Bernstein, Rational Expectations

William J. Bernstein has written a wonderful book for “adult” investors who are comfortable with basic math and statistics and who also enjoy a good turn of phrase. Bernstein, a retired neurologist turned financial theorist, has written about a dozen books, perhaps most memorably The Intelligent Asset Allocator, The Four Pillars of Investing, and The Investor’s Manifesto. Rational Expectations: Asset Allocation for Investing Adults (Efficient Frontier Publications, 2014) is his latest offering.

Bernstein is a firm believer in asset allocation and life-cycle planning. He is also a believer in statistical modeling. But he recognizes the inherent limitations of both planning and modeling. As he writes, “We could conduct, as I did in my prior books, complex spreadsheet and Monte Carlo exercises to predict just how many years it will take to reach a realistic retirement nest egg or at what rate it can be spent down. These calculations bring to mind the following joke: Q. How do we know that economists have a sense of humor? A. They use decimal points. There are just too many variables to pretend great precision: career and salary trajectory, personal and family health (and health expenses), to say nothing of the vicissitudes of the markets and of that cruelest mistress of all, human history. You might as well try to mathematically model your love life.” (p. 117)

Even though investing is a journey into the unknown, some quantitative measures help guide the way. Take variance drag, “a measure of how asset-class volatility reduces overall return.” It rears its ugly head in the relation between geometric return (the proper way of calculating investment returns) and arithmetic return. “The classic example of variance drag is the difference between two pairs of returns: +10%/-10% and +50%/-50%. Both sequences have the same A, which is zero, but their G’s are vastly different. The first sequence leaves you with $0.99 on the dollar; the second, with $0.75.” (p. 9)

Or consider extreme downward market movements, when “securities distributions appear to follow the same ‘power-law’ relationship followed by earthquakes, terrorist attacks, and terrestrial meteor/asteroid strikes, in which the logarithms of probability and of severity are linearly related. This relationship better predicts the much higher frequencies of severe events than the very low estimates from the Gaussian normal distribution.” (p. 20)




Rational Expectations is a sophisticated personal finance book, many cuts above the usual pap that gets served up to investors. It explains when the “rebalancing bonus” can actually be negative, describes “tilt factors” that are good short-term diversifiers as well as those that have longer-term benefits, and warns the investor away from eloquent forecasters (“Be especially suspicious of anyone with a plummy English accent.”) (p. 110)

And, for those who realize that sound investing is an informed process, it points the reader to resources with which he may be unfamiliar, such as Kenneth R. French’s 2008 presidential address to the American Finance Association on the cost of active investing and some books on financial history “listed in descending order of importance.” (p. 115) Heading that list are Edward Chancellor’s Devil Take the Hindmost (“what manias look like; how to recognize—and hopefully avoid—irrational exuberance”) and Benjamin Roth’s The Great Depression (“what the bottoms look like; how to keep your courage and your cash up”).

All in all, Rational Expectations is an eminently worthwhile read for the investor who hopes to retire one day, even if not from investing itself.

Gliner, Global Macro Trading

A few months back a reader asked me to recommend a good introductory book on macro trading, and I was stymied; I couldn’t think of a single title. Greg Gliner, a member of the global asset allocation team at AQR Capital Management and formerly an analyst at Tudor Investment Corporation, has set out to fill that void with Global Macro Trading: Profiting in a New World Economy (Bloomberg/Wiley, 2014).

The book assumes practically no knowledge either of trading vehicles or of trading itself. Imagine a fresh college graduate who majored in, let’s say, history and who has just been hired by a global macro firm. He knows next to nothing about bonds, commodities, foreign exchange, or international economics. He barely knows his way around equities and draws a blank when asked about technical analysis. Presumably, since the firm took a gamble on him, he’s a quick study. They give him Gliner’s book and tell him to digest it whole before his first day of work. Then and only then is he ready to start learning about hands-on global macro so he can eventually become a productive member of the team.

