E-Mail: ortega@est-econ.uc3m.es
Phone: +34 91 6249851
Fax: +34 91 6249849
Office: 10.1.19
Full Professor of Econometrics
Department of Statistics
Universidad Carlos III de Madrid
Research areas: time series and financial econometrics, including stochastic volatility models, unobserved component models, bootstrap procedures for prediction intervals.
Ph.D., London School of Economics, 1992. Thesis: "Heterocedasticity in financial time series". Supervisor: Professor Andrew C. HARVEY.
M.Sc., London School of Economics, 1988, Statistics.
B.A., Universidad del País Vasco, 1984, Economics and Business.
Full Professor of Econometrics, Statistics Department, Universidad Carlos III de Madrid, 2008-present
Associate Professor of Econometrics, Statistics Department, Universidad Carlos III de Madrid, 1994-2008.
Visiting Professor of Econometrics, Statistics Department, Universidad Carlos III de Madrid, 1992-1994.
Lecturer, Statistics Department, London School of Economics, 1991-1992.
Lecturer, Statistics Department, Universidad del País Vasco, 1985-1987.
40. Determining the number of factors after stationary univariate transformations, with F. Corona, P. Poncela and E. Ruiz, Universidad Carlos III de Madrid, Departamento de Estadística, WP 16-02 (Statistics and Econometrics)
39. Robust bootstrap forecast densities for GARCH models: returns, volatilies and value-at-risk, with C. Trucíos and L.K. Hotta, Universidad Carlos III de Madrid, Departamento de Estadística, WP 15-23 (Statistics and Econometrics)
38. Tradeoff between feasibility and flexibility in multivariate GARCH models, with D. de Almeida and L.K. Hotta, Universidad Carlos III de Madrid, Departamento de Estadística, WP 15-16 (Statistics and Econometrics)
37. Model uncertainty and the forecast accuracy of ARMA models: A survey, with Goncalves Mazzeu, J.H., and H. Veiga, Universidad Carlos III de Madrid, Departamento de Estadística, WP 15-08 (Statistics and Econometrics)
36. Identification of asymmetric conditional heteroscedasticity in the presence of outliers, in press, joint with A. Perez and M.A. Carnero, SERIEs
35. Frontiers in VaR forecasting and backtesting, 2016, joint with M.R. Nieto, International Journal of Forecasting, 32, 475-501
34. The uncertainty of conditional returns, volatilities and correlations in DCC models, in press, joint with D. Fresoli, Computational Statistics & Data Analysis.
33. Bootstrap multi-step forecasts of non-Gaussian VAR models,2015, joint with D. Fresoli and L. Pascual, International Journal of Forecasting, 31(3), 834-848.
32. Comparing univariate and multivariate models to forecast portfolio Value-at-Risk, 2013, joint with Santos, A.A.P. and F.J. Nogales, Journal of Financial Econometrics, 11(2), 400-441.
31. Optimal portfolios with minimum capital requirements, 2012, joint with Santos. A.A.P., F.J. Nogales and D. van Dijk, Journal of Banking and Finance, 36(7), 1928- 1942.
30. GARCH models with leverage effect: differences and similarities, 2012, joint with Rodríguez, M.J., Journal of Financial Econometrics, 10(4), 637-668.
29. Estimating and forecasting GARCH volatility in the presence of outliers, 2012, joint with Carnero, M.A. and D. Peña, Economics Letters, 114, 86-90
28. Bootstrap prediction mean squared errors of unobserved states based on the Kalman filter with estimated parameters, 2012, joint with Rodríguez, A., Computational Statistics & Data Analysis, 56, 62-74
27. Maximally autocorrelated power transformations: a closer look at the properties of stochastic volatility models, 2012, joint with Pérez, A., Studies in Nonlinear Dynamics & Econometrics, 16.2
26. Prediction intervals in conditionally heteroscedastic time series with stochastic components, 2011, joint with Pellegrini, S. and A. Espasa, International Journal of Forecasting, 27, 308-319.
25. Conditionally heterocedastic unobserved component models and their reduced form, 2010, with Pellegrini, S. and A. Espasa, Economics Letters, 107(2), 88-90.
24. A note on the properties of power-transformed returns in long-memory stochastic volatility models with leverage effect, 2009, with Pérez, A. and Veiga, H., Computational Statistics & Data Analysis
23. Testing for condicional heterocedasticity in the components of inflation, 2009, with C. Broto, Studies in Nonlinear Dynamics & Econometrics, 13.2
22. Bootstrap Prediction Intervals in State Space Models, 2009, with A. Rodríguez, Journal of Time Series Analysis, 30(2), 167-178.
21. Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH, 2008, with H. Veiga, Computational Statistics & Data Analysis, 52(6), 2846-2862.
20. Effects of outliers on the identification and estimation of GARCH models, 2006, with M.A. Carnero and D. Peña, Journal of Time Series Analysis, 28(4), 471-497.
19. Bootstrap prediction for returns and volatilities in GARCH models, 2006, with L.Pascual and J. Romo, Computational Statistics & Data Analysis, 50(9), 2293-2312.
