquirers with price-earnings ratios that were high relative to their industries.

    This paper examines the performance of bidders with a hubris management during a takeover bid. Data for the study comprises of successful bids in the UK during the 1990s, which have been identified as having a hubris management. Valuation ratios and bid premium sizes are the measures used to identify the sample of hubris bidders. Results show that hubris bidders significantly lose on the announcement of a bid.

    Non Linear, Non Parametric Quantile Regression, from James Sogi

    Here's a little fun for you TA guys. This R script from Quantile Regression by Roger Koenker uses change of 30 minute closes SP Big March for last 5 days. Play around with df degrees of freedom for fitting. This plot uses bspline fitting, which is kind of a supercharged regression plot. The advantage of non linear, non parametric quantile regression over linear regression is the sensitivity to the upper quantile that reveals information hidden by analysis of only the mean. Linear regression focuses on mean, and seems 'slower' on time series data to change of cycle.

    R Cran
    plot(times,accel,xlab="1/2 hrs",ylab="change", type="n")
    X <- model.matrix(accel ~ bs(times,df=20))
    for (tau in 1:3/4){
    fit <- rq(accel ~ bs(times,df=20),tau= tau, data = rr)
    accel.fit <- X %*% fit$coef

    Abelson a No-Show, but Not to Worry -- Bears Still Rule at Barron's , by Victor Niederhoffer

    Fresh from my weekly dose of nightmarish alchemy via the leading financial weekly, I have good news and bad news.

    The bad news is that for the second week in a row, Alan Abelson has not written a column, leading faithful readers like me to fear that he is sick -- or, more calamitously for the market, that he has retired. (This is bad news because he day he retires might well be the end of the bull market that carried the Dow from 700 to 11,000 during his 40 years of bearishness).

    The good news is M. Santolli wrote the lead editorial in Abelson's stead, and his place is headlined " Stocks Signal Lull, So Buckle Up," and The Trader column is headlined " Stocks...May Stay Rangebound."

    You see, as Santoli says, "Still, at some point, when it reaches some size, financed by a certain threshold of foreign debt, the Chicken Littles who have been raising alarms since the deficit turned negative 30 years ago might have cause to gloat,"

    Yes. And let us hope if the market doesn't rise 20-fold, adjusted for dividends, the way it has in the last 30 years while the Chickens Little wait for the investment climate of our trading partners to become as hospitable as ours. And let us not decry the current account deficit we all have with our supermarket in the same eschatological terms.

    One of the problems, according to Santoli, is that:

    ...last week, a Merrill Lynch gauge of expected bond-market volatility reached a record low, at a level last seen right before the Russian default and the Long-Term Capital Management implosion. The stock indexes could be characterized in much the same way as bond yields: Stretching toward the upper end of their established range and generally finding reasons not to pull back much. In stocks, as in bonds, there is a broad presumption that tomorrow will be as placid as today and yesterday. The long trading range has been lulling.... However, a smaller number of big stocks are trading at their highs than the bulls might wish....only five of the Dow's 30 components were at fresh peaks. Some leaders have fallen from grace, such as Google and Apple.

    Yes!!!!! The market is bearish because all the stocks are not at new highs, and it's lulling us to a false sense of security, and the vol is low, and there is a current account trade deficit. One always finds it particularly humorous when a supposed authority like the Trader hauls out the whole deck of canards: the market is weak because x% -- in this case, 10% -- of a group of stocks are trading at 10% or more away from their 52-week highs. But of course, every company can't be at the high every week, and the chances that any one company will indeed be at a high when the market goes up 1/4% a week, with a standard deviation of 1/2% each week, is about 1 in 20. The random distribution of the number of stocks selling at x% away from their new high each week is a complicated statistical question that depends on the kind of declines and rises that occurred in the previous period. And with a rise like the current one that followed a move to 1170-ish and 1140-ish on the two big tax days in 2005, the number of companies selling well off their highs for the year would be particularly great.

    The more serious question is whether there is any tested relation between how the ensemble of stocks is distributed relative to their highs for the year. It's too complicated to answer, because of the random factors relating to past moves that affect it, so it's much better to ask direct questions, like: What's the expectation for a market or individual stocks that is up 10% from its April month-end level in 10 months?

    Who needs Alan Abelson or the four-year bearish cycle or the possibility of a halving in Google, with relief pitchers of this caliber?

    GM Nigel Davies on Coded Yoghurt

    The start of the claimed use of parapsychology in chess was the Fischer - Spassky match of 1972. Prior to game 17 the Russians claimed that through hypnotism, electronics or chemicals mediated through the special chair that Fischer had imported from the US, or possibly through the lighting system (or by some other means), Fischer might be sapping Spassky's will to win. An investigation by a team of neutral experts found two dead flies in the lighting.

    The main event was the Karpov - Korchnoi match of 1978. Prior to game 3 Korchonoi's team made a formal protest claiming that the delivery of Karpov's yoghurt could contain a coded message: Thus a yoghurt after move 20 could signify 'we instruct you to offer a draw'; or a sliced mango could mean 'we order you to decline a draw'. A dish of marinated quails eggs could mean 'play N-N5 at once' and so on. The possibilities are endless. A dispute arose which resulted in Karpov being restricted to a particular yoghurt at a particular time, brought by a designated waiter.

    Prior to game 9 Dr Zukhar, a noted Soviet hypnotist (parapsychologist), is moved from the front to the back of the auditorium when Korchnoi's delegation complain he was disturbing their boy. A game of musical chairs followed in which Zukhar wandered all over the auditorium culminating in a Korchnoi's delegation counterattacking with a flood of their own parapsychologists, (some young female students of a Father Jaime Bulatao plus members of the religious sect, Ananda Marga, who at the time were on bail, pending appeal for the attempted murder of a diplomat).

    My take on these shenanigans? I think they're all essentially attempts to get the opponent to think about things other than the board. Probably it can work to an extent, though when both sides use them you get nothing more than a substandard match. As Korchnoi himself finally put it: "No number of gurus will help me if I play bad moves."

    Nigel Continues on the Topic of Fame:

    One of the more difficult aspects of being a Grandmaster is to have fame within a particular sphere but not much wealth. So an aspect of trading that most attracted me was the possibility of wealthy anonymity. In fact many traders appear to have written autobiographies in order to get noticed.

    A very few others have just attracted fame by virtue of who they are and their achievements both in and out of markets. But it would be a mistake to assume that they particularly enjoy the attention, especially certain aspects of it.

    Dick Sears Weekly Commentary: Rock and Roll

    Variations on Market Hydraulics, by Victor Niederhoffer

    1. Pascal's principle. The basic principle of hydraulics, the practical application of the mechanics of fluids, is that the pressure applied to one part of a closed system is transmitted equally to all other parts of the same height. This is usually expressed in the formula

      F1/A1 = F2/A2

      A force at the input applied to a small area can support and lift a much heavier object attached to a large area at the output. For example, the familiar car lift. A force of one pound applied to a small piston with a radius of 1 inch can lift a car that weighs 10,0000 pounds supported by a piston with a radius of 100 inches. The question emerges whether there are any small forces in markets that can be applied or noted at the input level that will have a comparably multiplied effect on the much larger area of the market.

    2. Individual stock market correlations. To test this at the individual stock level, the Minister looked at the correlation between the % returns of each of the individual stocks of the Dow in one day and the % returns of the market move the next day over the last three years. He found, as those who read this site might expect, that 24 of these 30 forward, predictive one-day correlations were negative. The five most negative with their correlations were:
      Name of Comp         One day forwd corr
              XOM                    -0.10
              PFE                    -0.11
              MRK                    -0.14
              MO                     -0.16
              DIS                    -0.20
      All these seem significant from a statistical sense, but none too valuable from a practical standpoint because of the principle of ever-changing cycles and the bias associated with multiple comparisons.(Thus the Minister's felicity.) Just for the record, the two companies with positive one-day correlations vis-a-vis the market the next day were AXP and AIG, with correlations of 0.03.
    3. Several questions immediately emerge. What individual markets predict general market moves? For example, does rice predict the GSC futures index? And what about the other way around -- does a large force on the ouptut side, i.e., the market, predict a much magnified move in distance (since the work is the same on both sides) on individual stocks?
    4. One wants to thank my daughter Kira and Charlie Turner for inspiring this line of reasoning. Charlie, one of the finest and most inventive gentlemen I ever met, invented the hydraulic lift that linemen used for telepone work in the '70s, and a car trip with Kira back from school inspired me to try to explain the principles involved.

