Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022)

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A Portfolio Strategy Based on XGBoost Regression and Monte Carlo Method

Authors
Mingxuan Wang1, *
1Department of Mathematics, University College London, London, UK
*Corresponding author. Email: mingxuan.wang.20@ucl.ac.uk
Corresponding Author
Mingxuan Wang
Available Online 31 December 2022.
DOI
10.2991/978-94-6463-036-7_132How to use a DOI?
Keywords
XGBoost; Monte Carlo; Portfolio Strategy; ETF; Machine learning; Optimization
ABSTRACT

In this research, XGBoost algorithm was used to choose stocks. The stock data was downloaded from Yahoo Finance. The volumes, the differences of open price and close price, the differences of high price and low price, the adjusted close prices of the previous three days were considered as factors. Based on XGBoost, the data were segmented and trained to obtain the importance of each factor for each stock. The price of the previous three days is the most important factor for most stocks. In addition, RMSE and MAPE were calculated. After selecting the stocks with the minimum MAPE, the mean variance portfolio optimization model and the Monte Carlo method were used to find a range of portfolio weights of each stock in the stock pool. The return was calculated under the condition of reducing the risk. When the weights of the stock portfolio with the maximum Sharpe ratio are applied to the next year, the portfolio will achieve higher returns. Therefore, the model can be considered as a suitable tool to help investors implement better portfolio strategies.

Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022)
Series
Advances in Economics, Business and Management Research
Publication Date
31 December 2022
ISBN
978-94-6463-036-7
ISSN
2352-5428
DOI
10.2991/978-94-6463-036-7_132How to use a DOI?
Copyright
© 2022 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Mingxuan Wang
PY  - 2022
DA  - 2022/12/31
TI  - A Portfolio Strategy Based on XGBoost Regression and Monte Carlo Method
BT  - Proceedings of the 2022 2nd International Conference on Economic Development and Business Culture (ICEDBC 2022)
PB  - Atlantis Press
SP  - 896
EP  - 902
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-036-7_132
DO  - 10.2991/978-94-6463-036-7_132
ID  - Wang2022
ER  -