On the Trader Performance blog, I recently posted an entry that looks at the process of defining and managing trade ideas from the perspective of lean manufacturing. One of the things I'm finding is that it is less difficult than I thought to identify trades that have a meaningful directional edge. If you have a good set of predictive measures, employ them properly over a truly representative lookback period, and then ensure that the relationships you identify apply to the entire lookback period, you can define an edge. The problem is managing this edge.
Let's say, apropos of my last analysis, that you find that a trade has a significant positive directional bias over the next ten days, with many more winning trades than losers. The question then becomes, over the next ten days, how do you determine whether or not the trade continues to possess its favorable edge? Suppose the market drops during the first two days of the trade period: do you continue to hold, add to the position, or exit? This is partly a question of risk management, but also a question of odds. If the two-day dip actually increases the odds of the trade going your way, exiting in the name of risk management seems perverse. It would be far better to start out with a position size that allows you to weather such adverse movement.
What I'm currently working on is something I call "sequence analysis". I examine every historical trade identified in my analyses and then walk them forward to identify the normal sequences of profits and losses. I'm specifically looking for key events that separate the winning trades from the losers, so that these could serve as rational exit points. To give but one simple example, if I find that 85% of all winning 10-day trades started out by being profitable in the first two days, I might not want to hold a loser after two days.
Sequence analysis becomes much more interesting and complex when you utilize predictors not in the original analysis to evaluate the likelihood that a historical pattern will repeat itself. For example, I might forecast a favorable ES over the next ten days based on the relative movements of Speculative and Non-Speculative stocks. My sequence analysis, however, may reveal that the vast majority of profitable trades occurred when the Adjusted TICK was positive in the first day of the 10-day period. That provides me with a tool for managing the trade. Do I really want to hold beyond the first day if the TICK is negative? Might I add to the trade if I see strength in the TICK?
We spend a lot of time studying entries, less time studying exits, but very little time truly studying the criteria that should keep us in or out of a trade. We might know the odds of success at the time we enter a trade, but can we update those odds based on current market movement to tell us whether to scale in or out? Sequence analysis would provide a rational basis for such updating, turning the management of trades into a lean process.
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