Craig W. Holden

Bio: Craig W. Holden is an academic researcher from Indiana University. The author has contributed to research in topics: Market liquidity & Capital asset pricing model. The author has an hindex of 23, co-authored 64 publications receiving 4404 citations. Previous affiliations of Craig W. Holden include Purdue University.

Long-Lived Private Information and Imperfect Competition

Abstract: We develop a multi-period auction model in which multiple privately informed agents strategically exploit their long-lived information. We show that such traders compete aggressively and cause most of their common private information to be revealed very rapidly. In the limit as the interval between auctions approaches zero, market depth becomes infinite and all private information is revealed immediately. These results are in contrast to those of Kyle (1985) in which the monopolistic informed trader causes his information to be incorporated into prices gradually, and, when the interval between auctions is vanishingly small, market depth is constant over time. FAMA (1970) DEFINES A "STRONG form" efficient market as one in which security prices fully reflect all available information, including both publicly and privately held information. In a pioneering and influential article, Kyle (1985) develops a model in which a single privately informed trader with long-lived information optimally exploits his monopoly power over time. Kyle's (1985) main results are: (i) the informed trader trades in a gradual manner, so that his information is incorporated into prices at a slow, almost linear rate, and (ii) when auctions are held continuously, the depth of the market is constant over time. However, Kyle's (1985) assumption of a single informed trader is strong, in the sense that in actual financial markets, it is reasonable to expect that at least a few players will have access to private information and will trade in the knowledge that they will face competition with other informed agents in the market. 1 We develop a multi-period auction model in which multiple (strategic) informed traders optimally exploit their long-lived informational advantage. We thus explore the restrictiveness of Kyle's assumption of a single informed trader, and also examine

What Are the Best Liquidity Proxies for Global Research

Abstract: Liquidity plays an important role in global research. We identify high quality liquidity proxies based on low-frequency (daily) data, which provide 1,000X to 10,000X computational savings compared to computing high-frequency (intraday) liquidity measures. We find that: (1) Closing Percent Quoted Spread is the best monthly percent-cost proxy when available, (2) Amihud, Closing Percent Quoted Spread Impact, LOT Mixed Impact, High-Low Impact, and FHT Impact are tied as the best monthly cost-per-dollar-volume proxy, (3) the daily version of Closing Percent Quoted Spread is the best daily percent-cost proxy, and (4) the daily version of Amihud is the best daily cost-per-dollar-volume proxy.

Liquidity Measurement Problems in Fast, Competitive Markets: Expensive and Cheap Solutions

Abstract: Do fast, competitive markets yield liquidity measurement problems when using the popular Monthly Trade and Quote (MTAQ) database? Yes. MTAQ yields distorted measures of spreads, trade location, and price impact compared with the expensive Daily Trade and Quote (DTAQ) database. These problems are driven by (1) withdrawn quotes, (2) second (versus millisecond) time stamps, and (3) other causes, including canceled quotes. The expensive solution, using DTAQ, is first-best. For financially constrained researchers, the cheap solution—using MTAQ with our new Interpolated Time technique, adjusting for withdrawn quotes, and deleting economically nonsensical states—is second-best. These solutions change research inferences.

What Are The Best Liquidity Proxies For Global Research

Abstract: We compare liquidity proxies constructed from low-frequency (daily) stock data to liquidity benchmarks computed from high-frequency (intraday) data for 18,472 firms on 43 exchanges around the world from January 1996 to December 2007. We evaluate eight percent-cost proxies (including a new one) relative to four percent-cost benchmarks: percent effective spread, percent quoted spread, percent realized spread, and percent price impact. We examine eleven cost-per-volume proxies (including a new one) relative to a costper-volume benchmark: the slope of the price function “lambda.” We test these proxies on three performance dimensions: average cross-sectional correlation with the benchmarks, portfolio correlations with the benchmarks, and prediction accuracy. We find that a new proxy, FHT, strongly dominates prior percent cost proxies. It is highly correlated with percent effective spread, percent quoted spread, percent realized spread, and percent price impact. It captures the level of percent effective spread and percent quoted spread, but does not capture the level of percent realized spread or percent price impact. We find that the best cost-per-volume proxies are FHT Impact, Zeros Impact, and Amihud. All three are highly correlated with lambda, but do not capture the level of lambda. Finally, we find that lower synchronicity, higher disclosure, lower turnover, and greater likelihood of prosecuting insider trading lead to higher performance of the best liquidity proxies.

Market Liquidity: Asset Pricing with Liquidity Risk

Abstract: This paper solves explicitly a simple equilibrium model with liquidity risk. In our liquidityadjusted capital asset pricing model, a security s required return depends on its expected liquidity as well as on the covariances of its own return and liquidity with the market return and liquidity. In addition, a persistent negative shock to a security s liquidity results in low contemporaneous returns and high predicted future returns. The model provides a unified framework for understanding the various channels through which liquidity risk may affect asset prices. Our empirical results shed light on the total and relative economic significance of these channels and provide evidence of flight to liquidity. r 2005 Elsevier B.V. All rights reserved.

The Microstructure Approach to Exchange Rates

Abstract: Historically, the fields of exchange-rate economics and microstructure finance have progressed independently of each other. Recent interaction, however, has given rise to a microstructure approach to exchange rates. This book focuses on the economics of financial information and how microstructure tools help to clarify the types of information most relevant to exchange rates. The microstructure approach views exchange rates from the perspective of the trading room, the place where exchange rates are actually determined. Emphasizing information economics over institutional issues, the approach departs from three unrealistic assumptions common to previous approaches: that all information relevant to exchange rates is publicly available, that all market participants are alike in their goals or in how they view information, and that how trading is organized is inconsequential for exchange rates. The book shows how exchange-rate behavior previously thought to be particularly puzzling can be explained using the microstructure approach. It contains a combination of theoretical and empirical work.

Transactions, Volume, and Volatility

Abstract: We show that the positive volatility-volume relation documented by numerous researchers actually reflects the positive relation between volatility and the number of transactions. Thus, it is the occurrence of transactions per se, and not their size, that generates volatility; trade size has no information beyond that contained in the frequency of transactions. Our results suggest that theoretical research needs to entertain scenarios in which (1) both the frequency and size of trades are endogenously determined, yet (2) the size of trades has no information content beyond that contained in the number of transactions. Article published by Oxford University Press on behalf of the Society for Financial Studies in its journal, The Review of Financial Studies.