Volatility and Correlation Modeling for Sector Allocation in International Equity Markets

Reliable estimates of volatility and correlation are crucial in asset allocation and risk
management. This paper investigates Static, RiskMetrics, and Dynamic Conditional
Correlation (DCC) models for estimating volatility and correlation by testing them in
an asset allocation context. Optimal allocation weights for one year found using esti-
mates from each model are carried to the subsequent year and the realized Sharpe ratio
is computed to assess portfolio performance. We also study cumulative risk-adjusted
returns over the entire sample period. Our ndings indicate that DCC does not consis-
tently have an advantage over the other two models, although it is optimal in certain
scenarios.

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