Rolling Window Analysis
Rolling window analysis is a technique where a model is trained on a fixed-size window of data that moves forward over time. Unlike expanding windows, rolling windows discard the oldest data, allowing the model to focus on the most recent market regime.
This is particularly useful in crypto markets, where historical data from several years ago may have little relevance to current liquidity or protocol dynamics. By continuously updating the model with fresh data, traders can ensure that their strategies remain aligned with current market trends.
This method helps in identifying structural shifts in the market and adjusting parameters accordingly. It is a cornerstone of adaptive strategy management in high-frequency and derivative environments.