As this description indicates, the book—to be more precise, the second part “Global Macro Trading Foundation”—includes chapters on foreign exchange, equities, fixed income, and commodities, as well as (not telegraphed above) the role of central banks in global macro and economic data releases and demographics. These chapters conveniently bring together in one place a multitude of information that, though for the most part readily available, is scattered across the internet.

The first part of the book deals more generally with trading, with the longest chapter devoted to technical analysis. It also has a chapter on the trading process, sizing trades, and monitoring performance. Here some tricky concepts are dealt with in a perfunctory way. Correlation gets two very short paragraphs; the Sharpe ratio, Sortino ratio, drawdowns, and VaR are dispensed with in two pages. Gliner spends a little more time on monitoring performance and offers helpful hints.

The chapter on systematic trading is appropriate for readers who have some background in the markets and who are interested in portfolio construction. It is unfortunately too brief to be more than a teaser. Gliner takes the four assets he discusses in the book (currencies, equities, fixed income, and commodities) and suggests that “there are two portfolio strategies that can be deployed in these assets: directional and relative value. Relative value is more desirable for capturing various factors over time and requires greater leverage and position sizes relative to outright directional trades.” He continues: “Each asset has an overlay of factors … that can help define the expected value of each strategy as being under- or overvalued. For purposes of this chapter we examine value, trend, carry, and fundamentals as our strategies. … One must identify the [optimal] weights of each strategy to calculate their weights relative to one another.” (p. 93) “The basic construct of a systematic model involves breaking each strategy style apart and selecting the factors for value, trend, carry, and fundamentals that gives the highest Sharpe ratio possible and lowest drawdown ex ante…. Prior to summing the four strategy styles together, one must take factors such as illiquidity, tail risks, growth, and inflation into account.” (pp. 98-99) As should be evident, systematic global macro is no walk in the park.

Global Macro Trading is a broad-based primer. It gives the reader a good sense of what is involved in this general strategy and where he needs to get up to speed.

Schulman, Sons of Wichita

I’m not exactly best buds with the Koch brothers. And, having read Daniel Schulman’s Sons of Wichita: How the Koch Brothers Became America’s Most Powerful and Private Dynasty (Grand Central Publishing, 2014), I can’t say that I find them any more sympathetic. But at least I now understand them better. They are no longer “just the latest incarnation of a familiar American archetype that stretched from Thomas Nast’s political cartoons through Lionel Barrymore’s Mr. Potter in It’s a Wonderful Life, and from the Duke brothers in Trading Places to The Simpsons’ Montgomery Burns.” (p. 240)

There are not two but four Koch brothers—Frederick, the “I’m not gay” firstborn who eschewed business for the arts; Charles, the quintessential hard-nosed businessman and head of Koch Industries who spearheads the fight for the political soul of the country; and twins David, “an endearing figure on the New York society scene” and Charles’ ally, and William, the litigious Koch empire spoiler and America’s Cup winner.

To understand the Koch brothers it is necessary to understand their father Fred, since the old saying “The apple doesn’t fall far from the tree” is particularly apt in this case. His pathological anti-communism, which he saw lurking behind American foreign aid, modernist painting, the American civil rights movement, government handouts, and labor unions; his distrust of government in general; and his sometimes questionable business practices became, along with his vast fortune, his legacy to his sons.

Fred was an engineer with an MIT pedigree whose firm Winkler-Koch touted a unique cracking method for oil refiners. The problem was that both the lower court and a three-judge panel in the Third Circuit determined that its process was a knockoff. As it turned out, however, Universal Oil Products, which had brought suit against Winkler-Koch, wanted to be sure of a favorable ruling and bribed one of the appellate judges. The patent infringement verdict was ultimately vacated. This two-decade legal battle, a saga that “his sons drank … in along with their milk at the family dinner table,” sent “a strong message that the U.S. legal system was deeply flawed.” (pp. 30, 32)

Worse, “the toll that the Universal Oil Products battle took on Winkler-Koch’s revenues had pushed Fred and his partner out of the United States and into the welcoming embrace of Josef Stalin’s Soviet Union.” (p. 35) In 1929 Winkler-Koch signed contracts to design and construct fifteen oil cracking stills in the U.S.S.R.

