We use the term structure of futures prices to test whether investors anticipate mean reversion in spot asset prices. The empirical results indicate mean reversion in each market we examine. For agricultural commodities and crude oil the magnitude of the estimated mean reversion is large; for example, point estimates indicate that 44 percent of a typical spot oil price shock is expected to be reversed over the subsequent eight months. For metals, the degree of mean reversion is substantially less, but still statistically significant. We detect only weak evidence of mean reversion in financial asset prices.

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We use the term structure of futures prices to test whether investors anticipate mean reversion in spot asset prices. The empirical results indicate mean reversion in each market we examine. For agricultural commodities and crude oil the magnitude of the estimated mean reversion is large; for example, point estimates indicate that 44 percent of a typical spot oil price shock is expected to be reversed over the subsequent eight months. For metals, the degree of mean reversion is substantially less, but still statistically significant. We detect only weak evidence of mean reversion in financial asset prices. IN THIS STUDY, WE provide evidence of mean reversion in the prices of several real and financial assets. Rather than examining evidence of ex post reversion using time series of asset prices, we use price data from futures contracts with varying delivery horizons to test whether investors expect asset prices to revert. This approach offers two advantages. First, since futures prices are readily available for many markets, our procedure can be implemented for many assets, including those for which reliable spot price data is elusive. Second, there is little ambiguity as to the source of any mean reversion detected using our method. Subject only to the maintained assumption that the no-arbitrage cost-of-carry condition holds, our test detects mean reversion that is expected to occur in equilibrium, but has no power to detect mean reversion resulting from noise or inefficiencies.Our methodology focuses on relations between price levels and the slope of the futures term structure, defined as the change across delivery dates in the futures prices observed on a given trading date. An inverse relation between prices and the futures term slope constitutes evidence that investors expect mean reversion in spot prices. To illustrate, initially assume there are no The Journal of Finance futures risk premia, so that each futures price equals the trading date expectation of the delivery date spot price. The term structure of futures prices then describes several points on the path that investors expect the spot price will take. Detecting an inverse relation between price levels and the term slope then implies a lower rate of expected intertemporal price appreciation when prices rise, and vice versa. This is indicative of mean reversion.This approach has power to detect mean reversion, because a subset of the causes of mean reversion also affects the slope of the equilibrium futures term structure. The cost-of-carry or storage model of futures prices describes the futures term structure based on a no-arbitrage condition: the slope of the futures term structure equals the net cost of holding the asset in inventory between delivery dates. This net cost is comprised of the interest rate less the rate of benefit (dividend, coupon payment, or service flow net of storage costs) accruing to the marginal holder of the asset. We refer to this benefit as the implied cash flow yield.Given the cost-of-carry condition, our approach can de...

Executive SummaryWe suggest that the use of traditional market, outcome, and process controls for innovative derivatives trading may not provide adequate safeguards for clients, investors, or the entire financial system to control "purposeful unintended consequences." We propose a more cautious examination of this aspect of the financial system using a combination of perspectives from finance and technology/innovation management.

This paper uses a characteristics-based approach to examine the pattern of abnormal returns after seasoned equity offerings. Unlike previous studies the risk class of issuers are allowed to change in each of a series of six-month holding periods and firms are classified into categories based on performance measures, the use of proceeds and market conditions at the time of issue. This methodology reveals that negative abnormal returns persist for only about 3.5 years on average following offers and are driven by the 37% of firms that reduce capital spending. These and other results suggest that post-issue abnormal returns vary in a way that is consistent with quasi-efficient capital markets.

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