Abstract not found

Financial press reports claim that internet stock message boards can move markets. We study the effect of more than 1.5 million messages posted on Yahoo! Finance and Raging Bull about the 45 companies in the Dow Jones Industrial Average, and the Dow Jones Internet Index. The bullishness of the messages is measured using computational linguistics methods. News stories reported in the Wall Street Journal are used as controls. We find significant evidence that the stock messages help predict market volatility, but not stock returns. Consistent with Harris and Raviv (1993), agreement among the posted messages is associated with decreased trading volume. (JEL: G12, G14)

Given the cross-sectional and temporal variation in their liquidity, emerging equity markets provide an ideal setting to examine the impact of liquidity on expected returns. Our main liquidity measure is a transformation of the proportion of zero daily firm returns, averaged over the month. We find that it significantly predicts future returns, whereas alternative measures such as turnover do not. Consistent with liquidity being a priced factor, unexpected liquidity shocks are positively correlated with contemporaneous return shocks and negatively correlated with shocks to the dividend yield. We consider a simple asset pricing model with liquidity and the market portfolio as risk factors and transaction costs that are proportional to liquidity. The model differentiates between integrated and segmented countries and time periods. Our results suggest that local market liquidity is an important driver of expected returns in emerging markets, and that the liberalization process has not fully eliminated its impact.

We build a model that helps explain why increases in liquidity⎯such as lower bid-ask spreads, a lower price impact of trade, or higher turnover⎯predict lower subsequent returns in both firm-level and aggregate data. The model features a class of irrational investors, who underreact to the information contained in order flow, thereby boosting liquidity. In the presence of short-sales constraints, high liquidity is a symptom of the fact that the market is dominated by these irrational investors, and hence is overvalued. This theory can also explain how managers might successfully time the market for seasoned equity offerings, by simply following a rule of thumb that involves issuing when the SEO market is particularly liquid. Empirically, we find that: i) aggregate measures of equity issuance and share turnover are highly correlated; yet ii) in a multiple regression, both have incremental predictive power for future equal-weighted market returns.

In this paper we examine whether and how accounting information about a firm manifests in its cost of capital, despite the forces of diversification. We build a model that is consistent with the CAPM and explicitly allows for multiple securities whose cash flows are correlated. We demonstrate that the quality of accounting information can influence the cost of capital, both directly and indirectly. The direct effect occurs because higher quality disclosures affect the firm’s assessed covariances with other firms ’ cash flows, which is non-diversifiable. The indirect effect occurs because higher quality disclosures affect a firm’s real decisions, which likely changes the firm’s ratio of the expected future cash flows to the covariance of these cash flows with the sum of all the cash flows in the market. We show that this effect can go in either direction, but also derive conditions under which an increase in information quality leads to an unambiguous decline the cost of capital.

This paper explores liquidity movements in stock and Treasury bond markets over a period of more than 1800 trading days. Cross-market dynamics in liquidity are documented by estimating a vector autoregressive model for liquidity (that is, bid-ask spreads and depth), returns, volatility, and order flow in the stock and bond markets. We find that a shock to quoted spreads in one market affects the spreads in both markets, and that return volatility is an important driver of liquidity. Innovations to stock and bond market liquidity and volatility prove to be significantly correlated, suggesting that common factors drive liquidity and volatility in both markets. Monetary expansion increases equity market liquidity during periods of financial crises, and unexpected increases (decreases) in the federal funds rate lead to decreases (increases) in liquidity and increases (decreases) in stock and bond volatility. Finally, we find that flows to the stock and government bond sectors play an important role in forecasting stock and bond liquidity. The results establish a link between “macro” liquidity, or money flows, and “micro” or transactions liquidity.

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The Morning Call and Midday Call segments on CNBC TV provide a unique opportunity to study the efficient market hypothesis. The segments report analysts ’ views about individual stocks and are broadcast when the market is open. We find that prices respond to reports within seconds of initial mention, with positive reports fully incorporated within one minute. Trading intensity doubles in the first minute, with a significant increase in buyer- (seller-) initiated trades after positive (negative) reports. Traders who execute within 15 seconds of the initial mention make small but significant profits by trading on positive reports during the

The views and opinions expressed in this article are those of the authors only, and do not necessarily represent the views and opinions of AlphaSimplex Group, MIT, the NBER, any of their affiliates and employees, or any of the individuals acknowledged below. The authors make no representations or warranty, either expressed or implied, as to the accuracy or completeness of the information contained in this article, nor are they recommending that this article serve as the basis for any investment decision---this article is for information purposes only. We thank Paul Bennett, Kent Daniel, Pankaj Patel, Steve Poser,

This article investigates the dynamic relation between market-wide trading activity and returns in 46 markets. Many stock markets exhibit a strong positive relation between turnover and past returns. These findings stand up in the face of various controls for volatility, alternative definitions of turnover, differing sample periods, and are present at both the weekly and daily frequency. The relation is more statistically and economically significant in countries with high levels of corruption, with short-sale restrictions, and in which market volatility is high. Do investors trade more when markets have done well in the recent past? If their trading relates to past returns, why do they behave that way? Answering these questions is important to our understanding of the determinants of trading volume, liquidity, and stock returns. Further-more, answers to these questions can help market makers and liquidity providers obtain forecasts of trading intensity, portfolio managers devise efficient trading strategies, and regulators and policymakers find ways to improve the liquidity and efficiency of financial markets.