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Sorting Out the Idiosyncratic Volatility Anomaly

| | Posted in: Volatility Effects

Does exceptional (idiosyncratic) stock volatility exploitably predict future returns? In her April 2013 paper entitled “Revisiting Idiosyncratic Volatility and Stock Returns”, Fatma Sonmez re-examines the relationship between idiosyncratic volatility and future stock returns. She defines idiosyncratic volatility as the standard deviation of daily residuals from monthly regressions of returns (in excess of the risk-free rate) for each stock versus Fama-French model factors. Using daily returns and contemporaneous market, size and book-to-market factors for U.S. listed stocks during 1963 through 2008, she finds that:

  • Confirming prior research, idiosyncratic volatility relates negatively to future stock returns. 
    • A hedge portfolio that is each month long (short) the value-weighted fifth of stocks with the lowest (highest) idiosyncratic volatilities generates a gross average monthly return of 0.96%.
    • However, this return disappears for equal weighting (with high-volatility stocks not underperforming), indicating concentration of the effect in large-capitalization stocks.
  • Same-month changes in idiosyncratic volatility drive the value-weighted relationship. In general, a portfolio of stocks contemporaneously migrating to higher (lower) idiosyncratic volatility ranks generate positive (negative) gross abnormal returns. Specifically, stocks that contemporaneously: 
    • Migrate from the lowest to the highest idiosyncratic volatility quintile generate a gross monthly three-factor alpha of 4.95%.
    • Migrate from the highest to the lowest idiosyncratic volatility quintile generate a gross monthly three-factor alpha of -0.73%.
    • Do not migrate generate an insignificant gross monthly three-factor alpha of 0.12%. Among these stocks, idiosyncratic volatility relates positively to future returns.
  • Many extreme changes in idiosyncratic volatility are jumps corresponding to news (such as bankruptcy or acquisition), which tend to increase uncertainty about a stock. After the event, uncertainty and idiosyncratic volatility revert to lower levels.
  • After 2000, the idiosyncratic volatility effect disappears. During 2001-2008, a hedge portfolio that is each month long (short) the value-weighted fifth of stocks with the lowest (highest) idiosyncratic volatilities generates an insignificant gross average monthly return of -0.14%. Nor is there any return pattern associated with stocks contemporaneously migrating to lower or higher idiosyncratic volatility ranks.

In summary, evidence indicates that the negative relationship between stock idiosyncratic volatility and future return derives from business-related events that drive idiosyncratic volatility higher. However, this idiosyncratic volatility effect is absent from recent data.

Cautions regarding findings include:

  • Reported returns are gross, not net. Incorporating reasonable trading frictions would materially reduce these returns. High volatility may indicate high bid-ask spread.
  • Data collection and processing burdens to support monthly portfolio reformation are substantial, or potentially costly if delegated. The methodology apparently allows no lag between monthly calculations and trading.
  • As described, returns associated with monthly changes in idiosyncratic volatility are contemporaneous and thus not exploitable.

See “No Reward for Risk?” for a summary of early research in this stream, which may have run its course.

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