Information-theoretic optimality of observation-driven time series models for continuous responses

Citations

Cited by:

1. Enzo D'Innocenzo & André Lucas & Anne Opschoor & Xingmin Zhang, 2024. "Heterogeneity and dynamics in network models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 150-173, January.
2. Mariana Arozo B. de Melo & Cristiano A. C. Fernandes & Eduardo F. L. de Melo, 2018. "Forecasting aggregate claims using score‐driven time series models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 354-374, August.
3. Lucas, André & Schwaab, Bernd & Zhang, Xin & D’Innocenzo, Enzo, 2026. "Joint extreme value-at-risk and expected shortfall dynamics with a single integrated tail shape parameter," Working Paper Series 3166, European Central Bank.
4. Gorgi, Paolo & Koopman, Siem Jan & Li, Mengheng, 2019. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1735-1747.
   • Paolo Gorgi & Siem Jan (S.J.) Koopman & Mengheng Li, 2018. "Forecasting economic time series using score-driven dynamic models with mixed-data sampling," Tinbergen Institute Discussion Papers 18-026/III, Tinbergen Institute.
5. Nguyen, Hoang & Ausín Olivera, María Concepción & Galeano San Miguel, Pedro, 2017. "Parallel Bayesian Inference for High Dimensional Dynamic Factor Copulas," DES - Working Papers. Statistics and Econometrics. WS 24552, Universidad Carlos III de Madrid. Departamento de Estadística.
6. Blasques, Francisco & Ji, Jiangyu & Lucas, André, 2016. "Semiparametric score driven volatility models," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 58-69.
7. Anne Opschoor & André Lucas, 2019. "Time-varying tail behavior for realized kernels," Tinbergen Institute Discussion Papers 19-051/IV, Tinbergen Institute.
8. Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2025. "Dynamic Mixture Vector Autoregressions With Score‐Driven Weights," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 40(4), pages 455-470, June.
   • Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Research Papers in Economics 2022-02, University of Trier, Department of Economics.
   • Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2022. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," Working Paper Series 2022-02, University of Trier, Research Group Quantitative Finance and Risk Analysis.
   • Alexander Georges Gretener & Matthias Neuenkirch & Dennis Umlandt, 2023. "Dynamic Mixture Vector Autoregressions with Score-Driven Weights," CESifo Working Paper Series 10366, CESifo.
9. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Expected Kullback-Leibler-based characterizations of score-driven updates," Papers 2408.02391, arXiv.org, revised Mar 2026.
10. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    • Aknouche, Abdelhakim & Francq, Christian, 2019. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," MPRA Paper 97382, University Library of Munich, Germany.
    • Abdelhakim Aknouche & Christian Francq, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Post-Print hal-05417229, HAL.
11. Roman Frydman & Søren Johansen & Anders Rahbek & Morten Nyboe Tabor, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations of Market Forecasts, and Sentiment," CREATES Research Papers 2017-23, Department of Economics and Business Economics, Aarhus University.
    • Roman Frydman & Soeren Johansen & Anders Rahbek & Morten Nyboe, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations Of Market Forecasts, And Sentiment," Discussion Papers 17-10, University of Copenhagen. Department of Economics.
    • Roman Frydman & Soren Johansen & Anders Rahbek & Morten Tabor, 2017. "The Qualitative Expectations Hypothesis: Model Ambiguity, Consistent Representations of Market Forecasts, and Sentiment," Working Papers Series 59, Institute for New Economic Thinking.
12. Zheng, Tingguo & Ye, Shiqi & Hong, Yongmiao, 2023. "Fast estimation of a large TVP-VAR model with score-driven volatilities," Journal of Economic Dynamics and Control, Elsevier, vol. 157(C).
13. Song, Shijia & Li, Handong, 2022. "Predicting VaR for China's stock market: A score-driven model based on normal inverse Gaussian distribution," International Review of Financial Analysis, Elsevier, vol. 82(C).
14. Opschoor, Anne & Lucas, André, 2021. "Observation-driven models for realized variances and overnight returns applied to Value-at-Risk and Expected Shortfall forecasting," International Journal of Forecasting, Elsevier, vol. 37(2), pages 622-633.