    Andrew Moe adds:

    You have to factor drift in the same way as adjusting the averages for a t-stat in F1/A1 = F2/A2. But this is right up my alley and I will put it to work over the weekend.

    I would add that in pure form "pressure at a point has the same magnitude in all directions". ME Reference Manual (15-4).

    Also "hydrodynamics is the study of fluid behavior based on theoretical considerations. Hydrodynamicists start with Newton's laws of motion and try to develop models of fluid behavior." (17-2 of ME + lots to google)

    Rich Bubb comments:

    "The question emerges whether there are any small forces in markets that can be applied or noted at the input level that will have a comparably multiplied effect on the much larger area of the market."

    Vic's percipience got me thinking about Fed funds rate increases, i.e., they change the direction [velocity, trajectory] of the economy through incremental piling on of rates. I can't think of any greater force-to-area magnifying effect, other than the treasury negatively drowning the economy in fiat money (aka: Snow-Job)


    Dr. Alex Castaldo Reviews Stock Market Speculation and Managerial Myopia

    This is an article of economic theory, the objective is to build and analyze a model of corporate behavior. (realism or practicality is not important, we are in the realm of theory).

    See full review

    The Importance of Consumer Sovereignty, by Victor Niederhoffer

    The Gravest Error

    The one thing everyone should know about the economy that the economics courses and texts and  analysts and media don't teach is that the consumer is the king who determines which businesses prosper and fail in providing us with goods. The classic expression of this comes in the most successful retailers like Wal-Mart, Home Depot, Stew Leonard's and numerous others who offer an unconditional money back guarantee, or lowest price guarantee, no questions asked. The purveyors do this out of self-interest. They know that one dissatisfied customer can do more damage than the good that a thousand satisfied customers can provide. They also know that word-of-mouth accounts for an ever increasing percentage of consumer decision-making. Most of all, they know that everything has substitutes, especially something that's supposedly invaluable like water (see below), and that competition is extraordinarily intense for every product, with companies waiting in the wings to produce a better product at a lower price with greater ease of use for every product, regardless of what the economists measure in terms of elasticity of demand or what they say about the absence of perfect competition in the real world.

    The Classic Sentiment

    The best modern update of consumer sovereignty is from Ludwig von Mises's "Human Action".

    The captain of the ship is the consumer. Neither the entrepreneur nor the farmers nor the capitalists determine what has to be produced. The consumers do that. If a businessman does not strictly obey the orders of the public as they are conveyed to him by the structure of market prices, he suffers losses; he goes bankrupt and is thus removed from his imminent position at the helm. Other men who did better in satisfying the demand of the consumer replace him.

    The consumers patronize those shops in which they can buy what they want at the cheapest price. Their buying and their abstention from buying decide who should run the plants and the farms. They make poor people rich and rich people poor. They determine precisely what should be produced, in what quality and in what quantities. They are merciless bosses, full of whims and fancies, changeable and unpredictable.

    After reading a passage like that, first written in English in 1949, but probably first enunciated in the Vienna of his youth in the 1920s, one wants to jump out of the skin and shout, "How did he know?"

    A Firing at Wal-Mart

    A classic lesson in consumer sovereignty came when a clerk at Wal-Mart gave a customer a lecture on the evils of not working and using food stamps. The boss rightfully gave him a dressing down, and the clerk rightfully quit. The key is that any customer can destroy the reputation of a business by telling all his associates about the bad attitude at Wal-Mart and how they should take their business elsewhere. I am reminded of one of the first businesses I sold, Sirloin Stockade in Oklahoma and California. They managed to give a full steak dinner for $1.19 in small communities, and they aced the repeat business with giving away free soft ice cream to their customers. "The happy kids are the best advertisement in the world."


    Everyone needs eight glasses of water a day, and there are no substitutes. That's the fallacy that Paul Heyne takes apart in his chapters about everything having substitutes. Are you sure that you can't have coffee or tea or soda instead, or a tangerine or tomato? What if the price of water were to rise to 60 cents a cup? Might you take a shower rather than a bath?

    Heyne beautifully gets to the core. Everyone faces scarcity. As you use more of your resources for one thing, you limit your ability to get other goods. Buying one good involves a sacrifice. As you purchase additional units of a good, the sacrifice or cost increases in terms of what you have to give up. This leads to a search for substitutes. When the benefits from the additional unit of a good exceeds the cost of the sacrifice plus the cost of search, a substitution is made. One of the main things that has increased competition in our society, and made substitutes even more prevalent than they were in the hay day of Heyne, Mises, and Smith is the reduced cost of search that is part and parcel of the Internet.

    Meet Galt Niederhoffer, Author of Critically Acclaimed A Taxonomy of Barnacles!

    Feb 22 Wed   7:00 Books and Company        Dayton          OH
    Feb 23 Thr   7:00 Left Bank Books          St. Louis       MO
    Feb 24 Fri   5:00 Square Books             Oxford          MS
    Feb 27 Mon   7:00 Quail Ridge Books        Raleigh         NC

    A Perspicacious Spec Reads the Newspaper (and Waxes Poetic), a Continuing Feature

    Fiorina: Technology will 'disappear' in 25 years
    By Munir Kotadia
    Special to CNET News.com
    Published: February 22, 2006, 10:23 AM PST
    The dot-com bust signaled the "end of the beginning" for technology, Carly Fiorina, the former CEO of Hewlett-Packard, told business leaders Wednesday.
    Never-ending shtick,
    but the dunces lap it up.
    She boards the G5.
    Miss Fiorina
    should be a game show hostess.
    It's Buzzword Bingo!
    Name an empty skirt
    motivational speaker.
    Uh, Paris Hilton?

    Wine Cycles, from Allen Gillespie

    My uncle is a muscadine grape farmer, juice, vinegar, and wine producer and a few of his charts regarding cycles are interesting. For over 30 years, from information he has collected from his own operations and other farmers, he has plotted yield/acre. Muscadine vines take three years to bear fruit, and with no problems, the yield curve takes on a S-shape, nothing at first, accelerating output then decline to a more stable level. Frequently, however, the cycles bring bad storms (hurricanes in his lower Alabama area), drought, etc. and these events frequently cluster per the chaos theorists, however, some of the events are catastrophic while others can be recovered with irrigation, fertilizer, etc.. Sometimes the fruit is damaged, sometimes the amount of rain causes the sugar content of the fruit to be too high or too low, sometimes the costs of watering and fertilizer are too high so field based corrections are not possible, sometimes you make juice, sometimes vinegar, sometimes wine, sometimes, you use cheaper bottles, sometimes you market less, sometime more, sometimes you cash an insurance policy, sometimes you don't, sometimes. The bottom line is that there are certainly cycles to business but the number of variables and opportunities a businessman has to influence the ultimate outcome must surely give one pause about betting too much on them.

    Life in Nicaragua, from Pitt Maner

    Working down here for the past month as an environmental geologist has been a fascinating experience. My current hotel in Managua, the pyramidal Crowne Plaza, was the home to Howard Hughes back in the early 70s before the massive 1972 earthquake centered around the nearby Tiscapa fault leveled the city, but not this hotel. Hughes evidently left after the earthquake and never returned.

    See Full Story.

    Summers in Winter: Haiku from George Zachar

    Larry's no longer
    the smartest guy in the room.
    Got Carly's number?
    Cl!nton's cabinet
    a mere parlor game next to
    Harvard's faculty.
    The search committee
    will have a narrow focus.
    Wanted: One eunuch.

