Author
Maureen O'Hara
Other affiliations: University of Technology, Sydney, Saint Petersburg State University
Bio: Maureen O'Hara is an academic researcher from Cornell University. The author has contributed to research in topics: Market liquidity & Market microstructure. The author has an hindex of 72, co-authored 165 publications receiving 32631 citations. Previous affiliations of Maureen O'Hara include University of Technology, Sydney & Saint Petersburg State University.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, the authors investigate the role of information in affecting a firm's cost of capital using a multi-asset rational expectations model and show that differences in the composition of information between public and private information affect the cost of investment, with investors demanding a higher return to hold stocks with greater private information.
Abstract: We investigate the role of information in affecting a firm's cost of capital. Using a multi-asset rational expectations model, we show that differences in the composition of information between public and private information affect the cost of capital, with investors demanding a higher return to hold stocks with greater private information. This higher return arises because informed investors are better able to shift their portfolio weights to incorporate new information, and uninformed investors are thus disadvantaged. The model demonstrates how in equilibrium the quantity and quality of information affect asset prices, resulting in cross-sectional differences in firms' required returns. We show how a firm can influence its cost of capital by choosing features like accounting treatments, financial analyst coverage, and market microstructure.
2,415 citations
TL;DR: In this paper, the effect of trade size on security prices was investigated and it was shown that informed traders tend to trade larger amounts at any given price, and market makers' pricing strategies must also depend on trade size.
2,287 citations
TL;DR: In this article, the authors investigate the role of information in affecting a firm's cost of capital, and they show that differences in the composition of information between public and private information affect the costs of capital.
Abstract: We investigate the role of information in affecting a firm's cost of capital. We show that differences in the composition of information between public and private information affect the cost of capital, with investors demanding a higher return to hold stocks with greater private information. This higher return arises because informed investors are better able to shift their portfolio to incorporate new information, and uninformed investors are thus disadvantaged. In equilibrium, the quantity and quality of information affect asset prices. We show firms can influence their cost of capital by choosing features like accounting treatments, analyst coverage, and market microstructure.
2,082 citations
TL;DR: In this paper, the authors investigated whether differences in information-based trading can explain observed differences in spreads for active and infrequently traded stocks and found that the probability of information based trading is lower for high volume stocks.
Abstract: This article investigates whether differences in information-based trading can explain observed differences in spreads for active and infrequently traded stocks. Using a new empirical technique, we estimate the risk of information-based trading for a sample of New York Stock Exchange (NYSE) listed stocks. We use the information in trade data to determine how frequently new information occurs, the composition of trading when it does, and the depth of the market for different volume-decile stocks. Our most important empirical result is that the probability of information-based trading is lower for high volume stocks. Using regressions, we provide evidence of the economic importance of information-based trading on spreads.
1,574 citations
Book•
06 Apr 1995
TL;DR: In this article, the authors present two types of strategic traders: informed traders and uninformed traders, based on information-based models: Informed traders are those who make decisions based on their knowledge of the market.
Abstract: Foreword. 1. Markets and Market--Making. 2. Inventory Models. 3. Information--Based Models. 4. Strategic Trader Models I: Informed Traders. 5. Strategic Trader Models II: Uninformed Traders. 6. Information and the Price Process. 7. Market Viability and Stability. 8. Liquidity and the Relationships between Markets. 9. Issues in Market Performance.
1,567 citations
Cited by
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TL;DR: In this article, the authors examine the different methods used in the literature and explain when the different approaches yield the same (and correct) standard errors and when they diverge, and give researchers guidance for their use.
Abstract: In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions to this problem. Corporate finance has relied on clustered standard errors, while asset pricing has used the Fama-MacBeth procedure to estimate standard errors. This paper examines the different methods used in the literature and explains when the different methods yield the same (and correct) standard errors and when they diverge. The intent is to provide intuition as to why the different approaches sometimes give different answers and give researchers guidance for their use.
7,647 citations
TL;DR: In this article, the authors show that expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock ex ante excess return partly represents an illiquid price premium, which complements the cross-sectional positive return-illiquidity relationship.
5,636 citations
TL;DR: In this paper, the effects of stock illiquidity on stock return have been investigated and it was shown that expected market illiquidities positively affects ex ante stock excess return (usually called risk premium) over time.
Abstract: New tests are presented on the effects of stock illiquidity on stock return. Over time, expected market illiquidity positively affects ex ante stock excess return (usually called â¬Srisk premiumâ¬?). This complements the positive cross-sectional return-illiquidity relationship. The illiquidity measure here is the average daily ratio of absolute stock return to dollar volume, which is easily obtained from daily stock data for long time series in most stock markets. Illiquidity affects more strongly small firms stocks, suggesting an explanation for the changes â¬Ssmall firm effectâ¬? over time. The impact of market illiquidity on stock excess return suggests the existence of illiquidity premium and helps explain the equity premium puzzle.
5,333 citations
TL;DR: This paper found that the majority of managers would avoid initiating a positive NPV project if it meant falling short of the current quarter's consensus earnings, and more than three-fourths of the surveyed executives would give up economic value in exchange for smooth earnings.
4,341 citations
TL;DR: In this article, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using ARCH and stochastic volatility models and it has been shown that volatility models produce strikingly accurate inter-daily forecasts for the latent volatility factor that would be of interest in most financial applications.
Abstract: A voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using ARCH and stochastic volatility models. While most of these studies have documented highly significant in-sample parameter estimates and pronounced intertemporal volatility persistence, traditional ex-post forecast evaluation criteria suggest that the models provide seemingly poor volatility forecasts. Contrary to this contention, we show that volatility models produce strikingly accurate interdaily forecasts for the latent volatility factor that would be of interest in most financial applications. New methods for improved ex-post interdaily volatility measurements based on high-frequency intradaily data are also discussed.
3,174 citations