Axioms for an individual's preferences over time, taken from the present perspective, usually assume that the individual will live, or expects to live, throughout a given horizon span. This paper offers an axiomatization that explicitly recognizes the uncertainty of an individual's lifetime. It divides a horizon span into n periods and assumes that if death is not immediate then it will occur at the end of one of the periods. The theory is based on an unconditional preference relation over potential future consumption streams that accounts for uncertain lifetime, along with a conditional preference order that is based on the hypothesis that death will occur at the end of period i. There is a conditional order for each i from 1 to n. The utility representation involves an order-preserving utility function for each of the n conditional orders such that one potential consumption stream is unconditionally preferred to another if, and only if, the sum of the conditional utilities for the first stream exceeds the sum of the conditional utilities for the second. It is argued that the theory seems fairly reasonable only if probability of survival does not depend significantly on past consumption.
C. C. Huang, D. Kira, I. Vertinsky; Stochastic Dominance Rules for Multi-attribute Utility Functions, The Review of Economic Studies, Volume 45, Issue 3, 1
Kenneth S. Lorek, James C. McKeown, The Effect on Predictive Ability of Reducing the Number of Observations on a Time-Series Analysis of Quarterly Earnings Data, Journal of Accounting Research, Vol. 16, No. 1 (Spring, 1978), pp. 204-214
Journal of Financial and Quantitative Analysis197813(2), 345
Stephen P. Bradley, Sherwood C. Frey, Jr., Equivalent Mathematical Programming Models of Pure Capital Rationing, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 2 (Jun., 1978), pp. 345-361
Journal of Financial and Quantitative Analysis197813(1), 133
The purpose of this paper is to provide evidence that the Bureau of the Census' X–ll program for seasonal adjustment [3] overstates the incidence of seasonality in some forms of times series data. This problem arises in a recent study by Bonin and Moses [1] (hereafter B-M) indicating that 7 of the 30 Dow Jones Industrial stocks exhibited persistent seasonal patterns during the period July 1962 through June 1971.
Journal of Financial and Quantitative Analysis197813(1), 79
According to a now classic study of stock market price behavior by Fama [6], the empirical distributions of daily log price relatives are usually stable Paretian, non-Gaussian. However, there appears to have been substantial reluctance to accept Fama's [6] research results as indicative of a fundamental return generating process which is stable Paretian, non-Gaussian. Blattberg and Gonedes [1], Clarke [4], Officer [18], Praetz [19], and Press [20] have each in their own way questioned the Fama [6] results. Most recently Hsu, Miller, and Wichern (HMW) [13] have suggested that in periods of homogeneous activity for a firm the empirical distribution of rates of return on a common share may be Gaussian, in other words, that the fundamental return generating process may be normal.
Journal of Financial and Quantitative Analysis197813(2), 299
Cheng F. Lee, Frank C. Jen, Effects of Measurement Errors on Systematic Risk and Performance Measure of a Portfolio, The Journal of Financial and Quantitative Analysis, Vol. 13, No. 2 (Jun., 1978), pp. 299-312