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A Portfolio Diversification Model of Alliances

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  • John A. C. Conybeare

    (University of Iowa)

Abstract

The theory of finance demonstrates that diversified investment portfolios produce superior combinations of risk and return, and that investors may choose a portfolio reflecting their preferred mix of risk and return. These techniques may be applied to military alliances. The rate of return and risk of an ally follows a positive linear relationship, as predicted by capital asset pricing theory. Random diversification of allies will, as with investment portfolios, reduce the country-unique components of alliance risk toward that which is inherent in the system as a whole. Some alliances will be more efficient at producing greater return and lower risk. The most efficient alliances will be those in which variations in ally effort move in opposite directions. Development of the demand side of portfolio analysis may predict which alliances are optimal, and therefore most likely to form. These principles are applied to the Triple Entente and Triple Alliance between 1879 and 1914. It is suggested that the Entente had superior efficiency characteristics and that ally choices were consistent with demand patterns.

Suggested Citation

  • John A. C. Conybeare, 1992. "A Portfolio Diversification Model of Alliances," Journal of Conflict Resolution, Peace Science Society (International), vol. 36(1), pages 53-85, March.
  • Handle: RePEc:sae:jocore:v:36:y:1992:i:1:p:53-85
    DOI: 10.1177/0022002792036001003
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    References listed on IDEAS

    as
    1. Ordeshook,Peter C., 1986. "Game Theory and Political Theory," Cambridge Books, Cambridge University Press, number 9780521315937.
    2. Li, Richard P. Y. & Thompson, William R., 1978. "The Stochastic Process of Alliance Formation Behavior," American Political Science Review, Cambridge University Press, vol. 72(4), pages 1288-1303, December.
    3. Christensen, Thomas J. & Snyder, Jack, 1990. "Chain gangs and passed bucks: predicting alliance patterns in multipolarity," International Organization, Cambridge University Press, vol. 44(2), pages 137-168, April.
    4. de Mesquita, Bruce Bueno, 1985. "The War Trap Revisited: A Revised Expected Utility Model," American Political Science Review, Cambridge University Press, vol. 79(1), pages 156-177, March.
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    3. Hein, Lars & Gatzweiler, Franz, 2006. "The economic value of coffee (Coffea arabica) genetic resources," Ecological Economics, Elsevier, vol. 60(1), pages 176-185, November.
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    6. Rizov, Marian, 2005. "Rural development under the European CAP: The role of diversity," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 42(4), pages 621-628.
    7. Keith Hartley & Todd Sandler, 2001. "Economics of Alliances: The Lessons for Collective Action," Journal of Economic Literature, American Economic Association, vol. 39(3), pages 869-896, September.
    8. Gerber, Nicolas, 2011. "Biodiversity measures based on species-level dissimilarities: A methodology for assessment," Ecological Economics, Elsevier, vol. 70(12), pages 2275-2281.
    9. Pavoine, Sandrine & Bonsall, Michael B., 2009. "Biological diversity: Distinct distributions can lead to the maximization of Rao’s quadratic entropy," Theoretical Population Biology, Elsevier, vol. 75(2), pages 153-163.
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    11. Safarzynska, Karolina, 2017. "The Implications of Industrial Development for Diversification of Fuels," Ecological Economics, Elsevier, vol. 137(C), pages 37-46.
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