15. Blazsek, Szabolcs & Escribano, Alvaro, 2023. "Score-driven threshold ice-age models: Benchmark models for long-run climate forecasts," Energy Economics, Elsevier, vol. 118(C).
    • Blazsek, Szabolcs & Escribano, Álvaro, 2022. "Score-driven threshold ice-age models: benchmark models for long-run climate forecasts," UC3M Working papers. Economics 34757, Universidad Carlos III de Madrid. Departamento de Economía.
16. Andre Lucas & Anne Opschoor, 2016. "Fractional Integration and Fat Tails for Realized Covariance Kernels and Returns," Tinbergen Institute Discussion Papers 16-069/IV, Tinbergen Institute, revised 07 Jul 2017.
17. Blasques, F. & Francq, Christian & Laurent, Sébastien, 2024. "Autoregressive conditional betas," Journal of Econometrics, Elsevier, vol. 238(2).
    • F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-05417169, HAL.
    • F. Blasques & Christian Francq & Sébastien Laurent, 2024. "Autoregressive conditional betas," Post-Print hal-04676069, HAL.
18. Drew Creal & Siem Jan Koopman & André Lucas & Marcin Zamojski, 2015. "Generalized Autoregressive Method of Moments," Tinbergen Institute Discussion Papers 15-138/III, Tinbergen Institute, revised 06 Jul 2018.
19. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
20. Caballero, Diego & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2020. "Risk endogeneity at the lender/investor-of-last-resort," Journal of Monetary Economics, Elsevier, vol. 116(C), pages 283-297.
    • Diego Caballero & André Lucas & Bernd Schwaab & Xin Zhang, 2019. "Risk endogeneity at the lender/investor-of-last-resort," BIS Working Papers 766, Bank for International Settlements.
    • Caballero, Diego & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2019. "Risk endogeneity at the lender/investor-of-last-resort," Working Paper Series 2225, European Central Bank.
    • Caballero, Diego & Lucas, Andr e & Schwaab, Bernd & Zhang, Xin, 2019. "Risk endogeneity at the lender/investor-of-last-resort," Working Paper Series 382, Sveriges Riksbank (Central Bank of Sweden).
21. Eric A. Beutner & Yicong Lin & Andre Lucas, 2023. "Consistency, distributional convergence, and optimality of score-driven filters," Tinbergen Institute Discussion Papers 23-051/III, Tinbergen Institute.
22. Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2022. "Implicit score-driven filters for time-varying parameter models," Tinbergen Institute Discussion Papers 22-066/III, Tinbergen Institute, revised 21 Nov 2024.
    • Rutger-Jan Lange & Bram van Os & Dick van Dijk, 2025. "Implicit score-driven filters for time-varying parameter models," Papers 2512.02744, arXiv.org, revised Dec 2025.
23. Giuseppe Buccheri & Stefano Grassi & Giorgio Vocalelli, 2021. "Estimating Risk in Illiquid Markets: a Model of Market Friction with Stochastic Volatility," CEIS Research Paper 506, Tor Vergata University, CEIS, revised 08 Nov 2021.
24. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
25. Nguyen, Hoang & Javed, Farrukh, 2023. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 272-292.
    • Nguyen, Hoang & Javed, Farrukh, 2021. "Dynamic relationship between Stock and Bond returns: A GAS MIDAS copula approach," Working Papers 2021:15, Örebro University, School of Business.
26. Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2016. "Spillover dynamics for systemic risk measurement using spatial financial time series models," Journal of Econometrics, Elsevier, vol. 195(2), pages 211-223.
    • Blasques, Francisco & Koopman, Siem Jan & Lucas, Andre & Schaumburg, Julia, 2014. "Spillover dynamics for systemic risk measurement using spatial financial time series models," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100632, Verein für Socialpolitik / German Economic Association.
    • Francisco Blasques & Siem Jan Koopman & Andre Lucas & Julia Schaumburg, 2014. "Spillover Dynamics for Systemic Risk Measurement using Spatial Financial Time Series Models," Tinbergen Institute Discussion Papers 14-107/III, Tinbergen Institute.
