Understanding Risk Management
le 17/01/2023 à 10:49 Citer ce messageUnderstanding Risk Management
Risk management occurs everywhere in the realm of finance. It occurs when an investor buys U.S. Treasury bonds over corporate bonds, when a fund manager hedges his currency exposure with currency derivatives, and when a bank performs a credit check on an individual before issuing a personal line of credit. Stockbrokers use financial instruments like options and futures, and money managers use strategies like portfolio diversification, asset allocation and position sizing to mitigate or effectively manage risk.
Inadequate risk management can result in severe consequences for companies, individuals, and the economy. For example, the subprime mortgage meltdown in 2007 that helped trigger the Great Recession stemmed from bad risk-management decisions, such as lenders who extended mortgages to individuals with poor credit; investment firms who bought, packaged, and resold these mortgages; and funds that invested excessively in the repackaged, but still risky, mortgage-backed securities (MBSs).
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Good, Bad, and Necessary Risk
We tend to think of "risk" in predominantly negative terms. However, in the investment world, risk is necessary and inseparable from desirable performance.
A common definition of investment risk is a deviation from an expected outcome. We can express this deviation in absolute terms or relative to something else, like a market benchmark.
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While that deviation may be positive or negative, investment professionals generally accept the idea that such deviation implies some degree of the intended outcome for your investments. Thus to achieve higher returns one expects to accept the greater risk. It is also a generally accepted idea that increased risk comes in the form of increased volatility. While investment professionals constantly seek—and occasionally find—ways to reduce such volatility, there is no clear agreement among them on how it's best done.
How much volatility an investor should accept depends entirely on the individual investor's tolerance for risk, or in the case of an investment professional, how much tolerance their investment objectives allow. One of the most commonly used absolute risk metrics is standard deviation, a statistical measure of dispersion around a central tendency. You look at the average return of an investment and then find its average standard deviation over the same time period. Normal distributions (the familiar bell-shaped curve) dictate that the expected return of the investment is likely to be one standard deviation from the average 67% of the time and two standard deviations from the average deviation 95% of the time. This helps investors evaluate risk numerically. If they believe that they can tolerate the risk, financially and emotionally, they invest.
Risk Management Example
For example, during a 15-year period from Aug. 1, 1992, to July 31, 2007, the average annualized total return of the S&P 500 was 10.7%. This number reveals what happened for the whole period, but it does not say what happened along the way. The average standard deviation of the S&P 500 for that same period was 13.5%. This is the difference between the average return and the real return at most given points throughout the 15-year period.
When applying the bell curve model, any given outcome should fall within one standard deviation of the mean about 67% of the time and within two standard deviations about 95% of the time. Thus, an S&P 500 investor could expect the return, at any given point during this period, to be 10.7% plus or minus the standard deviation of 13.5% about 67% of the time; he may also assume a 27% (two standard deviations) increase or decrease 95% of the time. If he can afford the loss, he invests.
Risk Management and Psychology
While that information may be helpful, it does not fully address an investor's risk concerns. The field of behavioral finance has contributed an important element to the risk equation, demonstrating asymmetry between how people view gains and losses. In the language of prospect theory, an area of behavioral finance introduced by Amos Tversky and Daniel Kahneman in 1979, investors exhibit loss aversion. Tversky and Kahneman documented that investors put roughly twice the weight on the pain associated with a loss than the good feeling associated with a profit.
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Often, what investors really want to know is not just how much an asset deviates from its expected outcome, but how bad things look way down on the left-hand tail of the distribution curve. Value at risk (VAR) attempts to provide an answer to this question
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