2 papers
q-fin.TR2026
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…
q-fin.RM2024
DeepVol: Volatility Forecasting from High-Frequency Data with Dilated Causal Convolutions
Fernando Moreno-Pino, Stefan Zohren
Volatility forecasts play a central role among equity risk measures. Besides traditional statistical models, modern forecasting techniques based on machine learning can be employed…