27. Giuseppe Buccheri & Giacomo Bormetti & Fulvio Corsi & Fabrizio Lillo, 2018. "A Score-Driven Conditional Correlation Model for Noisy and Asynchronous Data: an Application to High-Frequency Covariance Dynamics," Papers 1803.04894, arXiv.org, revised Mar 2019.
28. Bram van Os, 2023. "Information-Theoretic Time-Varying Density Modeling," Tinbergen Institute Discussion Papers 23-037/III, Tinbergen Institute.
29. Tobias Eckernkemper & Bastian Gribisch, 2021. "Intraday conditional value at risk: A periodic mixed‐frequency generalized autoregressive score approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 883-910, August.
30. Michel Ferreira Cardia Haddad & Szabolcs Blazsek & Philip Arestis & Franz Fuerst & Hsia Hua Sheng, 2023. "The two-component Beta-t-QVAR-M-lev: a new forecasting model," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(4), pages 379-401, December.
31. Daan Schoemaker & André Lucas & Anne Opschoor, 2025. "Conditional Fat Tails and Scale Dynamics for Intraday Discrete Price Changes," Tinbergen Institute Discussion Papers 25-039/III, Tinbergen Institute.
32. Rui Zhang & Xiaogang Dong, 2025. "Statistical inference for the binomial autoregressive model with time-varying parameters," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 88(6), pages 1395-1423, August.
33. Lucas, André & Zhang, Xin, 2016. "Score-driven exponentially weighted moving averages and Value-at-Risk forecasting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 293-302.
    • André Lucas & Xin Zhang, 2014. "Score Driven exponentially Weighted Moving Average and Value-at-Risk Forecasting," Tinbergen Institute Discussion Papers 14-092/IV/DSF77, Tinbergen Institute, revised 09 Sep 2015.
    • Lucas, André & Zhang, Xin, 2015. "Score Driven Exponentially Weighted Moving Averages and Value-at-Risk Forecasting," Working Paper Series 309, Sveriges Riksbank (Central Bank of Sweden).
34. Francisco (F.) Blasques & Andre (A.) Lucas & Andries van Vlodrop, 2017. "Finite Sample Optimality of Score-Driven Volatility Models," Tinbergen Institute Discussion Papers 17-111/III, Tinbergen Institute.
35. Song, Shijia & Tian, Fei & Li, Handong, 2021. "An intraday-return-based Value-at-Risk model driven by dynamic conditional score with censored generalized Pareto distribution," Journal of Asian Economics, Elsevier, vol. 74(C).
36. Domenico Di Gangi & Giacomo Bormetti & Fabrizio Lillo, 2022. "Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks," Papers 2202.09854, arXiv.org, revised Mar 2022.
37. Neves, César & Fernandes, Cristiano & Hoeltgebaum, Henrique, 2017. "Five different distributions for the Lee–Carter model of mortality forecasting: A comparison using GAS models," Insurance: Mathematics and Economics, Elsevier, vol. 75(C), pages 48-57.
38. Rui Zhang & Xiaogang Dong, 2026. "Statistical inference for the binomial autoregressive model with time-varying parameters," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 89(1), pages 29-57, January.
39. van Os, Bram & van Dijk, Dick, 2024. "Accelerating peak dating in a dynamic factor Markov-switching model," International Journal of Forecasting, Elsevier, vol. 40(1), pages 313-323.
    • Bram van Os & Dick van Dijk, 2020. "Accelerating Peak Dating in a Dynamic Factor Markov-Switching Model," Tinbergen Institute Discussion Papers 20-057/VI, Tinbergen Institute, revised 14 Dec 2020.
40. Peter Reinhard Hansen & Chen Tong, 2022. "Option Pricing with Time-Varying Volatility Risk Aversion," Papers 2204.06943, arXiv.org, revised Mar 2025.
41. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
42. Virbickaitė, Audronė & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian predictive distributions of oil returns using mixed data sampling volatility models," Resources Policy, Elsevier, vol. 86(PA).
    • Virbickaite, Audrone & Nguyen, Hoang & Tran, Minh-Ngoc, 2023. "Bayesian Predictive Distributions of Oil Returns Using Mixed Data Sampling Volatility Models," Working Papers 2023:7, Örebro University, School of Business.