The following year, when Fred went to the U.S.S.R. for a month and a half to check on the progress of his engineers, he was appalled at the conditions in the country. He was also subjected to the incessant taunts of his “minder” that the communists would infiltrate every aspect of American society. “The schools, the churches, the unions, the military, the government—all were communist targets.” (p. 37) When he returned home, Fred began a fervent anti-communist campaign.

His zeal eventually brought him to the notice of Robert Welch, founder of the John Birch Society. Fred joined the Society’s National Council and “threw himself more vigorously than ever into the fight against communism.” (p. 43) Although many people viewed him as “a red-baiting crackpot,” he was undeterred. For instance, he tried, and failed, to remove an admitted communist from the faculty of MIT, where three of his sons were studying.

“Of the four brothers, Charles most heartily imbibed their father’s hard-line political views…. Like his father, Charles occasionally speechified about the dangers of collectivism and the encroaching welfare state. … With Koch family friend Bob Love, Charles opened a John Birch Society bookstore on Wichita’s East 13th Street, down the road from his family’s compound. He curated a section there on Austrian economics (a school of thought that heavily influenced libertarianism) and enjoyed introducing customers to the works of economists including Ludwig von Mises and Friedrich Hayek.

“A family acquaintance recalled visiting the Koch family’s home one day in the 1960s, carrying a dog-eared copy of Ernest Hemingway’s The Sun Also Rises, the assigned reading in a college literature class. When Charles answered the door, his eyes lingered on the book’s cover. After an uncomfortable pause, he finally asked the visitor to leave the Hemingway book outside, since it could not enter the house.

“'Is there a problem?’ the puzzled visitor asked. It wasn’t like he was carrying a copy of Tropic of Cancer.

“'Well,’ Charles explained, ‘he was a communist.’

“The guest entered. Hemingway remained on the stoop.

“Communism may have been sweeping the world, but there was at least one threshold where, by God, it would not cross.” (p. 52)

Fifty years later Charles and David Koch are still fighting to remake America, promoting free-market economics and mainstreaming libertarianism. And with record revenues of $115 billion in 2012, Koch Industries can keep their dream alive.

Brown and Macke, Clash of the Financial Pundits

Clash of the Financial Pundits: How the Media Influences Your Investment Decisions for Better or Worse by Joshua M. Brown and Jeff Macke (McGraw-Hill, 2014) is a book by financial pundits about financial pundits. It alternates between reflections on the financial media (I assume written by Josh Brown) and interviews conducted by Jeff Macke. The interviewees are Jim Rogers, Ben Stein, Karen Finerman, Henry Blodget, Herb Greenberg, James Altucher, Barry Ritholtz, and Jim Cramer.

Since both authors are members of the financial media (Brown is author of The Reform Broker blog and a regular contributor to CNBC, Macke is the host of Breakout on Yahoo Finance), the reader can’t expect to be told: “just turn off the news.” Instead, the authors try to explain which pundits may be worth listening to and which ones are just noise, or worse.

For investors who are not intrinsically skeptical and who have no idea of how to separate the wheat from the chaff, the authors offer a few good pointers. For the rest of us—hardened, cynical folk that we are, the interviews offer some good tidbits.

The book has a strange subtext, along the lines of “I once was lost but now I’m found.” Jeff Macke recounts his career-killing “Car People” episode on the now defunct evening program CNBC Reports and his subsequent emotional descent and recovery. And he interviews three insiders who to a greater or lesser degree faced their own professional crises: Henry Blodget, banned from the securities industry but now the editor and CEO of Business Insider; Jim Cramer, who took a drubbing on Jon Stewart’s The Daily Show; and James Altucher, who seems to specialize in failing and bouncing back—and writing about it.