18. Unobserved component models with asymmetric conditional variances, 2006, with C. Broto, Computational Statistics & Data Analysis, 50(9), 2146-2166.
17. A powerful test for conditional heteroscedasticity for financial time series with highly persistent volatilities, 2005, with J. Rodríguez, J., Statistica Sinica, 15, 505- 526.
16. Bootstrap prediction intervals for power-transformed time series, 2004, with L. Pascual and J. Romo, International Journal of Forecasting, 21, 219-23.
15. Estimation methods for Stochastic Volatility models: A survey, 2004, with C. Broto, Journal of Economic Surveys, 18, 613-649
14. Bootstrap predictive inference for ARIMA processes, 2004, with L. Pascual, L. and J. Romo, Journal of Time Series Analysis, 25, 449-465
13. Persistence and kurtosis in GARCH and Stochastic Volatility Models, 2004, with M.A. Carnero and D. Peña, Journal of Financial Econometrics, 2, 319-342
12. Properties of the sample autocorrelations of non-linear transformations in long memory stochastic volatility models, 2003, with A. Pérez, A., Journal of Financial Econometrics, 1(3), 420-444
11. Asymmetric long memory GARCH: A reply to Hwang’s model, 2003, with A. Pérez, Economics Letters, 78(3), 415-422
10. Relaciones dinámicas en el mercado internacional de carne de vacuno, 2002, with N. Hernández and C. Pañeda, Revista de Economía Aplicada, 10(29), 137-149
9. Modelos de memoria larga para series temporales económicas y financieras, 2002, with A. Pérez, Investigaciones Económicas, 26(3), 359-410
8. Bootstraping financial time series, 2002, with L. Pascual, Journal of Economic Surveys, 16, 271-300
Reprinted in Contributions to Financial Econometrics: Theoretical and Practical Issues, 2002, M. McAleer and L. Oxley (eds.), Blackwel
7. Outliers and Conditional Autoregressive Heteroscedasticity in time series, 2001, with M.A. Carnero and D. Peña, Estadística, 53, 143-213.
6. Finite sample properties of a QML estimator of Stochastic Volatility models with long memory, 2001, with A. Pérez, Economics Letters, 70(2), 157-164
5. Effects of parameter estimation on prediction densities: A bootstrap approach, 2001, with L. Pascual, L. and J. Romo, International Journal of Forecasting, 17(1), 83-103
4. Stock Market Regulations and Internacional Financial Integration: the case of Spain, 1995, with J.I. Peña, European Journal of Finance, 1, 367-382
3. Quasi-Maximum Likelihood Estimation of Stochastic Variance Models, 1994, Journal of Econometrics, 63, 289-306
Reprinted in Recent developments in Time Series, 2003, P. Newbold and S.J. Leyburne (eds.), Edgard Elgar.
2. Multivariate Stochastic Variance Models, 1994, with A.C. Harvey and N.G. Shephard, Review of Economic Studies, 61, 247-264.
Reprinted in ARCH: Selected readings, 1995, R.F. Engle (ed.), Oxford University Press. Reprinted in Recent developments in Time Series, 2003, P. Newbold and S.J. Leyburne (eds.), Edgard Elgar. Reprinted in Selected Readings for Stochastic Volatility, 2005, N.G. Shephard (ed.), Oxford University Press.
1. Unobserved Component Time Series Models with ARCH Disturbances, 1992, with A.C. Harvey and E. Sentana, Journal of Econometrics, 52(1/2), 129-158
3. Small versus big-data factor extraction in dynamic factor models: An empirical assesment, 2015, with P. Poncela, in Hillebrand, E. and S.J. Koopman (eds.), Advance Econometrics, Vol. 35, Dynamci Factor Models, Emerald Publishing Group.
2. More is not always better: Kalman filtering in Dynamic Factor Models, 2015, with P. Poncela, in Koopman, S.J. and N.G. Shephard (eds.), Unobserved Components and Time Series Econometrics, Oxford University Press.
1. An overview of probabilistic and time series models in finance, 2005, with A. Balbás and M.R. Romera, in Baeza-Yates, R., J. Glaz, H. Gzil, J. Hüsler and J.L. Palacios (eds.), Recent Advances in Applied Probability, Springer.
15. Can we evaluate the predictability of financial markets?, 2012, with Nuno Crato, International Journal of Forecasting, doi 10.1016/j.ijforecast.2011.02.002
14. Estimando relaciones entre variables económicas (utilizando integrales, límites, inversión de matrices, maximización numérica y derivadas), 2011, Matematicalia, 7(1)
13. Entrevista con Profesor Andrew Harvey, 2011, BIAM, 200
12. El efecto de la crisis sobre la volatilidad y el riesgo del IBEX35, 2010, with M.R. Nieto, BIAM, 186, 79-87
11. Modelos de volatilidad estocástica: Una alternativa atractiva y factible para modelizar la evolución de la volatilidad, 2008, with H. Veiga, Anales de Valladolid, 18, 1- 59.