43. Francisco Blasques & Christian Francq & Sébastien Laurent, 2020. "A New Class of Robust Observation-Driven Models," Tinbergen Institute Discussion Papers 20-073/III, Tinbergen Institute.
44. Blasques, Francisco & van Brummelen, Janneke & Koopman, Siem Jan & Lucas, André, 2022. "Maximum likelihood estimation for score-driven models," Journal of Econometrics, Elsevier, vol. 227(2), pages 325-346.
    • Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Maximum Likelihood Estimation for Score-Driven Models," Tinbergen Institute Discussion Papers 14-029/III, Tinbergen Institute, revised 23 Oct 2017.
45. Buccheri, Giuseppe & Corsi, Fulvio & Flandoli, Franco & Livieri, Giulia, 2021. "The continuous-time limit of score-driven volatility models," Journal of Econometrics, Elsevier, vol. 221(2), pages 655-675.
46. Huaping Chen & Qi Li & Fukang Zhu, 2022. "A new class of integer-valued GARCH models for time series of bounded counts with extra-binomial variation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(2), pages 243-270, June.
47. Rogier Quaedvlieg & Peter Schotman, 2022. "Hedging Long-Term Liabilities [Pricing the Term Structure with Linear Regressions]," Journal of Financial Econometrics, Oxford University Press, vol. 20(3), pages 505-538.
48. Leopoldo Catania & Anna Gloria Billé, 2017. "Dynamic spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(6), pages 1178-1196, September.
    • Leopoldo Catania & Anna Gloria Bill'e, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," Papers 1602.02542, arXiv.org, revised Jan 2023.
    • Leopoldo Catania & Anna Gloria Billé, 2016. "Dynamic Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances," CEIS Research Paper 375, Tor Vergata University, CEIS, revised 31 Mar 2016.
49. Giacomo Bormetti & Fulvio Corsi, 2021. "A Lucas Critique Compliant SVAR model with Observation-driven Time-varying Parameters," Papers 2107.05263, arXiv.org, revised Feb 2022.
50. Creal, Drew & Koopman, Siem Jan & Lucas, André & Zamojski, Marcin, 2024. "Observation-driven filtering of time-varying parameters using moment conditions," Journal of Econometrics, Elsevier, vol. 238(2).
51. Lucas, André & Opschoor, Anne & Schaumburg, Julia, 2016. "Accounting for missing values in score-driven time-varying parameter models," Economics Letters, Elsevier, vol. 148(C), pages 96-98.
    • Andre Lucas & Anne Opschoor & Julia Schaumburg, 2016. "Accounting for Missing Values in Score-Driven Time-Varying Parameter Models," Tinbergen Institute Discussion Papers 16-067/IV, Tinbergen Institute.
52. Ramon de Punder & Timo Dimitriadis & Rutger-Jan Lange, 2024. "Kullback-Leibler-based characterizations of score-driven updates," Tinbergen Institute Discussion Papers 24-051/III, Tinbergen Institute, revised 22 Oct 2024.
53. Xu, Yingying & Lien, Donald, 2022. "COVID-19 and currency dependences: Empirical evidence from BRICS," Finance Research Letters, Elsevier, vol. 45(C).
54. Fuentes, Fernanda & Herrera, Rodrigo & Clements, Adam, 2023. "Forecasting extreme financial risk: A score-driven approach," International Journal of Forecasting, Elsevier, vol. 39(2), pages 720-735.
55. P Gorgi & P R Hansen & P Janus & S J Koopman, 2019. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Journal of Financial Econometrics, Oxford University Press, vol. 17(1), pages 1-32.
    • Peter Reinhard Hansen & Pawel Janus & Siem Jan Koopman, 2016. "Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model," Tinbergen Institute Discussion Papers 16-061/III, Tinbergen Institute.
56. Koopman, Siem Jan & Lit, Rutger, 2019. "Forecasting football match results in national league competitions using score-driven time series models," International Journal of Forecasting, Elsevier, vol. 35(2), pages 797-809.
    • Siem Jan (S.J.) Koopman & Rutger Lit, 2017. "Forecasting Football Match Results in National League Competitions Using Score-Driven Time Series Models," Tinbergen Institute Discussion Papers 17-062/III, Tinbergen Institute.
