Quant Macro Investing

Risk Taking Disciplined

January 21, 2010 – Stock Returns and Changes in Implied Volatility

http://www.cxoadvisory.com/blog/external/blog1-21-10/

Are there reliable and exploitable predictive relationships between stock returns and changes inimplied volatility? In the January 2010 version of their paper entitled “The Joint Cross Section of Stocks and Options”, Andrew Ang, Turan Bali and Nusret Cakici investigate the relationship between changes in implied volatility and stock returns for individual stocks. Using monthly implied volatilities and associated stock prices and firm fundamentals for a broad sample of U.S. stocks over the period January 1996 through September 2008 (153 months), they conclude that:

  • Stocks with large increases in call-implied (put-implied) volatilities tend to rise (fall) over the following month.
  • The spread in average next-month returns and three/four-factor alphas between the highest and lowest quintile portfolios formed monthly by ranking the entire sample on changes in call-implied volatilities is about 1% per month. A double ranking first on changes in put-implied volatility for the entire sample and then on changes in call-implied volatilities within the lowest put-ranked quintile enhances this spread. (See the chart below.)
  • Options for stocks with high returns over the past month tend to have increases in call-implied volatility over the next month, with an abnormal stock return of 1% implying an increase in call-implied volatility of about 3%.
  • The predictive power of changes in implied volatilities for stock returns stems from idiosyncratic, not systematic, volatility components. In other words, the predictive relationship derives from information about the stock and not information about the market.
  • Results are consistent with the presence of informed traders in both the equity and options markets, with slow inter-market information diffusion.

The following figure, constructed from data in the paper, shows the average next-month gross returns for two sets of equally weighted quintile portfolios formed monthly over the entire sample period. One set derives from ranking the entire sample on the monthly change in call-implied volatility. The other derives from ranking first on the monthly change in put-implied volatility and then ranking the lowest resulting quintile on the monthly change in call-implied volatility. Results indicate that: (1) the larger the change in call-implied volatility, the larger the expected stock return; and, (2) combining the information in changes in put-implied and call-implied volatilities may enhance power to predict stock returns.

It is not obvious that this predictive power is exploitable at the net level (after trading frictions), especially for individual investors.

In summary, evidence suggests that investors may be able to gain an edge from the power of changes in implied volatilities to predict returns for individual stocks, and the power of stock returns to predict future changes in implied volatilities.

For related research, see Blog Synthesis: Volatility Effects.

January 22, 2010 - Posted by | Case Study, Indicator setup

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