Nikolaos T. Milonas* he hypothesis that price variability increases as time to maturity nears-the T so-called "maturity effect"-has important implications on the behavior of futures prices. This article derives the theoretical basis for this effect in line with Samuelson's (1965) arguments, develops a methodology which tests this issue, and provides strong empirical support for the maturity effect based on 11 futures markets. Samuelson (1965) was the first to theoretically advance the maturity-effect hypothesis. He argues simply that the variability of prices increases monotonically as the contract approaches maturity. The non-convincing success in testing empirically this issue by earlier researchers (Rutledge, 1976 andMiller, 1979) led to two studies with better methodology (Castelino, 1981 andAnderson, 1985). The latter studies find strong evidence that time to maturity is an important determinant of the behavior of variability of futures prices.
The methodology of the present study takes into account the various nonstationarities ("month effect", "year effect", and "contract month effect") in spot and futures prices. We calculate price variability as variances over daily price changes within a month and record the number of months left to maturity for that contract. We adjust these variances for the three effects mentioned above and utilize parametric and non-parametric techniques that test for significant differences in variability among the different time to maturity groups of variances. We also estimate an equation in the model which derives the testable hypothesis of increasing price variability as contract maturity nears. *This study draws largely from my dissertation thesis at the City University of New York. I am grateful to Ashok Vora (chairman) for his invaluable comments and suggestions. I also thank the members of my committee, Steven Lustgarten, George Papaioannou, Joel Rentzler, Kishore Tandon and Stavros Thomadakis for helpful comments and criticism. All remaining errors are mine. I am grateful to CSFM of Columbia University for financial support and data provision.