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.

No abstract

No abstract

While limited attention has been analyzed in a variety of economic and psychological settings, its impact on financial markets is not well understood. In this paper, we examine individual NYSE specialist portfolios and test whether liquidity provision is affected as specialists allocate their attention across stocks. Our results indicate that specialists allocate effort toward their most active stocks during periods of increased activity, resulting in less frequent price improvement and increased transaction costs for their remaining assigned stocks. Thus, the allocation of effort due to limited attention has a significant impact on liquidity provision in securities markets. Copyright (c) 2008 The American Finance Association.

No abstract

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...

We examine the inf luence of NYSE specialist firm organizational form on the nature of liquidity provision. We compare closely held firms whose specialists provide liquidity with their own capital to widely held firms whose specialists provide liquidity with diffusely owned capital. We argue that specialists using their own capital have a greater incentive and ability to reduce adverse selection costs, but face a greater cost of capital. Differences in the proportion of spreads due to adverse selection costs, large trade frequency, the sensitivity between depth and spreads, and price stabilization support this argument.RECENT STUDIES BY CAO, CHOE, and Hatheway~1997! and Corwin~1999a! document differences across specialist firms in execution costs, trading halts due to order imbalances, and market stabilization. Why these differences in liquidity provision exist, however, is not well understood. We argue that differences in liquidity provision arise from differences in specialist firm organizational form; firms that make markets with capital supplied by their specialists~owner-specialist firms! offer economies with respect to asymmetric information costs, while firms that make markets with diffusely owned capital~employee-specialist firms! offer economies with respect to capital costs. Our empirical results support this argument.Since March 1997, the NYSE has allowed listing firms to choose which specialist firm handles their stock from a pool provided by the NYSE Allocations Committee~New York Stock Exchange~1997!!. Like the choice of debt, dividend, or compensation policies, the choice of a specialist firm po-

This paper provides a review of empirical research in four topics within the area of market microstructure. Specifically, the paper provides an overview of issues related to (a) the estimation of the components of the bid-ask spread, (b) the effects of order flow characteristics and regulations on market liquidity, (c) the differences and similarities between the NYSE and the Nasdaq and (d) the interaction between the options and underlying stock markets.Keywords: bid-ask spreads, components of spreads, order flow, Nasdaq, derivative and underlying market interactions JEL classifications: GlO/G12/G13/G14