    The Assistant Webmaster adds:

    Rusticated, he's
    drowning his sorrows in an
    ice-cold Diet Coke
    Cover of Time to
    the dustbin of history
    Seven years fly by
    Bubba and Larry
    Two ex-Presidents brought down
    by female troubles

    Toast, by GM Nigel Davies

    The sets are laid out and the clocks are set. Arriving 10-15 minutes before the games are due to start I sometimes catch the final stage of the preparations -- the arbiters or their assistants distributing the score sheets.

    I sit down at my board shortly after arrival. Often I'm the first to be seated. As other players arrive, there's always the temptation to be drawn into conversation if you stand around, but I've found this nervous chatter to be ruinous to concentration. Better to be silent and focused, contemplating the way you expect the game to open.

    My opponents almost always get to the board after me. I watch them carefully looking for clues and insights into their mindset, attempting to find common threads between their manner and anything I saw in their games. It's almost always a good sign if you're playing against the life and soul of the party; very few people can switch it off when their clock is started. No matter how talented they won't be as focused as the silent, businesslike types.

    When the game begins I'll tend to note my opponent's rhythm of play or a divergence from the moves that were expected. If someone plays something that does not form part of their usual game, it might mean they've found a flaw one of my previous games. If I smell such a rat I'll be looking for another way to play the position. At best I'll figure out what they have in mind and discover a way of rendering this particular plan harmless or even bad. That way their "preparation" might well rebound; on unfamiliar turf they might improvise poorly or continue with the thing I've started playing against.

    Rhythm is important throughout. Is the opponent spending long periods away from the board and if so why? Talking, smoking, looking at other games or what? And when he's at the board, do some moves take him much longer than others. This all provides clues as to his mental processes which may indicate how one might prepare a short circuit. If he's calculating a lot then I might veer towards a move that keeps plenty of tension. But against a strategist it might be better to "threaten" complexity; is he willing to join me as we dive into deadly uncertainty?

    If the guy offers a draw then what are his motives? Is it because of fear, a desire to save energy for the next game or cunning. Sometimes an opponent will offer you a draw just to get you to use time on the clock thinking about it. Of course he has to consider that you might accept, so there's an art to such offers.

    If you're going to refuse then do it quickly, the longer you think about it the more it will prey on your mind later on. Perhaps the best way to refuse is simply not to answer or even acknowledge that an offer was made (perfectly legal and quite correct etiquette). Sometimes this leaves them wondering whether you even heard the draw offer, but they'll be reluctant to ask in a room that is silent except for the ticking of clocks. It'll prey on their mind, dissipating concentration.

    As the time control approaches there is an increase in tension throughout the room. On some boards one or both players will have left themselves woefully short of time and sensing blood a crowd will gather. I avoid time-trouble like the plague, as Viktor Korchnoi once put it "there are no heroes in time-trouble, everybody plays badly." If my opponent is in time-trouble I'll try to use his surge in adrenaline against him. Time-trouble junkies will be calculating like crazy so they'll mainly be considering forcing moves. In such cases it's best to avoid such resolutions of tension, keeping the status quo unless there's an arithmetically simple win.

    Sometimes players will deliberately run themselves short of time so as to make their opponents nervous. If I sense that my nerves are getting on edge I'll take some deep breaths and try to relax. The more nervous I become, the more I'll want to force matters. And this can dissipate an advantage that took hours to build up.

    When the game is over I usually offer to go over it with my opponent, though I might wait for him to offer if he's the stronger player. These post mortems can be very useful for future games, you get to see what he was thinking as he does with you. So it might be better to hold back with regard to any insights into the opening, which might well get repeated in subsequent encounters. I always take notes during post mortems, writing key moves and ideas on my score sheet.

    In round-robin tournaments it can be very useful to watch the post mortems of your future opponents, seeing their manner of analysis, objectivity etc. Are they out to impress or on a search for the truth? It can reveal vital information above and beyond what you find in their games.

    Bent Larsen would always play through the games in the bulletin during a tournament and sometimes quiz people about certain points in their games over breakfast the following morning. Usually they'd answer because they'd be flattered that the great Larsen was taking an interest. But it would have been better to stay silent and tuck into their toast.

    Alan Millhone says:

    I really enjoyed GM Davies insight on tournament preparation (mentally and psychologically) on how to 'read' one's opponents. Next week-end I will be traveling to Lebanon, Tennessee for the three-day annual  tournament there. There will be around fifty entrants made up of three classes of Checker players. World Champion Alexander Moiseyev and GM James Morrison will top out the masters. I will play in that group of 'sharks' , and I find articles about mental preparedness on Chess will carry over nicely into tournament Checkers. I always look forward to any of GM Davies articles on your excellent site.

    The Assistant Webmaster Reviews "Do As I Say, Not As I Do: Profiles in Liberal Hypocrisy"

    Peter Schweizer's Do As I Say is a delicious bonbon, a quick read, meticulously researched, written with brio. On the surface, he's making the Zacharian point that liberal politics is a form of performance art, mere shtick, empty posturing, irrelevant even to the liberals' own life-choices. The dust-jacket summary: "Schweizer's conclusion is simple: liberalism in the end forces its adherents to become hypocrites. They adopt one pose in public, but when it comes to what matters most in their own lives -- their property, their privacy, and their children -- they jettison their liberal principles and embrace conservative ones." But Schweizer also makes another, more deeply cynical point, that the liberals' shtick, especially the S###sian "kick away the ladder now that I've climbed it" trope, is often taken seriously, and causes real harm to real people who aren't in on the joke, whilst enriching the liberals themselves. The author does a wonderful job of documenting instances of private conduct by leading liberals that directly contradict -- sometimes just hours or days after -- their pious public pronouncements.

    Excerpts from the first chapter, on Noam Chomsky, give the flavor. Subsequent chapters cover Michael Moore, Al Franken, Ted Kennedy, Hillary Cl!nton, Ralph Nader, Nancy Pelosi, George S###s, Barbra Streisand, Gloria Steinem and Cornel West.

    See full review.

    Meetings, by Victor Niederhoffer

    On March 29, Berkshire said that "Mr. B#ffett was not briefed on how the transactions (with AIG) were to be structured or on any improper use or purpose of the transactions")

    There are countless meetings that company executives go to where they are scheduled to talk about their stocks. The major ones appear to be meetings before security analysts ("analyst day" meetings at company headquarters), brokerage house meetings, conference calls, industry conferences, conventions, and shareholder and annual meetings. The normal tendency is for executives to speak at these meetings when they have something favorable to announce, or to augment a regularly scheduled meeting with something favorable held in the hip. A related time when good news is sure to be disseminated is at the presented papers at the major chemotherapy conferences where among the hundreds of speakers, companies regularly report on phase 1, 2, and 3 results (In fact, I have seen anecdotal, chart-based research that says the entire positive movement in biotech stocks comes in the one or two months before this meeting). Nevertheless, it is rare that the attendees at these meetings don't walk away with a favorable spin on the company..

    I have occasionally made a small profit by buying in front of these meetings, the most satisfactory being one that paid for a hip operation when I learned that the maker of my hip was coming to the US for a series of presentations before brokerage houses. And, a study by Cynthia Tori extends these findings to Federal Reserve meetings finding that the average gain on the days of these meetings from 1960 to 2000 is three times the normal average. This results appears to be a realization of the general effect that when risk is highest, investors are rewarded with the greatest returns.

    Even Google is now scheduling "Analyst Day Meetings", where they attempt to reassure investors. They held their first meeting on Feb 9, 2005, and offered a free scooter as a door prize for attending. During that meeting Eric Schmidt said, "One of the great secrets of Google is that we are not quite as unsensational as we say we are". Also presented was a 70-20-10 strategy to reassure investors that not all of Google's efforts will be devoted to solving such things as perpetual life, unlimited costly energy, and travel to the planets. Anything that Schmidt says I would advise anyone to pay careful attention to as he is the master that was able to parlay a $1 million investment in the preferred stock of Google into a 5% interest in the company. The second "Analyst Day" for Google is scheduled for March 2nd, and I wouldn't be surprised if the performance of the stock were to exceed that of their last meeting on Feb 9, 2005 where the stock dropped from 198.6 to 191.6 after a decline from 210.86 to 198.6 in the preceding 3 days. Hopefully, some operatives will generalize these findings to the systematic study and classification of many other kinds of meetings.