Whom do I personally consider worth listening to? First, those who readily admit they don’t know the answer. Bob Shiller comes to mind here. Second, those who move markets, such as David Tepper. And third, those who are both bright and entertaining, with Warren Buffett being perhaps the prime example. I assiduously avoid Cassandras, dim bulbs, and pompous pretenders—and does that ever save me a lot of time!

Cootner, The Random Character of Stock Market Prices, V

Today I conclude my series of posts on Paul Cootner’s classic book with some excerpts from his brief introduction to Part IV, “The Statistical Analysis of Option Prices.” Don’t forget that the articles in this section were written before the Black-Scholes pricing model was developed (1973).

* * *

“The richest field of application of the random walk theory of stock prices has been in the determination of the value of such derivative assets as puts, calls, and warrants and convertible bonds.” (p. 373)

“The second paper by Kruizenga and the one by A. J. Boness, both deal with the ‘rationality’ of put and call prices. … If both the buyer and the seller of such options could estimate, without error, the parameters of the distribution of stock prices, and if they each hoped to maximize their mathematical expectation of wealth, options would be so priced as to leave each without profit from repeated transactions. To test the correspondence between this view of option pricing and actual prices, Kruizenga examines hypothetical transactions at prices submitted to the Securities and Exchange Commission in the period 1948-1956. Boness looks at actual transactions during a shorter, and different, period (1958-1960). Kruizenga finds option purchasing to be mildly profitable; Boness finds it highly unprofitable. … Yet another study, by Richard Katz (1963, 1964), covering a slightly longer and different period, finds intermediate results: both purchases and sales of options are slightly unprofitable, these losses arising from the commissions paid to intermediaries.

“The general lack of agreement in these studies is not likely to fill the reader with confidence about the results. Still, some conclusions are probably safe. Option premiums are relatively more stable than rates of increase of stock market averages, so that when stock prices are generally rising rapidly results of call option buying will seem more attractive than in periods of relative price stability. This is not inconsistent with a random walk model of stock prices, in which expectations of future price changes remain constant at some long run average drift, because recent post rates of changes are no predictors of future changes.” (pp. 373-74)

“The final two papers address themselves to a different aspect of option trading—attitudes toward risk. If options are priced such that they offer consistent opportunities for profit to either buyer or seller, it can imply that such buyers and sellers either have consistently erred in their expectations about the future, or that they have attitudes toward risk which make them willing to buy or sell such options at prices different from their mathematical expectation.” (p. 374)

“A paper by Rosett (1964), to be published elsewhere, investigates a slightly more complex hypothesis. Rosett conjectures that buyers of puts and calls may have cubic utility functions, implying that they may be averse to increased variance in asset prices but that they may prefer assets that have positively skewed probability distributions; i.e., have greater likelihood of gain than loss. Using data on actual put and call transactions and exercise of those options, Rosett confirms this hypothesis.” (p. 375)

Cootner, The Random Character of Stock Market Prices, IV

Today I’ll share a few excerpts from Paul Cootner’s introduction to Part III of the book, “The Random Walk Hypothesis Reexamined.”

* * *

“Most of the work that follows the Moore paper stresses, in one way or another, the deviation of stock prices from the Einstein-Wiener process. The Alexander-Larson-Cootner-Steiger papers all question the independence hypotheses. The Fama-Mandelbrot material questions the assumption of Gaussian increments. The Osborne paper examines the stationarity of the process. In raising these questions it was necessary to invent subtle new tests, or to apply more esoteric probability distribution theory.” (p. 189)

“The central novel idea [in Larson’s essay] was the use of a test based on the range of a random walk to test in a more sensitive and powerful manner the resemblance of stock price series to a Wiener-Einstein type of Brownian motion model. If changes in stock prices tended to be succeeded by changes in the same direction, the range of segments of stock price series would tend to be greater, on the average, than segments drawn from a random walk. On the other hand, if changes tended to reverse themselves, the range would be less than that of random walk segments. The power of the range test lies in its sensitivity to nonlinear dependence.” (pp. 190-191)

