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View all- Liang JSui WChen GRen HLi X(2023)Multi-Indicator Early-Warning Model for Mine Water Inrush at the Yushen Mining Area, Shaanxi Province, ChinaWater10.3390/w1522391015:22(3910)Online publication date: 9-Nov-2023
Application of Cluster Analysis in Stock Selection in United States Stock Market
Author: 
Shuo WuAuthors Info & Claims
Shuo WuAuthors Info & ClaimsPages 310 - 313
Abstract
Quantitative trading plays a significant role in stock selection due to its great flexibility and operability. A stock selection strategy was introduced based on the K-means clustering model in machine learning. Some technical indicators, such as MA, KDJ, and MACD with short and long periods, were taken into consideration in our strategy. The United States market stocks were divided into several clusters. And stocks close to the center of the best cluster were chosen to construct a portfolio. Experimental results showed that the investment strategy has a higher excess return rate during the bull market and decreases synchronously with the market trend during the bear market. This strategy, however, is superior to the performance of the S&P500 index at any time. This paper proposes a feasible strategy, which could get a considerable rate of return, to solve the problem of US stock selection.
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- Application of Cluster Analysis in Stock Selection in United States Stock Market
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January 2020
441 pages
ISBN:9781450372947
DOI:10.1145/3377571
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Published: 03 May 2020
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IC4E 2020: 2020 the 11th International Conference on E-Education, E-Business, E-Management, and E-Learning
January 10 - 12, 2020
Osaka, Japan
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View all- Liang JSui WChen GRen HLi X(2023)Multi-Indicator Early-Warning Model for Mine Water Inrush at the Yushen Mining Area, Shaanxi Province, ChinaWater10.3390/w1522391015:22(3910)Online publication date: 9-Nov-2023
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