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Structural versus Temporary Drivers of Country and Industry Risk

Author

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  • Lieven Baele

    (Tilburg University, CentER, Netspar)

  • Koen Inghelbrecht

    (Ghent University)

Abstract

This paper analyzes the dynamics and determinants of the relative benefits of geographical and industry diversification over the last 30 years. First, we develop a new structural regime-switching volatility spillover model to decompose total risk into a systematic and a country (industry) specific component. Contrary to most other studies, we explicitly allow market betas and asset-specific risks to vary with both structural and temporary changes in the economic and financial environment. In a second step, we investigate the relative benefits of geographical and industry diversification by comparing average asset- specific volatilities and model-implied correlations across countries and industries. We find a large positive (negative) effect of the structural factors on country betas (country-specific volatility), especially in Europe, while industry betas are mainly determined by temporary factors. Not taking into account the time variation in betas leads to biases in measures of industry and country-specific risk of up to 33 percent. After correcting for this bias, we find that under the influence of globalization and regionial integration, the traditional dominance geographical over industry diversification has been eroded, and that over the last years geographical and industry diversification roughly yield the same diversification benefits. Finally, our results indicate that the surge in industry risk at the end of the 1990s was partly (but not fully) related to the TMT bubble.

Suggested Citation

  • Lieven Baele & Koen Inghelbrecht, 2005. "Structural versus Temporary Drivers of Country and Industry Risk," International Finance 0511005, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpif:0511005
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    Cited by:

    1. Ye Bai & Christopher Green, 2011. "Determinants of cross-sectional stock return variations in emerging markets," Empirical Economics, Springer, vol. 41(1), pages 81-102, August.
    2. Baele, Lieven & Pungulescu, Crina & Ter Horst, Jenke, 2007. "Model uncertainty, financial market integration and the home bias puzzle," Journal of International Money and Finance, Elsevier, vol. 26(4), pages 606-630, June.
    3. Mukherjee, Raja & Paul, Satya & Shankar, Sriram, 2018. "Equity home bias—A global perspective from the shrunk frontier," Economic Analysis and Policy, Elsevier, vol. 57(C), pages 9-21.
    4. Geert Bekaert & Robert J. Hodrick & Xiaoyan Zhang, 2009. "International Stock Return Comovements," Journal of Finance, American Finance Association, vol. 64(6), pages 2591-2626, December.
    5. Y. Bai, 2014. "Country factors in stock returns: reconsidering the basic method," Applied Financial Economics, Taylor & Francis Journals, vol. 24(13), pages 871-888, July.

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    More about this item

    Keywords

    International portfolio diversification; Country versus Industry Effects; Financial integration; Idiosyncratic risk; Time- Varying Correlations; Regime-switching models;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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