10. Interview with Prof. Rob Engle, 2007, BIAM, 159, 64-66
9. Comments on “Band-limited stochastic processes in discrete and continuous time” by D.S.G. Pollock, 2007, Proceedings of the 56th Session of the ISI. The Bulletin of the International Statistical Institute.
8. Introduction to nonlinearities, business cycles, and forecasting, 2005, with A. García- Ferrer, A., J.G. De Gooijer and P. Poncela, International Journal of Forecasting, 21, 623- 808
7. Robert Engle y Clive Granger. Métodos modernos de análisis de series temporales, 2004, with A. Espasa, Economistas, no. 100 extra, 382-384
6. QML and GMM estimators of stochastic volatility models: Response to Andersen and Sorensen, 1997, Journal of Econometrics, 76, 405
5. STAMP 5.0: Un programa para el análisis de series temporales, 1997, Revista de Economía Aplicada, 5, 175-193
4. Comment on “Bayesian Analysis of Stochastic Volatility models”, by E. Jacquier, N.G. Polson y E. Rossi, 1994, with A.C. Harvey, Journal of Business and Economic Statistics, 12(4), 402-403.
3. Modelos para series temporales heterocedásticas, 1994, Cuadernos Económicos del ICE, 56, 73-108
2. Comments on “Métodos Cuantitativos para el Análisis de la Coyuntura Económica”, by A. Espasa and J.R. Cancelo, 1993, Estadística Española, 35(133), 467-469
1. Comments on “Guía para la estimación de modelos ARCH”, by A. Novales and M. Gracia-Díez, 1993, Estadística Española, 35(132), 68-73
5. Score driven asymmetric stochastic volatility, with X. Mao and M.H. Veiga, Universidad Carlos III de Madrid, WP 14-26 (Statistics and Econometrics)
4. One for all: Nesting asymmetric stochastic volatility models, with Mao, X. and H. Veiga, Universidad Carlos III de Madrid, WP 13-11
3. Comparing sample and plug-in moments in asymmetric GARCH models, with Rodríguez, M.J., Universidad Carlos III de Madrid, WP 10-41
2. Modelling intra-daily volatility by functional data analysis: an empirical application to the Spanish stock market, 2009, with Alva, P.K. and J. Romo, Universidad Carlos III de Madrid, WP 09-28
1. Detecting level shifts in the presence of conditional heteroscedasticity, 2003, with M.A. Carnero and D. Peña, Universidad Carlos III de Madrid, WP 03-63(13).
5. Javier de Vicente (joint with Irene Albarrán)
4. Francisco CORONA (joint with Pilar Poncela)
3.Carlos TRUCIOS (joint with Luiz Hotta), Universidad de Campinas (Brazil)
2. Joao Henrique GONZALVES (joint with helena Veiga), Forecasting under model uncertainty, Dpto. De Estadística, Universidad Carlos III de Madrid
1. Daniel ALMEIDA (joint with Luiz Hotta), Further topics in Multivariate GARCH models, Dpto. de Estadística, Universidad Carlos III de Madrid
13. Julieta FUENTES, 2015, ESSAYS on forecasting with partial least sqaures methods, joint with Pilar Poncela and Julio Rodríguez, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
12. Xiuping MAO, 2015, Asymmetric stochastic volatility models, joint with Helena Veiga, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
11. Diego FRESOLI, 2014, Bootstrap forecasts of multivariate time series, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
10. María José RODRÍGUEZ, 2011, Volatility models with leverage effects, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
9. María Rosa NIETO, 2010, Estimación de riesgo financiero, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
8. Andre SANTOS, 2010, joint with Javier Nogales, Multivariate volatility models in financial risk management and portfolio selection, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
7. Alejandro RODRÏGUEZ, 2010, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
6. Santiago PELLEGRINI, 2009, joint with A. Espasa, Predicción en modelos de componentes inobservados con heterocedasticidad condicional, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
5. Carmen BROTO, 2004, Estimación de modelos de volatilidad estocástica y modelos de componentes inobservados condicionalmente heterocedásticos, Dpto. de Estadística, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
4. Ángeles CARNERO, 2003, joint with D. Peña, Heterocedasticidad condicional, atípicos y cambios de nivel en series temporales financieras, Dpto. de Estadística y Econometría, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad.
3. Lorenzo PASCUAL, 2001, joint with J. Romo, Predicción bootstrap en series temporales, Dpto. de Estadística y Econometría, Universidad Carlos III de Madrid, Sobresaliente CUM LAUDE por unanimidad. Premio extraordinario del doctorado en Ingeniería Matemática.
2. Ana PÉREZ, 2000, Estimación e identificación de modelos de volatilidad estocástica con memoria larga, Dpto. de Economía Aplicada (Estadística y Econometría), Universidad de Valladolid, Sobresaliente CUM LAUDE por unanimidad. Premio extraordinario del doctorado en Ciencias Empresariales.
1. Nuria HERNÁNDEZ NANCLARES, 1999, joint with C. Pañeda, Los efectos internacionales de la política agraria común en el sector de la carne del vacuno, Dpto. de Economía Aplicada, Universidad de Oviedo, Sobresaliente CUM LAUDE por unanimidad. Premio extraordinario del doctorado en Economía.