Core Insights - The article discusses the advancements made by Galaxy Fund's quantitative team in deep quantitative stock selection research, emphasizing the shift from traditional linear analysis to nonlinear analysis for better market insights and investment opportunities [1][2] Group 1: Quantitative Research Strategies - The quantitative research approach combines linear and nonlinear strategies, utilizing multi-factor models alongside nonlinear machine learning models to achieve stable excess returns and reduce tracking errors [1][2] - The team has developed strategies that include both linear methods, primarily multi-factor models, and nonlinear methods such as XGBoost and LightGBM, which enhance the model's adaptability to market changes [2][3] Group 2: Neural Network Development - The development of complex neural network learning is highlighted, where the approach integrates long-term rules with short-term information to improve the training of supervised learning models [3] - The focus is on extracting features from raw data while addressing the noise present in the data, which aids in the model's ability to adapt quickly to market fluctuations [3] Group 3: Satellite Strategies - To further enhance market adaptability, satellite strategies are employed, including dividend selection and large-cap growth selection, which target specific market characteristics [4] - The dividend selection strategy focuses on high dividend yield stocks, while the large-cap growth strategy emphasizes stocks with large market capitalization and high growth potential [4] Group 4: Risk Management and Product Development - A financial risk management strategy has been developed to mitigate unexpected impacts from risk events, forming a comprehensive quantitative strategy system [5] - The Galaxy Fund has launched two index enhancement products: the Galaxy CSI 300 Index Enhanced Fund and the Galaxy CSI A500 Index Enhanced Fund, with plans to issue the Galaxy CSI 800 Index Enhanced Fund, which offers a balanced representation of both large-cap and mid-cap growth styles [5]