IDEAS home Printed from https://ideas.repec.org/a/kap/compec/v66y2025i1d10.1007_s10614-024-10699-x.html
   My bibliography  Save this article

Multi-Stage International Portfolio Selection with Factor-Based Scenario Tree Generation

Author

Listed:
  • Zhiping Chen

    (Xi’an Jiaotong University
    Xi’an International Academy for Mathematics and Mathematical Technology)

  • Bingbing Ji

    (Xi’an Jiaotong University
    Xi’an International Academy for Mathematics and Mathematical Technology)

  • Jia Liu

    (Xi’an Jiaotong University
    Xi’an International Academy for Mathematics and Mathematical Technology)

  • Yu Mei

    (Xi’an Jiaotong University
    Xi’an International Academy for Mathematics and Mathematical Technology)

Abstract

To comprehensively reflect the heteroscedasticity, nonlinear dependence and heavy-tailed distributions of stock returns while reducing the huge cost of parameter estimation, we use the Fama-French three-factor model to describe stock returns and then model the factor dynamics by using the ARMA-GARCH and Student-t copula models. A factor-based scenario tree generation algorithm is thus proposed, and the corresponding multi-stage international portfolio selection model is constructed and its reformulation is derived. Different from the current literature, our proposed models can capture the dynamic dependence among international markets and the dynamics of exchange rates, and what’s more important, make it possible for the practical solution of large-scale multi-stage international portfolio selection problems. Considering three different objective functions and international investments in the USA, Japanese and European markets, we carry out a series of empirical studies to demonstrate the practicality and efficiency of the proposed factor-based scenario tree generation algorithm and multi-stage international portfolio selection models.

Suggested Citation

  • Zhiping Chen & Bingbing Ji & Jia Liu & Yu Mei, 2025. "Multi-Stage International Portfolio Selection with Factor-Based Scenario Tree Generation," Computational Economics, Springer;Society for Computational Economics, vol. 66(1), pages 35-75, July.
  • Handle: RePEc:kap:compec:v:66:y:2025:i:1:d:10.1007_s10614-024-10699-x
    DOI: 10.1007/s10614-024-10699-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10614-024-10699-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10614-024-10699-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    2. N. Edirisinghe & E. Patterson, 2007. "Multi-period stochastic portfolio optimization: Block-separable decomposition," Annals of Operations Research, Springer, vol. 152(1), pages 367-394, July.
    3. Hansen, Bruce E, 1994. "Autoregressive Conditional Density Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(3), pages 705-730, August.
    4. Hlouskova, Jaroslava & Schmidheiny, Kurt & Wagner, Martin, 2009. "Multistep predictions for multivariate GARCH models: Closed form solution and the value for portfolio management," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 330-336, March.
    5. Topaloglou, Nikolas & Vladimirou, Hercules & Zenios, Stavros A., 2011. "Optimizing international portfolios with options and forwards," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3188-3201.
    6. Duan Li & Wan‐Lung Ng, 2000. "Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation," Mathematical Finance, Wiley Blackwell, vol. 10(3), pages 387-406, July.
    7. Cheung, Yin-Wong & Lai, Kon S., 2000. "On cross-country differences in the persistence of real exchange rates," Journal of International Economics, Elsevier, vol. 50(2), pages 375-397, April.
    8. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Nalan G√ºlpinar & Berç Rustem & Reuben Settergren, 2003. "Multistage Stochastic Mean-Variance Portfolio Analysis with Transaction Costs," Chapters, in: Anna Nagurney (ed.), Innovations in Financial and Economic Networks, chapter 3, pages 46-66, Edward Elgar Publishing.
    11. Ronald Hochreiter & Georg Pflug, 2007. "Financial scenario generation for stochastic multi-stage decision processes as facility location problems," Annals of Operations Research, Springer, vol. 152(1), pages 257-272, July.
    12. Alexander, Gordon J. & Baptista, Alexandre M., 2002. "Economic implications of using a mean-VaR model for portfolio selection: A comparison with mean-variance analysis," Journal of Economic Dynamics and Control, Elsevier, vol. 26(7-8), pages 1159-1193, July.
    13. Jondeau, Eric & Rockinger, Michael, 2006. "The Copula-GARCH model of conditional dependencies: An international stock market application," Journal of International Money and Finance, Elsevier, vol. 25(5), pages 827-853, August.
    14. Kjetil Høyland & Stein W. Wallace, 2001. "Generating Scenario Trees for Multistage Decision Problems," Management Science, INFORMS, vol. 47(2), pages 295-307, February.
    15. Topaloglou, Nikolas & Vladimirou, Hercules & Zenios, Stavros A., 2008. "A dynamic stochastic programming model for international portfolio management," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1501-1524, March.
    16. Jón Steinsson, 2008. "The Dynamic Behavior of the Real Exchange Rate in Sticky Price Models," American Economic Review, American Economic Association, vol. 98(1), pages 519-533, March.
    17. Kole, Erik & Koedijk, Kees & Verbeek, Marno, 2007. "Selecting copulas for risk management," Journal of Banking & Finance, Elsevier, vol. 31(8), pages 2405-2423, August.
    18. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 437-480, Fall.
    19. Han, Yingwei & Li, Ping & Xia, Yong, 2017. "Dynamic robust portfolio selection with copulas," Finance Research Letters, Elsevier, vol. 21(C), pages 190-200.
    20. Libo Yin & Liyan Han, 2020. "International Assets Allocation with Risk Management via Multi-Stage Stochastic Programming," Computational Economics, Springer;Society for Computational Economics, vol. 55(2), pages 383-405, February.
    21. Dias, Alexandra & Embrechts, Paul, 2010. "Modeling exchange rate dependence dynamics at different time horizons," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1687-1705, December.
    22. Andrea Consiglio & Angelo Carollo & Stavros A. Zenios, 2016. "A parsimonious model for generating arbitrage-free scenario trees," Quantitative Finance, Taylor & Francis Journals, vol. 16(2), pages 201-212, February.
    23. Sefair, Jorge A. & Méndez, Carlos Y. & Babat, Onur & Medaglia, Andrés L. & Zuluaga, Luis F., 2017. "Linear solution schemes for Mean-SemiVariance Project portfolio selection problems: An application in the oil and gas industry," Omega, Elsevier, vol. 68(C), pages 39-48.
    24. Driessen, Joost & Laeven, Luc, 2007. "International portfolio diversification benefits: Cross-country evidence from a local perspective," Journal of Banking & Finance, Elsevier, vol. 31(6), pages 1693-1712, June.
    25. Zhe Yan & Zhiping Chen & Giorgio Consigli & Jia Liu & Ming Jin, 2020. "A copula-based scenario tree generation algorithm for multiperiod portfolio selection problems," Annals of Operations Research, Springer, vol. 292(2), pages 849-881, September.
    26. Yang Zhao & Charalampos Stasinakis & Georgios Sermpinis & Filipa Da Silva Fernandes, 2019. "Revisiting Fama–French factors' predictability with Bayesian modelling and copula‐based portfolio optimization," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1443-1463, October.
    27. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    28. Andrew J. Patton, 2006. "Modelling Asymmetric Exchange Rate Dependence," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 47(2), pages 527-556, May.
    29. Rocha, Paula & Kuhn, Daniel, 2012. "Multistage stochastic portfolio optimisation in deregulated electricity markets using linear decision rules," European Journal of Operational Research, Elsevier, vol. 216(2), pages 397-408.
    Full references (including those not matched with items on IDEAS)