57. André Lucas & Bernd Schwaab & Xin Zhang, 2017. "Modeling Financial Sector Joint Tail Risk in the Euro Area," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 32(1), pages 171-191, January.
    • Schwaab, Bernd & Lucas, André & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 1837, European Central Bank.
    • Lucas, André & Schwaab, Bernd & Zhang, Xin, 2015. "Modeling financial sector joint tail risk in the euro area," Working Paper Series 308, Sveriges Riksbank (Central Bank of Sweden).
58. Stephen Thiele, 2020. "Modeling the conditional distribution of financial returns with asymmetric tails," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 46-60, January.
59. Siem Jan Koopman & Rutger Lit & André Lucas, 2015. "Intraday Stock Price Dependence using Dynamic Discrete Copula Distributions," Tinbergen Institute Discussion Papers 15-037/III/DSF90, Tinbergen Institute.
60. Francisco Blasques & Noah Stegehuis, 2024. "A Score-Driven Filter for Causal Regression Models with Time- Varying Parameters and Endogenous Regressors," Tinbergen Institute Discussion Papers 24-016/III, Tinbergen Institute.
61. P. Gorgi & Siem Jan (S.J.) Koopman & R. Lit, 2018. "The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model," Tinbergen Institute Discussion Papers 18-009/III, Tinbergen Institute.
62. Anne Opschoor & André Lucas & István Barra & Dick van Dijk, 2021. "Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(4), pages 1066-1079, October.
    • Anne Opschoor & André Lucas & Istvan Barra & Dick van Dijk, 2019. "Closed-Form Multi-Factor Copula Models with Observation-Driven Dynamic Factor Loadings," Tinbergen Institute Discussion Papers 19-013/IV, Tinbergen Institute, revised 23 Oct 2019.
63. Telg, Sean & Dubinova, Anna & Lucas, Andre, 2023. "Covid-19, credit risk management modeling, and government support," Journal of Banking & Finance, Elsevier, vol. 147(C).
64. Vladim'ir Hol'y, 2022. "An Intraday GARCH Model for Discrete Price Changes and Irregularly Spaced Observations," Papers 2211.12376, arXiv.org, revised May 2024.
65. Enzo D’Innocenzo & André Lucas & Bernd Schwaab & Xin Zhang, 2024. "Modeling Extreme Events: Time-Varying Extreme Tail Shape," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 42(3), pages 903-917, July.
    • Bernd Schwaab & Xin Zhang & Andre Lucas, 2020. "Modeling extreme events: time-varying extreme tail shape," Tinbergen Institute Discussion Papers 20-076/III, Tinbergen Institute.
    • Schwaab, Bernd & Zhang, Xin & Lucas, André & D’Innocenzo, Enzo, 2020. "Modeling extreme events:time-varying extreme tail shape," Working Paper Series 399, Sveriges Riksbank (Central Bank of Sweden), revised 01 Jun 2023.
    • Schwaab, Bernd & Zhang, Xin & Lucas, André, 2021. "Modeling extreme events: time-varying extreme tail shape," Working Paper Series 2524, European Central Bank.
66. Anne Opschoor & André Lucas, 2019. "Observation-driven Models for Realized Variances and Overnight Returns," Tinbergen Institute Discussion Papers 19-052/IV, Tinbergen Institute.
67. Yicong Lin & André Lucas, 2025. "Functional Location-Scale Models with Robust Observation-Driven Dynamics," Tinbergen Institute Discussion Papers 25-027/III, Tinbergen Institute.
68. Shijia Song & Handong Li, 2023. "A new model for forecasting VaR and ES using intraday returns aggregation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1039-1054, August.
69. Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2017. "Time-Varying Transition Probabilities for Markov Regime Switching Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(3), pages 458-478, May.
    • Marco Bazzi & Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2014. "Time Varying Transition Probabilities for Markov Regime Switching Models," Tinbergen Institute Discussion Papers 14-072/III, Tinbergen Institute.
