Hostname: page-component-cb9f654ff-pvkqz Total loading time: 0 Render date: 2025-08-28T22:50:03.955Z Has data issue: false hasContentIssue false
  • English
  • Français

The Effects Of Sample Size And Correlation On The Accuracy Of The Ev Efficiency Criterion

Published online by Cambridge University Press:  06 April 2009

Erwin Saniga ,
Nicolas Gressis  and
Jack Hayya
Get access Rights & Permissions [Opens in a new window]

Extract

Traditionally, the problem of portfolio choice from risky assets has been solved by considering each asset as a probability distribution of future returns. Depending on the approach used to perform efficiency analysis, knowledge about the asset's probability distribution can be from summary to complete. Thus the mean-variance (EV) model of Markowitz [9] utilizes the first two moments of the distribution, whereas the stochastic dominance (SD) approach [3] employs the entire probability function.

Information

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 14 , Issue 3 , September 1979 , pp. 615 - 628
Copyright
Copyright © School of Business Administration, University of Washington 1979

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.)

Article purchase

Temporarily unavailable

References

REFERENCES

1Blume, Marshall. “On the Assessment of Risk.” Journal of Finance (03 1971), pp. 1–10.Google Scholar
2Frankfurter, George M.; Phillips, Herbert E.; and Seagle, John P.. “Portfolio Selection: The Effects of Uncertain Means, Variances, and Covariances.” Journal of Financial and Quantitative Analysis (12 1971) pp. 1251–1262.Google Scholar
3Hanoch, G., and Levy, H.. “The Efficiency Analysis of Choices Involving Risk.” Review of Economic Studies (07 1969), pp. 335–346.Google Scholar
4IBM Applications Program System 360, Scientific Subroutine Package, Version 3 (08 1970).Google Scholar
5Jensen, Michael C. “Capital Markets: Theory and Evidence.” The Bell Journal of Economics and Management Science, Vol. 3 (Autumn 1972), pp. 357–398.CrossRefGoogle Scholar
6Johnson, Keith H., and Burgess, Richard B.. “The Effects of Sample Sizes on the Accuracy of EV and SSD Efficiency Criteria.” Journal of Financial and Quantitative Analysis (12 1975), pp. 813–820.Google Scholar
7Johnson, N. L., and Kotz, S.. Distributions in Statistics: Continuous Multivariate Distributions. New York: John Wiley and Sons (1972).Google Scholar
8Levy, Robert A. “Beta Coefficients as Predictors of Return.” Financial Analysts Journal (01–02 1974), pp. 61–69.Google Scholar
9Markowitz, Harry M. “Portfolio Selection.” Journal of Finance, Vol. 1 (03 1952), pp. 77–91.Google Scholar
10Naylor, T. H.; Balintfy, J. L.; Burdick, D. S.; and Chu, K.. Computer Simulation Techniques. New York: John Wiley and Sons (1966).Google Scholar
11Officer, R. R. “The Distribution of Stock Returns.” Journal of the American Statistical Association, Vol. 67 (12 1972), pp. 807–812.Google Scholar
12Ord, J. K. “Probability That ,” personal communication, Dept. of Statistics, University of Warwick, Coventry, England (04 26, 1978).Google Scholar
13Porter, R. Burr. “An Empirical Comparison of Stochastic Dominance and Mean-Variance Portfolio Choice Criteria.” Journal of Financial and Quantitative Analysis (09 1973), pp. 587–608.CrossRefGoogle Scholar
14Robichek, A.; Cohn, R.; and Pringle, J.. “Returns on Alternative Investment Media and Implications for Portfolio Construction.” Journal of Business (07 1972), pp. 427–443.Google Scholar
15Tobin, J. “Comment on Borch and Feldstein.” Review of Economic Studies (01 1969), pp. 13–14.CrossRefGoogle Scholar
16Tsiang, S. C. “The Rationale of the Mean-Standard Deviation Analysis, Skewness Preferences, and the Demand for Money.” American Economic Review (06 1972), pp. 354–371.Google Scholar