Resilient Portfolio Optimization using Traditional and Data-Driven Models for Cryptocurrencies and Stocks
Author:
Affiliation:
1. University of Manitoba,Department of Computer Science,Winnipeg,Canada
2. University of Manitoba,Department of Statistics,Winnipeg,Canada
Funder
University of Manitoba
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10196792/10196808/10196966.pdf?arnumber=10196966
Reference20 articles.
1. Prediction based mean-value-at-risk portfolio optimization using machine learning regression algorithms for multi-national stock markets
2. Optimizing Portfolio Risk of Cryptocurrencies Using Data-Driven Risk Measures
3. Deep reinforcement learning for stock portfolio optimization by connecting with modern portfolio theory
4. A novel prediction based portfolio optimization model using deep learning
5. Novel Data-Driven Resilient Portfolio Risk Measures Using Sign and Volatility Correlations
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1. Hybrid Data-Driven and Deep Learning Based Portfolio Optimization;Journal of Mathematical Finance;2024
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