67 citations · 77 across the 6 of their papers we have counts for
3 papers · 1 filter
Deep Learning for Financial Time Series: A Large-Scale Benchmark of Risk-Adjusted Performance
Adir Saly-Kaufmann, Kieran Wood, Jan Peter-Calliess +1
We present a large scale benchmark of modern deep learning architectures for a financial time series prediction and position sizing task, with a primary focus on Sharpe ratio optim…
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…
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.…