70. Carlo Campajola & Domenico Di Gangi & Fabrizio Lillo & Daniele Tantari, 2020. "Modelling time-varying interactions in complex systems: the Score Driven Kinetic Ising Model," Papers 2007.15545, arXiv.org, revised Aug 2021.
71. Blasques, Francisco & Lucas, André & van Vlodrop, Andries C., 2021. "Finite Sample Optimality of Score-Driven Volatility Models: Some Monte Carlo Evidence," Econometrics and Statistics, Elsevier, vol. 19(C), pages 47-57.
72. Francisco (F.) Blasques & Paolo Gorgi & Siem Jan (S.J.) Koopman, 2017. "Accelerating GARCH and Score-Driven Models: Optimality, Estimation and Forecasting," Tinbergen Institute Discussion Papers 17-059/III, Tinbergen Institute.
73. Blazsek, Szabolcs & Escribano, Alvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions using score-driven threshold climate models," Energy Economics, Elsevier, vol. 134(C).
    • Blazsek, Szabolcs & Escribano, Álvaro & Kristof, Erzsebet, 2024. "Global, Arctic, and Antarctic sea ice volume predictions: using score-driven threshold climate models," UC3M Working papers. Economics 39546, Universidad Carlos III de Madrid. Departamento de Economía.
74. Enzo D'Innocenzo & Andre Lucas & Bernd Schwaab & Xin Zhang, 2024. "Joint extreme Value-at-Risk and Expected Shortfall dynamics with a single integrated tail shape parameter," Tinbergen Institute Discussion Papers 24-069/III, Tinbergen Institute.
    • D’Innocenzo, Enzo & Lucas, André & Schwaab, Bernd & Zhang, Xin, 2025. "Joint extreme Value-at-Risk and Expected Shortfall dynamics with a single integrated tail shape parameter," Working Paper Series 446, Sveriges Riksbank (Central Bank of Sweden).
75. Yu‐Sheng Lai, 2021. "Generalized autoregressive score model with high‐frequency data for optimal futures hedging," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(12), pages 2023-2045, December.
76. Yicong Lin & André Lucas & Shiqi Ye, 2025. "Matrix-Valued Spatial Autoregressions with Dynamic and Robust Heterogeneous Spillovers," Tinbergen Institute Discussion Papers 25-042/III, Tinbergen Institute.
77. Ayala Astrid & Blazsek Szabolcs & Escribano Alvaro, 2023. "Anticipating extreme losses using score-driven shape filters," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(4), pages 449-484, September.
78. Blasques, F. & Gorgi, P. & Koopman, S.J., 2019. "Accelerating score-driven time series models," Journal of Econometrics, Elsevier, vol. 212(2), pages 359-376.
79. Mariia Artemova & Francisco Blasques & Siem Jan Koopman & Zhaokun Zhang, 2021. "Forecasting in a changing world: from the great recession to the COVID-19 pandemic," Tinbergen Institute Discussion Papers 21-006/III, Tinbergen Institute.
80. Anna Gloria Billé & Leopoldo Catania, 2018. "Dynamic Spatial Autoregressive Models with Time-varying Spatial Weighting Matrices," BEMPS - Bozen Economics & Management Paper Series BEMPS55, Faculty of Economics and Management at the Free University of Bozen.
81. Ayala, Astrid & Blazsek, Szabolcs & Escribano, Álvaro, 2019. "Maximum likelihood estimation of score-driven models with dynamic shape parameters : an application to Monte Carlo value-at-risk," UC3M Working papers. Economics 28638, Universidad Carlos III de Madrid. Departamento de Economía.
82. Anna Dubinova & Andre Lucas & Sean Telg, 2021. "COVID-19, Credit Risk and Macro Fundamentals," Tinbergen Institute Discussion Papers 21-059/III, Tinbergen Institute.
83. Rutger-Jan Lange & Andre Lucas & Arjen H. Siegmann, 2016. "Score-Driven Systemic Risk Signaling for European Sovereign Bond Yields and CDS Spreads," Tinbergen Institute Discussion Papers 16-064/IV, Tinbergen Institute.
84. Opschoor, Anne & Lucas, André, 2023. "Time-varying variance and skewness in realized volatility measures," International Journal of Forecasting, Elsevier, vol. 39(2), pages 827-840.