CTMSTOU driven markets: simulated environment for regime-awareness in trading policies
This work addresses the challenge of defining and experimenting with market regimes in quantitative finance, though it is incremental as it builds on existing simulation and stochastic process methods.
The authors tackled the problem of studying trading policies in regime-switching markets by introducing a CTMSTOU stochastic process to model fundamental values and a simulated environment for explicit regime control, showing the importance of regime-awareness in order execution strategies.
Market regimes is a popular topic in quantitative finance even though there is little consensus on the details of how they should be defined. They arise as a feature both in financial market prediction problems and financial market task performing problems. In this work we use discrete event time multi-agent market simulation to freely experiment in a reproducible and understandable environment where regimes can be explicitly switched and enforced. We introduce a novel stochastic process to model the fundamental value perceived by market participants: Continuous-Time Markov Switching Trending Ornstein-Uhlenbeck (CTMSTOU), which facilitates the study of trading policies in regime switching markets. We define the notion of regime-awareness for a trading agent as well and illustrate its importance through the study of different order placement strategies in the context of order execution problems.