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Comparison of Volatility Measures: a Risk Management Perspective

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Author Info
Christian T. Brownlees () (Università degli Studi di Firenze, Dipartimento di Statistica)
Giampiero Gallo () (Università degli Studi di Firenze, Dipartimento di Statistica "G. Parenti")

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Abstract

In this paper we address the issue of forecasting Value–at–Risk (VaR) using different volatility measures: realized volatility, bipower realized volatility, two scales realized volatility, realized kernel as well as the daily range. We propose a dynamic model with a flexible trend specification bonded with a penalized maximum likelihood estimation strategy: the P-Spline Multiplicative Error Model. Exploiting UHFD volatility measures, VaR predictive ability is considerably improved upon relative to a baseline GARCH but not so relative to the range; there are relevant gains from modeling volatility trends and using realized kernels that are robust to dependent microstructure noise.

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Paper provided by Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti" in its series Econometrics Working Papers Archive with number wp2008_03.

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Date of creation: Feb 2008
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Handle: RePEc:fir:econom:wp2008_03

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Related research
Keywords: Volatility Measures; VaR Forecasting; GARCH; MEM; P-Spline.;

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Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Bonato, Matteo & Caporin, Massimiliano & Ranaldo, Angelo, 2009. "Forecasting realized (co)variances with a block structure Wishart autoregressive model," Working Papers 2009-3, Swiss National Bank. [Downloadable!]
  2. Christian T. Brownlees & Giampiero Gallo, 2007. "Volatility Forecasting Using Explanatory Variables and Focused Selection Criteria," Econometrics Working Papers Archive wp2007_04, Universita' degli Studi di Firenze, Dipartimento di Statistica "G. Parenti". [Downloadable!]
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