Dynamic allocation: extremes, tail dependence, and regime Shifts

TL;DR

This paper introduces a sophisticated dynamic regime switching model that captures tail dependence and volatility clustering to improve downside risk prediction and asset allocation strategies in global financial markets.

Contribution

It develops a GARCH-DCC-Copula risk model that enhances risk forecasting and tactical asset allocation by incorporating tail dependence and regime shifts.

Findings

Improved downside risk prediction accuracy.

Enhanced performance of global tactical asset allocation strategies.

Strong predictive power for equity factor performance.

Abstract

By capturing outliers, volatility clustering, and tail dependence in the asset return distribution, we build a sophisticated model to predict the downside risk of the global financial market. We further develop a dynamic regime switching model that can forecast real-time risk regime of the market. Our GARCH-DCC-Copula risk model can significantly improve both risk- and alpha-based global tactical asset allocation strategies. Our risk regime has strong predictive power of quantitative equity factor performance, which can help equity investors to build better factor models and asset allocation managers to construct more efficient risk premia portfolios.