We examine the volatility implications of around-the-clock foreign exchange trading with transaction data on futures contracts from the Chicago Mercantile Exchange and the London International Financial Futures Exchange. We find higher U.S.–European and U.S.–Japanese exchange-rate volatilities during U.S. trading hours and higher European cross-rate volatilities during European trading hours. While the disclosure of private information through trading may partly explain these volatility patterns, we conclude that the increased volatility is more likely driven by macroeconomic news announcements. An analysis of inter- and intraday data also reveals that volatility increases at times that coincide with the release of U.S. macroeconomic news.

This paper explores the recent decline in the fraction of unemployed workers who receive unemployment insurance benefits. Using March Current Population Surveys, we compare the fraction who are potentially eligible for benefits with the fraction who receive them. The decline in insured unemployment is almost entirely due to a decline in the early 1980s in the takeup rate for benefits. We analyze the determinants of the takeup rate, using both aggregated state-level data and micro-data. At least half the decline is due to an increasing share of unemployment in states with lower takeup rates.

This work examines the relation between option prices and the true, as opposed to risk-neutral, distribution of the underlying asset. If the underlying asset follows a diffusion with an instantaneous expected return at least as large as the instantaneous risk-free rate, observed option prices can be used to place bounds on the moments of the true distribution. An illustration of the paper's results is provided by the analysis of the information concerning the mean and standard deviation of market returns contained in the prices of S&P 100 Index Options. ALTHOUGH IT SEEMS NATURAL that the prices of claims to various parts of the underlying asset's distribution should contain information about the shape of that distribution, Cox and Ross (1976) established that an option's price equals its expected payoff discounted at the risk-free rate where the expectation is taken over the 'risk-neutral', rather than the true, distribution of the underlying asset. Linking the risk-neutral distribution implicit in option prices to the true distribution remains a comparative mystery. A necessary condition for the risk-neutral pricing methodology to be applicable is that the true and the risk-neutral distribution share a common support. The only information about the true distribution that can be obtained from observed option prices alone is information about that support. This paper demonstrates though that observed option prices, when used in conjunction with simple assume,d restrictions on the true distribution, do contain information about the noncentral moments of the true distribution not directly implied by those assumed restrictions alone.' The intuition for the result that option prices can be useful in placing bounds on the moments of the true distribution is straightforward. First, we generalize the results in Lo (1987) to show how the expected payoff to a call can be bounded above in terms of any chosen set of the noncentral moments of the return on the underlying asset. Second, we establish restrictions on the

This work examines the relation between option prices and the true, as opposed to risk‐neutral, distribution of the underlying asset. If the underlying asset follows a diffusion with an instantaneous expected return at least as large as the instantaneous risk‐free rate, observed option prices can be used to place bounds on the moments of the true distribution. An illustration of the paper's results is provided by the analysis of the information concerning the mean and standard deviation of market returns contained in the prices of S&P 100 Index Options.

This paper presents and implements statistical tests of stock-market forecastability and volatility that are immune from the severe statistical problems of earlier tests. It finds that although the null hypothesis of market efficiency is rejected, the rejections are only marginal. The paper also shows how volatility tests and recent regression tests are closely related, and demonstrates that when finite sample biases are taken into account, regression tests also fail to provide strong evidence of violations of the conventional valuation model.

In the authors' analysis of nonwork spells for Workers Compensation Insurance, they use the family of generalized gamma distributions for the structural model of failure time and both nonparametric and parametric controls for heterogeneity. These specifications allow for nested likelihood tests of not only the correct form for parametric heterogeneity, but for the structural distributions as well. The authors find in their data that while heterogeneity is important, both parametric and nonparametric types of control do about equally well. The "best" (in terms of statistical fit) structural distribution is the generalized gamma function; the exponential distribution fits especially poorly.

Michael D. Creel, John B. Loomis, Confidence Intervals for Welfare Measures with Application to a Problem of Truncated Counts, The Review of Economics and Statistics, Vol. 73, No. 2 (May, 1991), pp. 370-373