From: John Conover <john@email.johncon.com>

Subject: forwarded message from John Conover

Date: Thu, 20 Mar 1997 01:12:48 -0800

Well, after the tech sell off today, (yesterday, Cisco announced that Internet stuff was slowing down, affecting profitability, followed by a similar announcement by 3Com,) I got about a zillion emails on whether to bail out of the tech stocks. I don't give financial advice, (it requires predicting the future, and that presents epistemological issues for me,) but I will offer a few data points to add to your intuitional tool box in such affairs. If you consider any industrial market, operating in a free economy, it will have fractal characteristics. (No kidding. Look at the graphs. You can tell by looking, if you know what you are looking for.) This is because such things are a self referential system, which, bottom line, means that scientific method is not applicable. (Godelian issues are the reason.) However, the aggregate operations of many agents, as they struggle to make sense out of what to do, with the data they have, and make operational decisions, makes the characteristics of industrial markets a fractal, (ie., a stochastic system, sometimes loosing, sometimes winning, in a fashion that has a Gaussian, or normal, distribution. There are other distributions that fractals can have, but they are not the discussion here.) With that said, we would expect that, since such things are fractal, to see these large swings where the market pro forma, (if you want to call it that,) swings above "average" for extended periods of time, and then swings below "average" for extended periods of time. (I did *_NOT_* say such things were cyclic, nor did I say they were periodic-I did say that they were stochastic. For the record.) What needs to be discussed is what "extended periods" means. Well, here is the way it works. If you look at the graph of a market, when it goes through zero, the probability that it will stay on that side of zero for n many time units, (say years, for the sake of discussion-which is commonly the way we talk about such things,) is proportional to the reciprocal of n to the three half's power, ie., P = 1 / (t^(1.5)). If we are in an "extended period," say for n many years, then the probability that we will stay for one more time unit in the "extended period" is proportional to the reciprocal of the square root of n, ie., P = 1 / sqrt (1 + n). These are the definitions of a Brownian motion fractal. The reasons for such a scenario is quite complex, but comes from statistical mechanics. There is one other characteristic of a fractal that needs to be discussed. And that is the concept of "self similarity." What self similarity means is that there is no time scale to a fractal. In point of fact, if you take your data by the day, by the week, by the month, or by the year, the scaling of the statistical data is a constant, (which in our case is the square root of time, ie., n = 1 / sqrt (scale), where scale is days, months, etc. As a side bar, this has significant implications to the mathematical analysis of such things, since the mean value theorem breaks, and we can not take derivatives of such things-the derivative of such things is a mathematical "dust" at plus and minus infinity. Fractals are everywhere continuous, and everywhere non-differentiable. Bottom line, is that Newtonian/Leibnitz calculus, ie., the mathematics of the transcendentals like logarithms, exponents, sines, etc., is not applicable in such things. However, early in this century, the stochastic calculus was invented to handle just such affairs.) But the statistics are constant, ie., they are time scale invariant. With that said, what is the interpretation of these things? Well, we would expect, that once a crossing of "average" in a market pro forma is made, we would expect a probability of it staying there of 70.7 percent. (So much for actuary tables, which are based on statistical independence of time interval, ie., 50%. And, so much for MBO, and revenue variances, which are based on the same thing.) And what about it staying yet another? About 60%, (57.73%.) And a fourth? 50%. And this holds true, irregardless of whether the zero crossing was to the "above" or "below" "average." And, it also holds true whether we are looking at things in days, months, or years. And so, should you sell out of the high tech markets. How many years has it been hot? You can figure the probabilities for yourself, and make your own decision. John BTW, want an intuitive example to support this hypothesis? Lets suppose you were an operations person for a company in an industrial market, with a lot of tenure-say over many decades. One thing you know, from your experience, is that markets go up and down. Note that on the average, over many decades, a market will be up for 3 years, and down for 3 years. Walla! What every marketing person knows, business cycles are between 5 and 6 years. (Actually, the word "cycles" is quite incorrect, since it also holds for months and days, etc., also, ie., it can be up on months, but down on years, at the same time, etc.) Want another one? What is the probability of an industrial market staying stationary for 5 years, (the question I am asking is, suppose we have a really great idea for a company, and that the market