“Cootner’s work (1962) divides into two parts. One part, like Alexander’s papers, is devoted to the testing of a decision rule, in this case one which is commonly referred to by stock market professionals [buy if current price is above the 200-day moving average, sell short if it is less than the moving average; reverse to close]. This model, unlike Alexander’s, is applied to individual common stocks, but like Alexander’s, it does substantially better than random buying of stocks on a gross basis—before deducting commission costs. This alone is evidence of either dependence or nonstationarity, although it is not evidence of market imperfections large enough to permit profitable mechanical trading rules.” (p. 192)

“The second part of Cootner’s paper is an attempt to characterize the observed deviations from a Gaussian diffusion process. The hypothesis suggested is that stock prices behave like a restricted random walk, a hypothesis which would explain (1) certain aspects of behavior of the kurtosis, (2) part of the fluctuating behavior of the serial correlations, and (3) the success of the Alexander-Cootner decision rules.” (p. 192)

“Osborne’s second paper (1963) … deals with differences in the behavior of low and high price stocks, the distribution of trading volume, ‘seasonality’ of trading patterns and prices, and the tendency of buyers and sellers to ‘prefer’ certain prices to others. All of these deviations from a random walk have interesting implications for the theory of stock price formation.

“Osborne finds, for example, that the occurrence of a transaction in (say) a given stock is not independent of past history of trading. That is, trading tends to come in ‘bursts:’ If recent trading has been heavy, it is likely to continue large. This observation can help to explain a phenomenon noted by Alexander (1964) and possibly one by Mandelbrot (1963). Alexander has found that the price changes in different subsets of the 1928 to 1962 period are significantly different from one another. This suggests that stock prices are a nonstationary process, which would be hard to analyze. Now Osborne’s results indicate that the observed pattern of behavior could result from a stationary distribution of price changes per transaction and a temporally dependent pattern of volume changes, a process which would be more amenable to study. A second possibility arises from some earlier work by Berger and Mandelbrot (1963) which suggests that stochastic processes that appear to have ‘bursts’ of occurrences may be represented by a model of independent increments which are distributed according to what Mandelbrot calls a Pareto-Levy distribution. Briefly, Berger and Mandelbrot argue that the individual ‘trades’ (transmission errors in their formulation) are in fact independent of each other, but the appearance of clustering is given by a larger probability of long intervals between trades than would be suggested by a Poisson model.” (pp. 193-94)

“Alexander argues, with considerable merit, that there are two separate issues involved in the study of stock prices. The one he chooses to study is whether, in point of fact, stock prices are a random walk, and his conclusion is that they certainly are not. A quite different question is whether or not stock prices are a sufficiently close approximation of a random walk, where the standard of ‘closeness’ is an economic one—that market participants cannot improve their performance by acting on the regularities.” (p. 194)

“The most striking material that Alexander brings to bear on the random walk question is … his investigation into the sources of the dependence of stock price changes. Such dependence does not appear to stem from the distribution of daily price changes themselves, since price series constructed by randomly rearranging the order of actual changes do not show the same nonrandom behavior.

“The ‘profits’ shown by the filter rule seem to derive from a tendency for ‘swings’—intervals between turning points defined by the filters—to persist slightly longer than would be expected in a random walk, for most ranges of durations of ‘swings.’ Since there is no similar tendency for daily price changes to come in runs, the Alexander data suggest that the nonrandomness of price changes is a complex nonlinear process.” (pp. 194-95)

“Mandelbrot’s main empirical argument is of two parts. The Pareto-Levy distribution would be expected to have more extreme values than would be expected from a Gaussian distribution. This is undoubtedly true from all empirical evidence, and to this degree the Pareto-Levy distributions clearly describe a phenomenon which is not explicable in a Gaussian random walk. The second underpinning of Mandelbrot’s empirical argument is the instability of the sequential second moment of changes in speculative prices. If we designate a series of squared deviations of successive price changes from their mean, the means of the successive (or partial) cumulative sums of those squared deviations are what we call the sequential second moment.” (p. 197)

Bulkowski, Getting Started in Chart Patterns

Thomas Bulkowski is probably the best known chart pattern researcher. Among his credits are the Encyclopedia of Chart Patterns and the three-volume Evolution of a Trader. In this second edition of Getting Started in Chart Patterns (Wiley, 2014), a book originally published in 2006 and newly revised and expanded with updated statistics, he introduces more than forty chart formations. Better yet, he explains how to trade using them.

