Chess: A Valuable Teaching Tool for Risk Managers?
By Igor Postelnik
How does chess resemble risk analysis? Are there similarities, for example, between the way a chess player studies opponents’ games and the way a risk analyst studies clients’ portfolios? Igor Postelnik takes a comprehensive look at chess strategy and discusses the lessons that risk managers can learn from chess.
One of the most obvious features of financial markets is that prices move up and down unpredictably. This has led to random walk models that, in turn, suggest that practitioners should look for insight to games based on randomization: e.g., coin flips, dice rolls and card shuffles. In this article, I’d like to look at risk analysis from a chess master’s perspective. I’ll try to compare chess analysis to risk analysis and explain what risk management might learn from chess.
Although chess has no randomness or concealed information, it is nonetheless unpredictable. If two players sit down to play a game of chess, neither the game nor the result is the same as the game the same two players played yesterday.
Imagine a risk manager and a hedge fund manager trying to decide an appropriate leverage level for a portfolio and two opposing chess masters trying to decide how complicated they want their positions to be. Are there no similarities? Let’s see.
Just as higher leverage may enhance return or cause bigger loss for a risk manager or a hedge fund manager, a more complicated chess position may open unexpected variations that will lead to first-prize money or leave a player without a prize at all. Each chess move has advantages and disadvantages. While each move’s advantages include creating the possibility of a certain desirable future line of play, there is a risk that each move will open up possibilities for (perhaps unforeseen) lines of play that are desirable for the other side. Weighing the risks of this play and counterplay is the key to good judgment in chess and is really a type of risk management.
Before moving forward, let me dispel a myth that chess is a deterministic game with full information available to both players. In theory, this is true. However, in practice, it is hardly ever the case that a player sees all possibilities at once. And even if he or she actually sees them, it’s hard to predict how well an opponent will react to them. So, it comes down to probabilities: i.e., how likely is the opponent to know a certain opening or a certain type of a position?
For example, I am a 2200-rated chess player. Against someone rated below 2000, I definitely prefer to reach a simple position as soon as possible. Against someone rated above 2400, I want to keep the position very complicated for as long as possible.
As more pieces come off the board, the less room there is for calculations. Why does it matter? A simple position doesn’t require deep calculations but does require a deep understanding of strategy. Chess players, as their strength grows, learn to calculate first and understand later.
In risk management, an analyst takes a first look at a fund’s portfolio (chess position) and has to make a first move (approve for leverage). Once a certain level of leverage is approved (the first move is made), we have to consider how the portfolio manager will respond — as well as what factors will cause the trader to complicate the position (increase risk in the portfolio) and, when that happens, how the risk manager should respond.
There are other similarities between chess strategy and risk analysis. Under time pressure in a tough position, a chess player has to choose a move, while a risk manager has to choose a position in the portfolio to liquidate to meet a margin call when a portfolio is tanking. Chess players also study opponents’ games trying to anticipate how the next game will develop, while risk analysts study clients’ portfolios trying to anticipate how the next trade will affect the portfolio.
Here is the full article.
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