Uncertainty and Financial Markets

Sam Ngooi Comments

The recent appearance of the fast-spreading and at times fatal Coronavirus; the tragic deaths of Kobe Bryant, his daughter, and seven others; and the warning from Larry Swedroe (above) that we repeat each month; all have a common underlying theme, which is that the future is unknowable, and uncertainty is very much part of the human condition. This has been a basic principle of Park Piedmont’s investment management since its inception in 2003. That said, we thought it would be of interest to reach back into our archives and share an updated version of our October 2007 Comments, offering a detailed review of a book all about uncertainty, namely Nassim Nicholas Taleb’s The Black Swan: The Impact of the Highly Improbable.

Note also that for most of the first week in February, stock prices gained, even with Coronavirus impacts expanding. This is another totally unexpected short-term result, since the same virus was blamed for the declines at the end of January.

It would seem obvious that no one can predict the future. But in the investment world, many investors seem willing to listen to the predictions of so-called experts regarding many crucial pieces of information that influence their investment decisions. Wall Street analysts, economists, and media personalities on financial networks and in the financial press are constantly making predictions about such market-moving subjects as the likely growth rate of the overall economy, employment rates, the direction of inflation and interest rates, oil prices, the value of currencies, and corporate earnings. Why investors pay so much attention to predictions on these subjects, when they would likely concede that the future is unpredictable, is a question addressed by Taleb.

The book’s Prologue explains the idea of the Black Swan. “Before the discovery of Australia, people in the Old World were convinced that all swans were white… The sighting of the first black swan… illustrates a severe limitation to our learning from observations or experience and the fragility of our knowledge. One single observation can invalidate a general statement derived from millennia of confirmatory sightings of millions of white swans. All you need is one single black bird” (Prologue, xvii).

He continues that “a Black Swan is an event with the following three attributes. First, it is an outlier, as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. Second, it carries an extreme impact. Third, in spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact, making it explainable and predictable…. To summarize: rarity, extreme impact, and retrospective (though not prospective) predictability. A small number of Black Swans explains almost everything in our world, from the success of ideas and religions, to the dynamics of historical events, to elements of our own personal lives” (xviii). In a footnote, he also states that “the highly expected not happening is also a Black Swan” (xviii).

Taleb writes that “Black Swan logic makes what you don’t know far more relevant than what you do know… The inability to predict outliers implies the inability to predict the course of history… Our inability to predict in environments subjected to Black Swan, coupled with a general lack of awareness of this state of affairs, means that certain professionals, while believing they are experts, are in fact not… Black Swan, being unpredictable, we need to adjust to their existence (rather than naively try to predict them)” (Prologue, xix and xx). So before the Prologue has been completed, Taleb makes his case for not relying on experts to predict matters “in environments subjected to Black Swan,” which includes the financial markets.

Taleb presents the Black Swan problem in its original form: “How can we know the future, given knowledge of the past; or more generally, how can we figure out properties of the (infinite) unknown based on the finite known?” (pg. 40). He writes about the turkey which, after being fed one thousand days in a row, and expecting the same indefinitely, encounters the day before Thanksgiving. Taleb observes that “the history of a process over a thousand days tells you nothing about what is to happen next. This naïve projection of the future from the past can be applied to anything” (Figure 1, pg. 41). In a footnote (pg. 42), he discusses a hedge fund that lost most of its money in a few days during September 2006, as follows: “A few days prior to the event (that is, the huge losses), the company made a statement to the effect that investors should not worry because they had twelve risk managers – people who use models of the past to produce risk measures on the odds of such an event. Even if they had 112 risk managers…, they still would have blown up. Clearly you cannot manufacture more information than the past can deliver… We just don’t know how much information there is in the past.” While the managers believed they could control risk by analyzing past occurrences, they missed the whole idea that something could happen that was not captured in their analysis of the past.

Another major idea presented in the book is referred to as “silent evidence.” The example Taleb uses to present this idea is of a nonbeliever shown portraits of survivors of a shipwreck who had prayed for survival. The nonbeliever asks, where are the pictures of those who prayed, then drowned (pg. 100). “Drowned worshippers do not write histories of their experiences (it is better to be alive for that), so it is with the losers in history, whether people or ideas…” (pg. 102). “People who fail do not seem to write memoirs, and if they did, business publishers would not even consider returning their call… The graveyard of failed persons will be full of people who shared the traits of courage, risk taking, optimism, etc.… What truly separates the failed from the millionaires is for the most part a single factor: luck. Plain luck” (pgs. 105-106). Taleb uses the fund management industry as an example: “The industry claims that some people are extremely skilled, since year after year they have outperformed the market. They will identify these ‘geniuses’…He (Taleb) used computer simulations to show how it would be impossible to not have these geniuses produced just by luck. Every year you fire the losers, leaving only the winners, and thus end up with long-term steady winners. Since you do not observe the cemetery of failed investors, you will think that some operators are considerably better than others” (pg. 106).

