To Optimize or Not
posted under
Philosophy of Technical Analysis
by ceecabolos
The first edition of this book included the results of extensive research produced by Merrill Lynch, which published a series of studies on computerized trading techniques applied to the futures markets from 1978-82. Extensive testing of various moving average and channel breakout parameters was performed to find the best possible combinations in each futures market. The Merrill Lynch researchers produced a different set of optimized indicator values for each market.
Most charting packages allow you to optimize systems and indicators. Instead of using the same moving average in all markets, for example, you could ask the computer to find the moving average, or moving average combinations, that have worked the best in the past for that market. That could also be done for daily
and weekly breakout systems and virtually all technical indicators included in this book. Optimization allows technical parameters to adapt to changing market conditions.
Some argue that optimization helps their trading results and others that it doesn't. The heart of the debate centers on how the data is optimized. Researchers stress that the correct procedure is to use only part of the price data to choose the best parameters, and another portion to actually test the results. Testing the optimized parameters on "out of sample" price data helps ensure that the final results will be closer to what one might experience from actual trading.
The decision to optimize or not is a personal one. Most evidence, however, suggests that optimization is not the Holy Grail some think it to be. I generally advise traders following only a handful of markets to experiment with optimization. Why should Treasury Bonds or the German mark have the exact same moving averages as corn or cotton? Stock market traders are a different story. Having to follow thousands of stocks argues against optimizing. If you specialize in a handful of markets, try optimizing. If you're a generalist who follows a large number of markets, use the same technical parameters for all of them.
Most charting packages allow you to optimize systems and indicators. Instead of using the same moving average in all markets, for example, you could ask the computer to find the moving average, or moving average combinations, that have worked the best in the past for that market. That could also be done for daily
and weekly breakout systems and virtually all technical indicators included in this book. Optimization allows technical parameters to adapt to changing market conditions.
Some argue that optimization helps their trading results and others that it doesn't. The heart of the debate centers on how the data is optimized. Researchers stress that the correct procedure is to use only part of the price data to choose the best parameters, and another portion to actually test the results. Testing the optimized parameters on "out of sample" price data helps ensure that the final results will be closer to what one might experience from actual trading.
The decision to optimize or not is a personal one. Most evidence, however, suggests that optimization is not the Holy Grail some think it to be. I generally advise traders following only a handful of markets to experiment with optimization. Why should Treasury Bonds or the German mark have the exact same moving averages as corn or cotton? Stock market traders are a different story. Having to follow thousands of stocks argues against optimizing. If you specialize in a handful of markets, try optimizing. If you're a generalist who follows a large number of markets, use the same technical parameters for all of them.
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