Skip to main content
SpringerLink
Log in

Modeling the Dependence Dynamics and Risk Spillovers for G7 Stock Markets

  • Conference paper
  • First Online:
Structural Changes and their Econometric Modeling (TES 2019)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 808))

Included in the following conference series:

Abstract

This study investigates the time varying beta risk and spillovers of G7 stock markets. The ICAPM and Markov-switching copula approaches are employed to achieve our study goal. The overall result shows that there is a dependence between individual stock index and aggregated G7 and that beta risk varies depending on the time period. Several copula functions are employed here to find the best fit dependence structure of the data. The results show that Clayton and Gumbel present the appropriate dependence structure in each country and aggregated G7 market. The computed beta risks led to the findings that G7 beta spillovers are substantial and time-varying across the seven countries.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Adler, M., Dumas, B.: International portfolio choice and corporation finance: a synthesis. J. Financ. 38(3), 925–984 (1983)

    Article  Google Scholar 

  2. Araichi, S., de Peretti, C., Belkacem, L.: Reserve modelling and the aggregation of risks using time varying copula models. Econo. Model. 67, 149–158 (2017)

    Article  Google Scholar 

  3. Diebold, F.X., Yilmaz, K.: Better to give than to receive: predictive directional measurement of volatility spillovers. Int. J. Forecast. 28(1), 57–66 (2012)

    Article  Google Scholar 

  4. Embrechts, P., Lindskog, F., McNeil, A.: Modelling dependence with copulas. Rapport technique, Département de mathématiques, Institut Fédéral de Technologie de Zurich, Zurich (2001)

    Google Scholar 

  5. Engle, R.: Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroskedasticity models. J. Bus. Econ. Stat. 20(3), 339–350 (2002)

    Article  MathSciNet  Google Scholar 

  6. Glosten, L.R., Jagannathan, R., Runkle, D.E.: On the relation between the expected value and the volatility of the nominal excess return on stocks. J. Financ. 48, 1779–1801 (1993)

    Article  Google Scholar 

  7. Goodman, S.N.: Toward evidence-based medical statistics. 1: The P value fallacy. Ann. Internal Med. 130(12), 995–1004 (1999)

    Article  Google Scholar 

  8. Hansen, B.E.: Autoregressive conditional density estimation. Int. Econ. Rev. 35(3), 705–730 (1994)

    Article  Google Scholar 

  9. Held, L., Ott, M.: How the maximal evidence of p-values against point null hypotheses depends on sample size. Am. Stat. 70(4), 335–341 (2016)

    Article  MathSciNet  Google Scholar 

  10. Joe, H.: Multivariate Models and Multivariate Dependence Concepts. CRC Press, London (1997)

    Book  Google Scholar 

  11. Komorník, J., Komorníková, M.: Modelling financial time series using reflections of copulas. Kybernetika 49(3), 487–497 (2013)

    MathSciNet  MATH  Google Scholar 

  12. Lintner, J.: The valuation of risk assets and the selection of risky investments in stock portfolios and capital budgets. Rev. Econ. Stat. 47(1), 13–37 (1965)

    Article  Google Scholar 

  13. Liow, K.H., Newell, G.: Real estate global beta and spillovers: an international study. Econ. Model. 59, 297–313 (2016)

    Article  Google Scholar 

  14. Najafabadi, A.T.P., Qazvini, M., Ofoghi, R.: The impact of oil and gold prices’ shock on tehran stock exchange: a copula approach. Iranian J. Econ. Stud. 1(2), 23–47 (2012)

    Google Scholar 

  15. Ostrup Christensen, M., Ellegaard, J.: Gold investment (2014)

    Google Scholar 

  16. Pastpipatkul, P., Yamaka, W., Sriboonchitta, S.: Analyzing financial risk and co-movement of gold market, and Indonesian, Philippine, and Thailand stock markets: dynamic copula with Markov-switching. In: Causal Inference in Econometrics, pp. 565–586. Springer, Cham (2016)

    Google Scholar 

  17. Pastpipatkul, P., Yamaka, W., Sriboonchitta, S.: Dependence structure of and co-movement between Thai currency and international currencies after introduction of quantitative easing. In: Causal Inference in Econometrics, pp. 545–564. Springer, Cham (2016)

    Google Scholar 

  18. Patton, A.J.: Modelling asymmetric exchange rate dependence. Int. Econ. Rev. 47(2), 527–556 (2006)

    Article  MathSciNet  Google Scholar 

  19. Sharpe, W.F.: Capital asset prices: a theory of market equilibrium under conditions of risk. J. Financ. 19(3), 425–442 (1964)

    MathSciNet  Google Scholar 

  20. Sklar, M.: Fonctions de repartition an dimensions et leurs marges. Publ. Inst. Statist. Univ. Paris 8, 229–231 (1959)

    MathSciNet  MATH  Google Scholar 

  21. Silva Filho, O.C.D., Ziegelmann, F.A., Dueker, M.J.: Modeling dependence dynamics through copulas with regime switching. Insur. Math. Econ. 50(3), 346–356 (2012)

    MathSciNet  MATH  Google Scholar 

  22. Tófoli, P.V., Ziegelmann, F.A., Silva Filho, O.C.: A comparison study of copula models for European financial index returns. In: 34 Meeting of the Brazilian Econometric Society (2012)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. International College of Digital Innovation, Chiang Mai University, Chiang Mai, Thailand

    Noppasit Chakpitak & Rungrapee Phadkantha

  2. Center of Excellence in Econometrics, Chiang Mai University, Chiang Mai, Thailand

    Rungrapee Phadkantha

  3. Center of Excellence in Econometrics, Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Woraphon Yamaka

Authors
  1. Noppasit Chakpitak
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rungrapee Phadkantha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Woraphon Yamaka
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rungrapee Phadkantha .

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Texas at El Paso, El Paso, TX, USA

    Vladik Kreinovich

  2. Faculty of Economics, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Chakpitak, N., Phadkantha, R., Yamaka, W. (2019). Modeling the Dependence Dynamics and Risk Spillovers for G7 Stock Markets. In: Kreinovich, V., Sriboonchitta, S. (eds) Structural Changes and their Econometric Modeling. TES 2019. Studies in Computational Intelligence, vol 808. Springer, Cham. https://doi.org/10.1007/978-3-030-04263-9_39

Download citation

Publish with us

Policies and ethics

Search

Navigation