Time Heals Wounds
I RECENTLY WROTE about the fallacy of time diversification. Time diversification is the widely held belief that market risk declines as our holding period lengthens. It���s one of the cornerstones of many investors��� approach to asset allocation and risk management.
Financial theory, however, refutes time diversification because market risk���as measured by standard deviation���actually increases with longer holding periods. The math tells us that the dispersion of potential results widens with longer time horizons. This counterintuitive insight rests on the assumption that total returns have a normal, bell-shaped distribution and that year-to-year returns are uncorrelated.
As an example, if stocks have an average historical return of 5% with a standard deviation of 30% and you hold for 30 years, the worst 1% of possible outcomes is a cumulative 90% loss. History teaches us that losses of this magnitude are within the realm of possibility. During the Great Depression, the Dow plunged 89% from its 1929 peak. It didn���t reach new highs, at least in nominal terms, until 1954���or 25 years later. Similarly, in 2002, the Nasdaq Composite index closed 78% lower than the peak it reached in 2000. It would take 15 years for the Nasdaq to return to its prior 2000 high.
But there���s a major weakness in the argument against time diversification. Recall that it assumes that annual returns are uncorrelated. In other words, stock returns are assumed to take a random walk around their mean. While this assumption may be reasonable most of the time, it falls apart over longer time horizons and at market extremes.
Consider what happens after the stock market experiences a major decline. First, dividend yields climb. It���s estimated, for example, that the dividend yield of the overall stock market was close to 14% in July 1932, when the Dow reached its Great Depression low.
As share prices decline, the expected return from stocks rises. The Gordon equation states that the return we can expect from stocks are a function of dividends and the growth in dividends. By raising the dividend yield, tumbling stock prices sow the seeds for higher future returns.
Result? A lost decade for stocks would set the stage for higher expected returns in the decade that followed. In other words, returns over long time periods aren���t random, but rather negatively correlated. What I���m describing, of course, is reversion��to the mean. It���s the countervailing force that lowers the probability of long market streaks���both positive and negative. This doesn���t mean that a 30-year bear market could never happen. It���s just far less likely than standard statistical theory would predict.
The other major argument in favor of time diversification: Most people save and invest over many decades. Such dollar-cost averaging substantially lowers the risk of stock investing during our working years, because we���re buying over time, rather than at a single price that could prove to be a market peak.
Financial theory, however, refutes time diversification because market risk���as measured by standard deviation���actually increases with longer holding periods. The math tells us that the dispersion of potential results widens with longer time horizons. This counterintuitive insight rests on the assumption that total returns have a normal, bell-shaped distribution and that year-to-year returns are uncorrelated.
As an example, if stocks have an average historical return of 5% with a standard deviation of 30% and you hold for 30 years, the worst 1% of possible outcomes is a cumulative 90% loss. History teaches us that losses of this magnitude are within the realm of possibility. During the Great Depression, the Dow plunged 89% from its 1929 peak. It didn���t reach new highs, at least in nominal terms, until 1954���or 25 years later. Similarly, in 2002, the Nasdaq Composite index closed 78% lower than the peak it reached in 2000. It would take 15 years for the Nasdaq to return to its prior 2000 high.
But there���s a major weakness in the argument against time diversification. Recall that it assumes that annual returns are uncorrelated. In other words, stock returns are assumed to take a random walk around their mean. While this assumption may be reasonable most of the time, it falls apart over longer time horizons and at market extremes.
Consider what happens after the stock market experiences a major decline. First, dividend yields climb. It���s estimated, for example, that the dividend yield of the overall stock market was close to 14% in July 1932, when the Dow reached its Great Depression low.
As share prices decline, the expected return from stocks rises. The Gordon equation states that the return we can expect from stocks are a function of dividends and the growth in dividends. By raising the dividend yield, tumbling stock prices sow the seeds for higher future returns.
Result? A lost decade for stocks would set the stage for higher expected returns in the decade that followed. In other words, returns over long time periods aren���t random, but rather negatively correlated. What I���m describing, of course, is reversion��to the mean. It���s the countervailing force that lowers the probability of long market streaks���both positive and negative. This doesn���t mean that a 30-year bear market could never happen. It���s just far less likely than standard statistical theory would predict.
The other major argument in favor of time diversification: Most people save and invest over many decades. Such dollar-cost averaging substantially lowers the risk of stock investing during our working years, because we���re buying over time, rather than at a single price that could prove to be a market peak.
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