Achieving Mean–Variance Efficiency by Continuous-Time Reinforcement Learning-Reference-Cited by-同舟云学术

Achieving Mean–Variance Efficiency by Continuous-Time Reinforcement Learning

Published:2022-10-26 Issue: Volume: Page:
ISSN:
Container-title:3rd ACM International Conference on AI in Finance
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Author:

Huang Yilie¹,Jia Yanwei¹,Zhou Xunyu²

Affiliation:

1. Industrial Engineering and Operations Research, Columbia University, US

2. Industrial Engineering and Operations Research, Columbia University, US and The Data Science Institute, Columbia University, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3533271.3561760

Reference46 articles.

1. On the Sensitivity of Mean-Variance-Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results

2. The Sampling Error in Estimates of Mean-Variance Efficient Portfolio Weights

3. Deep hedging

4. Victor DeMiguel , Lorenzo Garlappi , and Raman Uppal . 2009. Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy?The Review of Financial Studies 22, 5 ( 2009 ), 1915–1953. Victor DeMiguel, Lorenzo Garlappi, and Raman Uppal. 2009. Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy?The Review of Financial Studies 22, 5 (2009), 1915–1953.

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