Sometimes Learning Is Very Slow
Our best finance theories predict riskier assets gain high returns. From the July Journal of Financial Economics:
Previous studies typically find a statistically insignificant relation between the market risk premium and its expected volatility. … {But] even 100 years of data constitute a small sample … Using the nearly two century history of U.S. equity market returns [1802-2003] … I estimate a positive and statistically significant risk return tradeoff.
Remember this whenever someone says that your theory doesn’t seem to give significant results on ten years of data – sometimes you just need a lot more data.
Added: I should have been more critical of this paper. See good comments by Eric Falkenstein.
Yes, but where does clustered volatility come from? Only the Santa Fe Institute has what seems to me to be a plausible model. The road to hell is paved with models that assume Gaussian distributions, and ignore heteroskedacity.
Tony K's comment was a good summary of Warren Buffett's stance on the issue:"I wonder if the problem is our definition of risk. I would contend that volatility may not be the same as risk. Volatility is more a function of time preference of returns. Risk to me, should be default or failure risk."
How many of these academics can predict future results, rather than just finding patterns in the past? Anybody can find statistically significant correlations, given enough data.