Patrick J. Kelly

Bio: Patrick J. Kelly is an academic researcher from University of Melbourne. The author has contributed to research in topics: Emerging markets & Hedge fund. The author has an hindex of 11, co-authored 26 publications receiving 1204 citations. Previous affiliations of Patrick J. Kelly include University of Florida & Temple University.

Do Market Efficiency Measures Yield Correct Inferences? A Comparison of Developed and Emerging Markets

Abstract: Using data from 56 markets, we find that short-term reversal, post-earnings drift, and momentum strategies earn similar returns in emerging and developed markets. Variance ratios and market delay measures often show greater deviations from random walk pricing in developed markets. Conceptually, we show that commonly used efficiency tests can yield misleading inferences because they do not control for the information environment. Our evidence corrects misperceptions that emerging markets feature larger trading profits and higher return autocorrelation, highlights crucial limitations of weak and semi-strong form efficiency measures, and points to the importance of measuring informational aspects of efficiency. © The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved.

How Important Is the Financial Media in Global Markets

Abstract: This article studies differences in the information content of 870,000 news announcements in 56 markets around the world. In most developed markets, a firm’s stock price moves much more on days with public news about the firm. In contrast, in many emerging markets volatility is similar on news and non-news days. We examine several hypotheses for our findings. Cross-country differences in stock price reactions are best explained by insider trading, followed by differences in the quality of the news dissemination mechanism. Our findings are useful for quantifying the extent of insider trading and how the financial media affects international markets. ( JEL G14, G15) Public news announcements are a major mechanism for disseminating information to investors. Each day the financial media releases thousands of articles covering companies in markets worldwide. Investors use this news to estimate assets’ fundamental values. Despite the perceived importance of the

Information Efficiency and Firm-Specific Return Variation

Abstract: Reasoning that private firm-specific information causes firm-specific return variation that drives down market-model R2s, [Morck et al., 2000, The Information Content of Stock Markets: Why do Emerging Markets have Synchronous Stock Price Movements? Journal of Financial Economics, 58, 215–260] begin a large body of research which interprets R2 as an inverse measure of price informativeness. Low-R2s or "synchronicity," as it is called in this literature, signal that prices more efficiently incorporate private firm-specific information, and high R2s indicate less. For this to be true, we would expect that low-R2 stocks have characteristics that facilitate private informed trade, i.e., lower information costs and fewer impediments to arbitrage. However, in this paper we document the opposite: Low-R2 stocks are small, young, and followed by few analysts, and have high bid-ask spreads, high price impact, greater short-sale constraints and are infrequently traded. In fact, microstructure measures suggest that private-information events are less likely for low-R2 stocks than high, and that differences in R2 are driven as much by firm-specific volatility on days without private news as by firm-specific volatility on days with private news. These results call into question prior research using R2 to measure the information content of stock prices.

Information Efficiency and Firm-Specific Return Variation

Abstract: Reasoning that private firm-specific information causes firm-specific return variation that drives down market-model R2s, Morck, Yeung, and Yu (2000) begin a large body of research which interprets R2 as an inverse measure of price informativeness. Low R2s or “synchronicity,” as it is called in this literature, signal that prices more efficiently incorporate private firm-specific information, and high R2s indicate less. For this to be true, we would expect that low-R2 stocks have characteristics that facilitate private informed trade, i.e. lower information costs and fewer impediments to arbitrage. However, in this paper we document the opposite: Low-R2 stocks are small, young, and followed by few analysts, and have high bid-ask spreads, high price impact, greater short-sale constraints and are infrequently traded. In fact, microstructure measures suggest that private-information events are less likely for low-R2 stocks than high, and that differences in R2 are driven as much by firm-specific volatility on days without private news as by firm-specific volatility on days with private news. These results call into question prior research using R2 to measure the information content of stock prices.

Sentiment and Stock Returns: The SAD Anomaly Revisited

Abstract: Widely-cited research by Kamstra et al. (2003) argues that changes in mood resulting from Seasonal Affective Disorder (SAD) drive changes in investor risk aversion and cause seasonal patterns in aggregate stock returns around the world. In this paper we reexamine the so-called SAD effect by replicating and extending Kamstra et al. (2003). We study the psychological underpinnings of the SAD hypothesis and show that the time-series predictions of the SAD model do not correspond to the seasonal patterns in depression found in the general population. We also investigate the cross-sectional prediction that SAD has a greater effect on stock markets in countries where SAD is more prevalent and find no relation between the prevalence of SAD and stock returns. Finally, we document that the SAD effect is mechanically driven by an overlapping dummy-variable specification and higher returns around the turn of the year.

A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Prices

Abstract: We develop a bid-ask spread estimator from daily high and low prices. Daily high (low) prices are almost always buy (sell) trades. Hence, the high-low ratio reflects both the stock’s variance and its bid-ask spread. While the variance component of the high-low ratio is proportional to the return interval, the spread component is not. This allows us to derive a spread estimator as a function of high-low ratios over one-day and two-day intervals. The estimator is easy to calculate, can be applied in a variety of research areas, and generally outperforms other low-frequency estimators.

Sentiment during Recessions

Abstract: This paper studies the effect of sentiment on asset prices during the 20th century (1905 to 2005). As a proxy for sentiment, we use the fraction of positive and negative words in two columns of financial news from the New York Times. The main contribution of the paper is to show that, controlling for other well-known time-series patterns, the predictability of stock returns using news' content is concentrated in recessions. A one standard deviation shock to our news measure during recessions predicts a change in the conditional average return on the DJIA of 12 basis points over one day.

A Simple Way to Estimate Bid-Ask Spreads from Daily High and Low Prices

Abstract: We develop a bid-ask spread estimator from daily high and low prices. Daily high (low) prices are almost always buy (sell) trades. Hence, the high–low ratio reflects both the stock's variance and its bid-ask spread. Although the variance component of the high–low ratio is proportional to the return interval, the spread component is not. This allows us to derive a spread estimator as a function of high–low ratios over 1-day and 2-day intervals. The estimator is easy to calculate, can be applied in a variety of research areas, and generally outperforms other low-frequency estimators.

The Information Content of Annual Earnings Announcements and Mandatory Adoption of IFRS

Abstract: This study examines whether the information content of earnings announcements--abnormal return volatility and abnormal trading volume -- increases in countries following mandatory IFRS adoption, and conditions and mechanisms through which increases occur. Findings suggest information content increased in 16 countries that mandated adoption of IFRS relative to 11 that maintained domestic accounting standards, although the effect of mandatory IFRS adoption depends on the strength of legal enforcement in the adopting country. Utilizing a path analysis methodology, we find evidence of three mechanisms through which IFRS adoption increases information content: reducing reporting lag, increasing analyst following, and increasing foreign investment.