    What an Opportunity!, by Victor Niederhoffer

    Recent moves in Google tell an incredible tale of woe, loss, hope destroyed, and opportunity.

                 Open      High        Low         Close
     Fri 2/10    362       365         353         363
     Mon 2/13    347       351         342         346
     Tue 2/14    345       352         342         343
     Wed 2/15    341       346         338         342
     Thu 2/16    346       367         344         366
     Fri 2/17    370       372         364         369

    As is well known, the financial weekly published a bearish piece about Google that hit the stands after the close on Friday, Feb. 10. The stock promptly opened down 5% on Monday, trading 20 million shares around the opening of 347. Like night follows day, the canes were taken out, and after backing and filling to further unloose any weaks and falling an additional 2% by early Wednesday, the mistress of markets moved the stock 2% above its Friday close by the end of the week. As Bacon would say, "The public has no right ...." Perhaps some poor shaver will read the above and generalize this observation.

    Two Books on Academic Volatility Research, Reviewed by Dr. Alex Castaldo

    Half of the 2003 Nobel prize in economics was given to R.F.Engle "for methods of analyzing economic time series with time-varying volatility" (with the other half to Clive Granger "for methods of analyzing economic time series with common trends (co integration)"). Since Engle discovered ARCH models on a trip to England in 1979 there has developed a large (and probably excessive) research literature that tries to refine and extend these models. There has been a proliferation of models with names like GARCH, EGARCH, IGARCH and so on. What is the value of this research to investors?

    The basic ideas are simple enough:

    P. Rossi, ed: "Modeling Stock Market Volatility" (Academic Press, 1996

    This book is a collection of advanced research papers written during the boom phase of volatility research. Daniel Nelson (of the University of Chicago) is the author of more than half of these papers, he is joined by well known authors such as Engle himself, Hansen, Bollerslev and others. The papers' mathematics are very advanced, at the frontiers of econometrics; I have not been able to fully work through any of the 14 chapters! Most of the book is taken up by proofs of various results.

    It is difficult to know what value, if any, this book will have in the long run. One chapter "ARCH models as diffusion approximations" has already become somewhat well known. The author shows that there is a relationship between the ARCH models of Engle and stochastic volatility models (such as Heston's) that are used in option research; that is important theoretically, and it is not too surprising since they are trying to model the same phenomena in different ways (discrete time in the former case, continuous time in the latter). Chapter 3, which introduced the EGARCH model, is probably important. For the other chapters, it is impossible to judge now how important its contribution will be without being an expert in the field. The final chapters, for example one about bond option pricing, don't seem to fit very well in a book about stock market volatility.

    Probably the only way to make money from this book is to avoid buying it. It belongs in university libraries or on the shelves of a few researchers who need proofs of certain theoretical results. Most of the material would seem to belong in research journals rather than a book, although I can understand the decision to honor Daniel Nelson by publishing it after his death.

    S-H. Poon: A Practical Guide to Forecasting Financial Market Volatility (Wiley, 2005)

    This book is addressed to a more general audience than the previous one. It is an expanded version of a survey article published in 2003 and tries to give an overview of the huge amount of volatility research of the last few years. It promises in some sense to be the antidote to the Rossi book.

    The author has reviewed 93 published articles dealing with volatility forecasting. These are listed in an appendix, together with a telegraphic summary of the findings (for example: Tse and Tung (1992) looked at the Singapore market from 1975 to 1988, the best vol. forecast was EWMA, the next best the Historical Vol., GARCH was last). Looking at this appendix it is clear that the Implied Volatility from the option markets is often the best or one of the best forecasts of Vol. The market can often do a better job than the models.

    The book starts with a review of the definition of volatility and some of its basic properties. There is a chapter on forecast evaluation, including the new Diebold-Mariano technique that has attracted a lot of attention. This is followed by chapters on ARCH and related vol. models. Finally a discussion of option pricing and risk management in light of these models.

    I found this book useful in learning the latest academic thinking about vol., even though it is not as readable or well organized as it could be (with sometimes too little detail and sometimes too much, and some jumping around between topics). It does not cover how to actually estimate Arch models (for that the Diebold book's appendix, recommended by the Chair, can be used), and it is more "academic" than "practical" despite its title. But it is an informative and useful book.

    Alston Mabry Analyzes the Effect of State Corporate Tax Rates on Stock Performance

    Risk Aversion as a Cultural Norm, from George Zachar

    The paired notions of risk/reward that we see in markets can also be applied to the sphere of scientific/industrial research.

    An article entitled The Culture of Fear discusses evolving social attitudes toward risk, and there are many many parallels to what we see in public/official reactions to events in finance.

    "...there has been a shift in moral reaction to harm. People no longer believe in natural disasters or acts of God. Today, people suspect that someone is behind a disaster, an irresponsible corporation or a cowardly bureaucrat. Indeed, accidents don't happen anymore; they have been redefined as preventable injuries..."

    "...a return to pre-modern days of higher superstition, where every event has a deeper meaning. In the medieval era, the hand of God or the malevolent influence of Satan explained why people suffered misfortunes. Today the malevolent hand of government or corporate America is to blame for every catastrophe..."

    "...that the nature of harms is represented in increasingly dramatic fashion. People are no longer expected to rise above adversity or encouraged to get on with their lives after they experience a hard knock. They are instead victims who are "scarred for life" and perpetually "haunted" by their misfortunes..."

    "...fear that actions like inventing new medicines, chemicals, and energy sources might have unknowable, irreversible, and ultimately catastrophic effects in the future..."

    "...Worst case thinking decreases our cultural capacity to deal with uncertainty. Risk becomes something to avoid, not an opportunity to be seized..."

    "...the increasing treatment of safety as an end in itself..."

    "...Policy is focused on reassuring and supporting people, and risk taking is stigmatized..."

    Many of the above items can simply be traced to the government/legal/press cabal of folks who specifically profit from the creation and exploitation of a fear/blame culture.

    Aspergers and Game Theory -- A Contribution to the Personal Development Department, from Mark Goulston

    As a clinical psychiatrist for more than 25 years I have seen many successful, goal-oriented-to-a-fault Aspergers or Asperger-featured men who succeeded in the world of business but had a heck of a time with their personal relationships.

    I remember one such man who brought his eleven year old daughter who he was having a lot of trouble with to see me. She just didn't seem to do what he wanted her to do. During the session I asked his daughter what it was like to have a frustrating conversation with him, close her bedroom door, and then flip her middle finger at him, muttering f**k you to him. She had not told me that she did that, I just intuited it. When I said that to her, she started sobbing deeply, clearly feeling the pain of hating someone that she also loved. After she kept crying for nearly a minute, her Asperger dad started crying. He touched the tears, not quite understanding why he was crying. I adim what was going on. As bright and successful as he was in business was as clueless as he was about his relationships. He looked at me with tears running down both cheeks and said in a puzzled and distressed voice: "My daughter is in pain and I think I may have caused it" (since that was the last thing he ever wanted to do, he couldn't comprehend how she could be in such pain).

    I have also done house calls to dying patients for my entire clinical career and some of these people I have treated have also been a bit tormented towards the end.

    I remember a world famous composer and musician, an icon in his field, known as much for his joylessness as his incredibly productive career. Near the end of his life I asked him why he was so miserable for most of his life (not to mention how he made those around him feel.) He told me that despite being popular and successful for more than 40 years, there were only five times when the music in his head matched the music he composed or played. Knowing what perfection was on those five occasions, every day he tried to make it happen, only to be disappointed.

