Book of Value: Flaws in the Academic Approach to Risk and Uncertainty

Standard deviation and beta may be popular metrics, but are of limited value

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Mar 25, 2020
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Chapter 13 of “Book of Value: The Fine Art of Investing Wisely” began with Anurag Sharma reminding us of economist Frank Knight’s distinction between risk and uncertainty. Risk can be quantified and measured; uncertainty, on the other hand, refers to the unknown and the unknowable. Uncertainty cannot be measured or quantified.

That difference is an important one in the world of investing. Speculators (and gamblers) often operate on the uncertainty side, hoping that their hunches will pay off in a windfall. Investors, on the other hand, prefer to deal with risk and smaller but more consistent returns. That means trying to find situations where the odds are in their favor and avoiding anything with long odds.

The author has a finer point, though. He argued that “the essential task for you as an investor is not so much to measure risk but to understand the key uncertainties and develop well-informed judgments to try to resolve those uncertainties the best you can.” When those uncertainties cannot be resolved, then investors must reduce their confidence levels.

That advice seems particularly appropriate in March 2020, even though the book was published in 2016. Uncertainties abound in the current health and economic spheres, not to mention future social reactions. Two prominent examples come to mind as a result of reading yesterday morning’s (March 24) newsletter from Institutional Investor magazine.

First, it reported on a CNBC interview with David Tepper (Trades, Portfolio), a guru followed by GuruFocus. He said he has been “nibbling” around the edges of the market and would like to plunge in, but is waiting to find out what’s in the government’s economic stimulus package.

The second was titled “Managers Were Getting Bad News Before Markets Crashed,” and the lead paragraph reported, “Before the worst of the market carnage was unleashed in mid-March, institutional equity managers were already experiencing some of the worst outflows in years.”

What are we humble investors to think when given two conflicting reports, one indicating that everything should return to normal when the coronavirus recedes and the government provides a good relief package, while another report argued that trouble was already in the air and the virus may just be making a bad situation worse? Well, we are bound to feel uncertain.

Sharma argued that while we have no control over macro events and their outcomes, investors should articulate the issues involved and try to understand how they might affect their investment case. He went on to call investment analysis the process of determining the odds that are “built into” a situation. The better the odds, the more you invest in that area.

In keeping with the author’s theme that investment theory needs a qualitative side, as well as the quantitative side emphasized by academic finance, he discussed standard deviation and beta.

Standard deviation is a statistical measurement that tells us how volatile a stock’s price has been in the past. Low standard deviation means low volatility, while high deviation means high volatility. It became popular in academic finance and is often used as a measure of risk. However, there is a problem: Sharma told us we have to use past returns to estimate future returns and, as the old programmers’ saying goes, “Garbage in, garbage out.”

Beta refers to risks coming from the broad market or economy-wide effects, rather than company-specific issues. An obvious example is the current coronavirus pandemic, the resulting shutdown of much of the economy and stock markets reeling as a result. Sharma explained that beta assumes a normal underlying distribution, something that is not always true.

In the broader context, though, he warned that the process of quantifying risk will distract investors from trying to understand the issues that lead to uncertainty. Objectivity and precision are, to whatever extent, false goals. Besides not knowing the shape of the underlying distributions, there is the danger of confirmation bias and the need to disregard many risk and uncertainty issues.

And, of course, there is the questionable assumption that the efficient market hypothesis is true, that the prices of all stocks reflect all available information and that it is shared equally among all investors. I used the word questionable because Warren Buffett (Trades, Portfolio) and I theoretically should have the same returns if we have access to the same information. However, his record is far superior to mine.

Both standard deviation and beta are based entirely on market prices. So what are we to make of risk in the current market crash? Obviously, if you judge it by standard deviation, or volatility, it’s very high, but also somewhat meaningless. On the other hand, if you think of risk in the old-fashioned way, of losing real money, then it is quite meaningful.

What if you are thinking about investing this week, grabbing bargains even though we may not yet have hit bottom? Again, the academic finance answers—standard deviation and beta—have practically no use.

All of which underlines Sharma’s point that objectivity and precision are meaningless if we do not grasp the broader themes driving the markets and individual stocks. As proposed by academic finance, objectivity is simply ignoring all but one variable (price) in a complex mix, and precision is a delusion if only one variable counts.

Conclusion

In chapter 13 of “Book of Value: The Fine Art of Investing Wisely,” Sharma has shown a key weakness in the academic finance model, which is to say, a model in which everything can be worked using just prices and mathematics.

He has shown that two key features of the academic model, standard deviation and beta, are weak pillars for an investment theory despite their widespread use. Among the reasons for this weakness are the academic dependence on normal distribution patterns and all-too-human issues such as confirmation bias.

And perhaps with the subtitle of his book in mind, Sharma wrote, “Rigorous thinking, rather than precision, is the key to investing wisely.”

Disclaimer: This review is based on the book, “Book of Value: The Fine Art of Investing Wisely,” by Anurag Sharma, which was published in 2016 by Columbia Business School Publishing. Unless otherwise noted, all ideas and opinions in this review are those of the author.

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