Yannan Zhong’s research while affiliated with Guangdong University Of Finances and Economics and other places

Investors are often affected by emotion, cognition, and other psychological factors in stock trading when making decisions. At present, people can use machine learning and other technologies to obtain a massive amount of text data from the Internet to mine information related to investor behavior and sentiment. Building intelligent online portfolio trading strategies that consider investor sentiment has become an important topic and key challenge in the financial field. Therefore, this paper explores how to use text data to depict investor sentiment, fuzzifies historical stock price data, designs a new weight transfer equation, and finally obtains a novel fuzzy mean regression strategy that considers investor sentiment based on text data. We conduct empirical tests on this strategy by using the stock price data selected from CSI300 constituent stocks, as well as the text data of investors’ opinions on the internet. The results show that the strategy proposed in this study has a higher Calmar ratio than other mean regression strategies previously studied.

Intelligent online portfolios have become an important research topic in the field of quantitative finance. This paper proposes an online portfolio based on trend trading strategy using fuzzy logic technology analysis method and considering investor sentiment. Firstly, the paper uses SVM classification algorithm to analyze stock comment text data in online forums and constructs investor sentiment indicators. Secondly, the paper transforms the heuristic algorithm of technical trading into corresponding fuzzy IF-THEN rules and combines them into a fuzzy investment decision system. Thirdly, the paper constructs a new online portfolio based on trend trading strategy. Finally, the paper uses the text data of investor reviews and stock trading data on the internet for empirical analysis to illustrate the effectiveness of the online portfolio strategy constructed. The results indicate that online portfolios constructed based on trend trading strategies can achieve higher performance than benchmark strategies while considering transaction costs.