End-to-End Policy Learning of a Statistical Arbitrage Auto encoder Architecture

By Fabian Krause, Jan-Peter Calliess

Published 2024-02-13

Everscope rating

1393

Relevance to quantitative trading

9 / 10

Implementation complexity

7 / 10

Reproducibility

3 / 5

About this paper

Methodology: End-to-End Policy Learning Autoencoder. Problem types: Time Series Forecasting, Portfolio Optimization, Statistical Arbitrage.

arXiv:2402.08233 · Paper rankings

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