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Geometric Mean Approximations

Published online by Cambridge University Press:  06 April 2009

Extract

In 1959, Henry Lataná [2] proposed an approximation to the geometric mean that was a simple function of the arithmetic mean and variance, thereby indicating a mathematical relationship between the risky investment choice model of Bernoulli and the Markowitz mean-variance model. In 1969, Young and Trent [4] presented empirical test results of the Latané approximation, as well as a set of other approximations to the geometric mean based on moments, and concluded that the Latane formula yielded a quite accurate approximation to the geometric mean. In Jean's 1980 paper [1] relating the geometric mean model to stochastic dominance models, the infinite series representation of the geometric mean used suggests a more accurate approximation with moments of the geometric mean than that contained in the earlier papers may be possible. Various forms of that series expressed in alternate-origin moments are tested empirically below, and the results confirm that this later series does yield the greatest accuracy of the three approaches.

Type
Research Article
Copyright
Copyright © School of Business Administration, University of Washington 1983

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References

[1]Jean, William H.The Geometric Mean and Stochastic Dominance.” Journal of Finance, Vol. 35 (03 1980), pp. 151158.CrossRefGoogle Scholar
[2]Latané, Henry A.Criteria for Choice among Risky Ventures.” Journal of Political Economy, Vol. 67 (04 1959), pp. 144155.CrossRefGoogle Scholar
[3]Michaud, Richard O.Risk Policy and Long-term Investment.” Journal of Financial and Quantitative Analysis, Vol. 16 (06 1981), pp. 147167.CrossRefGoogle Scholar
[4]Young, William E. and Trent, Robert H.. “Geometric Mean Approximations of Individual Security and Portfolio Performance.” Journal of Financial and Quantitative Analysis, Vol. 4 (06 1969), pp. 179199.CrossRefGoogle Scholar