V.10:7 (303-308): System Optimization Techniques by David S. Nicol
Product Description
System Optimization Techniques
by David S. Nicol
What is system optimization and is it good or bad? It's a little of both, system designers will tell you. David Nicol explains the whys and wherefores.
System optimization is a controversial subject among market analysts, but it is also misunderstood by analysts and traders. So what is system optimization? When designing a technical trading system, the designer must use a mathematical formula or algorithm of some kind to produce trading signals. This is usually referred to as an indicator and can be as simple as a single moving average or as complex as a fast Fourier transform. Whatever the indicator may be, all indicators have one characteristic in common: they all contain one or more parameters. A parameter can be set to one of several possible numeric values, the value of which can greatly alter the behavior and performance of the indicator. Because parameters exist in every indicator, the system designer must set each parameter to some value . For each system designer, the dilemma is what value to assign each parameter. That is where optimization occurs. Optimization is the process of choosing the best parameter values for the indicator. So what do we mean by "best parameter value"?
FINDING THE BEST VALUE
One approach to finding the best parameter value is to backtest the indicator with a range of parameter values and simply choose which parameter value produced the most profitable trading signals . This approach has several problems. First, how far back should the testing go? Should the parameters be changed during the test run? If so, when and how? The way that the system designer handles these questions will greatly affect the validity and utility of the optimization process.
However, those systems that are optimized without the benefit of hindsight experimentation because of the fear of curve-fitting are not properly optimized because no effort has been made to verify the validity of their parameters. This process is simply choosing parameters randomly. This is the dart-board method to optimization, because money is risked based on parameters that could have been chosen by the toss of a dart.
What is system optimization and is it good or bad? It's a little of both, system designers will tell you. David Nicol explains the whys and wherefores.
System optimization is a controversial subject among market analysts, but it is also misunderstood by analysts and traders. So what is system optimization? When designing a technical trading system, the designer must use a mathematical formula or algorithm of some kind to produce trading signals. This is usually referred to as an indicator and can be as simple as a single moving average or as complex as a fast Fourier transform. Whatever the indicator may be, all indicators have one characteristic in common: they all contain one or more parameters. A parameter can be set to one of several possible numeric values, the value of which can greatly alter the behavior and performance of the indicator. Because parameters exist in every indicator, the system designer must set each parameter to some value . For each system designer, the dilemma is what value to assign each parameter. That is where optimization occurs. Optimization is the process of choosing the best parameter values for the indicator. So what do we mean by "best parameter value"?
FINDING THE BEST VALUE
One approach to finding the best parameter value is to backtest the indicator with a range of parameter values and simply choose which parameter value produced the most profitable trading signals . This approach has several problems. First, how far back should the testing go? Should the parameters be changed during the test run? If so, when and how? The way that the system designer handles these questions will greatly affect the validity and utility of the optimization process.
However, those systems that are optimized without the benefit of hindsight experimentation because of the fear of curve-fitting are not properly optimized because no effort has been made to verify the validity of their parameters. This process is simply choosing parameters randomly. This is the dart-board method to optimization, because money is risked based on parameters that could have been chosen by the toss of a dart.
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