Extreme value models in a conditional duration intensity framework
AbstractThe analysis of return series from financial markets is often based on the Peaks-over-threshold (POT) model. This model assumes independent and identically distributed observations and therefore a Poisson process is used to characterize the occurrence of extreme events. However, stylized facts such as clustered extremes and serial dependence typically violate the assumption of independence. In this paper we concentrate on an alternative approach to overcome these difficulties. We consider the stochastic intensity of the point process of exceedances over a threshold in the framework of irregularly spaced data. The main idea is to model the time between exceedances through an Autoregressive Conditional Duration (ACD) model, while the marks are still being modelled by generalized Pareto distributions. The main advantage of this approach is its capability to capture the short-term behaviour of extremes without involving an arbitrary stochastic volatility model or a prefiltration of the data, which certainly impacts the estimation. We make use of the proposed model to obtain an improved estimate for the Value at Risk. The model is then applied and illustrated to transactions data from Bayer AG, a blue chip stock from the German stock market index DAX.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2011-022.
Length: 34 pages
Date of creation: May 2011
Date of revision:
Extreme value theory; autoregressive conditional duration; value at risk; self-exciting; point process; conditional intensity;
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
- C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
- F30 - International Economics - - International Finance - - - General
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.:
- Alfonso Dufour & Robert F Engle, 2000. "The ACD Model: Predictability of the Time Between Concecutive Trades," ICMA Centre Discussion Papers in Finance, Henley Business School, Reading University icma-dp2000-05, Henley Business School, Reading University.
- Meitz, Mika & Terasvirta, Timo, 2006.
"Evaluating Models of Autoregressive Conditional Duration,"
Journal of Business & Economic Statistics, American Statistical Association,
American Statistical Association, vol. 24, pages 104-124, January.
- Meitz, Mika & Teräsvirta, Timo, 2004. "Evaluating models of autoregressive conditional duration," Working Paper Series in Economics and Finance, Stockholm School of Economics 557, Stockholm School of Economics, revised 13 Dec 2004.
- Luc BAUWENS & Pierre GIOT, 2000.
"The Logarithmic ACD Model: An Application to the Bid-Ask Quote Process of Three NYSE Stocks,"
Annales d'Economie et de Statistique,
ENSAE, issue 60, pages 117-149.
- BAUWENS, Luc & GIOT, Pierre, . "The logarithmic ACD model: an application to the bid-ask quote process of three NYSE stocks," CORE Discussion Papers RP, UniversitÃ© catholique de Louvain, Center for Operations Research and Econometrics (CORE) -1497, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- Joachim Grammig & Kai-Oliver Maurer, 2000. "Non-monotonic hazard functions and the autoregressive conditional duration model," Econometrics Journal, Royal Economic Society, Royal Economic Society, vol. 3(1), pages 16-38.
- Robert F. Engle & Jeffrey R. Russell, 1998. "Autoregressive Conditional Duration: A New Model for Irregularly Spaced Transaction Data," Econometrica, Econometric Society, Econometric Society, vol. 66(5), pages 1127-1162, September.
- Paul Embrechts, 2009. "Linear Correlation and EVT: Properties and Caveats," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 7(1), pages 30-39, Winter.
- Jon DANIELSSON & Casper G. DE VRIES, 2000.
"Value-at-Risk and Extreme Returns,"
Annales d'Economie et de Statistique,
ENSAE, issue 60, pages 239-270.
- Jón Daníelsson & Casper G. de Vries, 1998. "Value-at-Risk and Extreme Returns," Tinbergen Institute Discussion Papers, Tinbergen Institute 98-017/2, Tinbergen Institute.
- BAUWENS, Luc & HAUTSCH, Nikolaus, .
"Stochastic conditional intensity processes,"
CORE Discussion Papers RP, UniversitÃ© catholique de Louvain, Center for Operations Research and Econometrics (CORE)
-1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
- John Cotter & Kevin Dowd, 2011.
"Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements,"
- Cotter, John & Dowd, Kevin, 2006. "Extreme spectral risk measures: An application to futures clearinghouse margin requirements," Journal of Banking & Finance, Elsevier, Elsevier, vol. 30(12), pages 3469-3485, December.
- Cotter, JOhn & Dowd, Kevin, 2006. "Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements," MPRA Paper 3505, University Library of Munich, Germany.
- John Cotter & Kevin Dowd, 2011. "Extreme Spectral Risk Measures: An Application to Futures Clearinghouse Margin Requirements," Working Papers, Geary Institute, University College Dublin 200516, Geary Institute, University College Dublin.
- Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, Econometric Society, vol. 59(2), pages 347-70, March.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (RDC-Team).
If references are entirely missing, you can add them using this form.