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A Nonlinear Model to Estimate the Long Term Correlation between Market Capitalization and GDP per capita in Eastern EU Countries

Author

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  • Albu, Lucian Liviu

    (Institute for Economic Forecasting, Romanian Academy)

  • Lupu, Radu

    (Institute for Economic Forecasting, Romanian Academy)

  • Calin, Cantemir

    (Institute for Economic Forecasting, Romanian Academy)

Abstract

The connection between the macroeconomic development on one hand and the stock market dynamics on the other hand is the focus of many research initiatives. We are trying to apply the methodology used in the field of macroeconomic convergence to the dynamics of market capitalization for European economies. Under the general standard form of the convergence theory, which states that in the long run, as income per capita increases its corresponding growth rate will decrease, we propose a non-linear model that simulates the convergence based on data for the Central and Eastern European countries pursuing the estimation of a theoretical (hypothetical) optimal trend with respect to certain rational criteria. The model is applied on both macroeconomic variables and the market capitalization and we relate the differences that were found to the increased volatility of the latter set of data.

Suggested Citation

  • Albu, Lucian Liviu & Lupu, Radu & Calin, Cantemir, 2014. "A Nonlinear Model to Estimate the Long Term Correlation between Market Capitalization and GDP per capita in Eastern EU Countries," Working Papers of Institute for Economic Forecasting 141115, Institute for Economic Forecasting.
    • Handle: RePEc:rjr:wpiecf:141115
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    References listed on IDEAS

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    1. Lucian Liviu Albu & Radu Lupu & Cantemir Adrian Călin & Oana Cristina Popovici, 2014. "Estimating the Impact of Quantitative Easing On Credit Risk through an ARMA-GARCH Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 39-50, October.
    2. Fratzscher, Marcel, 2002. "Financial Market Integration in Europe: On the Effects of EMU on Stock Markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 7(3), pages 165-193, July.
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    6. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
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    8. Kpate ADJAOUTÉ & Jean-Pierre DANTHINE, 2003. "European Financial Integration and Equity Returns: A Theory-Based Assessment," FAME Research Paper Series rp84, International Center for Financial Asset Management and Engineering.
    9. Reszat, Beate, 2003. "How has the European Monetary Integration Process Contributed to Regional Financial Market Integration?," HWWA Discussion Papers 221, Hamburg Institute of International Economics (HWWA).
    10. Adrian Cantemir Calin & Tiberiu Diaconescu & Oana – Cristina Popovici, 2014. "Nonlinear Models for Economic Forecasting Applications: An Evolutionary Discussion," Computational Methods in Social Sciences (CMSS), "Nicolae Titulescu" University of Bucharest, Faculty of Economic Sciences, vol. 2(1), pages 42-47, June.
    11. Chen, Nai-Fu & Roll, Richard & Ross, Stephen A, 1986. "Economic Forces and the Stock Market," The Journal of Business, University of Chicago Press, vol. 59(3), pages 383-403, July.
    12. Reszat, Beate, 2003. "How Has the European Monetary Integration Process Contributed to Regional Financial Market Integration?," Discussion Paper Series 26179, Hamburg Institute of International Economics.
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    Citations

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    Cited by:

    1. POPOVICI, Oana Cristina, 2015. "A Volatility Analysis Of The Euro Currency And The Bond Market," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 67-79.
    2. Wang Tianqiong & Shu Yang & Shamila Saddique, 2017. "Effect of Economic Announcements on FX Fluctuations: Testing a Unified Approach for Prediction," International Journal of Economics and Financial Issues, Econjournals, vol. 7(2), pages 631-640.
    3. Lucian-Liviu Albu, 2016. "Trends in the relation between regional convergence and economic growth in EU," ERSA conference papers ersa16p244, European Regional Science Association.
    4. Lucian-Liviu Albu & Radu Lupu & Adrian Cantemir Calin, 2015. "Interactions between financial markets and macroeconomic variables in EU: a nonlinear modeling approach," ERSA conference papers ersa15p685, European Regional Science Association.
    5. Adrian Cantemir CALIN, 2015. "The Impact of Trade Announcements on Financial Markets. An Event Study Analysis," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 81-91, June.
    6. Daniel Belingher, 2015. "A Short-Run Relationship Between 1-Year Bonds Yield And The Domestic Consumption In Romania," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 2, pages 28-36, April.
    7. CĂLIN, Adrian Cantemir, 2015. "Connection Of European Economic Growth With The Dynamics Of Volatility Of Stock Market Returns," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 19(1), pages 53-66.
    8. Lucian-Liviu Albu, 2016. "Modelling of the relation between financial market and growth in EU: convergence and behavioural regimes," EcoMod2016 9694, EcoMod.
    9. Vilizar Chupetlovski & Peter Chobanov & Yavor Rusinov, 2021. "The Western Balkans Stock Exchanges Unification in Response to the Pandemic Crisis," Economic Alternatives, University of National and World Economy, Sofia, Bulgaria, issue 3, pages 372-388, September.
    10. LUPU, Radu & CALIN, Adrian Cantemir, 2014. "A Mixed Frequency Analysis Of Connections Between Macroeconomic Variables And Stock Markets In Central And Eastern Europe," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 18(2), pages 69-79.

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    More about this item

    Keywords

    market capitalization; GDP per capita; nonlinear models; eastern EU countries.;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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