Volatility and Correlation Modeling for Sector Allocation in International Equity Markets
Abstract
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
estimates 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 findings indicate that DCC does not consistently
have an advantage over the other two models, although it is optimal in certain scenarios.
Type
Honors thesisDepartment
EconomicsPermalink
https://hdl.handle.net/10161/5135Citation
Fan, Melanie; & Yuan, Kate Xiaoxiao (2012). Volatility and Correlation Modeling for Sector Allocation in International Equity
Markets. Honors thesis, Duke University. Retrieved from https://hdl.handle.net/10161/5135.Collections
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