You can find an interview of me in the July 2009 issue of Technical Analysis of Stocks & Commodities magazine. I mentioned in that interview and also in my book that I believe stop loss should only be applied to momentum strategies but not to mean-reverting strategies. I explained my reasoning better in my book than in the interview, and so I will paraphrase the explanation here.
In algorithmic trading, it is reasonable and intuitive that we should always make use of the latest information in determining whether we should enter into a position, whether that information is price, news, or some analysis. Let's call this the Principle of Latest Information. (If someone can think of a better or sexier name, let me know!)
So let's say we have a stock model based on price momentum, and we entered into a long position based on a recent positive return on price. A few minutes later, the price went down instead of up, causing a big loss on our position. If we now ran this momentum model again, very likely it would tell us to short the stock instead because of the recent negative return on price. If we did that, we would be exiting the previously long position and became flat. This is in effect a stop loss, and it follows strictly from adhering to our model and our Principle of Latest Information.
In contrast, suppose we now have a stock model based on mean-reversion, and we entered into a long position based on a recent drop in price. A few minutes later, the price went down further instead of up, again causing a big loss on our position. If we now ran this mean-reversion model again, it would definitely tell us to buy the stock again because of the ever cheaper price. The model would not ask you to exit this position and take a loss. Hence, adhering to the model and the Principle of Latest Information will not lead to a stop loss for a mean-reverting model.
(Now, if we hold this losing long position long enough, the model will incorporate new historical prices into determining its long or short signals as it retrain itself, as the Principle of Latest Information says it should! At that time, it may indeed recommend that we exit the previously held long position at a loss. But this adjustment takes place at a much longer time scale, and therefore cannot really be considered a stop-loss in its usual sense.)
More generally, I find that at every turn, and not only in the realm of stock trading, applying the Principle of Latest Information always help me to be disciplined and not be afraid to enter into new positions, take loss or endure a drawdown as the case may be.
Monday, June 29, 2009
Thursday, June 25, 2009
A job opening for quants
Alphacet told me that they have a job opening for a quant who will be helping their clients backtest trading strategies, among other responsibilities. Given that Alphacet's clients include several major investment banks and hedge funds, this position should provide pretty good close-up view of how the major quantitative players operate.
Monday, June 15, 2009
A good book for quantitative traders
Larry Connors and Cesar Alvarez (the guys behind tradingmarkets.com) recently published Short Term Trading Strategies That Work, a nice collection of simple technical trading strategies that you can easily backtest and verify.
As I have argued in my own book, simple strategies are often the ones that work best. As with any published strategies, you may find that their backtest performance may not be as high as advertised if you test them on a different time period or a different security, or with different transaction cost assumptions; but the main value of these strategies is that they serve as an inspiration to trigger your own imagination and motivate you to refine them further.
(For e.g., though the book mainly covers long-only strategies, you can easily imagine the accompanying short strategies.)
To be quite honest, this is one of the few books on trading strategies that I actually manage to finish reading from cover to cover.
As I have argued in my own book, simple strategies are often the ones that work best. As with any published strategies, you may find that their backtest performance may not be as high as advertised if you test them on a different time period or a different security, or with different transaction cost assumptions; but the main value of these strategies is that they serve as an inspiration to trigger your own imagination and motivate you to refine them further.
(For e.g., though the book mainly covers long-only strategies, you can easily imagine the accompanying short strategies.)
To be quite honest, this is one of the few books on trading strategies that I actually manage to finish reading from cover to cover.
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