matt's notes

I wanted to give a brief overview of the quantitative stock models I’ve been using for some of my “active” portfolio money. The basic idea of these models is to use either a stock screen or stock ranking system along with buy filters and sell rules.

Most investors are familiar with stock screens which are available over the internet. Some of the better free ones are MSN Money Deluxe screener, Yahoo Stock Screener, and Multex Investor Netscreen. Many discount brokers also supply a stock screening capability.

Ranking systems are more sophisticated than stock screeners. In fact, a stock screen is really just a special case of a ranking system where there are only two outcomes- pass or fail. Most stock analysts use a three-way ranking system of sorts when they classify stocks as buy, sell or hold. Value Line and Zacks both sell proprietary 5-way ranking stocks for stocks, while MSN Money publishes a 10-way ranking with their Stock Scouter ratings.

I use some of the above services, and also subscribe to a service Portfolio123 which allows you to develop and test ranking systems that assign percentile ratings (0.0 to 100) to each stock in the universe, where the top rated stocks would generally have a rating of 99.5 or more.

Once you have selected your ranking or screening system, you also define buy filters and sell rules and a re-balancing frequency. The buy filters can be used to eliminate certain undesirable stocks from consideration. You can filter out penny stocks, stocks which do not trade sufficient volume, low market cap stocks etc. Filters can also be added for fundamental factors such as P/E ratio, industry group etc.

A sell rule is needed to determine when stocks will be sold. The most common sell rules are based on a drop in the ranking system below a certain level or a stock failing the stock screen, but numerous other criteria can be used- stock price weakness- either absolute or relative to the industry sector or benchmark index, stock price strength- selling when stock may be “overbought”, sell rules based on elapsed time etc.

Quantitative models can be backtested over different time periods to see how they would have performed but there are some caveats- For larger portfolios which use small cap stocks, you can get a variation on the Heisenberg Uncertainty Principle. The buying and selling of your portfolio can affect the execution prices significantly, so the backtesting results may not be realistic. You also must make sure to test the model under a variety of market conditions and time periods.

One big advantage that a small investor has over the larger institutions is the ability to use some of these active quantitative models. A large mutual fund managing over 500 million dollars is very restricted in the kinds of models they can use.