In the WFSD method, the out-of-sample is the next year. This process is repeated at the end of 2013, 2014, 2015, 20. This means that as new data become available at the end of the year, we then use it to develop a new strategy, one for the extended and one for the deep cluster. Then, we repeat the standard method of development by extending the in-sample to. We record the performance for 2012, which is the same for both methods. We start as in standard method with the two strategies, one for the extended and one for the deep cluster. Walk Forward Strategy Development (WFSD) method The remaining parameters are set as shown in the search workspace below: We employ the extended and the deep clusters of features and we obtain two different strategies, one for each cluster, called INEXT and INDEEP, respectively. We use profit target and stop-loss of 4%. We use DLPAL S to develop a strategy for QQQ ETF with in-sample data from to and then validate it out-of-sample from to. Our objective in this article is to compare the results of strategy developed using the standard method of in-sample training/testing followed by out-of-sample validation to a method that rebalances the strategy at the end of each year after the in-sample. We find a significant advantage in using the walk forward method as compared to a static strategy. We compare the results of trading strategy development using standard in-sample/out-of-sample method to a walk forward method that involves rebalancing the strategy at the end of each year.
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