Although the title indicates that the book is for novices, it is equally valuable—perhaps even more valuable—for more experienced pattern traders. Without continually reviewing, testing, and revising pattern trading strategies, it’s all too easy to trade yesterday’s market.

In two action-packed chapters Bulkowski explores trendlines and support and resistance. He considers support and resistance to be “the most important chart patterns” because “they show how much you are likely to make and how much you are likely to lose on each trade. That’s like playing poker and knowing the hands of your opponents. You won’t always win, but it helps.” (p. 35)

In the next two chapters he offers ten buy signals and ten sell signals. For each he explains how to identify the pattern and serves up trading tips. In some instances he also includes sections on measuring success and case studies.

Especially valuable are his chapters on special situations and busted patterns. Among the special situations are dead-cat bounces, gaps, and spikes and tails. My personal favorites are busted patterns. Bulkowski explains the general principle: “A busted pattern occurs when price breaks out in one direction, fails to move more than 10% before reversing and breaking out in the opposite direction.” The best performance, he’s found, comes from rectangles with downward breakouts. “They bust, and price shoots up through the pattern, rising an average of 61% above the top of the rectangle.” (p. 252)

Bulkowski can always be counted on to deliver a lively blend of pictures and number-crunching. This book is no exception.

Cootner, The Random Character of Stock Market Prices, III

Herewith some excerpts from Paul Cootner’s introduction to Part II, “Refinement and Empirical Testing.”

* * *

“Despite Bachelier’s very early interest in stochastic analysis of speculative prices and Working’s renewed interest in the 1920’s, stock market research from this point on was very slow to develop. While professional practitioners displayed a strong and continuing interest in the stock market, it enjoyed relatively little academic attention until after the debacle of 1929. While such lack of attention was not absolute, it stands out very sharply in comparison with the extensive research on commodity prices and on prices of those financial instruments which came under the rubric of 'money.' This disinterest was compounded of many parts: the smaller role played by organized equity markets in industrial finance, a conviction that stock markets were the product of mass (irrational) psychology akin to gambling, and a shortage, among economists, of the mathematical and statistical skills necessary for effective research in this field.

“These last two reasons bulk particularly large. When research into stock prices did attract renewed attention in the 1930’s, most of it focused among the same American economists who were important in the embryo school of economists interested in the use of mathematics and statistics. Aside from Working, the major name in this period is that of Alfred Cowles. The Cowles Commission (now Foundation) organized the first major collection of statistical data on the U.S. stock market resulting in the publication of Common Stock Indexes published in 1938. Even before that publication, however, Cowles has begun to analyze stock prices from the unique point of view that motivates this collection.

“What research into stock prices had come before was largely devoted to attempts to predict such prices based on 'outside' data, whether earnings, industrial production, or sunspots. While Cowles was interested in somewhat related phenomena, such as the predictive ability of stock brokers’ market letters, a major part of his research focused on the question of forecasting stock market prices from the past history of prices themselves. It may be worthwhile to dwell on this distinction since it is sometimes a source of confusion among nonexperts. When statisticians hypothesize that the course of stock prices describes a random walk or Brownian motion, they do not imply that a skilled student of the subject cannot forecast price changes. They merely imply that one cannot forecast the future based on past history alone.” (pp. 79-80)

“Because of [the upward long-term trend of the market], any large sample of price changes contains more positive changes than negative. As a result, in any study of runs, there is a greater tendency for positive changes to be followed by positive changes (long up-runs) and a smaller tendency for negative changes to be followed by negative changes (shorter down-runs) than would be found in a series with zero mean. The significant differences found by Cowles are indicative of this general uptrend rather than a serial dependence among price changes after correction for such trend.” (p. 81)

