Predicting Volatility & Liquidity Regimes using Machine Learning

There are many potential applications for trying to understand what particular state or regime a market is currently in, and more importantly, what regime is predicted. For example, attempting to predict price momentum from an alpha or execution timing perspective, or predicting volatility and liquidity regimes to assist in execution decision making. At BestX, our regime research has initially focused on the latter and in order to provide a predictive component to the regime analysis we have employed the use of machine learning, a particularly hot topic in its own right with many different methods and approaches now available. Rather than simply choosing the most complex sounding method for quantitative and intellectual satisfaction, we have conducted a rigorous study of 6 different methods to determine which is the most appropriate to help solve our particular problem of predicting regimes in volatility and liquidity. Interestingly, we found that the more complex deep learning/neural net methodologies were not as successful for regime prediction as a simpler classification method. This has reiterated the importance to us of ensuring you pick the right tools for the job. If you are a BestX client and would like a copy of the research paper, please email us at