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Improving Wealth Management Strategies Through the Use of Reinforcement Learning Based Algorithms. A Study on the Romanian Stock Market

Ștefan-Constantin Radu (), Lucian Anghel () and Ioana Simona Ermiè˜ ()
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Ștefan-Constantin Radu: Romanian Economic Studies Academy
Lucian Anghel: National University of Political Studies and Public Administration

Management Dynamics in the Knowledge Economy, 2021, vol. 9, issue 3, 405-416

Abstract: In the context of the growing pace of technological development and that of the transition to the knowledge-based economy, wealth management strategies have become subject to the application of new ideas. One of the fields of research that are increasing in influence in the scientific community is that of reinforcement learning-based algorithms. This trend is also manifesting in the domain of economics, where the algorithms have found a use in the field of stock trading. The use of algorithms has been tested by researchers in the last decade due to the fact that by applying these new concepts, fund managers could obtain an advantage when compared to using classic management techniques. The present paper will test the effects of applying these algorithms on the Romanian market, taking into account that it is a relatively new market, and compare it to the results obtained by applying classic optimization techniques based on passive wealth management concepts. We chose the Romanian stock market due to its recent evolution regarding the FTSE Russell ratings and the fact that the country is becoming an Eastern European hub of development in the IT sector, these facts could indicate that the Romanian stock market will become even more significant in the future at a local and maybe even at a regional level.

Keywords: reinforcement learning; wealth management strategies; stock market; East European economies. (search for similar items in EconPapers)
Date: 2021
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