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Why Weather Forecasters Are More Accurate Than Stock Market Analysts


Paradoxically, those with "less precise knowledge" tend to be more self-assured.

MINYANVILLE ORIGINAL According to New York Times statistical wunderkind Nate Silver, the National Hurricane Center's accuracy has improved 250% over the last 25 years.

More accurate weather predictions benefit the economy, boosting the efficiency of businesses like FedEx (FDX), which employs 15 in-house meteorologists, as well as companies working offshore, like BP (BP) and Transocean (RIG). Weather is such an important factor in financial markets that Goldman Sachs (GS) employs staff meteorologists, as do Citigroup (C) and JPMorgan Chase (JPM).

While meteorologists have improved, other analysts -- specifically financial ones – are still off the mark more often than not.

"In November 2007, economists in the Survey of Professional Forecasters -- examining some 45,000 economic-data series -- foresaw less than a 1-in-500 chance of an economic meltdown as severe as the one that would begin one month later," Silver writes.

"Why are weather forecasters succeeding when other predictors fail? It's because long ago they came to accept the imperfections in their knowledge. That helped them understand that even the most sophisticated computers, combing through seemingly limitless data, are painfully ill equipped to predict something as dynamic as weather all by themselves. So as fields like economics began relying more on Big Data, meteorologists recognized that data on its own isn't enough."

We took a look at this phenomenon back in June 2010, when Tadeusz Tyszka and Piotr Zielonka of the Leon Kozminski Centre for Market Psychology at the Academy of Entrepreneurship and Management in Warsaw published a study called Expert Judgments: Financial Analysts vs. Weather Forecasters. Tyszka and Zielonka asked two groups of experts to "predict corresponding events (the value of the Stock Exchange Index and the average temperature of the next month)."

They found that "[a]lthough both groups of experts revealed the overconfidence effect, this effect was significantly higher among financial analysts than among the weather forecasters."

Their conclusion:

In the group of financial analysts one-third of the participants succeeded in their forecast and in the group of weather forecasters approximately two-thirds of the participants succeeded in their forecast.

Further analysis showed that "[e]xperts who assigned confidence estimates of 80% or higher were correct only in 45% of cases. As quoted by Korn & Laird (1999), a high level of overconfidence seems to be characteristic for finance analysts as well and most probably for many other kinds of experts."

In a slightly larger than usual nutshell, the crux of the issue was this: Weather forecasters have an "awareness of uncertainty" about the natural world that "causes these experts to manifest a lower overconfidence effect than experts from the other domain."

"Paradoxically," Tyszka and Zielonka discovered, "financial analysts, having less precise knowledge than the weather forecasters about the underlying system, can be more self-assured."

That self-assurance, according to John Nofsinger, associate professor of finance at Washington State University, a specialist in behavioral finance, and the author of The Psychology of Investing, "causes people to overestimate their knowledge, underestimate risks, and exaggerate their ability to control events."

"In fact, studies have shown that the ratio of confidence to accuracy is an inverse one -- that is, a lesser confidence level tends to correlate with a higher degree of accuracy," he explained.

Further, financial analysts were also found to be unwilling or unable to be self-critical after a failure -- something that Raymond Dacey, Professor of Finance and of Statistics and Adjunct Professor of Philosophy at the University of Idaho, suggested to the authors "could pertain to the clients."

In an interview, Dacey told me that the "Overconfidence Effect" tends to lead to the "Disposition Effect," a concept first explored by Hersh Shefrin, the Mario Belotti Chair in the Department of Finance at Santa Clara University's Leavey School of Business and a pioneer in the field of behavioral finance, and Meir Statman, the Glenn Klimek Professor of Finance at Leavey.

Simply put, the "Disposition Effect" has to do with risk attitude and what Shefrin and Statman colloquially term "get-evenitis" -- an aversion to loss realization.

"If you have a winner," Dacey said, "you become risk averse. If you have a loser, in the realm of losses, you are risk seeking. That difference in curvature in asset pricing is what makes the difference."

Here's the concept in Shefrin and Statman's words, from their 1984 study, The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence:

First, we place this behavior pattern into a wider theoretical framework concerning a general disposition to sell winners too early and hold losers too long. This framework includes other elements, namely mental accounting, regret aversion, self-control, and tax considerations. Significantly, we argue that the tendency to concentrate loss realizations in December is not normatively based; however, it is consistent with our descriptive theory. Second, we discuss evidence which suggests that this disposition shows up in real-world financial markets, not just in contrived laboratory experiments. In particular, we find that tax considerations alone cannot explain the observed patterns of loss and gain realization, and that the patterns are consistent with a combined effect of tax considerations and a disposition to sell winners and ride losers.

While this paper has focused upon stocks and mutual funds, the general tendency to treat sunk costs as relevant has much wider application. For example, both corporate managers and shareholders are well aware of a tendency "to throw good money after bad" by continuing to operate losing ventures in the hope that a recovery will somehow take place. The case of Lockheed's (LMT) decision to terminate its well-known L-1011 white elephant was greeted with joy by the investment community. The price of Lockheed stock jumped 18% in the day following the formal announcement of cancellation. Other examples abound.

Of course, there is a school of thought regarding predictions and forecasting that takes a less-than-confident view of those (over-confident) prognosticators among us.

From Zach Weiner's Saturday Morning Breakfast Cereal:

No positions in stocks mentioned.
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