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- W4387428020 abstract "Stock market has always been a risky and changeable field filled with opportunities and traps. Recently, with the burgeoning development of financial theory and statistically tools, investment methods based on quantitative analysis has become immensely predominant aiding accurate stock market predictions. The implementation of effective quantitative stock selection model can reduce risks at a greater level by accurately predicting the future performance of the stocks. The paper develops a multi-factor stock regression model and implements the same of the Chinese market as part of its research object. The proposed model establishes significant relationships between companies’ and also discovers the effective financial indicators in association to their expected return. Thus, the multi-factor regression model thus helps to predict the stock’s expected return by quantifying the multi-variable linear relationship between a company’s financial ratios and its expected return. This enables companies to develop trading strategies considering companies’ predicted returns. The results reveal the superiority of the multi-factor regression trading model in achieving an annualized rate of return of 28% during the back test period. The model when implemented on dataset indicates it ability as an effective framework to reduce risk and increase excess return." @default.
- W4387428020 created "2023-10-08" @default.
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- W4387428020 date "2023-01-01" @default.
- W4387428020 modified "2023-10-09" @default.
- W4387428020 title "Quantamental Trading: Fundamental and Quantitative Analysis with Multi-factor Regression Model Strategy" @default.
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- W4387428020 doi "https://doi.org/10.1007/978-981-99-6441-3_131" @default.
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