====== Walk Forward ======

===== Introduction =====

Walk Forward analysis (WFA) or Walk Forward optimization (WFO) is a sequential optimization applied to an investment strategy. The name of the analysis is called "walk forward" because we have a moving window that progressively traverses the whole period of the data history with a pre-established step.

Algorithmic traders apply such analysis to decrease the over-optimized parameters used in the investment strategy as we don’t want only a great looking backtest result, we want also a system that don't fail in live real money account.


===== Step through the Process  =====

As you already know WFA consist on multiple optimization stages and to perform the analysis we need to do this within a time window, where we first have the optimization in a larger window (in-sample) and a test in a smaller window (out-of-sample, unseen data).

During segment 1 all parameters combinations for the trading strategy will be tested (in-sample) and the parameter combination that is considered to be the most robust by the optimizer criteria will be used in the first ouf-of-sample segment.

The process will be repeat until the optimizer has traversed the whole data history with a pre-established step selected in the **Options** and results of the out-of-sample results will be at the **Statistics** page.

===== Equity chart and Output===== 

Once the optimization has completed you can analyze the equity chart and the statistics to understand if the strategy has performed better or survive market dynamics changes.

===== Statistics =====

You can analyse the result on the tested segments and most relevant metric's as start date, end date, profit, return / dd, trades, sqn, win/loss and more.

===== Options =====

Change the inputs for the analysis as: number of segments, out of sample, numeric values range and optimization goal.

===== Validation =====

Apply a performance metric in each segment to validate the success of a strategy.