黑翼资产：AI全流程赋能，追求更多阿尔法

Group 1 - The core viewpoint emphasizes that the index enhancement strategy, which combines "market beta returns + excess alpha returns," is expected to be an important allocation tool for investors navigating market cycles, particularly focusing on the CSI 1000 index strategy that targets small-cap growth stocks [1][22] - The CSI 1000 index is characterized by its focus on small-cap companies, selecting 1000 securities that are smaller and more liquid than those in the CSI 800 index, complementing other indices like the CSI 300 and CSI 500 [5][28] - The top three industries within the CSI 1000 index are industrials, information technology, and materials, accounting for 26.59%, 21%, and 12.98% respectively, indicating a strong presence of high-growth and high-profitability sectors [10][31] Group 2 - Blackwing Asset, established in 2014, is one of the first quantitative investment institutions in China, focusing on scientific and rational investment strategies, emphasizing risk control and long-term performance [2][23] - The founding team consists of experienced quantitative investment managers with 18 years of practical experience, and the company has implemented a comprehensive AI-driven quantitative investment process across various strategy lines [2][24] - The research and investment team at Blackwing Asset comprises approximately 70% of the workforce, with an average experience of over 10 years, and over 60% of team members holding PhDs from prestigious universities [3][25] Group 3 - Blackwing Asset is among the early adopters of AI technology in financial markets, integrating AI throughout the quantitative investment process, including data collection, factor mining, return prediction, portfolio optimization, and algorithmic trading [4][27] - The firm employs a diversified factor configuration strategy, combining machine learning factors, fundamental factors, and price-volume factors to create a collaborative factor system aimed at achieving diversified excess returns [16][37] - A systematic risk control framework is established, encompassing pre-trade, in-trade, and post-trade risk management to enhance performance stability and mitigate risks effectively [22][44]