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Semi-correlations as a tool for geographical and sector asset allocation

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  • Giampaolo Gabbi

Abstract

Many studies show that international correlations have changed over time. This phenomenon has modified the practices of many portfolio managers, which are now preferably linked with sector behaviour. In order to prove the benefits of this management style, some new evidence is provided for correlation dynamics among geographic areas and business sectors. The concept of semi-correlation is applied to asset allocation in order to compare whether it applies efficiently to sectors and countries. The paper shows that use of semi-correlations has the potential both to improve expected return and to reduce volatility.

Suggested Citation

  • Giampaolo Gabbi, 2005. "Semi-correlations as a tool for geographical and sector asset allocation," The European Journal of Finance, Taylor & Francis Journals, vol. 11(3), pages 271-281.
    • Handle: RePEc:taf:eurjfi:v:11:y:2005:i:3:p:271-281
    DOI: 10.1080/13518470500039220
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    References listed on IDEAS

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    1. Kaplanis, Evi C., 1988. "Stability and forecasting of the comovement measures of international stock market returns," Journal of International Money and Finance, Elsevier, vol. 7(1), pages 63-75, March.
    2. Groenen, Patrick J. F. & Franses, Philip Hans, 2000. "Visualizing time-varying correlations across stock markets," Journal of Empirical Finance, Elsevier, vol. 7(2), pages 155-172, August.
    3. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    4. Leitch, Gordon & Tanner, J Ernest, 1991. "Economic Forecast Evaluation: Profits versus the Conventional Error Measures," American Economic Review, American Economic Association, vol. 81(3), pages 580-590, June.
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    Cited by:

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    3. Burcu Kapar & Giulia Iori & Giampaolo Gabbi & Guido Germano, 2020. "Market microstructure, banks’ behaviour and interbank spreads: evidence after the crisis," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 15(1), pages 283-331, January.
    4. Lee, Chien-Chiang & Chiu, Yi-Bin, 2016. "Globalization and insurance activity: Evidence on the industrial and emerging countries," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 328-349.
    5. Pavel Krupskii & Harry Joe, 2015. "Tail-weighted measures of dependence," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(3), pages 614-629, March.
    6. Cyril Bénézet & Emmanuel Gobet & Rodrigo Targino, 2023. "Transform MCMC Schemes for Sampling Intractable Factor Copula Models," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-41, March.
    7. Cyril Bénézet & Emmanuel Gobet & Rodrigo Targino, 2023. "Transform MCMC schemes for sampling intractable factor copula models," Post-Print hal-03334526, HAL.

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