Value at risk, outliers and chaotic dynamics

WIT Transactions on Information and Communication Technologies

Volumn 41, Issue , 2008, Pages 197-205

  Kyrtsou, C ^a   Terraza, V ^b  

^a UNIVERSITY OF MACEDONIA   (Greece)

^b UNIVERSITY OF LUXEMBOURG   (Luxembourg)

Author keywords

GARCH model; Mackey Glass GARCH model; Outliers; Value at risk

Indexed keywords

DYNAMICS; FINANCE; FREQUENCY HOPPING; GLASS; RISK ASSESSMENT; VALUE ENGINEERING;

BEST MODELS; CHAOTIC DYNAMICS; EMPIRICAL STUDIES; EXTREME EVENTS; FINANCIAL RETURNS; GARCH MODEL; MACKEY-GLASS GARCH MODEL; NON LINEARITIES; NON-LINEAR MODELS; OUTLIERS; PERFORMANCE TESTS; STOCK RETURNS; STYLIZED FACTS; VALUE AT RISK; VOLATILITY CLUSTERING;

RISK PERCEPTION;

EID: 58849120914     PISSN: 17433517     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2495/CF080191     Document Type: Conference Paper

References (26)

1. Alexander C.O, Leigh C.T., (1997): On the covariance matrices used in value at risk models, Journal of Derivatives pp. 50-62 spring 1997
2. Dijk DJC Van, Franses PH HBF, Lucas A., (1999): testing for smooth transition non linearity in the presence of outliers, Journal of Business and Economic Statistics 17(2), pp. 217-235.
3. Engle R.F., (1982): Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation, Econometrica, vol. 50, no. 4, pp. 987-1007.
4. Franses PH HBF, Ghijsels H., (1999): Additive outliers, GARCH and forecasting volatility, International Journal of Forecasting, 15 pp. 1-9.
5. Hinich M.J., (1982): Testing for Gaussianity and linearity of a stationary time series, Journal of Time Series Analysis, vol. 3, no. 1, pp. 169-176.
6. Hinich, M. Patterson, D.M., (1995): Detecting epochs of transient dependence in white noise, Working Paper, University of Texas at Austin.
7. Jorion P (1997): Value at risk: The new benchmark for controlling market risk, McGraw - Hill.
8. JP Morgan (1996): Riskmetrics: technical document.
9. Kyrtsou C., (2008): On the role of complexity in economic time series: New evidence for the crude oil and Gasoline price series relationship, accepted under revisions, Energy Economics.
10. Kyrtsou C., Labys W., (2006): Evidence for chaotic dependence between US inflation and commodity prices, Journal of Macroeconomics, 28(1), pp. 256-266.
11. Kyrtsou C., Labys W., (2007): Detecting positive feedback in multivariate time series: the case of metal prices and US inflation, Physica A, 377(1), pp. 227-229.
12. Kyrtsou C., Serletis A., (2006). Univariate tests for nonlinear structure, Journal of Macroeconomics, vol. 28, 1, 154-168
13. Kyrtsou C., Labys W., Terraza M., (2004): Noisy chaotic dynamics in commodity markets, Empirical Economics, 29 (3), pp. 489-502.
14. Kyrtsou C., Malliaris A., (2008): The impact of information signals on market prices, when agents have non-linear trading rules, Economic Modelling, accepted subject to revisions.
15. Kyrtsou C., Terraza M., (2002): Stochastic chaos or ARCH effects in stock series? A comparative study, International Review of Financial Analysis, vol. 11, no. 4, pp. 407-431.
16. Kyrtsou C., Terraza M., (2003): It is possible to study chaotic and ARCH behaviour jointly? Application of a noisy Mackey-Glass equation in the Paris Stock Exchange returns series, Computational Economics, 21, pp. 257-276.
17. Kyrtsou C., Terraza V., (2003): Evidence for mixed non-linearity in daily stock exchange series, Political Economy, 13, pp. 71-97.
18. Lopez J.A (1998): Methods for evaluating value at risk estimates, Working Paper, Federal reserve bank of New York #9802.
19. Mackey M, Glass L., (1977): Oscillation and chaos in physiological control systems, Science, 50, pp. 287-289
20. Mcleod, A.I., Li, W.K., (1983): Diagnostic checking ARMA time series models using squared-residuals autocorrelations, Journal of Time Series Analysis, 4, pp. 269-273.
21. Pafka S, Kondor I (2001): Evaluating the riskmetrics methodology in measuring volatility and value at risk in financial markets, Working Paper, March 2001.
22. Terraza V., (2002): Modélisations de la Value at Risk du CAC 40. Un essai d'amélioration de l'approche RISKMETRICS par la modélisation hétéroscédastique saisonnière. Actes de Collogue Journée d'économétrie de Paris X Nanterre, April 2002.
23. Terraza V., (2002): Modélisations de la Value at Risk, une évaluation de l'approche Riskmetrics, Thèse de Doctoral, université Paris 2.
24. Theiler J., Eubank S., Longtin A., Galdrikian B., Farmer D., (1992): Testing for nonlinearity in time series: the method of surrogate data, Physica D, 58, pp. 77-94
25. Tsay R.S., (1986): Nonlinearity tests for time series, Biometrica, 73, pp. 461-466.
26. White, H., (1989): Some asymptotic results for learning in single hidden layer feedforward networks models, Journal of the American Statistical Association, Vol. 84, pp. 1003-1013.