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Walk forward optimization is a method used in finance to determine the optimal parameters for a trading strategy. The trading strategy is optimized with in-sample data for a time window in a data series. The remaining data is reserved for out of sample testing. A small portion of the reserved data following the in-sample data is tested and the results are recorded. The in-sample time window is shifted forward by the period covered by the out of sample test, and the process repeated. Lastly, all of the recorded results are used to assess the trading strategy.

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  • Walk forward optimization is a method used in finance to determine the optimal parameters for a trading strategy. The trading strategy is optimized with in-sample data for a time window in a data series. The remaining data is reserved for out of sample testing. A small portion of the reserved data following the in-sample data is tested and the results are recorded. The in-sample time window is shifted forward by the period covered by the out of sample test, and the process repeated. Lastly, all of the recorded results are used to assess the trading strategy. After the most suitable parameters are found, the system is run using another segment of data. The two segments of data do not overlap each other. It is the culmination of the following methods and aids in creation of robust systems. Past data is used for Backtesting of a trading system. It refers to applying a trading system to historical data to verify how a system would have performed during the specified time period and is useful if a system was not profitable in the past. Forward testing (also known as Walk forward testing) is the simulation of the real markets' data on paper only. One moves along the markets live and is not using real money, but virtually trading in the markets to understand their movements better. Hence, it is also called Paper Trading. Forward performance testing is a simulation of actual trading and involves following the system's logic in a live market. (en)
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  • Walk forward optimization is a method used in finance to determine the optimal parameters for a trading strategy. The trading strategy is optimized with in-sample data for a time window in a data series. The remaining data is reserved for out of sample testing. A small portion of the reserved data following the in-sample data is tested and the results are recorded. The in-sample time window is shifted forward by the period covered by the out of sample test, and the process repeated. Lastly, all of the recorded results are used to assess the trading strategy. (en)
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  • Walk forward optimization (en)
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