AbstractIn this paper, we apply a collection of parametric (Normal, Normal GARCH, Student GARCH, RiskMetrics and high-frequency duration models) and non-parametric (empirical quantile, extreme distributions models) Value-at-Risk (VaR) techniques to intraday data for three stocks traded on the NewY ork Stock Exchange. Because of the small time horizon of the intraday returns (15 and 30 minute returns), intraday VaR can be useful to market participants (traders, market makers)involved in frequent trading. As expected, the volatility features an important intraday seasonality, which must be removed prior to using theVaR models. The estimation and assessment of the VaR techniques indicate that the data displays a high kurtosis (fat tails), and that VaR models should take this important feature into account. More particularly, Student GARCH, empirical quantile and extreme distributions models perform relatively well.
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Bibliographic InfoPaper provided by Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) in its series CORE Discussion Papers with number 2000045.
Date of creation: 00 Sep 2000
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Intraday volatility; Intraday Value-at-Risk; Duration models; NYSE.;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
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- Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
- Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, vol. 66(5), pages 1127-1162, September.
- Dominique M. Guillaume & Olivier V. Pictet & Michel M. Dacorogna, . "On the intra-daily performance of GARCH processes," Working Papers 1994-07-31, Olsen and Associates.
- Tim Bollerslev, 1986.
"Generalized autoregressive conditional heteroskedasticity,"
EERI Research Paper Series
EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
- Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
- Paul H. Kupiec, 1995. "Techniques for verifying the accuracy of risk measurement models," Finance and Economics Discussion Series 95-24, Board of Governors of the Federal Reserve System (U.S.).
- Jean -Luc Prigent & Olivier Renault & Olivier Scaillet, 1999.
"An Autoregressive Conditional Binomial Option Pricing Model,"
99-65, Centre de Recherche en Economie et Statistique.
- Olivier Renault & Jean-Luc Prigent & Olivier Scaillet, 2000. "An Autoregressive Conditional Binomial Option Pricing Model," FMG Discussion Papers dp364, Financial Markets Group.
- R.W.J. van den Goorbergh & P.J.G. Vlaar, 1999.
"Value-at-Risk Analysis of Stock Returns Historical Simulation,Variance Techniques or Tail Index Estimation?,"
DNB Staff Reports (discontinued)
40, Netherlands Central Bank.
- R.W.J. van den Goorbergh & P.J.G. Vlaar, 1999. "Value-at-Risk analysis of stock returns: Historical simulation, varinace techniques or tail index estimation ?," WO Research Memoranda (discontinued) 579, Netherlands Central Bank, Research Department.
- Engle, Robert F. & Russell, Jeffrey R., 1997. "Forecasting the frequency of changes in quoted foreign exchange prices with the autoregressive conditional duration model," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 187-212, June.
- Andersen, Torben G. & Bollerslev, Tim & Lange, Steve, 1999. "Forecasting financial market volatility: Sample frequency vis-a-vis forecast horizon," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 457-477, December.
- Jón Daníelsson & Casper G. de Vries, 1998.
"Value-at-Risk and Extreme Returns,"
Tinbergen Institute Discussion Papers
98-017/2, Tinbergen Institute.
- R.W.J. van den Goorbergh, 1999. "Value-at-Risk and least squares tail index estimation," WO Research Memoranda (discontinued) 578, Netherlands Central Bank, Research Department.
- GIOT, Pierre, 1999. "Time transformations, intraday data and volatility models," CORE Discussion Papers 1999044, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Andersen, Torben G. & Bollerslev, Tim, 1997. "Intraday periodicity and volatility persistence in financial markets," Journal of Empirical Finance, Elsevier, vol. 4(2-3), pages 115-158, June.
- Beltratti, Andrea & Morana, Claudio, 1999. "Computing value at risk with high frequency data," Journal of Empirical Finance, Elsevier, vol. 6(5), pages 431-455, December.
- Richard B. Olsen & Ulrich A. Müller & Michel M. Dacorogna & Olivier V. Pictet & Rakhal R. Davé & Dominique M. Guillaume, 1997. "From the bird's eye to the microscope: A survey of new stylized facts of the intra-daily foreign exchange markets (*)," Finance and Stochastics, Springer, vol. 1(2), pages 95-129.
- Holly,Sean & Weale,Martin (ed.), 2000. "Econometric Modelling," Cambridge Books, Cambridge University Press, number 9780521650694.
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