    I told him that to know absolute perfection once in a lifetime was a lot, to know it five times was something nobody experienced. I told him to let it go already. He had blown it (his chance to live a satisfying life) by trying to make perfection the standard, when it can only be an ideal.

    I also attended a world famous giant in the entertainment industry, who two weeks prior to his death looked just awful. I asked him: "What's wrong and I don't think it's about dying, since you've been dying as long as I've known you?"

    He looked at me and said: "I don't think I've ever done anything important in my life."

    I tried to list all his accomplishments, the industry he had , started and grown, the thousands of jobs he had created, the medical center named after him. He interrupted me and said: "Don't con a con man, especially when he's dying. I have all the love that money can buy and that's all it's worth. I also have two ex-wives I beat up pretty badly in my divorce and a bunch of kids that will never be able to support themselves."

    As smart as he was, he felt he had out-smarted himself.

    Victor Niederhoffer on Resources for Managerial Economics

    The articles of Mark Hirschey, the famous value investor "who has spent every waking minute for the last 30 years thinking of which stocks to buy" whilst leading annual pilgrimages to the Sage, are very much of interest. He has written on subjects such as incentives, advertising, good will, patent quality, research and development, spin-offs, extreme returns, internet promotions, loan loss reserves and corporate governance, and should be read by all those interested in individual stocks.

    Many of the articles document anomalies that existed in say, the five years ending 1999 or 2002, and should be updated for profits with prospective data sources, rather than the retrospective ones that all professors use, (if only the professors would use the relatively contemporaneous past issues of Value Line rather than Compustat, they would be so much closer to the right track.) A current edition of his textbook Fundamentals of Managerial Economics provides a good foundation for other excursions in these areas, including the extent to which companies maximize profits, demand theory with its current emphasis on asymmetric information, agency theory, game theory and contract theory.

    I am also reading and can highly recommend Nick Wilkinson's Managerial Economics, and find that a reading is very good for putting in perspective the dynamics of decision-making in a firm or in the marketplace that arise from the often conflicting economic, legal and psychological constraints and incentives that face stockholders, management, boards of directors, owners and consumers.

    The backdrop for analyzing the dynamic and static aspects of management actions in such areas as pricing, quantities, costing, profit maximizing or smoothing, risk, innovation, economies of scale, mergers, marketing, dividend, capital budgeting, reporting and inventory management has become both richer and deeper over recent years . Both of these books document many interesting past and outdated studies in this area, provide a good introduction to the current state of economic thinking that puts these decisions in perspective and provide a springboard for many fruitful studies that have the potential for landing the readers in relatively untraveled territory.

    P.S. Something I have noticed on my periodic visits to universities is how much of current economics and business research is directly relevant to finding anomalies in the markets. Most recently this occurred on my visits to Yale, NYU, the University of Vienna and Wharton. While at each of these Universities I found literally hundreds of ongoing studies and researchers working on the practical and theoretical goings-on in this field.

    This memory was sparked by coming across a site from the Stockholm School of Economics Center for Financial Analysis and Managerial Economics in Accounting. Here studies of funding requirements, capital structure, dividends, financial rations, accounting numbers, bankruptcy, "statistical association between accounting numbers and stock or bond market prices" and information content of financial statements are ongoing. Multiply the output of this center by several such departments in each of say 200 major universities and then square it with the work going on in not-often-seen centers such as those in the Ukraine or Lithuania, and the extensive unpublished work of hedge fund research centers becomes enormous and mind boggling. Note for example that to search "managerial economics" "stock market" on Google finds 22,100 entries, and using the Managerial ~Economics ~Stock Market (the tilde for synonyms) gives 1.56 million entries.

    In considering this landscape:

    It is good thus to try in our imagination to give any form, some advantage over another. Probably in no single instance should we know what to do, so as to succeed. It will convince us of our ignorance on the mutual relations ((((and competition between))), a conviction as necessary (for proper research and investment decision making ), as it seems difficult to acquire ... When we reflect on this struggle, we may console ourselves that no fear is felt, that death is generally prompt, and that the vigorous, the healthy, and the happy survive and multiply.-- Charles Darwin, The Origin of Species, Chapter 4

    I have just read this passage out loud again, and recommend that others with humble and inquiring but profit-seeking minds do so as well.

    Stories to Tell

    HE: Your father advises me to invest my fortune in Wall Street. It would be politic, I suppose.

    SHE: No, don't you do it! After he'd won all your money he'd never let us marry.

    ["Love and Duty," Life, January 23, 1896, cover. From the Kelly Collection of American Illustrations, on exhibit at the Dahesh Museum of Art, Manhattan]

    Briefly Speaking, by Victor Niederhoffer

    Markets at Extremes: A good way to start the day off is to see which markets are at extremes. Note the particularly unusual constellation at present. A particularly glaring set of minima occurred once again in the commodity indexes, typified by the eight-month low in the Goldman Sachs Commodity Index at 404.50, compared with the previous low of 403 on June 3. It is no coincidence that this low occurs in conjunction with the closing of the S&P Managed Futures Index, widely considered to be an investable trend-following index, at 1044.8, the lowest since Nov. 24, and about flat for the last three years. Such lows are all too predictable, considering the zero-sum-game aspects and transaction costs involved. It is always good to keep in mind the role of prices in a competitive system such as ours, covered empirically in Julian Simon's books The State of Humanity, and The Ultimate Resource. The analytical reasons for this regularity are succinctly summarized in one of my favorite books on microeconomics --  the previously very rare but now reprinted Price Theory of Milton Friedman. He queries what prices do to adjust the quantities people want with what is available. "Prices transmit information, they provide an incentive to uses of resources to be guided by this information, and they provide an incentive to owners to follow this information".

    Looking at the most recent seventy 10-day minima in the Goldman Sachs Index, there is some good news for that vast majority of the public who came in, as they must, with the greatest dollar values near the top. On average, while such minima lead to random moves in bonds and gold over the next five days, they are somewhat predictive for the next five days in the commodity index, with an average gain of 1% and a 60% chance of a rise. However, because of the upward drift in the series of commodity spot prices, starting January 2002 at 167 and ending at 421, the moves must be adjusted downward by half, since for any five-day period in the last four years, the average change was 0.5%, leading to an adjusted z of a mere 0.1 and a wide 95% confidence interval ranging from -5.5% to 6.5% Someone's going to tell me that this rise from 167 to 421 in the spot index, which roughly parallels the rise from 200 to 404 in the futures index over this period, shows the wisdom of investing in commodities and validates the meme coming down the academic and sellside pike that commodities are just as good an investment as stocks over the long run. I would refer these to Simon and Friedman above and add that such studies and ideas are always guaranteed to happen after ephemeral moves.

    Louis L'Amour: I always find the proverbs, wisdom and depiction of everyday life in the West of Louis L'Amour worthy of the most careful consideration. For one, he has sold more Westerns than all other writers in the genre combined from the first, i.e., Owen Wister's The Virginian. My most recent learning experience came from reading High Lonesome, the story of the economics of the bank robbing business, and Son of a Wanted Man, a Godfather-type family story of bringing up a son to take over the family business as head of an outlaw syndicate. One of the lessons that L'Amour teaches is that Jesse James and other very successful outlaws made less per hour than they would have from working in legitimate jobs on the range. Plus, they would have had the advantage of not being treated by the public as an enemy and worse yet, as L'Amour says in a typical incisive touch, they wouldn't have been forced to treat the public as an enemy. I recommend the book A Trail of Memories: The Quotations of Louis L'Amour for a thousand insightful lessons about survival skills appropriate for a life of adventure and success in the West or the markets. My favorite L'Amour short story is Doc Yak in Yondering. It describes the sorry decline of a seaman forced to sell off and pawn all his possessions one by one as his fortunes suffer reverses. Both High Lonesome and Dr. Yak have great lessons for those who are overconfident in using or selling fixed systems following ephemeral moves in one market or another, and those who rely unduly on ballyhoo. And after drying the tears and reading them out loud to your family, both are also guaranteed to teach you much about avoiding an ambush, and the taking of excessive risk, two key dangers in the West and Wall Street. One of L'Amour's best is From the Listening Hills, which describes the last hours of a hunted man surrounded in the desert by numerous enemies almost certain to shoot him dead as he desperately pens a letter to his unborn son with lessons on how to avoid such a fate, in between fruitless attempts to ward off his inevitable capture.

