AlphaPortfolio: Direct Construction Through Deep Reinforcement Learning and Interpretable AI

70 Pages Posted: 20 Apr 2020 Last revised: 4 Aug 2021

See all articles by Lin William Cong

Lin William Cong

Cornell University - Samuel Curtis Johnson Graduate School of Management

Ke Tang

Institute of Economics, School of Social Sciences, Tsinghua University

Jingyuan Wang

Beihang University (BUAA)

Yang Zhang

Beihang University (BUAA)

Date Written: July 10, 2021

Abstract

We directly optimize the objectives of portfolio management via reinforcement learning---an alternative to conventional supervised-learning-based paradigms that entail first-step estimations of return distributions, pricing kernels, or risk premia. Building upon breakthroughs in AI, we develop multi-sequence neural network models tailored to distinguishing features of economic and financial data, while allowing training without labels and potential market interactions. The resulting AlphaPortfolio yields stellar out-of-sample performances (e.g., Sharpe ratio above two and over 13% risk-adjusted alpha with monthly re-balancing) that are robust under various economic restrictions and market conditions (e.g., exclusion of small stocks and short-selling). Moreover, we project AlphaPortfolio onto simpler modeling spaces (e.g., using polynomial-feature-sensitivity) to uncover key drivers of investment performance, including their rotation and nonlinearity. More generally, we highlight the utility of deep reinforcement learning in finance and invent "economic distillation" tools for interpreting AI and big data models.

Keywords: Artificial Intelligence, Distillation, LSTM, Machine Learning, Portfolio Theory, Reinforcement Learning.

Suggested Citation

Cong, Lin and Tang, Ke and Wang, Jingyuan and Zhang, Yang, AlphaPortfolio: Direct Construction Through Deep Reinforcement Learning and Interpretable AI (July 10, 2021). Available at SSRN: https://ssrn.com/abstract=3554486 or http://dx.doi.org/10.2139/ssrn.3554486

Lin Cong (Contact Author)

Cornell University - Samuel Curtis Johnson Graduate School of Management ( email )

Ithaca, NY 14853
United States

HOME PAGE: http://www.linwilliamcong.com/

Ke Tang

Institute of Economics, School of Social Sciences, Tsinghua University ( email )

No.1 Tsinghua Garden
Beijing, 100084
China

Jingyuan Wang

Beihang University (BUAA) ( email )

37 Xue Yuan Road
Beijing 100083
China

Yang Zhang

Beihang University (BUAA) ( email )

37 Xue Yuan Road
Beijing 100083
China

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