Field of play
Rising prices are a narcotic
There are four words that cause investors much grief. They are random, unpredictable, risk and uncertainty. This post is about the word random.
Investing is a field that is necessarily strewn with masses of data. The data include prices, price changes, trading volumes, financial data, economic data and so on.
In investing, none of this data is random. Any investor who treats such data as random is guilty of fuzzy thinking and will suffer as a consequence.
Random numbers
Random is a common word in English usage. In ordinary use it means haphazard or without aim. In math and statistics, it means each data item has an equal chance of selection. The defining feature of randomness of a series of data is that each data event be independent from all other data events in the series.
So, for example, if I flip a fair coin, the outcome heads or tails, is random. In political polling, the sample of several thousand voters before an election, is chosen at random. If it were not chosen at random, the poll would not be valid statistically.
Mathematics has supplied two valuable ways to tame masses of data. These are statistics and graphs. Statistics and graphs are useful with non-random data but they must be treated with special care.
Statistics
Random data produce normal distributions. Non-random data do not. So, with non-random data you get things like fat tails and warped standard deviations.
One of the most revealing outcomes of the Great Financial Crisis of 2008 was the failure of a number of sophisticated financial models that were based on statistics. Long Term Capital Management collapsed losing billions when their risk models failed them. Banks found their Value-At-Risk (VAR) models didn’t work.
One remarkable admission came when the CFO of Goldman Sachs, David Viniar, announced in August 2008 that Goldman’s flagship GEO hedge fund had lost 27% of its value since the start of the year. As Mr. Viniar explained, “We were seeing things that were 25-standard deviation moves, several days in a row.”
At the time a lot of commentators huffed that a 25-standard deviation event should only occur once in 100,000 years. Later, mathematician calculated that the 100,000-year estimate was way off the mark. The number of zeros to add would stretch for miles. The best estimate was of a 25-sigma event being on a par with Hell freezing over.
Graphs
Graphing of data has been around for hundreds of years and generations of scientists have developed skills in sussing out what can be learned by simple inspection of a graph.
Even random data, such as the results of flipping a coin one hundred times, are susceptible to recording and analyzing and graphing. The amazing thing about random numbers is that they can show apparent patterns. Of course, the patterns are only illusions. They aren’t telling us anything. It seems humans constantly fall into the trap of reading something into patterns in random numbers.
Daniel Kahneman explains: “Random processes produce many sequences that convince people that the process is not random after all.” (Kahneman, Thinking, Fast and Slow. 2011) p115 This is a risk we must be conscious of.
Confusion begins
It seems that in 1953 “Maurice Kendall, a British statistician, found that, instead of behaving in predictable ways, share and commodity prices followed a “random walk”.” The Economist magazine on December 5th 1992. This mischaracterization led to decades of confusion.
The term ‘random walk’ is a mathematics term to describe movements that are completely random. It seems that scientists started using this term to describe the motion of molecules in a fluid. It is also sometimes called a ‘drunkard’s walk’. (Mlodinow, The Drunkard’s Walk, How Randomness Rules our Lives, 2008) p167
As reported by Jeremy Siegel, in the 1950s Professor Harry Roberts at the University of Chicago, “…simulated movements in the market by plotting price changes that resulted from completely random events, such as flips of a coin. These simulations looked like the charts of actual stock prices, forming shapes and following trends that are considered by chartists to be significant predictors of future returns. But since the next period’s price change was, by construction, a completely random event, such patterns could not logically have any predictive content. This early research supported the belief that the apparent patterns in past stock prices were the result of completely random movements.” (Siegel, Stocks for the Long Run – The Definitive Guide to Financial Market Returns and Long-Term Investment Strategies. 1998) p242 (Emphasis Added)
This was a mistake. Non-random data produce patterns. And random data produce what appear to be patterns. The mistake is to argue that since random data produce patterns, any data like stock prices that produce patterns must be random.
While the patterns in graphs of random data are illusions, and the patterns in graphs of non-random data may be valid and informative, there are also illusions of patterns in non-random data. Buyer beware!
More confusion
In a paper published in 1965 in the Financial Analysts Journal titled ‘Random Walks in Stock Prices’, Professor Eugene Fama at the University of Chicago, Booth School of Business wrote: “In an efficient market, the actions of the many competing participants should cause the actual price of a security to wander randomly about its intrinsic value.” (Fox, The Myth of the Rational Market, A History of Risk, Reward, and Delusion on Wall Street, 2009) p97 (Emphasis Added)
Fama is best known for his empirical work on portfolio theory, asset pricing, and the efficient-market hypothesis. He is Robert R. McCormick Distinguished Service Professor of Finance at the University of Chicago Booth School of Business. In 2013 he was awarded the Nobel Prize in Economics.
Fama conflated his efficient market theory and the claimed randomness of stock prices. Both ideas are fundamentally flawed. As for efficient markets see my post The conventional view of market efficiency is badly mistaken and related posts inefficient markets
Confusion spreads
Burton Gordon Malkiel is an American economist, financial executive, and writer most noted for his classic finance book A Random Walk Down Wall Street, first published in 1973. He is the Chemical Bank chairman’s professor of economics at Princeton University, and is a two-time chairman of the economics department there. This book has sold more than one million copies and is now in its tenth edition. It has misled tens of millions of investors about the stock market and random walks.
The title of the book is catchy. It uses the term ‘random walk’. Malkiel would have known that the term was coined by mathematicians and scientists. It is a term of art for them.
But, here’s Malkiel’s definition: “A random walk is one in which future steps or directions cannot be predicted on the basis of past actions. When the term is applied to the stock market, it means that the short-run changes in stock prices cannot be predicted. Investment advisory services, earnings predictions, and complicated chart patterns are useless.” (Malkiel, 1973,2007) p24
What is misleading is that the definition is dead wrong. Unpredictable does not mean the same thing as random, either in common parlance or statistics.
