Volatility and VaR forecasting in the Madrid Stock Exchange

Spanish Economic Review

Volumn 10, Issue 3, 2008, Pages 169-196

  Ñíguez, Trino Manuel ^a  

^a UNIVERSITY OF WESTMINSTER   (United Kingdom)

Author keywords

FIAPARCH; Heavy tailed distributions; Leverage effect; Long memory; VaR

Indexed keywords

EID: 49649089445     PISSN: 14355469     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10108-007-9030-6     Document Type: Article

References (81)

1. Andersen TG, Bollerslev T (1998) Answering the skeptics: yes, standard volatility models do provide accurate forecasts. Int Econ Rev 39:885-905
2. Arteche J (2004) Gaussian semiparametric estimation in long memory in stochastic volatility and signal plus noise models. J Econom 119:131-154
3. Baillie RT (1996) Long memory processes and fractional integration in econometrics. J Econom 73:5-59
4. Baillie RT, Bollerslev T, Mikkelsen H (1996) Fractionally integrated generalized autoregressive conditional heteroscedasticity. J Econom 74:3-30
5. Bauwens L, Laurent S, Rombouts JVK (2006) Multivariate GARCH models: a survey. J Appl Econom 21:79-109
6. Black F (1976) Studies of stock price volatility changes. In: Proceedings from the American statistical association. Business and economic statistics section, pp 177-181
7. Bollerslev T (1986) Generalized autoregressive conditional heteroscedasticity. J Econom 31:307-327
8. Bollerslev T (1987) A conditional heteroskedastic time series model for speculative prices and rates of return. Rev Econ Stat 69:542-547
9. Bollerslev T, Chou RY, Kroner KF (1992) ARCH modeling in finance. J Econom 52:5-59
10. Bollerslev T, Engle RF (1993) Common persistence in conditional variances. Econometrica 61:167-186
11. Bollerslev T, Mikkelsen H (1996) Modeling and pricing long memory in stock market volatility. J Econom 73:151-184
12. Bollerslev T, Mikkelsen H (1999) Long-term equity anticipation securities and stock market volatility dynamics. J Econom 92:75-99
13. Bollerslev T, Wooldridge JM (1992) Quasi-maximum likelihood estimation and inference in dynamics models with time-varying covariances. Econom Rev 11:143-172
14. Brailsford TJ, Faff RW (1996) An evaluation of volatility forecasting techniques. J Bank Finance 20:419-438
15. Breidt FJ, Crato N, De Lima P (1998) The detection and estimation of long memory in stochastic volatility. J Econom 83:325-348
16. Brooks C, Persand G (2003) The effect of asymmetries on stock index return value-at-risk estimates. J Risk Finance 4:29-42
17. Caporin M (2003) Identification of long memory GARCH models. Stat Methods Appl 12:133-151
18. Chung CF (1999) Estimating the fractionally integrated GARCH model. Manuscript. National Taiwan University, Taiwan
19. Conrad C, Haag BR (2006) Inequality constraints in the fractionally integrated GARCH model. J Financ Econom 4:413-449
20. Danielsson J, Shin H, Zigrand JP (2004) The impact of risk regulation on price dynamics. J Bank Finance 28:1069-1087
21. Davidson J (2004) Moment and memory properties of linear conditional heteroscedasticity models, and a new model. J Bus Econ Stat 22:16-29
22. Diebold FX, Inoue A (1999) Long memory and structural change. Manuscript. New York University, Stern School of Business, Department of Finance
23. Diebold FX, Mariano R (1995) Comparing predictive accuracy. J Bus Econ Stat 13:253-264
24. Diebold FX, Gunther TA, Tay SA (1998) Evaluating density forecasts with applications to financial risk management. Int Econ Rev 39:863-883
25. Ding Z, Granger CWJ (1996) Modeling volatility persistence of speculative returns: a new approach. J Econom 73:185-215
26. Ding Z, Granger CWJ, Engle RF (1993) A long memory property of stock market returns and a new model. J Empir Finance 1:83-106
27. Engle RF (1982) Autoregressive conditional heteroscedasticity with estimates of the variance of UK inflation. Econometrica 50:987-1008
28. Engle RF (2001) Garch 101: the use of ARCH/GARCH models in applied econometrics. J Econ Perspect 15:157-168
29. Engle RF, Bollerslev T (1986) Modeling the persistence of conditional variances. Econom Rev 5:1-50
30. Engle RF, Lilien DM, Robins RP (1987) Estimating time varying risk premia in the term structure: the ARCH-M model. Econometrica 55:391-407
31. Engle RF, Manganelli S (2004) CAViaR: conditional value at risk by regression quantiles. J Bus Econ Stat 22:367-381
32. Ferreira MA, López JA (2005) Evaluating interest rate covariance models within a Value-at-Risk framework. J Financ Econom 3:126-168
33. Fiorentini G, Sentana E, Calzolari G (2003) Maximum likelihood estimation and inference in multivariate conditional heteroskedastic dynamic regression models with Student t innovations. J Bus Econ Stat 21:532-546
34. Giraitis L, Kokoszka P, Leipus R (2000) Stationary ARCH models: dependence structure and central limit theorem. Econom Theory 16:3-22
35. Glosten LR, Jagannathan R, Runkle D (1993) On the relation between the expected value and the volatility of the nominal excess return on stocks. J Finance 48:1779-1801
36. Gradshteyn IS, Ryzhnik IM (1980) Tables of integrals, series and products. Academic, New York
37. Granger CWJ, Ding Z (1996) Varieties of long memory models. J Econom 73:61-77