    One of the bittersweet things about reading a L'Amour book is that I always know someone exactly like the anti-hero who always ends up in boot hill after rounding up too many head of maverick, riding too close to the edge of a precipice, and wheeling and dealing with the big outfits. Often that person, especially one who rides in somewhat unfamiliar territory, bears too close a resemblance to me.

    Stefan Jovanovich responds:

    When I was in Key West supervising all the washouts from the Fleet Sonar School (they cut the grass while waiting for transfers; I drank coffee with the Chief), I got to know the Commanding Officer, and he got to know me. He gave me lousy fitness reports (deserved) and at the same time taught me how to be something at least approaching a mensch. He survived 2 sinkings in WW II. He thought only the 1st one was his fault. "But," he told me, "I got just as wet both times."

    The Assistant Webmaster notices the connection to Prof. St#ven L#vitt's new book:

    So why do drug dealers still live with their mothers? Because most of them don't make much money. Based on unbelievably detailed records of an actual Chicago neighborhood gang, L#vitt found that, while the leader (who's now in jail) made $100,000 a year (tax free) over four years, his officers made only $700 a month and his foot soldiers made only $3.30 an hour, less than the minimum wage. "They had no choice but to live with their mothers." Who knew?

    From the Ministry of Non-Predictive Studies: Sharpe Ratio for Holding Periods, by Kim Zussman

    Recently, I saw in a Bodie and Merton text that there is no time diversification, in the sense that holding period does not reduce risk. So here is a study (yet another proving what is already known)  using SP500 daily returns from 1950 to present.

    The idea was to check what kind of reward/risk ratio was associated with various holding periods, and whether this follows a pattern. Constructed a kind of Sharpe ratio (sans risk free term) defined as [return/(stdev of returns)] for an assortment of non-overlapping holding periods. Periods chosen in days were 1,3,5,10,20,50,100, and 200.

    Here are the results, with columns being #days, mean return, stdev of returns for the periods, and "Sharpe" [ (return-1)/stdev ]:

    DAYS    MEAN       STDEV     SHARPE
    1       1.0003     0.0089    0.0388
    3       1.0010     0.0159    0.0658
    5       1.0018     0.0211    0.0833
    10      1.0035     0.0292    0.1198
    20      1.0070     0.0417    0.1689
    50      1.0174     0.0625    0.2781
    100     1.0346     0.0849    0.4080
    200     1.0707     0.1297    0.5449

    One can immediately see that reward/risk increases with duration of holding period. Plotting this showed the relationship to be non-linear, but there was a linear regression of Sharpe on days holding (for a reason shown later):

    Coefficients 0.002517
    Standard Error 0.00027709
    t Stat 9.083688784
    P-value 9.99166E-05

    OK, the regression thinks the relationship is linear, and, in any case, Sharpe is highly correlated with length of holding period. However, I seem to recall that diversification of a stock portfolio scales with SQRT(# stocks), so I ran same regression with independent variable as SQRT(DAYS)

    Coefficients 0.039411123
    Standard Error 0.000677065
    t Stat 58.20880773
    P-value 1.72725E-09

    Which is essentially a perfect fit straight line. So reward/risk scales as SQRT(days holding period); if you want to double your Sharpe (for alpha free strategies), quadruple your days, etc.

    So what? For those of us who trade longer term, there could be less pain and associated risk of bad trades by looking at portfolios less frequently. Such shock factor risk declines with SQRT days as above.

    For those who do trade frequently and don't have any alpha, the transaction costs will eat your Sharpe. Assuming a very modest -0.1% cost round trip (per period), the table looks like this:

    DAYS     MEAN       STDEV     SHARPE
    1        0.9993     0.0089    -0.0730
    3        1.0000     0.0159     0.0031
    5        1.0008     0.0211     0.0360
    10       1.0025     0.0292     0.0856
    20       1.0060     0.0417     0.1449
    50       1.0164     0.0625     0.2621
    100      1.0336     0.0849     0.3962
    200      1.0697     0.1297     0.5372

    Comparing this with no transaction costs, Sharpe drops pretty badly for periods less than 20 days.

    The Minister speaks:

    The ratio of return over standard deviation is definitely something you'd expect to go with the square root of time, because the numerator will go with time and the denominator with the square root of time.

    If you have a trading strategy that has expected one-day returns of 0.2% and standard deviation of 1%, then first of all please call me, and second of all, its annualized Sharpe ratio (neglecting the risk free rate) would be sqrt(250)*(0.2)/(1.0)=3.2, where the "250" is the number of trading days in a year. I think the usual convention is to annualize the Sharpe ratio, so you can compare apples to apples.

    (Of course there's false precision in all this.)

    Survivorship Bias? by James Sogi

    I have a 1956 Les Paul Jr. Bob Marley and John Lennon played the same model. It's a real collectors item and it's worth some bucks. But is it good because it's old? No. When made, it was one of thousands-- a mid priced model, nothing out of the ordinary. But among the thousands, a handful, by random chance were fit together well, sounded good, the wood was just right, and played well. These few were played, treasured and survived. The rest are in the trash where they belong, just poorly made cheap guitars. It's an old good guitar because it's good, not that they did things better in the old days. I just got a new G&L Asat Classic Blues Boy Butterscotch blond guitar.

    It's sweet. Keith Richards plays one that looks like it. It's a well made modern guitar with the latest technology and it plays and sounds as good as the classic Les Paul that is worth 10 times more. The mistaken belief that old guitars are good by virtue of their age is survivorship bias.

    Update to Low Tax States and Stock Performance Study, By Dr. Alex Castaldo, Vic Niederhoffer & Vincent C. Fulco

    A recent Barron's article (“Revolution on Wheels” by Karen Hube, 02/13/06) highlighted an emerging demographic trend of individuals fleeing high tax states for those which provide for higher retention of one’s disposable income. The focus on this migration caused us to revisit a December 2005 study of the aggregate performance of public companies domiciled in similarly low tax states. The premise for our study was that companies in business friendly environments were more likely to be strong stock performers. Simply put, lower corporate taxes mean the owners of the firm get to retain more of their hard earned and costly capital which can be paid out or put back into productive use thereby perpetuating value creation. As for employee incentives, our research supports the notion that states with low corporate taxes also maintain low individual taxes. This should lead to a corporation’s enhanced ability to attract highly educated, productive employees seeking to retain more of their paycheck as the Barron’s article suggests is happening at a quickening pace. Moreover, state governments ongoing de facto pledge to keep taxes low can signal that they are pro-enterprise and pro-stockholder.

    The findings of our earlier study bore out our speculation. We examined indices created by Bloomberg for companies in Arizona, Nevada, North Carolina, South Carolina and Florida. The indices are a diverse and deep set with as many as 400 constituent members. Representative companies include Altria Corp. (MO) in North Carolina, Office Depot (ODP) in Florida, AVX Corp. (AVX) in South Carolina and Dell Corp. (DELL) in Texas. From the respective index’s inception to 12/05/05, we found that every index out-performed the SPX by a wide margin; ranging from 16.14% in the case of North Carolina to 137.85% for Arizona.

    The updated results remain equally impressive as the companies underlying the state indices continue to handily beat the SPX.