Are stock prices and price changes random?
Let’s look at whether stock prices are random. Coin flipping is considered to produce random data – a series of heads and tails. Assuming the coin is perfectly tossed and is perfectly symmetrical, the series will be random. As noted, the defining feature of randomness of a series of data is that each data event be independent from all other data events in the series.
The question then is whether the data in a series or sequence of stock prices of an individual stock or an index are independent. They would be independent if all prices in the series are completely independent of (i.e. uninfluenced by) prices that have come before.
Let us reflect on some of the factors that are at work in the real world of the stock market. The real-world story of stock prices is about human herding behavior, not about random walks.
Wisdom of seasoned practitioners
Gerald Loeb’s book, The Battle for Investment Survival, was published in 1935 and was the most popular book on investing written for individual investors for at least the next twenty-five years. (Loeb, 1935, 2007) Loeb was a stockbroker. He joined E.F. Hutton in 1924. Through the 1960’s he was one of the best known and most often quoted figures on Wall Street. The first edition of his book sold 250,000 copies. It was republished time and again, most recently in 2007.
Loeb wrote about the forces behind market swings: “Market conditions are fixed only in part by balance sheets and income statements; much more by the hopes and fears of humanity; by greed, ambition, acts of God, invention, financial stress and strain, weather, discovery, fashion, and numberless other causes impossible to be listed without omission.” He adds, “Even the price of a stock at a given moment is a potential influence in fixing its subsequent market value. Thus, a low figure might frighten holders into selling, deter prospective purchasers, or attract bargain seekers. A high figure has equally varying effects on subsequent quotations.” (Loeb, 1935, 2007) p2
What Loeb is talking about is not interest rates or expectations for profits. He is talking about the behavior of investors as human beings.
In 1937, Keynes wrote in ‘The General Theory of Employment’, published in Economic Journal, 51, 2 (1937), p.214, as quoted by Niall Ferguson: “(1) We assume that the present is a much more serviceable guide to the future than a candid examination of past experience would show it to have been hitherto. In other words, we largely ignore the prospect of future changes about the actual character of which we know nothing. (2) We assume that the existing state of opinion as expressed in prices and the character of existing output is based on a correct summing up of future prospects… (3) Knowing that our own individual judgment is worthless, we endeavor to fall back on the judgment of the rest of the world which is perhaps better informed. That is, we endeavor to conform with the behavior of the majority or the average.” (Ferguson, 2008)p.344. [emphasis added]
For an example of how investor confidence ebbs and flows we can turn to Peter Lynch who wrote: “For two decades after the Crash [1929], stocks were regarded as gambling by a majority of the population, and this impression wasn’t fully revised until the late 1960s when stock once again were embraced as investments, but in an overvalued market that made most stocks very risky. Historically, stocks are embraced as investments or dismissed as gambles in routine and circular fashion, and usually at the wrong times. Stocks are most likely to be accepted as prudent at the moment they’re not.” (Lynch, One Up on Wall Street. 1989,1990) p59
What is fascinating from this quote and from Loeb is that investor confidence can ebb and flow over long periods of time. Yes, it can fluctuate from day to day or from month to month. But, investors’ faith in the stock market can be crushed from time to time and may take years or even decades to recover. More recently, many investors were still afraid to put money into equities years after the fiasco of the financial crisis and stock market bath that took place centered on 2008.
George Soros offers his theory of reflexivity which is based on a feedback mechanism. Soros writes: “Rising prices often attract buyers and vice versa.” (Soros, The Crash of 2008 and What it Means, 2008,2009) p56 (Emphasis added)
What he is saying is that buoyant stock prices can cause investors to become more bullish thus increasing stock prices even if the fundamentals don’t change. He explains this further in an earlier book. (Soros, The Alchemy of Finance, Reading the Mind of the Market, 1987,1994)pp. 50-54.
The following assertions by George Soros seem to be supported by the ideas of behavioral psychology:
“Buy and sell decisions are based on expectations about future prices, and future prices, in turn, are contingent on present buy and sell decisions.” (Soros, The Crash of 2008 and What it Means, 2008,2009) p56 (Emphasis Added)
“Rising prices often attract buyers and vice versa.” (Soros, 2008,2009) p56 (Emphasis added)
Howard Marks has also written on this issue: “We learn in Microeconomics 101 that the demand curve slopes downward to the right; as the price of something goes up, the quantity demanded goes down. In other words, people want less of something at higher prices and more of it at lower prices. Makes sense; that’s why stores do more business when goods go on sale.
It works that way in most places, but far from always, it seems, in the world of investing. There, many people tend to fall further in love with the thing they’ve bought as its price rises, since they feel validated, and they like it less as the price falls, when they begin to doubt their decision to buy.” (Marks, The Most Important Thing Illuminated: Uncommon Sense for the Thoughtful Investor. 2013) p27 (Emphasis added)
Warren Buffett is reported to have told Congress on June 2, 2010: “Rising prices are a narcotic that affect the reasoning power up and down the line.” (Marks, 2013)p.101 (emphasis added)
So, when Malkiel says the price “cannot be predicted on the basis of past actions” he may be right. But that does not make the price change a random walk. It just means that it’s unpredictable in the short to medium term.
Conclusion
Prices and price changes in the stock market are not random. They are largely unpredictable, but not completely so. Ironically, it is possible to make a prediction as to where the S&P 500 will be in thirty years. One could say that all you have to do is compound the index at between 4% and 12% per annum and you will have a range that will have a moderate accuracy you can have some confidence in. On the other hand, no one can offer any confident prediction of where the index will be twelve minutes or twelve months hence.
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