Irregularly Spaced Intraday Value at Risk (ISIVaR) Models: Forecasting and Predictive Abilities

Christophe Hurlin, Gilbert Colletaz and Sessi Tokpavi ()
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Gilbert Colletaz: LEO - Laboratoire d'économie d'Orleans [2008-2011] - UO - Université d'Orléans - CNRS - Centre National de la Recherche Scientifique

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Abstract: The objective of this paper is to propose a market risk measure defined in price event time and a suitable backtesting procedure for irregularly spaced data. Firstly, we combine Autoregressive Conditional Duration models for price movements and a non parametric quantile estimation to derive a semi-parametric Irregularly Spaced Intraday Value at Risk (ISIVaR) model. This ISIVaR measure gives two information: the expected duration for the next price event and the related VaR. Secondly, we use a GMM approach to develop a backtest and investigate its finite sample properties through numerical Monte Carlo simulations. Finally, we propose an application to two NYSE stocks.

Keywords: Value at Risk; High-frequency data; ACD models; Irregularly spaced market risk models; Backtesting (search for similar items in EconPapers)
Date: 2007-07-13
Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-00162440
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Irregularly Spaced Intraday Value-at-Risk (ISIVaR) Models: Forecasting and Predictive Abilities (2007)
Working Paper: Irregularly Spaced Intraday Value-at-Risk (ISIVaR) Models: Forecasting and Predictive Abilities (2007)
Working Paper: Irregularly Spaces Intraday Value-at-Risk (ISIVaR) Models: Forecasting and Predictive Abilities (2007)
Working Paper: Irregularly Spaced Intraday Value at Risk (ISIVaR) Models Forecasting and Predictive Abilities (2007)
Working Paper: Irregularly Spaced Intraday Value at Risk (ISIVaR) Models: Forecasting and Predictive Abilities (2007)
Working Paper: Irregularly Spaced Intraday Value-at-Risk (ISIVaR) Models: Forecasting and Predictive Abilities (2007)
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