The performance of a model on data outside that used in its construction remains the touchstone for assessing its utility in any application. Described as an Out of Sample Process, walk-forward simulation improves the fidelity of portfolio simulation by only allowing decisions to be made based on what was known at that point in time. 

In portfolio management, accurately predicting how a model will perform with new, unseen data is a key measure of its effectiveness. This is where ‘walk-forward simulation’ plays an important role. It enhances the realism of portfolio simulations by basing decisions on the information that was available at each historical point, thus replicating real-world decision-making more closely. 

 Evaluating a portfolio’s design is essential to ensure its robustness for future conditions. The key question we consider is: Will the portfolio remain effective in the future? 

 To test this, we use a method involving historical data, segmented into specific periods. The process involves two main phases: 

  • Training Phase (In Sample Period): Here, we use a portion of historical data to configure the optimal portfolio. This phase is like preparing a strategy based on past information. 
  • Testing Phase (Rolling Out of Sample Period): The portfolio, once set during the training phase, is then tested over a subsequent period. This period directly follows the training phase and serves to evaluate how the portfolio would have performed. 

During the testing phase, the composition of the portfolio is kept constant. However, its value may change due to market fluctuations. This approach simulates real-time portfolio management, where decisions are based on past data, and future market conditions are unknown. 

 At the end of each testing phase, a new portfolio is configured using the next set of historical data (the new In Sample period), and then tested over the following period (the new Rolling Out of Sample period). This step-by-step approach covers the entire dataset, allowing for an iterative process of refinement and testing. 

 Finally, the overall performance over a longer period is determined by combining the outcomes of these shorter testing phases. This composite performance gives a comprehensive view of how the portfolio might respond to varying market conditions over time. 

In Sample and Rolling Out of Sample process stepping through time