A factor model that I can believe in

Some of you may remember that I preached about the uselessness of factor models in predicting short term return, and the unreliability of many exotic factors even for the long term. In particular, factor models are especially inaccurate in valuing growth stocks (i.e. stocks with low book-to-market ratio), as evidenced by such models' poor performance during the internet bubble. This is not surprising because most commonly used factors rely on historical sales or earnings measures to judge companies, while many growth stocks have very short history and little or no earnings to report. However, as pointed out recently by Barry Rehfeld in the New York Times, Professor Mohanram of Columbia University has devised a simple factor model that rely on 8 very convincing factors to score growth stocks. These factors are:

1. Normalized return on assets.
2. Normalized return on assets based on cash flow.
3. Cash flow minus net income. (i.e. negative of accrual.)
   
4. Normalized earnings variability.
5. Normalized sale growth variability.
6. Normalized R&D expenses.
7. Normalized capital spending.
8. Normalized advertising expenses.

By "normalized", I mean we need to standardize the numbers with respect to the industry median. To Prof. Mohanram's credit, he claims only that these factors will generate returns after 1 or 2 years, not the short-term returns that many traders expect factor models to deliver. The excess annual return based on buying the group of stocks with the highest score and shorting the group with the lowest score is a good 21.4%. Not only does the combined score generate good returns, but each individual factor also delivers good correlation with future returns, proving that the performance is not due to some questionable alchemy of mixing the factors. For example, it makes good intuitive sense that extra spending on R&D and advertising will boost future earnings for growth stocks.

Interestingly, Prof. Mohanram pointed out that most of the out-performance of the high-score stocks occur around earnings announcements. Hence for those investors who don't like holding a long-short portfolio for a full year, they can just trade during earnings season.

One caveat of this research is that it was based on 1979-99 data (at least for the preprint version that I read). As many traders have found out, strategies that work spectacularly in the 90's don't necessarily work in the last few years. At the very least, the returns are usually greatly diminished. In the future, I hope to perform my own research to see whether this strategy is still holding up with the latest data.

Platinum vs. Gold

The Economist magazine has given us a fundamental reason to buy platinum (if not to short gold), in addition to my seasonal one.

Recap: Australian dollar futures seasonal trade

Yesterday was the exit of the Australian dollar futures seasonal trade which I discussed in my premium content. It incurred a loss of $920 per contract, despite a 12-year winning streak previously. This may be the peril of a trade that is not based on any fundamental rationale that I know of, as well as an in-sample bias that I alluded to in my previous article. I will keep it on my watchlist for another year.

By the way, due to a technical glitch, my previous article on seasonality in commodities futures was not sent to many subscribers, so here is the link.