SMU Data Science Review

Intelligent Investment Portfolio Management using Time-Series Analytics and Deep Reinforcement Learning

Sachin Chavan, SMUFollow
Pradeep Kumar, SMUFollow
Tom Gianelle, SMUFollow

Abstract

Abstract. – With globalization, the capital markets have exploded in size and value, making them exceedingly difficult to predict. These days the public has access to real-time data of the market-leading to more participation. As a positive step, this might lead to better wealth distribution in the society, and it also adds to the random nature of the market, making it more unpredictable. The portfolio accounts consisting of stocks and bonds are considered serious investment assets. They can make or break a person’s future. It is also a way of shielding one against market risk or rising inflation. These accounts, when managed well, will grow in value and can keep an individual’s finances healthy. The management of these accounts requires good knowledge of markets and periodic adjustment of assets in the account. This paper utilized Reinforcement Learning and Time-Series analytics to create stock-trading models for research purposes.

Recommended Citation

Chavan, Sachin; Kumar, Pradeep; and Gianelle, Tom (2021) "Intelligent Investment Portfolio Management using Time-Series Analytics and Deep Reinforcement Learning," SMU Data Science Review: Vol. 5: No. 2, Article 7.
Available at: https://scholar.smu.edu/datasciencereview/vol5/iss2/7