Kaufman, A Guide To Creating A Successful Algorithmic Trading Strategy
Source: Brenda Jubin
Perry J. Kaufman, the author of twelve trading books, encapsulates some of his best ideas in A Guide to Creating a Successful Algorithmic Trading Strategy (Wiley, 2016). The book is short (under 200 pages and a small page size) because, as Kaufman explains, "it just deals with the most important issues of developing a successful trading system and because you're more likely to read it all." (p. 2)
Kaufman differentiates between long-term and short-term trading strategies. In the long term, most markets exhibit trends, although some trend more efficiently than others. For instance, the equity markets of mature economies are, or at least were, noisier than those of emerging economies. Short term, markets are noisy and tend to mean revert.
In practical terms, this means that profit taking doesn't work for trend following "because you cut your profits short and give up the fat tail, the extremely big profits." (p. 51) If you're a short-term trader, however, and "if you get a larger-than-average move in your direction, then you should take at least part of your gains off the table because you expect prices to reverse." (p. 54)
As for stops, they are "short sighted for a trend strategy." Using stops "looks to reduce a short-term loss by giving up a long-term profit, and it can significantly lower the percentage of good trades, which are already low for moving averages." (p. 46) Stops are not the most efficacious way to control risk for most short-term systems either. "If you have a mean-reversion or arbitrage strategy, its profile will be a lot of small profits and a few large losses. When you add a stop-loss, you reduce the high percentage of small profitable trades and upset the balance. You can turn a profitable system into a losing one." (p. 56)
How should you manage risk in a trend following portfolio? Kaufman recommends, among other things, that you start every trade with the same risk, and he suggests that system diversification is better than market diversification.
I've extracted just a couple of illustrative points from Kaufman's book. The trader who is looking for a detailed guide on how to create and backtest trading strategies will be disappointed with this book. But anyone who is trying to develop a conceptual framework for systematic trading, which he can then implement with the appropriate algorithms, will find a lot of useful information here.
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