38. Hansen PR, Lunde A (2005) A forecast comparison of volatility models: does anything beat a GARCH(1,1)?. J Appl Econom 20:873-889
39. Hansen PR, Lunde A (2006) Consistent ranking of volatility models. J Econom 131:97-121
40. Hidalgo J (1997) Non-parametric estimation with strongly dependent multivariate time-series. J Time Ser Anal 18:95-122
41. Higgins M, Bera A (1992) A class of non-linear ARCH models. Int Econ Rev 33:137-158
42. Hosking JRM (1981) Fractional differencing. Biometrika 68:165-176
43. Morgan JP (1996) RiskMetrics-technical document, 4th edn. Morgan Guaranty Trust Company, New York
44. Jorion P (2001) Value at risk: the new benchmark for controlling financial risk. McGraw-Hill, London
45. Jorion P (2002) Fallacies about the effects of market risk management systems. J Risk 5:75-96
46. Koenker R, Bassett G (1978) Regression quantiles. Econometrica 46:33-50
47. Komunjer I (2005) Quasi-maximum likelihood estimation for conditional quantiles. J Econom 128:137-164
48. Lee KY (1991) Are the GARCH models best in out-of-sample performance?. Econ Lett 37:305-308
49. León A, Mora J (1999) Modeling conditional heteroscedasticity: application to the IBEX 35 stock-return index. Span Econ Rev 3:215-238
50. Ling S, McAleer M (2002) Necessary and sufficient moment conditions for the GARCH(r, s) and asymmetric power GARCH(r, s) models. Econom Theory 18:722-729
51. Lobato IN, Robinson PM (1997) A non-parametric test for I(0). Rev Econ Stud 65:475-495
52. Lobato IN, Savin NE (1998) Real and spurious long memory properties of stock market data. J Bus Econ Stat 16:261-268
53. López JA (1999) Methods for evaluating value-at-Risk estimates. Federal Reserve Bank of San Francisco Economic Review, vol 2, pp 3-17
54. López JA, Walter CA (2001) Evaluating covariance matrix forecasts in a value-at-risk framework. J Risk 3:69-98
55. Lucas A (2000) A note on optimal estimation from a risk-management perspective under possibly misspecified tail behavior. J Bus Econ Stat 18:31-39
56. Mandelbrot B (1963) The variation of certain speculative prices. J Bus 36:1279-1313
57. Mármol F, Reboredo JC (2000) Dependencia temporal en la volatilidad estocástica. Una aplicación al índice IBEX 35. Centro de Investigación Económica y Financiera Working Paper no. 4. Fundación Caixa Galicia
58. Mincer J, Zarnowitz V (1969) The evaluation of economic forecasts. In: Mincer J (ed) Economic forecasts and expectations. NBER, New York
59. Morana C, Beltratti A (2004) Structural change and long-range dependence in volatility of exchange rates: either, neither or both? J Empir Finance 11:629-658
60. Muller UA, Dacorogna MM, Davé RD, Olsen RB, Pictet OV, von Weizsacker JE (1997) Volatilites of different times resolutions-analyzing the dynamics of markets components. J Empir Finance 4:213-239
61. Nelson CR (1976) Applied time series analysis. Holden-Day, San Francisco
62. Nelson DB (1991) Conditional heteroskedasticity in asset returns: a new approach. Econometrica 59:347-370
63. Newey W, West K (1987) A simple positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix. Econometrica 55:703-708
64. Newey W, Steigerwald D (1997) Asymptotic bias for quai-maximum-likelihood estimators in conditional heteroskedasticity models. Econometrica 65:587-599
65. Ñíguez TM, Rubia A (2006) Forecasting the conditional covariance matrix of a portfolio under long-run temporal dependence. J Forecast 25:439-458
66. Pagan A (1986) Two stage and related estimators and their applications. Rev Econ Stud 53:517-538
67. Pantula SG (1986) Modeling the persistence of conditional variance: a comment. Econom Rev 5:71-74
68. Perron PY, Ng S (1996) Useful modifications to some unit-root tests with dependent errors and their local asymptotic properties. Rev Econ Stud 63:435-463
69. Poon SH, Granger CWJ (2003) Forecasting volatility in financial markets. J Econ Lit 41:478-539
70. Robinson PM (2003) Time series with long memory. Oxford University Press, Oxford
71. Ryden T, Teräsvirta T, Asbrink S (1998) Stylized facts of daily returns series and the hidden Markov model. J Appl Econom 13:217-244
72. Sentana E (1995) Quadratic ARCH models. Rev Econ Stud 62:639-661
73. Sentana E, Wadhwani S (1992) Feedback traders and stock return autocorrelations: evidence from a century of daily data. Econ J 102:415-425
74. Schwert GW (1989) Why does stock market volatility change over time?. J Finance 44:1115-1153
75. Straumann D, Mikosch T (2006) Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: a stochastic recurrence equations approach. Ann Stat 34:2449-2495
76. Tse YK (1998) The conditional heteroscedasticity of the yen-dollar exchange rate. J Appl Econom 13:49-55
77. Vilasuso J (2002) Forecasting exchange rate volatility. Econ Lett 76:59-64
78. Weiss AA (1986) Asymptotic theory of ARCH models: estimation and testing. Econom Theory 2:107-131
79. White H (1982) Maximum likelihood estimation of misspecified models. Econometrica 50:1-26
80. White H (1994) Estimation, inference and specification analysis. Cambridge University Press, Cambridge
81. Zakoian J (1994) Threshold heteroscedasticity model. J Econ Dyn Control 15:931-955