really, really, wants, and our information about such things is 100% accurate, and we want to form a company to exploit this market-what is the chance of a VC getting a payoff from investing in us? That depends on how long the market will remain up, before changing its mind.) Well, how about a probability of 1 / 5^(1.5) = 0.089, or about 1 in 11. Which, not coincidentally, is very close to what VC's run, about 1 in 12. And, just for another one, but at a different time scale, what is the chance of a market success of an IC design that takes 6 months to design? (Fortunately, I have an abundance of data on such matters, since I have been curious about such things for a long time. A polite way of saying I'm old.) Let me see now, 1 / 6^(1.5) = 6.8%, (which happens to coincide to the third decimal place with published data for the ASIC industry. This is an important concept, and is why John's maxim has been "time is the enemy," and "he that does the most the quickest, wins," since a 1 / t^n'th type of function falls off very quickly. Simple concepts, really, and also why programmed traders run by the minute on the ticker. Faster is better in things fractal.) ------- start of forwarded message (RFC 934 encapsulation) ------- Message-ID: <"0Tnr61.0.YF5.WcCCp"@netcom20> From: John Conover <conover@netcom.netcom.com> To: John Conover <john@email.johncon.com> NEW YORK (Reuter) - Stocks cut their losses Wednesday after suffering another bruising as investors turned negative on technology shares and long-term interest rates jumped briefly above the 7 percent level. The Dow Jones industrial average closed 18.88 points lower at 6,877.68 following a 70-point plunge. In the broader market, declining issues beat advances 1,532 to 931 on active volume of 535 million shares on the New York Stock Exchange. In the bond market, the 30-year Treasury bond was off 10/32, and its yield ended at 6.99 percent following a brief rally to 7 percent from Tuesday's close of 6.96 percent. ``We're nearly at seven percent on the long bond and we're certainly not going to make much progress while that's the case,'' said Harry Laubscher, an analyst at Tucker Anthony. ``For now, people seem very concerned about next week's (Federal Reserve) meeting,'' Laubscher said. Contributing to the worries about interest rates was a 0.3 percent rise in the Consumer Price Index for February, up from 0.1 percent in January. Economists had forecast a 0.2 percent increase. While the slightly higher reading was not greeted with alarm, economists said the data failed to show sufficient weakness to change the unusually uncertain outlook for the March 25 meeting of the central bank's Federal Open Market Committee, whose job is to determine the level of interest rates. ``The February CPI report won't change any minds about what the Fed will do,'' Bruce Steinberg, manager of Macroeconomics at Merrill Lynch said in a research note. ``We expect the Fed to leave policy unchanged, but we admit it is almost a 50-50 call at this point,'' he said. While stock traders remain extremely divided on the outlook for interest rates, their attitude appears far clearer regarding technology stocks, which have endured an extended thumping since peaking in late January. That trend continued in force, sending the Nasdaq Composite index to its lowest since early November, 1996. The Nasdaq lost 20.05 points, or 1.58 percent, to 1,249.29. The selling momentum appeared to gain momentum, hitting a wide variety of tech stocks. Networking, semiconductor and computer makers all finished with heavy losses. Intel Corp. fell 3 3/8 to 133 3/8, Ascend Communications Inc. fell 2 3/8 to 45 3/4, International Business Machines Corp. lost 1 1/2 to 137 7/8 and Microsoft Corp. sank 2 7/8 to 96 3/4. ``Everyone who wanted to sell is sold,'' said Gary Kaltbaum, director of technical research at J.W. Charles Securities Inc. ''I think we're bottoming for a bounce, but that said, I don't know how well we're going to bounce.'' Also hit hard were transportation stocks, which backtracked sharply from their recent rally. Among the losers, Burlington Northern Santa Fe Corp. fell 3 7/8 to 78 1/2 after the railroad company warned of weak first-quarter results. Airlines also finished lower, hit by profit-taking and rising fuel costs. Delta Air Lines Inc. fell 3 1/4 to 84 1/2 and United Airlines' parent UAL Corp. shed 2 1/4 to 68 1/4. Among other individual issues, Adobe Systems Inc. jumped 4 1/8 to 39, bucking the trend in tech stocks. The company reported first-quarter earnings that were stronger than analysts had expected. Lexmark International Group Inc. fell 3 7/8 to 23 7/8. The maker of printers and related products said its first-quarter earnings would meet analysts' estimates but revenues would fall short of expectations. The Standard & Poor's composite index of 500 stocks fell 3.89 points to 785.77. The American Stock Exchange index lost 3.65 to 591.80. The NYSE Composite index of all listed common stocks fell 1.81 to 413.59. The average share was down 18 cents. The Wilshire Associates Equity Index -- the market value of NYSE, American and Nasdaq issues -- was 7,468.572,down 49.322, or 0.66 percent. ------- end ------- -- John Conover, john@email.johncon.com, http://www.johncon.com/

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