Hostname: page-component-84b7d79bbc-c654p Total loading time: 0 Render date: 2024-07-26T05:29:47.175Z Has data issue: false hasContentIssue false

An Empirical Comparison of Stochastic Dominance among Lognormal Prospects

Published online by Cambridge University Press:  06 April 2009

Extract

The theory of portfolio selection and diversification developed by Markowitz [22] and Tobin [33] was based primarily on the criterion of meanvariance (MV) efficiency. The objective was to select an efficient set of portfolios from which every risk averter will choose the optimal portfolio which maximizes his expected utility. The MV criterion is the appropriate rule either for the case in which the utility function is quadratic or if the returns are normally distributed and risk aversion is assumed.

Type
Research Article
Copyright
Copyright © School of Business Administration, University of Washington 1982

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

[l]Barnes, Amir, and Downes, David H.. “A Reexamination of the Empirical Distribution of Stock Price Changes.” Journal of the American Statistical Association (06 1973), pp. 348350.Google Scholar
[2]Bernoulli, Daniel. “Exposition of a New Theory on the Measurement of Risk.” Econometrica (01 1954), pp. 2336.Google Scholar
[3]Blattberg, Robert C, and Gonedes, Nicholas J.A Comparison of the Stable and Student Distributions as Statistical Models of Stock Prices.” Journal of Business (04 1974), pp. 244280.Google Scholar
[4]Cootner, P. H., ed. The Random Character of Stock Market Prices. Cambridge, MA: MIT Press (1964).Google Scholar
[5]Fama, Eugene F.The Behavior of Stock Market Prices.” Journal of Business (01 1965), pp. 34105.Google Scholar
[6]Feldstein, M. S. “Mean-Variance Analysis in the Theory of Liquidity Preference and Portfolio Selection.” Review of Economic Studies (01 1969), pp. 512.Google Scholar
[7]Gibbons, J. D.Nonparametric Statistical Inference. NY: McGraw-Hill (1971).Google Scholar
[8]Hadar, J., and Russel, W. R.. “Rules for Ordering Uncertain Prospects.” American Economic Review (03 1969), pp. 2534.Google Scholar
[9]Hakansson, Nils H.Capital Growth and the Mean-Variance Approach to Portfolio Selection.” Journal of Financial and Quantitative Analysis (01 1971), pp. 517557CrossRefGoogle Scholar
[10]Hanoch, G., and Levy, H. “The Efficiency Analysis of Choices Involving Risk.” Review of Economic Studies (07 1969), pp. 335346.Google Scholar
[11]Helms, B. P.; Mansfield, E. R.; and Strong, G. Q.. “Distribution of Returns on Common Stock.” Working Paper presented at the American Statistical Association meeting in Detroit (08 1981).Google Scholar
[12]Jean, W. H.The Geometric Mean and Stochastic Dominance.The Journal of Finance (03 1980), pp. 151158.CrossRefGoogle Scholar
[13]Kendall, M. G.The Analysis of Economic Time Series.” Journal of the Royal Statistical Society, Ser. A, XCVI (1953), pp. 1125.Google Scholar
[14]Latané, Henry. “Criteria for Choice among Risky Ventures.” Journal of Political Economy (04 1959), pp. 144155Google Scholar
[15]Latané, Henry and Tuttle, Donald L.. “Criteria for Portfolio Building.” Journal of Finance (09 1967), pp. 359373Google Scholar
[16]Leitch, R. A., and Paulson, A. S.. “Estimation of Stable Law Parameters: Stock Price Behavior Application.” Journal of the American Statistical Association (09 1975), pp. 690697.Google Scholar
[17]Levy, H. “Stochastic Dominance among Log-normal Prospects.” International Economic Review (10 1973), pp. 601614.Google Scholar
[18]Levy, H., and Markowitz, H. M. “Approximating Expected Utility fay a Function of Mean and Variance.” American Economic Review (06 1979), pp. 308317.Google Scholar
[19]Lilliefors, H. W.On the Kolmogorov-Smirnov Test for Normality with Mean and Variance Unknown.” Journal of the American Statistical Association, Vol. 62, No. 318 (06 1967), pp. 399–402.Google Scholar
[20]Lintner, John. “The Lognormality of Security Returns, Portfolio Selection and Market Equilibrium.” Working Paper, Graduate School of Business Administration, Harvard University (1980).Google Scholar
[21]Mandelbrot, Benoit. “The Variation of Speculative Prices.The Journal of Business (10 1963), pp. 394410.Google Scholar
[22]Markowitz, H. M.Portfolio Selection, Cowles Foundation Monograph 16. NY: John Wiley and Sons, Inc. (1959).Google Scholar
[23]Massey, F. J. Jr, “The Kolmogorov-Smirnov Test for Goodness of Fit.” Journal of the American Statistical Association, Vol. 45, No. 253 (03 1951), pp. 6878.CrossRefGoogle Scholar
[24]Merton, RobertOptimal Consumption and Portfolio Rules in a Continuous Time Model.” Journal of Economic Theory (12 1971), pp. 373413.Google Scholar
[25]Moore, Arnold “A Statistical Analysis of Common Stock Prices.” Unpublished Doctoral Dissertation, Graduate School of Business, University of Chicago (1962).Google Scholar
[26]Osborne, M. F. M. “Brownian Motion in the Stock Market.” Operations Research (03 1959), pp. 145173.CrossRefGoogle Scholar
[27]Praetz, P. D.The Distribution of Share Price Changes.” Journal of Business (01 1972), pp. 4955.Google Scholar
[28]Press, S. J.A Compound Events Model for Security Prices.” Journal of Business (07 1967), pp. 317335Google Scholar
[29]Quirk, J. P., and Saposnik, R. “Admissibi1ity and Measurable Utility Function.” Review of Economic Studies (02 1962), pp. 104144.Google Scholar
[30]Samuelson, Paul “Lifetime Portfolio Selection by Dynamic Stochastic Programming.” Review of Economics and Statistics (08 1969), pp.139–146.Google Scholar
[31]Samuelson, Paul “The Fallacy of Maximizing the Geometric Mean in Long Sequences in Investing or Gambling.” Proceeding-National Academy of Science (10 1971), pp. 24932496.Google Scholar
[32]Teichmoeller, John. “A Note on the Distribution of Stock Price Changes.” Journal of the American Statistical Association (06 1971), pp. 282284.Google Scholar
[33]Tobin, J. “Liquidity Preference as Behavior towards Risk.” Review of Economics Studies (02 1958), pp. 6585Google Scholar
[34]Whitmore, G. A. “Third Degree Stochastic Dominance.” American Economic Review(06 1970), pp. 457459.Google Scholar