Publications (12)
End-to-End Policy Learning of a Statistical Arbitrage Autoencoder Architecture
Fabian Krause, Jan-Peter Calliess
In Statistical Arbitrage (StatArb), classical mean reversion trading strategies typically hinge on asset-pricing or PCA based models to identify the mean of a synthetic asset. Once…
Sentiment Correlation in Financial News Networks and Associated Market Movements
Xingchen Wan, Jie Yang, Slavi Marinov +3
In an increasingly connected global market, news sentiment towards one company may not only indicate its own market performance, but can also be associated with a broader movement…
Lipschitz Optimisation for Lipschitz Interpolation
Jan-Peter Calliess
Techniques known as Nonlinear Set Membership prediction, Kinky Inference or Lipschitz Interpolation are fast and numerically robust approaches to nonparametric machine learning tha…
Conservative collision prediction and avoidance for stochastic trajectories in continuous time and space
Jan-Peter Calliess, Michael Osborne, Stephen Roberts
Existing work in multi-agent collision prediction and avoidance typically assumes discrete-time trajectories with Gaussian uncertainty or that are completely deterministic. We prop…
Fast Agent-Based Simulation Framework with Applications to Reinforcement Learning and the Study of Trading Latency Effects
Peter Belcak, Jan-Peter Calliess, Stefan Zohren
We introduce a new software toolbox for agent-based simulation. Facilitating rapid prototyping by offering a user-friendly Python API, its core rests on an efficient C++ implementa…
Constrained Policy Optimization with Cantelli-Bounded Value-at-Risk
Rohan Tangri, Jan-Peter Calliess
We introduce Canary, a risk-averse method designed to optimize Value-at-Risk (VaR) constrained reinforcement learning (RL) problems. We employ Cantelli's inequality to obtain a tra…