Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/188420 
Authors: 
Year of Publication: 
2010
Citation: 
[Journal:] Journal of Industrial Engineering and Management (JIEM) [ISSN:] 2013-0953 [Volume:] 3 [Issue:] 1 [Publisher:] OmniaScience [Place:] Barcelona [Year:] 2010 [Pages:] 199-220
Publisher: 
OmniaScience, Barcelona
Abstract: 
In this study, we predict the daily volatility of the S&P CNX NIFTY market index of India using the basic "heterogeneous autoregressive" (HAR) and its variant. In doing so, we estimated several HAR and Log form of HAR models using different regressor. The different regressors were obtained by extracting the jump and continuous component and the threshold jump and continuous component from the realized volatility. We also tried to investigate whether dividing volatility into simple and threshold jumps and continuous variation yields a substantial improvement in volatility forecasting or not. The results provide the evidence that inclusion of realized bipower variance in the HAR models helps in predicting future volatility.
Subjects: 
realized volatility
forecasting
time series analysis
autoregressive model
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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