When I started this blog, I mentioned a system I call Compact Model Portfolio.

This is a portfolio selection system in which econometric methods are applied to the time series of daily dollar volume for stocks traded on U.S. exchanges. The goal is to answer the question: which stocks are market participants most interested in, using dollar value traded as a metric of interest. Using this data we select a small portfolio which represents the stocks voted by the market as those most likely to outperform.

I call this a "semi-efficient markets" approach because we accept the hypothesis that the market is a voting method which possesses the ability to efficiently select the best stocks; however, we do not accept the hypothesis that all information about these companies is fully and efficiently incorporated into their current prices.

I select these stocks daily, although the turnover is low, and a
representative portfolio is available from my website. Historical regression analysis shows that this portfolios' next day returns are well correlated with the NASDAQ-100 index, but that it outperforms this benchmark over the long run.

I did this analysis before the current work on dynamic trading risk factors; however, since this is a dynamically selected portfolio, it is interesting to ask whether there is a covariance between this system and what, we have found to be, is a common factor behind the returns of many large hedge funds.

If this system is well characterized by the null hypothesis (α,β)=(0,1), then we have a discovered a simple procedure that replicates what we have discovered to be an explanatory factor for the returns of several large hedge funds — this is a very interesting outcome!

The chart shows a comparison of the monthly returns accruing to the Compact Model Portfolio when hedged by allocating one third of the assets to a long position in the ProShares UltraShort QQQ ETF (AMEX:QID).

The results of this regression shows an insignificant but positive alpha of (1.04±0.73)%/month and a beta onto the dynamic trading risk factor of 0.84±0.32, which is not significantly different from unity. Overall, the R² is 20%.

This analysis is restricted to the period for which QID traded. For a longer period we have to look at hedging with a short position in QQQQ.