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Pawel Janus

Personal Details

First Name:Pawel
Middle Name:
Last Name:Janus
Suffix:
RePEc Short-ID:pja250
[This author has chosen not to make the email address public]
Terminal Degree:2011 School of Business and Economics; Vrije Universiteit Amsterdam (from RePEc Genealogy)

Affiliation

(in no particular order)

Afdeling Econometrie and Operations Research (Department of Econometrics and Operations Research)
School of Business and Economics
Vrije Universiteit Amsterdam (VU University Amsterdam)

Amsterdam, Netherlands
https://sbe.vu.nl/nl/afdelingen-en-instituten/econometrie-en-or-nieuw/
RePEc:edi:ectvunl (more details at EDIRC)

Tinbergen Instituut (Tinbergen Institute)

Amsterdam, Netherlands
http://www.tinbergen.nl/
RePEc:edi:tinbenl (more details at EDIRC)

Research output

as
Jump to: Articles

Articles

  1. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Janus, Paweł & Koopman, Siem Jan & Lucas, André, 2014. "Long memory dynamics for multivariate dependence under heavy tails," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 187-206.

    Cited by:

    1. 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.
    2. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    3. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    4. Francisco Blasques & Siem Jan Koopman & Andre Lucas, 2012. "Stationarity and Ergodicity of Univariate Generalized Autoregressive Score Processes," Tinbergen Institute Discussion Papers 12-059/4, Tinbergen Institute.
    5. Christos Agiakloglou & Anil Bera & Emmanouil Deligiannakis, 2022. "Evaluating measures of dependence for linearly generated nonlinear time series along with spurious correlation," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 535-552, July.
    6. Ryoko Ito, 2016. "Asymptotic Theory for Beta-t-GARCH," Cambridge Working Papers in Economics 1607, Faculty of Economics, University of Cambridge.
    7. Mario Cerrato & John Crosby & Minjoo Kim & Yang Zhao, 2015. "Correlated Defaults of UK Banks: Dynamics and Asymmetries," Working Papers 2015_24, Business School - Economics, University of Glasgow.
    8. 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.
    9. 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.
    10. Harvey, A., 2021. "Score-driven time series models," Cambridge Working Papers in Economics 2133, Faculty of Economics, University of Cambridge.
    11. 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.
    12. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    13. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    14. Pawel Janus & André Lucas & Anne Opschoor & Dick J.C. van Dijk, 2014. "New HEAVY Models for Fat-Tailed Returns and Realized Covariance Kernels," Tinbergen Institute Discussion Papers 14-073/IV, Tinbergen Institute, revised 19 Aug 2015.
    15. Alanya-Beltran Willy, 2023. "Modelling volatility dependence with score copula models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 27(5), pages 649-668, December.
    16. Catania, Leopoldo & Grassi, Stefano, 2022. "Forecasting cryptocurrency volatility," International Journal of Forecasting, Elsevier, vol. 38(3), pages 878-894.
    17. 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.
    18. 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.
    19. Golosnoy, Vasyl & Gribisch, Bastian, 2022. "Modeling and forecasting realized portfolio weights," Journal of Banking & Finance, Elsevier, vol. 138(C).
    20. 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.
    21. Dark, Jonathan, 2018. "Multivariate models with long memory dependence in conditional correlation and volatility," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 162-180.
    22. Ito, R., 2016. "Spline-DCS for Forecasting Trade Volume in High-Frequency Finance," Cambridge Working Papers in Economics 1606, Faculty of Economics, University of Cambridge.
    23. Mokni, Khaled & Mansouri, Faysal, 2017. "Conditional dependence between international stock markets: A long memory GARCH-copula model approach," Journal of Multinational Financial Management, Elsevier, vol. 42, pages 116-131.
    24. Andrew J. Patton & Yasin Simsek, 2023. "Generalized Autoregressive Score Trees and Forests," Papers 2305.18991, arXiv.org.
    25. Ouyang, Ruolan & Zhang, Xuan, 2020. "Financialization of agricultural commodities: Evidence from China," Economic Modelling, Elsevier, vol. 85(C), pages 381-389.

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