The problems are that: (1) no one can identify the consistent winners in advance of the achievement, and (2) the fact of the past achievement in no way indicates future success. Taleb suggests “not to compute odds from the vantage point of the winner, but from all those who started. If you look at the population of all those who begin, you can be close to certain that one of them (but you do not know in advance which one) will show stellar results just by luck. From the reference point of all those beginning, this is not a big deal. But from the reference point of the winner (who does not take the losers into account), a long string of wins will appear to be too extraordinary an occurrence to be explained by luck. Note that a ‘history’ is just a series of numbers through time” (pg. 119). In a further pertinent observation, Taleb writes that “randomness and uncertainty are abstractions. We respect what has happened (history), ignoring what could have happened” (pg. 132).

Taleb then moves to a section entitled, “We Just Can’t Predict”: “You would expect our record of prediction to be horrible: the world is far, far more complicated than we think, which is not a problem, except when most of us don’t know it… We have seen how good we are at narrating backward, at inventing stories that convince us that we understand the past…. I find it scandalous that in spite of the empirical record we continue to project into the future as if we were good at it, using tools and methods that exclude rare events (pg. 135).  The problem with experts is that they do not know what they do not know (pg. 147). “Our predictors may be good at predicting the ordinary, but not the irregular, and that is where they ultimately fail… What matters is not how often you are right, but how large your cumulative errors are (pg. 149). Experts, when they are wrong, invoke the outlier defense… given that what happened was not predictable, they are not to blame. You cannot predict the Black Swan…. When experts are right, they attribute this to their expertise; when wrong, they attribute this to the situation, which was unusual, or worse, they did not recognize they were wrong” (pg. 152).

“We cannot truly plan, because we do not understand the future – but this is not necessarily bad news. We could plan while bearing in mind such limitations. It just takes guts. Even if you agree with a given forecast, you have to worry about the real possibility of significant divergence from it. These divergences may be welcomed by a speculator; a retiree however, with set risk attributes, cannot afford such gyrations. It is the lower bound of estimates (i.e., the worst case) that matters when engaging in a policy – the worst case is far more consequential than the forecast itself. This is particularly true if the bad scenario is not acceptable” (pgs. 157-163).  (Note these last few observations, and the paragraph that follows, bring Larry Swedroe’s quoted comments to mind.)

The implications of this inability to predict what will happen with an investment allocation and the choices used to implement it are most important. As Taleb notes, what is good for the speculator is unacceptable to the retiree. We agree and believe that the soundest investment advice focuses on reducing your exposure to the unacceptable scenarios, even if it means reducing expectations for your investment returns at the same time. Taleb’s arguments: (1) warn against relying unquestioningly on history repeating itself with regard to investment returns, since the history we know is only one possible series of outcomes as compared to all those that could have happened; and (2) call for acknowledging that the inability to predict makes efforts at setting expected future returns a highly questionable activity.

Returning to the text, and specifically with regard to investments, Taleb writes that “people are often ashamed of losses, so they engage in strategies that produce very little volatility but contain the risk of a large loss… If you accept most ‘risk measures’ are flawed because of Black Swan, then instead of putting your money in ‘medium risk’ investments (based on so-called experts, and history), put a large portion of your money in the safest investment (T-Bills), and take the rest and make extremely speculative bets” (pgs. 204-5). “You need to focus on the consequences (which you can know) of an event, rather than its probability (which you can’t know), and this is the central idea of uncertainty. Invest amounts you are not willing to ever lose in less risky securities” (pg. 211).

It is here where we part company from Taleb. Our allocation and implementation advice is based more on David Swensen’s views of investing, set forth in his book Unconventional Success and discussed in many of our Comments (references available on request). Swensen advocates developing an asset allocation that seeks to reduce risk by controlling the allocation to the historically higher-returning but more volatile asset class (i.e., stocks), and implementing the allocation with a mix of low-cost, market-mimicking, tax-efficient indexed stock and bond investments (see section titled “Portfolio Construction” (pgs. 81-91), and consider this quote: ”Rational investors allow risk preferences to influence portfolio choices, increasing the likelihood of maintaining asset allocations through the inevitable rough patches and ultimately benefiting from expected portfolio risk and return characteristics… Incorporating personal preferences in portfolio decisions guards investors from counter-productive actions to adverse developments after the fact by limiting exposure to poorly loved asset classes before the fact” (pg. 84-85).

Swensen clearly relies more on historical returns than Taleb would ever consider. And Swensen’s portfolio mix of stocks and bonds is not in line with Taleb’s advice to invest most money in ultra-safe US government bonds, and then use some modest percentage to invest in very high-risk ventures with very high potential payoffs. According to Taleb, in these high-risk ventures you can at least identify and recognize them as high-risk ventures. He worries more about the “promising” stock market and the “safe” blue chips than he does about speculative ventures; the former present invisible risks while the latter offer no surprises, since you know how volatile they are and can limit your downside by investing smaller amounts (pg. 296).

Our problem with Taleb’s allocation advice is that if the high-risk investment “blows up” and declines significantly (or, in the worst case, goes to zero), the investor is left only with the T-Bill investments, which could end up providing too low a return to meet the investor’s goals. Therefore, we advocate the more balanced stock and bond portfolio recommended by Swensen. But Taleb’s points on uncertainty, and the inability to predict, also influence our advice that clients have the smallest allocation to the broadly-based stock market consistent with providing the opportunity to earn a return adequate to their needs. This is our effort to combine two points of view that we highly respect.