67 citations · 77 across the 7 of their papers we have counts for
7 papers
How do standard time series forecasting benchmarks translate to finance? A broad study of risk adjusted performance
Adir Saly-Kaufmann, Kieran Wood, Jan-Peter Calliess +2
Forecasting financial asset returns is challenging due to low signal-to-noise ratios, non-stationarity and heavy-tailed distributions. We benchmark 16 deep learning architectures f…
Cantelli Constrained Policy Optimization
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…
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…
Lipschitz Interpolation: Non-parametric Convergence under Bounded Stochastic Noise
Julien Walden Huang, Stephen Roberts, Jan-Peter Calliess
This paper examines the asymptotic convergence properties of Lipschitz interpolation methods within the context of bounded stochastic noise. In the first part of the paper, we esta…
Asynchronous Deep Double Duelling Q-Learning for Trading-Signal Execution in Limit Order Book Markets
Peer Nagy, Jan-Peter Calliess, Stefan Zohren
We employ deep reinforcement learning (RL) to train an agent to successfully translate a high-frequency trading signal into a trading strategy that places individual limit orders.…
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…
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…