Visser, Marcel P. (2008): Ranking and Combining Volatility Proxies for Garch and Stochastic Volatility Models.
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Daily volatility proxies based on intraday data, such as the high-low range and the realized volatility, are important to the specification of discrete time volatility models, and to the quality of their parameter estimation. The main result of this paper is a simple procedure for combining such proxies into a single, highly efficient volatility proxy. The approach is novel in optimizing proxies in relation to the scale factor (the volatility) in discrete time models, rather than optimizing proxies as estimators of the quadratic variation. For the S&P 500 index tick data over the years 1988-2006 the procedure yields a proxy which puts, among other things, more weight on the sum of the highs than on the sum of the lows over ten-minute intervals. The empirical analysis indicates that this finite-grid optimized proxy outperforms the standard five-minute realized volatility by at least 40%, and the limiting case of the square root of the quadratic variation by 25%.
|Item Type:||MPRA Paper|
|Original Title:||Ranking and Combining Volatility Proxies for Garch and Stochastic Volatility Models|
|Keywords:||volatility proxy; realized volatility; quadratic variation; scale factor; arch/garch/stochastic volatility; variance of logarithm|
|Subjects:||G - Financial Economics > G1 - General Financial Markets
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling > C65 - Miscellaneous Mathematical Tools
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection
C - Mathematical and Quantitative Methods > C2 - Single Equation Models; Single Variables > C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
|Depositing User:||Marcel Visser|
|Date Deposited:||14. Oct 2008 11:12|
|Last Modified:||11. Feb 2013 22:58|
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Available Versions of this Item
Volatility Proxies for Discrete Time Models. (deposited 14. Sep 2007)
- Ranking and Combining Volatility Proxies for Garch and Stochastic Volatility Models. (deposited 14. Oct 2008 11:12) [Currently Displayed]