                                                                                SPX       Out Perf.
    State             Start       StartDate     Cur      CurDate     PrcChg    PrcChg     vs.SPX
    Arizona           229.94      12/31/1999    529.22   2/10/2006   130.16%   -13.77%    143.92%
    Nevada            Not Avail.            
    North Carolina    100         1/2/2002      127.56   2/10/2006    27.56%     9.73%     17.83%
    South Carolina    100         12/31/2001    148.3    2/10/2006    48.30%    10.36%     37.94%
    Florida           100         12/31/1999    135.16   2/10/2006    35.16%   -13.77%     48.93%
    Texas             178.89      12/31/1999    395.19   2/10/2006   120.91%   -13.77%    134.68% 

    If the data is segregated more finely into annual performance we find the following:

    States’ Percent Outperformance vs. SPX           
                          Year                                             YTD 
    State                 2000      2001     2002      2003      2004      2005       2006 
    Arizona               2.45%    30.59%    6.44%    41.60%    21.14%     8.80%      2.97% 
    North Carolina                           6.75%     1.30%     3.74%     0.58%      1.11% 
    South Carolina                           9.15%     2.37%     9.55%    10.44%     -1.65% 
    Florida             -11.48%    24.63%    7.32%    14.34%    14.69%    -0.75%      1.93% 
    Texas                28.62%     6.49%    9.97%     9.34%    20.00%    19.74%      5.73% 
    Average               6.53%    20.57%    7.93%    13.79%    13.82%     7.76%      2.02% 
    SPX Return          -10.14%   -13.04%   -23.37%   26.38%     8.99%     3.00%      1.50% 
    Russell 3000 Return  -8.52%   -12.62%   -22.81%   28.73%    10.08%     4.28%      1.96%                                      

    * S&P 500 and Russell 3000 returns included for reference purposes.

    With underperformance by Florida based firms in 2 periods, there were 24 out of 26 winning periods annually.

    Note: We used price weighted stock indices provided by Bloomberg that track the performance of each state. The companies are headquartered in the state (or have a substantial portion of their operations there) and have a minimum market cap of $15 million. We used 12/31/1999 as a start date or the first date the index is available. The indices include from 45 to 400 companies and are price-weighted indexes.

    Follow-on comments by Vincent C. Fulco

    Since its been well established that the extraordinary performance exists, we thought it would be interesting to look at the actual tax burden faced by the typical company residing in the states under review vs. a peer group of companies residing in high tax states mentioned in the Barron’s piece. While the high tax states were noted in the context of high individual income taxes, we correctly surmised that, other than Utah, the states also have some of the highest corporate taxes.

    State Income Tax Rates- Fiscal Year 2005

    US Average   6.68%      
    Low Tax States Under Study        
                  Vs. Natl.    
         Rate      Average    
    AZ   6.97%     0.29%    
    FL   5.50%    -1.18%    
    NV   0.00%    -6.68%    
    NC   6.90%     0.22%    
    SC   5.00%    -1.68%    
    TX   4.50%    -2.18%    
         Ave        Ave    
         4.81%    -1.87%    
    States Mentioned in Barron’s Article    
                  Vs. Natl.      
         Rate      Average      
    ME   8.93%     2.25%      
    D.C. 9.98%     3.30%      
    NY   8.78%     2.10%      
    HI   6.40%    -0.28%      
    RI   9.00%     2.32%      
    WI   7.90%     1.22%      
    VT   9.75%     3.07%      
    OH   8.50%     1.82%      
    NE   7.81%     1.13%      
    UT   5.00%    -1.68%      
         Ave        Ave      Differential  
         8.21%     1.52%       -3.39%                                                                                                                                                                                                                                                                                                                                                                                                                                                                           

    Source: Small Business Survival Committee

    Companies in the low tax states enjoy a benefit of 1.87% vs. the national average tax burden. More impressive is the full 3.39% differential vs. competitors in the high tax states. Ask a businessperson what they would do for an additional 3+ pts of profit margin. It is as if one were running in a footrace and given at least a 30 second head start.

    There are numerous reasons worth considering for why these lightly taxed firms’ stock performance is so robust. It is an elemental point of business that the more profit flowing to the bottom line, and the more sustainable those profits, the more valuable the franchise becomes. Another reason could be that funds not allocated to state taxes are available for debt service, higher capital expenditures or R&D investment relative to one’s peers in higher tax states; all activities that improve a firm’s future financial condition and flexibility. A healthier corporation is more likely to add employees, grow their operations and pay above market wages. From the government’s perspective, if we assume the level of low corporate taxes is a proxy for a state’s commitment to maintaining an attractive, hospitable business environment, one can see the positive tone leading to increased capital formation, risk taking and lower capital gains taxes. The last of our theories is that of improved employee productivity which can take many forms. At the corporate level, one can conjecture that with the aforementioned commitment to a reduced state tax bite, it may be less necessary to allocate finance staff and resources to handle complex and changing tax regulations. This human capital can be redirected to improving one’s competitive advantage; typically through sales, marketing, strategy and product development.

    Besides explicit stock performance, other tangible measures of a more benevolent tax regime can accrue in the form of improved profit margins, higher levels of sales and income per employee, higher returns on R&D expenses and improved capital utilization among others. It really comes down to the creation of a virtuous circle of improving financials leading to stock performance leading to better opportunities for the company, i.e. raising cheaper capital, being able to purchase acquisitions with high priced currency (stock transactions).

    In an increasingly transparent and interconnected world, capital, whether intellectual or monetary, is highly transferable and can seek the best environment in which to reside and grow. If the 5 years of stellar returns from the companies in our study is representative, state governments, particularly those which are increasing the already onerous burdens, should heed the market’s message.

    A Curious Situation, from David Wren Hardin

    Pinning is a fact of life for stocks. The open interest in AMAT right now on the 20 line is roughly 60,000 contracts. That's 6 million shares of stock, or over 20% of the day's volume to date.

    The question a lot of players have is whether stocks get pinned on their own, just as a matter of the trading around the strike by the participants in the open interest, or if Big Cyborg Banks (BCBs, not sure who coined this earlier, but I like it so I'm stealing it) nefariously "push" the stock to a pin to maximize their profit at the expense of your poor grandmother in Iowa.

    I think it's mostly random, except of course when it isn't.

    Nigel Davies on Chess and Poker

    Just a quick note to say that there is a much stronger relationship between Chess and Poker than many people suppose, and that chess professionals have been switching to poker in droves.

    On Being George (Washington not Bush) and Presidential: What a Difference 210 Years Makes. By Mark Goulston, M.D. and Kevin Gregson

    Friends, And Fellow Citizens

    The period for a new election of a citizen to administer the executive government of the United States, being not far distant, and the time actually arrived when your thoughts must be employed in designating the person who is to be clothed with that important trust, it appears to me proper, especially as it may conduce to a more distinct expression of the public voice, that I should now apprise you of the resolution I have formed, to decline being considered among the number of those out of whom a choice is to be made...

    Though, in reviewing the incidents of my administration, I am unconscious of intentional error, I am nevertheless too sensible of my defects not to think it probable that I may have committed many errors. Whatever they may be, I fervently beseech the Almighty to avert or mitigate the evils to which they may tend. I shall also carry with me the hope, that my country will never cease to view them with indulgence; and that, after forty-five years of my life dedicated to its service with an upright zeal, the faults of incompetent abilities will be consigned to oblivion, as myself must soon be to the mansions of rest. -- George Washington, United States, 17th September 1796

    These words represent a transition of leadership unprecedented in all of human history up to that time. This can be said without American bias. This was the first time a soldier, turned citizen-leader, willingly and voluntary turned over the power of a civilian government to another yet to be determined citizen leader. Known as Washington's Farewell address, it was not an address at all but an open letter to the then nascent American People.

    In order to fully appreciate the magnitude of this transfer of power, some historical context is important. Also, there is much that can be learned by entrepreneurs from George Washington, aside from this act of selfless leadership and dedication to his ultimate objective of creating a nation. Washington was after all, an entrepreneur himself. He had to creatively resource the new and under-resourced Continental Army. As a leader he had to train, organize, motivate and manage this new and different fighting force. His competition was larger, better trained, more mature and better established in its approach and very well capitalized. He led his people through very adverse circumstances, always keeping them focused on their higher purpose rather than their current difficult state of affairs.

