ABSTRACT A nonparametric statistical procedure is employed to examine the returns to speculators in wheat, corn, and soybeans futures markets. We find that the theory of normal backwardation is supported. Moreover, the presence of the risk premiums to speculators tends to be more prominent in recent years than in earlier years. We also find that large wheat speculators as a whole possessed some superior forecasting ability. The evidence is inconsistent with the hypothesis that commodity futures prices are unbiased estimates of the corresponding future spot prices.

A nonparametric statistical procedure is employed to examine the returns to speculators in wheat, corn, and soybeans futures markets. We find that the theory of normal backwardation is supported. Moreover, the presence of the risk premiums to speculators tends to be more prominent in recent years than in earlier years. We also find that large wheat speculators as a whole possessed some superior forecasting ability. The evidence is inconsistent with the hypothesis that commodity futures prices are unbiased estimates of the corresponding future spot prices.

This paper analyzes dual trading on futures contracts restricted by Chicago Mercantile Exchange Rule 552. Using floor trader data, several categories of traders are identified, and differences in strategies and profitability are examined. When unrestricted, dual traders execute most customer orders and few personal trades. The evidence supports the hypothesis that dual traders are superior brokers. However, there is no evidence of informational advantages in dual traders' personal trading. Dual traders are shown to provide liquidity with their personal trades. Finally, Rule 552 does not appear to have increased trading costs.Journal of Economic LiteratureClassification Numbers: G12, G13, D82.

Results of tests contrasting tax-loss selling with intertemporal information variation as explanations of the January seasonal in stock returns are reported. Closed-end fund shares display the typical size-related January seasonal while their net asset values do not. Interpreting the net asset value return as a proxy for information about underlying assets, this result indicates information variation is not a necessary condition for the January effect in stocks. The share returns at the turn of the year are negatively related to their mean preceding year returns and positively related to the standard deviations of their preceding year returns. These results are consistent with tax-loss selling.

This paper examines the pricing of exchange-traded long-term corporate bond portfolios. Observable instruments measuring the term structure of interest rates, levels of bond and stock prices, and a January dummy are found to predict excess returns on corporate bonds. An intertemporal asset pricing model with changing expectations and unobservable factors is then estimated for the predictable excess returns using Hansen's Generalized Method of Moments. The results show that a multibeta linear time-varying model of con? ditional expected returns with constant betas can successfully value corporate bonds. Spe? cifically, the tests indicate the presence of two time-varying hedge portfolios. The data, however, support a single latent variable specification when all January observations are excluded. This result suggests the existence of a strong January seasonal in one of the latent variables.

Despite nonstationarities in the factor betas and factor prices of the Chen, Roll, Ross (1986) multifactor model, investors are rewarded for bearing risks associated with the change in expected inflation and industrial production in non-January months; however, variations in these factors have opposite influences on stock prices. These findings may partially explain why several recent studies fail to detect a significant non-January risk premium in the stock market, but this evidence is only suggestive since theoretical and statistical difficulties prevent precise interpretations of specific pricing relations in the Chen, Roll, Ross model.

[Results of tests contrasting tax-loss selling with intertemporal information variation as explanations of the January seasonal in stock returns are reported. Closed-end fund shares display the typical size-related January seasonal while their net asset values do not. Interpreting the net asset value return as a proxy for information about underlying assets, this result indicates information variation is not a necessary condition for the January effect in stocks. The share returns at the turn of the year are negatively related to their mean preceding year returns and positively related to the standard deviations of their preceding year returns. These results are consistent with tax-loss selling.]

February and August peaks in the growth rates of the seasonally unadjusted Industrial Production Index follow the stock market peaks documented by Rozeff and Kinney (1976) by one month. Coefficients on one-month lead growth rates in industrial production for small firms are positive and significant in time-series regressions even in the presence of the market factor. Moreover, whereas returns on large firms' stocks unidirectionally Granger cause (i.e., predict) future growth rates in industrial production at least six months in advance, returns on small firms' stocks reflect one-month lead as well as past growth rates in industrial production. For these reasons, we argue that seasonal real growth provides a partial explanation for the January stock seasonal among small firms.