The objective of a quantitative hedging strategy is to achieve robust absolute returns. The optimal portfolio is constructed in perfect equilibrium, where the investment manager fully exposes the portfolio to alpha factors while eliminating other destabilizing style factor distractions. In a multi-factor model, the equity portfolio's weighting is critical in determining the robustness of the strategy's returns. Therefore, portfolio weight optimization plays a crucial role in pursuing return stability for multi-factor models.
Regarding specific research ideas, we aim to use the Barra risk model to predict the volatility of the equity portfolio. The Barra risk model is a multi-factor model developed by Barra Inc. that measures the overall risk associated with a security relative to the market. The model incorporates more than 40 data metrics, including earnings growth, share turnover, and senior debt rating. It then measures risk factors associated with three main components: industry risk, exposure to different investment themes, and company-specific risk. Finally, we will calculate the weight optimization of the stock portfolio based on the predicted portfolio risk to obtain the optimal portfolio under various risk constraints.
Barra/
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├── Barra/
│ ├── scripts/
│ └── data/
│
├── tests/
│
├── docs/
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├── .gitignore
├── LICENSE
├── README.md
├── requirements.txt
└── setup.py