6,105
Views
46
CrossRef citations to date
0
Altmetric
Articles

New HEAVY Models for Fat-Tailed Realized Covariances and Returns

, , &
Pages 643-657 | Received 01 Aug 2015, Published online: 16 May 2017

References

  • Amisano, G. , and Giacomini, R. (2007), “Comparing Density Forecasts via Weighted Likelihood Ratio Tests,” Journal of Business and Economic Statistics , 25, 177–190.
  • Andres, P. (2014), “Computation of Maximum Likelihood Estimates for Score Driven Models for Positive Valued Observations,” Computational Statistics and Data Analysis , 76, 34–43.
  • Asai, M. , McAleer, M. , and Yu, J. (2006), “Multivariate Stochastic Volatility: A Review,” Econometric Reviews , 25, 145–175.
  • Barndorff-Nielsen, O. , Hansen, P. , Lunde, A. , and Shephard, N. (2009), “Realized Kernels in Practice: Trades and Quotes,” Econometrics Journal , 12, 1–32.
  • Bauer, G. , and Vorkink, K. (2011), “Forecasting Multivariate Realized Stock arketM Volatility,” Journal of Econometrics , 160, 93–101.
  • Bauwens, L. , Laurent, S. , and Rombouts, J. (2006), “Multivariate Garch Models: A Survey,” Journal of Applied Econometrics , 21, 79–109.
  • Blasques, C. , Koopman, S. , and Lucas, A. (2015), “Information Theoretic Optimality of Observation Driven Time Series Models for Continuous Responses,” Biometrika , 102, 325–343.
  • Boussama, F. (2006), “Ergodicité des Chaînes de Markov à Valeurs Dans Une Variété Algébrique: Application aux Modèles GARCH Multivariés,” Comptes Rendus Mathematique, Académie Science Paris, Serie I , 343, 275–278.
  • Brownlees, C. , and Gallo, G. (2006), “Financial Econometric Analysis at Ultra-High Frequency: Data Handling Concerns,” Computational Statistics and Data Analysis , 51, 2232–2245.
  • Cappiello, L. , Engle, R. , and Sheppard, K. (2006), “Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns,” Journal of Financial Econometrics , 4, 537–572.
  • Chiriac, R. , and Voev, V. (2011), “Modelling and Forecasting Multivariate Realized Volatility,” Journal of Applied Econometrics , 26, 922–947.
  • Corsi, F. (2009), “A Simple Approximate Long-Memory Model of Realized Volatility,” Journal of Financial Econometrics , 7, 174–196.
  • Cox, D. (1981), “Statistical Analysis of Time Series: Some Recent Developments,” Scandinavian Journal of Statistics , 8, 93–115.
  • Creal, D. , Koopman, S. , and Lucas, A. (2011), “A Dynamic Multivariate Heavy-Tailed Model for Time-Varying Volatilities and Correlations,” Journal of Business and Economic Statistics , 29, 552–563.
  • ——— (2013), “Generalized Autoregressive Score Models with Applications,” Journal of Applied Econometrics , 28, 777–795.
  • Creal, D. , Schwaab, B. , Koopman, S. , and Lucas, A. (2014), “Observation Driven Mixed-Measurement Dynamic Factor Models with an Application to Credit Risk,” Review of Economics and Statistics , 96, 898–915.
  • Diebold, F. , and Mariano, R. (1995), “Comparing Predictive Accuracy,” Journal of Business and Economic Statistics , 13, 253–263.
  • Engle, R. (2002), “Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroscedasticity Models,” Journal of Business and Economic Statistics , 20, 339–350.
  • Engle, R. , and Gallo, G. (2006), “A Multiple Indicators Model for Volatility using Intra-Daily Data,” Journal of Econometrics , 131, 3–27.
  • Giacomini, R. , and White, H. (2006), “Tests of Conditional Predictive Ability,” Econometrica , 74, 1545–1578.
  • Golosnoy, V. , Gribisch, B. , and Liesenfeld, R. (2012), “The Conditional Autoregressive Wishart Model for Multivariate Stock Market Volatility,” Journal of Econometrics , 167, 211–223.
  • Gourieroux, C. , Jasiak, J. , and Sufana, R. (2009), “The Wishart Autoregressive Process of Multivariate Stochastic Volatility,” Journal of Econometrics , 150, 167–181.
  • Gupta, A. , and Nagar, D. (2000), Matrix Variate Distributions , Boca Raton, FL: Chapman & Hall/CRC.
  • Hansen, P. , Huang, Z. , and Shek, H. (2012), “Realized Garch: A Joint Model for Returns and Realized Measures of Volatility,” Journal of Applied Econometrics , 27, 877–906.
  • Hansen, P. , Janus, P. , and Koopman, S. (2016), “Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model,” TI 2016-061/III, Tinbergen Institute Discussion Paper.
  • Harvey, A. (2013), Dynamic Models for Volatility and Heavy Tails: With Applications to Financial and Economic Time Series , Cambridge: Cambridge University Press.
  • Harvey, A. , and Luati, A. (2014), “Filtering With Heavy Tails,” Journal of the American Statistical Association , 109, 1112–1122.
  • Huang, X. , and Tauchen, G. (2005), “The Relative Contribution of Mumps to Total Price Variance,” Journal of Financial Econometrics , 3, 456–499.
  • Janus, P. , Koopman, S. , and Lucas, A. (2014), “Long Memory Dynamics for Multivariate Dependence Under Heavy Tails,” Journal of Empirical Finance , 29, 187–206.
  • Jin, X. , and Maheu, J. (2013), “Modeling Realized Covariances and Returns,” Journal of Financial Econometrics , 11, 335–369.
  • ——— (2016), “Bayesian Semiparametric Modeling of Realized Covariance Matrices,” Journal of Econometrics , 192, 19–39.
  • Konno, Y. (1991), “A Note on Estimating Eigenvalues of Scale Matrix of the Multivariate F-Distribution,” Annals of the Institute of Statistical Mathematics , 43, 157–165.
  • Lee, S. , and Mykland, P. (2008), “Jumps in Financial Markets: A New Nonparametric Test and Jump Dynamics,” Review of Financial Studies , 21, 2535–2563.
  • Lucas, A. , Schwaab, B. , and Zhang, X. (2014), “Conditional Euro Area Sovereign Default Risk,” Journal of Business and Economic Statistics , 32, 271–284.
  • Markowitz, H. (1952), “Portfolio Selection,” Journal of Finance , 7, 77–91.
  • Mitchell, J. , and Hall, S. (2005), “Evaluating, Comparing and Combining Density Forecasts Using the Klic With an Application to the Bank of England and Niesr Fan-Charts of Inflation,” Oxford Bulletin of Economics and Statistics , 67, 995–1033.
  • Noureldin, D. , Shephard, N. , and Sheppard, K. (2012), “Multivariate High-Frequency-Based Volatility (Heavy) Models,” Journal of Applied Econometrics , 27, 907–933.
  • Oh, D. , and Patton, A. (2016), “Time-Varying Systemic Risk: Evidence from a Dynamic Copula Model of CDS Spreads,” Journal of Business and Economic Statistics .
  • Shephard, N. , and Sheppard, K. (2010), “Realising the Future: Forecasting With High-Frequency-Based Volatility (heavy) Models,” Journal of Applied Econometrics , 25, 197–231.
  • Tan, W. (1969), “Note on the Multivariate and the Generalized Multivariate beta Distributions,” Journal of the American Statistical Association , 64, 230–241.