Do you want to understand the importance of correlation in a trading strategy? Correlation metrics help traders in evaluating the strategy performance reports which would have created while testing a trading model.
Correlations also help in establishing the similarities between the performance and overall trends of the data sets.
Correlation plays a very important factor in evaluating a trading strategy. As we have already discussed the importance of the partition of historical data in our last published post.
Correlation in Trading Strategy
One method of determining the performance of the system is by splitting historical data into 3 parts. One-third needs to be reserved for out-of-sample testing whereas two-thirds would be used for in-sample testing of a trading system.
Out-Sample In-Sample Forward Performance
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As we can see above, the distribution of historical data. Here comes the role of correlation. It refers to the performance and overall trends. Correlation metrics can be used while evaluating trading strategy performance reports created in the testing period. The better or stronger the correlation between the two, the higher the chances of success of the performance of the system in forward performance testing or in real-time trading.
Evaluate a Trading Strategy
Once a trading system has been developed with the use of in-sample trading data, it then is ready to be applied to out-of-sample data. Providing traders an option to evaluate and compare the results of the performance between In-sample and out-sample data.
If a strong connection is seen then the next step is to involve the addition type of out-of-sample testing also known as the forward performance testing.