Using RiskMetrics Stress Data In Hedge Fund Portfolio Optimization
ABC Quant offers a number of unique and propriety risk management techniques developed in collaboration with the best fund managers and addressing needs of our clients. The integration of the Risk Shell portfolio optimization with the stress test results coming from RiskMetrics is one of these techniques. This tutorial discusses the fundamentals of advanced optimization models imposing constraints from RiskMetrics holding-based stress tests into Risk Shell optimization and their implementation in practice, for a hedge fund investor.
Hedge Fund Portfolio Optimization: Why Include Stress Test Data?
- Hedge fund stress testing: Holdings-Based vs. Returns-Based Analysis.
- RiskMetrics Stress test data, the methodology and data structure.
- Benefits of adding stress test data as constraints of the portfolio optimization model.
- Market-neutral portfolios: factor constraints vs. stress constraints. Advantages and pitfalls of each model.
Risk Shell Portfolio Optimization And Stress Test Data - Step-By-Step Tutorial
- Importing stress test data as custom beta constraints.
- Adding beta constraints into optimization models.
- Monitoring portfolio market neutrality via the Efficient Frontier. Tips of including 'the best' stressing factors into the model.
- Portfolio backtesting: comparing factor constraints with stress constraints when constructing market neutral portfolios.
- Using both factor constraints and stress test constraints ti enhance portfolio neutrality.
Institutional portfolio managers, institutional risk managers, hedge FoF and multi-asset portfolio managers, CIOs, endowments, private banks.