Every Saturday I download the “weekly scoreboard” from the blog Between the Hedges. It summarizes changes in the indices, sentiment/internals, futures spot prices, and the economy. I admit I don’t do much with this information; after glancing at it, I simply save it in case I need it for a study some time in the future.
Jack Ablin doesn’t want me to be so lackadaisical. In Reading Minds and Markets: Minimizing Risk and Maximizing Returns in a Volatile Global Marketplace (FT Press, 2009) written with Suzanne McGee, he sets out a five-step plan to improve portfolio performance. Although touted as something that any investor can do, it’s in fact an outline of how Ablin, the chief investment officer of Harris Private Bank, professionally manages portfolios. The average investor simply wouldn’t have the time or expertise to evaluate all the data points Ablin includes in his models.
Let me summarize how Ablin, a self-proclaimed quant, puts data to work in managing portfolios. First, the investor has to respect momentum because “trends are much more powerful, resilient, and long-lasting than we like to admit.” (p. 99) How can one know when momentum has shifted? Well, there’s the standard 200-day moving average for looking at individual markets. When comparing one market against another, however, one needs a longer moving average. The 20-month moving average, for instance, would have been useful in predicting when the S&P 500 would start to outperform the Russell 2000. In commodities as measured by the CRB index the 52-week moving average would have been the critical demarcation line. Moreover, the buy and sell rules are not constant in all three cases. In the Dow 200-day moving average study the rule was to buy when the Dow moved one percent above its 200-day moving average and to sell when it dropped one percent below. The rules for commodities are virtually the same—buy and sell when the movement is more than one percent. But when it comes to the relative momentum of large caps versus small caps, the one percent rule becomes a three percent rule. In brief, backtest and optimize. And once that’s done move on to breadth indicators.
Since financial markets don’t exist in a vacuum, the investor also has to analyze the economy. Ablin considers the yield curve and the fed funds futures curve to be crucial predictors of the direction of U.S. stocks. But, of course, the investor also has to weigh global economic conditions.
The third factor in this investment plan is liquidity as measured by such data as yield spreads, fund flows into closed-end mutual funds, the number of shares outstanding in an ETF over time, and M2. The fourth factor is psychological—greed vs. fear. Here Ablin references the standard sentiment gauges and the NYSE short interest ratio; he also cautions against giving them too much weight, against being an automatic contrarian. The final factor and the lynchpin for any investment strategy is fundamentals and valuation. Ablin’s favorite metric here is the earnings yield model, though valuation quickly becomes much more complicated.
To those who complain that there’s got to be a simpler way, Ablin claims that there isn’t; at least, there’s no magic formula for bringing the markets into focus. If Ablin is correct, the do-it-yourselfer is doomed; he’d best give up and hand his portfolio over to a professional money manager. But this do-it-yourselfer will keep on going in the perhaps self-delusional hope that over the long haul with simpler, more targeted systems she will outperform traditional money management metrics.