how to avoid curve fitting during back testing
TRANSCRIPT
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The process of testing a trading strategy on
relevant historical data to ensure its viability
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Unfortunately with computerized back
testing we also need to deal with the curse of
curve fitting
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Parameters are tuned so that they produce
optimized results for the historical data
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Same parameters would yield drastically
reduced or even negative results
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There are three back testing strategies we
can use to alleviate the curve fitting issue
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Optimize one variable at a time
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Optimize over several different
historical data sets
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Optimize the variables on a historical set of
data and then validate by applying them to a different set of data
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We'll focus on theout of sample
testing
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We separate the available historical test
data into two sets
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The first set for computerized back
testing and optimization.
This is called the in-sample period
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The optimized test results are applied to the
untested data set referred to as the
out of sample period
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Typically we use the most recent data for
the out of sample testing
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Begin by adding your strategies and setting
the optimization parameters
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StrategyPerformance Report
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Curve Fitted System Optimized System
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The drawback is the testing is performed over a
limited period of time
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The market may have experienced different
levels of price volatility
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Walk forward testing will be covered in a later video