Investment portfolio research on a multi-factor quantitative investment model

Abstract: This paper focuses on the study of investment portfolios based on a multifactor quantitative investment model. The aim is to develop an effective strategy that can maximize returns while minimizing risks in the investment process. The multifactor quantitative investment model takes into account various factors such as company fundamentals, market trends, macroeconomic indicators, and investor sentiment. By analyzing these factors, it aims to identify undervalued assets and predict their future performance. The research methodology involves collecting historical data on different factors and using statistical techniques to analyze their impact on asset prices. By incorporating multiple factors and considering their interactions, the model is able to generate higher risk-adjusted returns. The research utilizes a multifactor model to select the necessary research factors and applies a quantitative investment model to identify stocks for portfolio construction. Subsequently, the selected stocks are analyzed and tested using the concept of the efficient frontier to obtain the optimal investment portfolio. Finally, the Sharpe ratio is employed as a final validation measure, confirming that the investment portfolio exhibits a high level of suitability. The results are then used to construct optimal investment portfolios that provide a balance between risk and return. The findings of this research suggest that a multifactor quantitative investment model can significantly outperform traditional investment strategies.