I’ve just finished reading Short-Term Trading Strategies Work for at least the tenth time. That may make it the most read book of my life. Of course, it short (less than 150 pages with lots of charts), and that helps considerably. Thanks to Ernest Chan for recommending it in his blog.
The book is good solid science. The approach they take is totally quantified and verifiable. They describe everything completely enough so that you can test every assertion, every rule, and every strategy. We tested almost everything, and we found that they all hold up under close scrutiny. These are short-term strategies that work.
You may be asking yourself why anyone would give away a money-making strategy that works. My guess would be that they have short-term strategies that work better, and they are keeping those to themselves. Also, technical analysis is not a privileged information approach like arbitrage that gets less valuable with broader visibility; rather, when there are enough people who believe in the same technical analysis, it becomes a self-fulfilling prophecy.
That’s no guarantee of how well these strategies will work in the future, but as they consistently and correctly point out, quantified analysis is about getting an edge, not a guarantee. This book is about the simple basics of getting and exploiting an edge. They follow a simple engineering process.
1. Observe the data.
2. Measure anything of potential relevance.
3. Analyze those measurements.
4. Look to turn those measurements into strategies.
5. Test the strategies thoroughly.
For example, they observe that stocks that hit short-term lows tend to rebound from there as long as those short-term lows are above the long-term moving average. They develop a precise definition of a short-term low (has to be precise to feed it to a test program) and adopt a precise definition of a long-term moving average. That allows them to search for specific trade opportunities. They add a specific exit strategy and test it using historical market data.
As an aside, one reviewer of this book labeled their approach as mean reversion theory in a new wrapper. I see no such underlying bias. This strategy, for example, could appeal as much to people who believe that the long-term trend dominates the short-term trend as to those who believe in mean reversion. Besides, the real question is whether or not a strategy works rather than what kind of underlying theory supports it.
There will be many people who find that simply adopting these strategies will be a big improvement over their current approach, but the proper perspective is that here are a set of basic building blocks. If you want better performance than what Connors and Alvarez had you on a platter, there is still a lot of work to do.