Does Modeling Jumps Help? A Comparison of Realized Volatility Models for Risk Prediction
Australian National University (ANU); Financial Research Network (FIRN)
June 1, 2012
Centre for Applied Macroeconomic Analysis Working Paper No. 26/2012
Recent literature has focuses on realized volatility models to predict financial risk. This paper studies the benefit of explicitly modeling jumps in this class of models for value at risk (VaR) prediction. Several popular realized volatility models are compared in terms of their VaR forecasting performances through a Monte Carlo study and an analysis based on empirical data of eight Chinese stocks. The results suggest that careful modeling of jumps in realized volatility models can largely improve VaR prediction, especially for emerging markets where jumps play a stronger role than those in developed markets.
Number of Pages in PDF File: 42
Keywords: value at risk (VaR), realized volatility, jumps
JEL Classification: C13, C32, C52, C53, G17working papers series
Date posted: June 5, 2012
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