Practical Application of Dynamic Risk Budgeting Models in Hybrid Asset Allocation

China's hybrid asset market exhibits dynamic volatility, rendering traditional asset allocation methods ill-suited to its rapidly shifting risk structure. This paper constructs a dual-layer dynamic risk budgeting model that innovatively integrates economic cycle identification with market state classification. It employs risk budgeting matrix mapping to achieve dynamic risk allocation adjustments. The model employs an improved alternating direction method of multipliers to solve non-convex optimization problems, with dual trigger conditions designed to reduce adjustment frequency and transaction costs. Empirical research demonstrates the model's robust performance under extreme market conditions, delivering significantly superior risk-adjusted returns compared to traditional approaches. This provides Chinese investors with an effective tool for navigating complex market environments.