“The publication in 1959 of both the Roberts and Osborne papers marked the beginning of the sharp recent increase in interest in this subject, by bringing it to the attention of the American academic audience for the first time since Cowles’ articles in the thirties. Although attention was an important factor in stimulating interest, the soil had been fertilized in an important way by the widening introduction of electronic computing machinery.” (p. 82)

“… Moore’s work strongly supports the results found previously by Kendall and Osborne. Autocorrelation coefficients are uniformly small and usually quite insignificant; runs tests support the independence hypothesis, and the distribution of price changes seemed at least approximately log-normal. The careful testing did, however, yield some mildly disturbing evidence which was to become more important in the research and theories of future students. For one thing, the distributions of price changes, while ‘close’ to normal, showed a consistent tendency for more large price changes than expected. For another, autocorrelations of successive one-week changes, while individually statistically insignificant, are predominantly negative to a degree which is statistically significant. Actually, Kendall’s empirical results with price indexes had foreshadowed this, although in the case of indexes, the overwhelming number of autocorrelations at one-week intervals were positive, becoming predominantly negative at longer intervals.

“C. W. J. Granger and O. Morgenstern’s paper on spectral analysis brings into play modern techniques of time series analysis which had previously been confined to data in the physical sciences. The spectrum of a time series is a representation (through Fourier transforms) of the autocorrelation function of that series. In that respect it is a close, if more sophisticated relative of the correlelogram. Within the limitations of available data, the spectrum gives a complete picture of autocorrelation in any stationary stochastic process with finite variance. It also determines the best linear predictor for such a time series. If, however, the series is not stationary, or if its variance does not exist (Mandelbrot, 1963), the results may be ambiguous or incorrect. Also the failure to find any linear predictive relation does not rule out the possibility (Alexander, 1961) that a nonlinear relation exists. With these provisos in mind, however, the Granger-Morgenstern research lends strong support to the random walk thesis.” (p. 83)

McCann, Tactical Portfolios

Bailey McCann, a member of the Opalesque news and research team, introduces readers to the complex world of hedge funds in Tactical Portfolios: Strategies and Tactics for Investing in Hedge Funds and Liquid Alternatives (Wiley, 2014). In this task she had help from Benedicte Gravrand and Mark Melin, who wrote the chapters on emerging managers and managed futures, respectively. The book also includes lengthy inserts by experts in the field.

This is essentially a “how” and “how to” book—how hedge fund strategies work and how to approach investing in hedge funds (investment structures, service providers, due diligence, and investment mechanics). It also has a chapter on regulatory regime changes and impact, both in the US and the EU. One of the strengths of the book is that it takes readers beyond the borders of the United States.

Let’s look briefly at one very simple portfolio hedging strategy that even retail investors could implement: using quantitative trend following as an equity risk hedge. Unfortunately, in recent years “trend following managers have reduced their core style exposures and increased risk-on trades, which have a greater correlation to equities.” (p. 172) Moreover, for some years trend followers have benefited from using fixed income as a means of cheap equity hedging, but “this may not be the case indefinitely.” In fact, according to the authors of the TF study quoted extensively in the text, “The market environment is primed for a major change to happen because volatility is compressed and the skew is very negative.” (p. 173) Investors looking for a better equity hedge might consider “working within classical trend following strategies such as the 10-day to 100-day simple moving average crossover.” The study’s authors propose a “covariance filter on TF trades to accept only trades that have negative covariance to equities.” In this way, “investors can realize the equity hedge they hope for from CTAs, while realizing alpha. This approach also sets the strategy apart from tail-risk strategies, which are typically negative carry until a significant correction.” (p. 175)

Tactical Portfolios has something of a scattershot feel to it, which makes it a poor choice for the novice wanting to learn about hedge fund investing. But more sophisticated readers who are willing to pick their way through the book will undoubtedly find some useful information.