    Washington had a keen understanding of the importance of making time your ally rather than your enemy. He did this through conscious procrastination, the art of picking your spots and not acting in haste. He knew that in order to achieve his ultimate objective, he did not have to defeat his enemy in every situation. He needed to achieve small, important victories that would inspire his people and sow the seeds of doubt in his enemy. Washington understood that the most important thing was to sustain and persevere. Rather than defeat the British militarily, he had to break their will. He had to convince the British command and the British soldier in the field that while the Continental Army might not achieve a decisive military victory, they would also deny that opportunity to the British. He needed to give the new enterprise known as America the gift of time. The time to develop, congeal and coalesce as a nation. Then the people would have even more to fight for, their higher purpose.

    To understand the monumental task that Washington had undertaken, is to understand his stature in having achieved it. Achieving victory with the forced expulsion of the British via the Treaty of Paris, gave Washington nearly unprecedented power and popularity. He was a truly mythic figure. His likeness was everywhere. Nearly all revered him and even his enemies and detractors had deep respect for his achievement. There were greater thinkers, orators and writers at the time, but no greater recognized leader then Washington. Washington could have had himself crowned king of America at that time and there would have been little to stop him.

    Instead he chose a different path. And with that choice set off a chain of events that has led to over two hundred years of peaceful, orderly transitions of power in the world's oldest operating democratic republic.

    In September of 1796, Washington demonstrated that he knew something that entrepreneurs, founders and leaders of all types should know but all too often fail to realize; that it was time. It was time to transition to the next level of stability and maturity as a government and as a nation. Good leaders know how and when to lead, great leaders also know how and when to leave. Had Washington chosen to continue, he knew intuitively, that the entire future, and nature of leadership in America would be forever different; and not better. He would have left this new democratic republic with the sense of dependency on charismatic leadership vested in a man, rather than the independence derived from faith in themselves, institutions, process and their guiding principles.

    In effect, Washington had come to an inflection point in the development of the new nation. Done well, the orderly transition would set this new country on an upward trajectory for growth and prosperity. Done poorly, the course would be set for dissention, dependency and the strong possibility this new enterprise would never reach its potential or survive at all.

    By powerful example, Washington created a fundamental precept that resonates today in American culture. That dedication to a cause, an idea, or a principle larger than yourself, demands that you subjugate yourself to it for the good of the whole. The power of humility cannot be underestimated in a great leader. A clear understanding and recognition of our faults can have a profound impact on others. The Farewell Address is a masterfully conceived message that in its entirety embodies both great ideas with the humility of a Virginia farmer of the day.

    The Farewell Address is a great study of how one gets the message out, and also about knowing your audience. The Farewell Address was never delivered as a speech, as many messages of its type were delivered at the time. Instead it was published as an open letter in to the American public in a local newspaper and subsequently picked up and reprinted all over the country.

    Washington was a master of symbolism, rituals and traditions from his years of military service. The crafting and placement of this message is no exception. Instead of an address to the Congress which may or may not have made its way to the people, he bypassed Congress completely and took his case directly to the public. It was his way of sending a powerful message about their role as a central player in the future success of their country. Again, an unprecedented notion for the time.

    The new country and its people were still trying to find their way in this new experiment, in effect, seeking their vision. This strategically brilliant use of media and direct communication not only conveyed the message in its content, but reinforced it through its method and use of plain language. Certainly, most of those reading the message then, did not take the time to analyze the strategic nature of it, but it set a tone and created an environment that while conceptual, was also palpable. That is what great leaders do. They set the tone and create the environment for future success for those best placed to make it happen, on the street, the shop floor or the local cubicle.

    Lobagola Analysis, by Steve Leslie

    I am working through the observations of Lobagola with respect to stampeding elephants as you mentioned in your book. Now I find this to be a fascinating observation on your behalf and upon further reflection one finds that there are corollaries that are found with respect to other animals in the wild. Some examples: terns travel thousands of miles to retrace their paths exactly; salmon journey upstream to lay their eggs in the same place that they were hatched. Such behavior is also evident in loggerhead turtles as they come onto the beach to lay their eggs and return to the ocean; and, of course, the Canadian geese as they fly along the Eastern Maryland shore during their migration. With those thoughts in mind let's move the discussion along.

    Now these observations to the naturalist are observed, cataloged and registered. He notices that they are predictable, not random, and as such observations became very valuable provided they are identified early enough in the process. Here is where it gets interesting. Where is the practicality of such observations. Notice in the wild the outcome is virtual death for the unsuspecting--the elephant, the salmon and the goose:

    1. The African hunter receives notice that a stampede of elephants has occurred and lies in wait for the return of the elephant to subsequently shoot the animal hack, off the ivory tusks and ship them to the orient for re-manufacture into artwork.
    2. The American hunter dons his L.L.Beans, waders, and GoreTex, loads his Benelli and lies in wait in his duck blind gets practically frozen to the bejeesus and shoots the unsuspecting fowl that fly overhead.
    3. The Grizzly stands on an outcropping and slashes at the king salmon with his razor sharp claws who struggle to swim upstream. The poor salmon are merely trying to return to their breeding grounds to procreate their species. The mother, filets the salmon and serves it to her cubs that provides a meal that in her mind equals any delicacy offered at Tavern on-the-Green.

    At this juncture you are probably wondering what is the point of this discussion. Who benefits from these patterns. It is that which is highest on the food chain. Whether it is the grizzly or man, it is the observant one, the cunning, the wily veteran who profits the most. The ones who note that said migration is in process. Who is the "victim". It is the poor animal lower on the food chain who is acting out of instinct merely doing their job, contributing to the process.

    The same is true in the markets. Let's take one example in the stock market. Substitute a stock from the late 1990's: Cisco. At one time Cisco was priced at 80 dollars per share. The unsuspecting public reading research reports and hearing glowing testimony from such renowned celebrities as Blodgett, Meeker and Grubman buy all the dreck that the well informed are now selling. As the fortunes of the market turn and the stock now begins to fall, the public begins selling into a market that has bids falling daily on a journey to perdition.

    In commodities, look at silver after the Hunts had their fun in driving it to such nosebleed levels as 50 dollars an ounce. After six months the commodity falls faster than a sack of dirt off the back of a pick-up truck, eventually settling in at 5 dollars an ounce. Even the Hunts could not catch bids to salvage their mounting losses. The one Hunt who did not endure the carnage was Lamar Hunt who refused to play into the market like his brothers. Finally, this the important point, after it went down it stayed down, it did not rise miraculously like a phoenix out of the ashes. Now the security may be mostly dead (see The Princess Bride) but the point is once it loses its luster it loses it for a long time. So the moral is:

    1. During an advance of a security be very aware of any change in the movement of the security and use whatever sophisticated tools are available to observe that a major advance has stopped.
    2. Once a retreat has begun let it run its course and just get out of the way. Buying into the decline is a recipe for certain disaster and you will merely be added to the fodder for consumption. What do you find between the toes of an elephant? Slow running natives.
    3. After an intangible has fallen an inordinate amount realize that it may take a great deal of time for it to regroup and rebuild and it will not be overnight. It is far better for the speculator or investor to search out the securities that are beginning their advance, increasing their sales and earnings, building their management team and adding valuable employees. A procreation, if you will, an exponential growth that will fuel an eventual magnificent advance that can significantly add to the investor's net worth. And eventually repeat the pattern that has happened innumerable times in history.

    The Segway Creator Reveals His Next Act, from Prof. Ross Miller

    I saw an article on inventor Dean Kamen and his next idea, "to put entrepreneurs to work bringing water and electricity to the world's poor." This started me thinking; I spent several days in the Boston area over the past month, which would be the perfect place for Segways and the sort of people who would use them, yet I counted exactly zero Segways in use. Also, South Park did an amazingly hilarious take on the Segway that really nails the insane mindset behind the product. Extrapolating Dean Kamen's success with Segway to poverty, I fear he would eliminate poverty by eliminating all the poor people.

    Roger Arnold Contributes to the Daily Spec Real Estate Department