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Tag Archives: Dynamic Correlation
By Yuci Zhang
In nance, the beta of an investment is a measure of the risk arising from exposure to general market movements as opposed to idiosyncratic factors. Therefore, reliable estimates of stock portfolio betas are essential for many areas in modern nance, including asset pricing, performance evaluation, and risk management. In this paper, we investigate Static and Dynamic Conditional Correlation (DCC) models for estimating betas by testing them in two asset pricing context, the Capital Asset Pricing Model (CAPM) and Fama-French Three Factor Model. Model precision is evaluated by utilizing the betas to predict out-of-sample portfolio returns within the aforementioned asset-pricing framework. Our findings indicate that DCC-GARCH does consistently have an advantage over the Static model, although with a few exceptions in certain scenarios.
Advisor: Andrew Patton, Michelle Connolly | JEL Codes: C32, C51, G1, G12, G17 | Tagged: Beta, Asset Pricing, Dynamic Correlation, Equity, U.S. Markets
By Melanie Fan
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 ndings indicate that DCC does not consistently have an advantage over the other two models, although it is optimal in certain scenarios.
Advisor: Aino Levonmaa, Emma Rasiel | JEL Codes: C32, C51, G11, G15 | Tagged: