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Efficient Algorithms for Conducting Stochastic Dominance Tests on Large Numbers of Portfolios: Reply

Published online by Cambridge University Press:  19 October 2009

R. Burr Porter  and
Roger C. Pfaffenberger
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Extract

In their comment on a paper by Porter, Wart, and Ferguson [7], Professors Frankfurter and Phillips [2] have raised two serious objections to “any attempt to compare and contrast SD and EV efficiency criteria on empirical grounds.” Essentially, they have argued that empirical comparisons of SD and EV selection rules are invalid because:

a. The EV portfolio building algorithms are not allowed to operate in such tests, and

b. While the estimators of true E and V are derived from and supported by elementary sampling theory, there exists no comparable sampling theory for the estimation of total probability functions.

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Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 10 , Issue 1 , March 1975 , pp. 181 - 185
Copyright
Copyright © School of Business Administration, University of Washington 1975

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References

REFERENCES

[1]Conover, W. J.Practical Nonparametric Statistics. New York: John Wiley & Sons, 1971.Google Scholar
[2]Frankfurter, George M., and Phillips, Herbert E.. “Efficient Algorithms for Conducting Stochastic Dominance Tests on Large Numbers of Portfolios: A Comment.” Journal of Financial and Quantitative Analysis, March 1975.CrossRefGoogle Scholar
[3]Joy, O. Maurice, and Porter, R. Burr. “Stochastic Dominance and Mutual Fund Performance.” Journal of Financial and Quantitative Analysis, January 1974, pp. 25–31.Google Scholar
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[7]Porter, R. Burr; Wart, James R.; and Ferguson, Donald L.. “Efficient Algorithms for Conducting Stochastic Dominance Tests on Large Number of Portfolios.” Journal of Financial and Quantitative Analysis, January 1973, pp. 71–82.CrossRefGoogle Scholar
[8]Porter, R. Burr; Ezzell, John R.; and Goldschmidt, John. “An Empirical Test of the Stationarity of Probability Functions of Security Returns.” Eastern Finance Association.Google Scholar
[9]Wilks, Samuel S.Mathematical Statistics. New York: John Wiley and Sons, 1962.Google Scholar