IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-01242248.html
   My bibliography  Save this paper

A Socio-Finance Model: Inference and empirical application

Author

Listed:
  • Jørgen Vitting Andersen

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Ioannis D. Vrontos

    (AUEB - Athens University of Economics and Business)

  • Petros Dellaportas

    (AUEB - Athens University of Economics and Business)

  • Serge Galam

    (CEVIPOF - Centre de recherches politiques de Sciences Po (Sciences Po, CNRS) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this report, we show the empirical application of our socio-finance model introduced in Andersen, Vrontos, Dellaportas and Galam (2014).

Suggested Citation

  • Jørgen Vitting Andersen & Ioannis D. Vrontos & Petros Dellaportas & Serge Galam, 2015. "A Socio-Finance Model: Inference and empirical application," Post-Print halshs-01242248, HAL.
  • Handle: RePEc:hal:journl:halshs-01242248
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-01242248
    as

    Download full text from publisher

    File URL: https://shs.hal.science/halshs-01242248/document
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Fiorentini, Gabriele & Calzolari, Giorgio & Panattoni, Lorenzo, 1996. "Analytic Derivatives and the Computation of GARCH Estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 399-417, July-Aug..
    2. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "Communication impacting financial markets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01215750, HAL.
    3. Biondi, Yuri & Giannoccolo, Pierpaolo & Galam, Serge, 2012. "Formation of share market prices under heterogeneous beliefs and common knowledge," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5532-5545.
    4. Mak, T. K. & Wong, H. & Li, W. K., 1997. "Estimation of nonlinear time series with conditional heteroscedastic variances by iteratively weighted least squares," Computational Statistics & Data Analysis, Elsevier, vol. 24(2), pages 169-178, April.
    5. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    6. Ioannis Vrontos, 2012. "Evidence for hedge fund predictability from a multivariate Student's t full-factor GARCH model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1295-1321, November.
    7. Ernst R. Berndt & Bronwyn H. Hall & Robert E. Hall & Jerry A. Hausman, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 653-665, National Bureau of Economic Research, Inc.
    8. I. D. Vrontos & P. Dellaportas & D. N. Politis, 2003. "A full-factor multivariate GARCH model," Econometrics Journal, Royal Economic Society, vol. 6(2), pages 312-334, December.
    9. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "Communication impacting financial markets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01215750, HAL.
    2. Naji Massad & Jørgen Vitting Andersen, 2018. "Three Different Ways Synchronization Can Cause Contagion in Financial Markets," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01951164, HAL.
    3. Naji Massad & Jørgen Vitting Andersen, 2018. "Three Different Ways Synchronization Can Cause Contagion in Financial Markets," Post-Print hal-01951164, HAL.
    4. Naji Massad & J{o}rgen Vitting Andersen, 2019. "Three Different Ways Synchronization Can Cause Contagion in Financial Markets," Papers 1902.10800, arXiv.org.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jørgen Vitting Andersen & Ioannis Vrontos & Petros Dellaportas & Serge Galam, 2014. "A Socio-Finance Model: Inference and empirical application," SciencePo Working papers Main hal-01215605, HAL.
    2. Jørgen Vitting Andersen & Ioannis D. Vrontos & Petros Dellaportas & Serge Galam, 2015. "A Socio-Finance Model: Inference and empirical application," SciencePo Working papers Main halshs-01242248, HAL.
    3. K. Diamantopoulos & I. Vrontos, 2010. "A Student-t Full Factor Multivariate GARCH Model," Computational Economics, Springer;Society for Computational Economics, vol. 35(1), pages 63-83, January.
    4. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871.
    5. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    6. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723.
    7. Bucevska Vesna, 2013. "An Empirical Evaluation of GARCH Models in Value-at-Risk Estimation: Evidence from the Macedonian Stock Exchange," Business Systems Research, Sciendo, vol. 4(1), pages 49-64, March.
    8. Panayiotis Theodossiou, 1998. "Financial Data and the Skewed Generalized T Distribution," Management Science, INFORMS, vol. 44(12-Part-1), pages 1650-1661, December.
    9. Nikolaos Dritsakis & Paraskevi Klazoglou, 2018. "Forecasting Unemployment Rates in USA using Box-Jenkins Methodology," International Journal of Economics and Financial Issues, Econjournals, vol. 8(1), pages 9-20.
    10. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    11. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
    13. Nimitha John & Balakrishna Narayana, 2018. "Cointegration models with non Gaussian GARCH innovations," METRON, Springer;Sapienza Università di Roma, vol. 76(1), pages 83-98, April.
    14. Booth, G. Geoffrey & Kaen, Fred R. & Koutmos, Gregory & Sherman, Heidemarie C., 2000. "Bundesbank intervention effects through interest rate policy," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 10(3-4), pages 263-274, December.
    15. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    16. Stavros Degiannakis & Evdokia Xekalaki, 2005. "Predictability and model selection in the context of ARCH models," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 21(1), pages 55-82, January.
    17. Geoffrey F. Loudon & Wing H. Watt & Pradeep K. Yadav, 2000. "An empirical analysis of alternative parametric ARCH models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(2), pages 117-136.
    18. Chin-Tsai Lin & Yi-Hsien Wang, 2007. "The impact of party alternative on the stock market: the case of Japan," Applied Economics, Taylor & Francis Journals, vol. 39(1), pages 79-85.
    19. Bohl, Martin T. & Diesteldorf, Jeanne & Siklos, Pierre L., 2015. "The effect of index futures trading on volatility: Three markets for Chinese stocks," China Economic Review, Elsevier, vol. 34(C), pages 207-224.
    20. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.

    More about this item

    Keywords

    Socio-finance; communication; stylized facts;
    All these keywords.

    JEL classification:

    • G0 - Financial Economics - - General
    • C0 - Mathematical and Quantitative Methods - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:halshs-01242248. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.