Cootner, The Random Character of Stock Market Prices, II

Today I’m offering some excerpts from Cootner’s introduction to Part I of the book, which includes a paper entitled “Stock-Market ‘Patterns’ and Financial Analysis: Methodological Suggestions” by Harry V. Roberts as well as Louis Bachelier’s “Theory of Speculation.”

* * *

“The sensitivity of speculative prices and the huge volume of securities traded result in an impressive total of gains and losses in each trading day. The changes in wealth represented by these fluctuations have served as a constant lure to men who hope to earn fame and fortune by somehow unraveling the puzzle of price forecasting, who yearn for the discovery of a predictive formula which will unlock those gold-filled vaults. … [U]ntil fairly recently, the study of these prices was the province of the speculator, rather than the academician. … In more recent years, however, economists and statisticians alike have brought their research tools to bear on this subject, not primarily to find an easy road to fortune (though who is to say such a thought did not occur) but to establish the relationship of the securities markets to the ideal constructs of their theories. Primarily because those ideal markets would not offer a road to easy fortune, these academic studies have proven to be more skeptical about the folklore of the market place than those of the professional practitioners. To several of the authors represented in this volume the ‘patterns’ described by some market analysis are mere superstitions. Julian Huxley has argued that mythology, religion, and superstition all flourish when men have to make decisions about matters over which they have no control. Whether or not that is the reason, it is hard to find a practitioner, no matter how sophisticated, who does not believe that by looking at the past history of prices one can learn something about their prospective behavior, while it is almost as difficult to find an academician who believes that such a backward look is of any substantial value.” (pp. 1-2)

“In his paper, Roberts presents briefly and clearly the largely heuristic reasoning that lies behind what has come to be known as the random walk theory of stock prices. The basic proposition depends upon a characteristic of competition in perfect markets: That participants in such a market will eliminate any profits above the bare minimum required to induce them to continue in the market, except for any profits which might accrue to someone who can exercise some degree of market monopoly. There is, for example, no reason why a trader with special information about future events cannot profit from that monopolized knowledge. On the other hand, we should not expect, in such a market, that traders could continue to profit from the use of a formula depending only upon past price data and generally available rules of ‘technical analysis.’ If this is so, all changes in prices should be independent of any past history about a company which is generally available to the trading public. Then, except possibly for a trend which is related to the desired rate of return, future changes in stock prices could just as well be determined by a flip of a coin as by any elaborate analysis of past data.” (p. 2)

“Roberts’ second point, which arises first in the U.S. literature in the writings of H. Working (1934), is the demonstration that a random walk series will, in fact, look very much like an actual stock series…. This seems to be due to a tendency to ascribe to sums of independent random variables, behavior which is typical of the individual random variables themselves.” (p. 3)

“In [Bachelier’s] paper we find the Chapman-Kolmogorov-Smoluchowski equation for continuous stochastic processes, the derivation of the Einstein-Wiener Brownian motion process and the recognition that this process is a solution of the partial differential equation for heat diffusion. The Einstein-Wiener process is the analogue, for continuous time and continuous random variables, of the discrete random walk process. … Most of this theory was later to be developed by the mathematicians who were transforming probability theory into a rigorous discipline, Levy, Kolmogorov, Borel, Khinchine, and Feller. Compared to these standards of rigor, Bachelier’s work was heuristic, and scorn for the heuristics led to an underestimation by contemporaries of the significance of the contributions.” (p. 3)

“[F]or Bachelier the mathematical formulation of the problem was but the first step towards empirically testing the results with the real world. The results are striking, the prices of the options correspond very closely to their calculated expected values, suggesting strongly that the option pricing process is rational and the bond pricing process is an independent increment process. If successive increments were positively correlated, we would expect options to be priced more expensively than Bachelier’s theory implies. If price changes had a tendency to reverse themselves, options should be less expensive. Furthermore, actual option buying proved profitable about as often as the theory predicted.” (pp. 5-6)