This paper uses the pricing models of Cox, Ingersoll and Ross (1981), Richard and Sundaresan (1981), and French (1982) to examine the relation between futures and forward prices for copper and silver. There are significant differences between these prices. The average differences are generally consistent with the predictions of the futures and forward price models. However, these models are not helpful in describing intra-sample variations in the futures-forward price differences. This failure is apparently caused by measurement errors in both the price differences and in the explanatory variables.

This paper examines two alternative models of the process generating stock returns. Under the calendar time hypothesis, the process operates continuously and the expected return for Monday is three times the expected return for other days of the week. Under the trading time hypothesis, returns are generated only during active trading and the expected return is the same for each day of the week. During most of the period studied, from 1953 through 1977, the daily returns to the Standard and Poor's composite portfolio are inconsistent with both models. Although the average return for the other four days of the week was positive, the average for Monday was significantly negative during each of five-year subperiods.

Abstract Value premiums, which we define as value portfolio returns in excess of market portfolio returns, are on average much lower in the second half of the July 1963–June 2019 period. But the high volatility of monthly premiums prevents us from rejecting the hypothesis that expected premiums are the same in both halves of the sample. Regressions that forecast value premiums with book-to-market ratios in excess of market (BM–BMM) produce more reliable evidence of second-half declines in expected value premiums, but only if we assume the regression coefficients are constant during the sample period. Received: January 21, 2020; editorial decision: July 21, 2020; Editor: Jeffrey Pontiff.

We use bootstrap simulations to examine the properties of long-horizon U.S. stock market returns. We document the rate at which continuously compounded market returns converge toward normal distributions as we extend the horizon from 1 month to 30 years, and the rate at which dollar payoffs converge toward lognormal. We also verify that, though largely irrelevant at short horizons, uncertainty about the expected market return has a substantial impact on uncertainty about long-horizon payoffs. Received date May 18, 2017; Accepted date December 26, 2017 By Editor Raman Uppal

ABSTRACT I compare the fees, expenses, and trading costs society pays to invest in the U.S. stock market with an estimate of what would be paid if everyone invested passively. Averaging over 1980–2006, I find investors spend 0.67% of the aggregate value of the market each year searching for superior returns. Society's capitalized cost of price discovery is at least 10% of the current market cap. Under reasonable assumptions, the typical investor would increase his average annual return by 67 basis points over the 1980–2006 period if he switched to a passive market portfolio.

Asset prices are much more volatile during exchange trading hours than during non-trading hours. This paper considers three explanations for this phenomenon: (1) volatility is caused by public information which is more likely to arrive during normal business hours; (2) volatility is caused by private information which affects prices when informed investors trade; and (3) volatility is caused by pricing errors that occur during trading. Although a significant fraction of the daily variance is caused by mispricing, the behavior of returns around exchange holidays suggests that private information is the principle factor behind high trading-time variances.

Much of Mike Jensen's research is foundational, including his early publications, which focus on empirical asset pricing. For example, Jensen's alpha, which he developss in Jensen (1968 and 1969) to evaluate mutual fund managers, is the foundation for most measures of investment performance. Similarly, in Fama et al (1969), Jensen and coauthors present the first event study, Thereafter, event studies play a major role in finance, accounting, and legal research. Finally, Black, Jensen, and Scholes (1972) develop a key insight about the importance of interdependence of sampling errors in the precision of asset pricing tests.

Our goal is to develop insights about the maximum squared Sharpe ratio for model factors as a metric for ranking asset pricing models. We consider nested and non-nested models. The nested models are the capital asset pricing model, the three-factor model of Fama and French (1993), the five-factor extension in Fama and French (2015), and a six-factor model that adds a momentum factor. The non-nested models examine three issues about factor choice in the six-factor model: (1) cash profitability versus operating profitability as the variable used to construct profitability factors, (2) long-short spread factors versus excess return factors, and (3) factors that use small or big stocks versus factors that use both.