    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. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    2. Gilles Boevi Koumou, 2020. "Diversification and portfolio theory: a review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(3), pages 267-312, September.
    3. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    4. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    5. Peter Christoffersen & Kris Jacobs & Xisong Jin & Hugues Langlois, 2013. "Dynamic Diversification in Corporate Credit," CREATES Research Papers 2013-46, Department of Economics and Business Economics, Aarhus University.
    6. Zhe Yan & Zhiping Chen & Giorgio Consigli & Jia Liu & Ming Jin, 2020. "A copula-based scenario tree generation algorithm for multiperiod portfolio selection problems," Annals of Operations Research, Springer, vol. 292(2), pages 849-881, September.
    7. Nathan Lael Joseph & Thi Thuy Anh Vo & Asma Mobarek & Sabur Mollah, 2020. "Volatility and asymmetric dependence in Central and East European stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1241-1303, November.
    8. Bernardi, Mauro & Catania, Leopoldo, 2018. "Portfolio optimisation under flexible dynamic dependence modelling," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 1-18.
    9. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    10. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," SIRE Discussion Papers 2015-78, Scottish Institute for Research in Economics (SIRE).
    11. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    12. Avdulaj, Krenar & Barunik, Jozef, 2015. "Are benefits from oil–stocks diversification gone? New evidence from a dynamic copula and high frequency data," Energy Economics, Elsevier, vol. 51(C), pages 31-44.
    13. Christoffersen, Peter & Langlois, Hugues, 2013. "The Joint Dynamics of Equity Market Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1371-1404, October.
    14. Hofert, Marius & Prasad, Avinash & Zhu, Mu, 2022. "Multivariate time-series modeling with generative neural networks," Econometrics and Statistics, Elsevier, vol. 23(C), pages 147-164.
    15. Tong, Bin & Diao, Xundi & Wu, Chongfeng, 2015. "Modeling asymmetric and dynamic dependence of overnight and daytime returns: An empirical evidence from China Banking Sector," Economic Modelling, Elsevier, vol. 51(C), pages 366-382.
    16. 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.
    17. De Lira Salvatierra, Irving & Patton, Andrew J., 2015. "Dynamic copula models and high frequency data," Journal of Empirical Finance, Elsevier, vol. 30(C), pages 120-135.
    18. Arthur Charpentier, 2015. "Prévision avec des copules en finance," Working Papers hal-01151233, HAL.
    19. Silva Filho, Osvaldo Candido da & Ziegelmann, Flavio Augusto & Dueker, Michael J., 2012. "Modeling dependence dynamics through copulas with regime switching," Insurance: Mathematics and Economics, Elsevier, vol. 50(3), pages 346-356.
    20. Cerrato, Mario & Crosby, John & Kim, Minjoo & Zhao, Yang, 2015. "US Monetary and Fiscal Policies - Conflict or Cooperation?," 2007 Annual Meeting, July 29-August 1, 2007, Portland, Oregon TN 2015-78, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:kap:compec:v:66:y:2025:i:1:d:10.1007_s10614-024-10699-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.