Analyst recommendations and investment strategies in ADRs: star and non-star reputation

Sell-side analysts have become one of the key intermediaries in the capital markets linking investors and publicly traded corporations. The importance of sell-side analysts has developed since late 90th, when sell-side research market was valued in billion dollars. During this period media started to question the inner value of analysts reports and the content of the report, that is recommendations, earning estimates, and target price revisions. Specifically, they were blamed for receiving huge compensation for being lucky, because under efficient market hypothesis, it is impossible to generate access returns. Following the rising media concern, academic community started to study the nature of sell-side analysts and their reports. First, scholars were interested whether analyst recommendations, target price revisions are able to impact the stock prices, without mentioning the profitability pattern. Having proved that analyst recommendations are able to change stock prices, the next topic of interest was whether the stock reaction to analyst recommendation results in profitability, which is higher than the market return (e.g., S&P 500). In continuation, more and more studies appeared linking recommendation profitability with various analyst and brokerage house related attributes, such as reputation, size of the brokerage house etc. However, there is no strict conclusions on the analyst performance and recommendation profitability since scholars used different samples, methods, or rankings. As a continuation of recent studies, this paper examines whether the analysts’ recommendations can generate abnormal return and whether the analysts ranked as Stars in StarMine’s “Top Stock Pickers” and “Top Earnings Estimators” rankings make more profitable recommendations in comparison to Non-Star group. Previously, only one paper compared 3 different rankings and concluded that rankings issues by Institutional Investor magazine - which are most often utilized in the literature - are subjective. Hence, this study is the second to utilize StarMine’s objective ranking’s hand-collected data. The sample of the research is narrowed to American Depositary Stock receipts to see whether recommendations differently touch the stocks of foreign companies. By applying buy-and-hold calendar-time-portfolios methodology with 30-day holding period, 2 portfolios (Long and Short) are formed for each Stars, Non-stars, and Star-1 groups resulting in 6 portfolios. The access returns of the portfolios are calculated using Fama-French 3/5/6 factor models with different risk factors. The results suggest that in the Long portfolio, Stars underperform Non-stars, while in the Short portfolio Stars and both Star-1 outperform Non-stars. The reason behind underperforming Stars in Long portfolio is mostly explained by risk-aversion of Stars in recommending risky stocks, while Non-stars “have nothing to lose” and take higher risk by recommending large number of ADRs. The same explains the outperformance of Stars in Short portfolio since Stars tend to conduct advanced research before shorting risky stocks

Loan Portfolio Risk and Capital Adequacy: A New Approach to Evaluating the Riskiness of Banks

We develop a Loan Portfolio Risk (LPR) variable that measures time-varying volatility in default risk for a portfolio of bank loans. An Equity-to-LPR ratio (ELPR) is incrementally important in predicting bank failure up to five years in advance, even after controlling for all the CAMELS variables. Publicly-listed banks with higher ELPR have lower market implied costs-of-capital. ELPR also strongly predicts cross-sectional stock returns under stress conditions. During the financial crisis (7/2007-6/2011), a cash-neutral strategy that longs high-ELPR and shorts low-ELPR banks yields a monthly alpha of 3.3% to 4.2%. We conclude LPR captures key aspects of bank risk missed by a risk-weighted-asset approach

Short-term Momentum

We document a striking pattern in U.S. and international stock returns: double sorting on the previous month’s return and share turnover reveals significant short-term reversal among low-turnover stocks, whereas high-turnover stocks exhibit short-term momentum. Short-term momentum is as profitable and as persistent as conventional price momentum. It survives transaction costs and is strongest among the largest, most liquid, and most extensively covered stocks. Our results are difficult to reconcile with models imposing strict rationality but are suggestive of an explanation based on some traders underappreciating the information conveyed by prices

Essays on Trust and Its Economic Consequences

Ph.D

Two Essays on Investor Disagreement and Asset Prices

My dissertation studies the measurement of investor disagreement and the effects of investor disagreement on asset prices. In my first essay, I clarify the seemingly contradicting theoretical predictions of Miller (1977), and Varian (1985, 1989) and Abel (1989), and design empirical analysis to test the predictions in a unified framework. Miller models the effect of the level of disagreement on asset prices and predicts a negative relation between investor disagreement and subsequent asset returns. Varian and Abel present results on the effect of the change in disagreement on asset prices and the resulting positive relation between disagreement and subsequent asset returns. I find that, consistent with Varian (1985) and Abel (1989), increases (decreases) in disagreement are always associated with lower (higher) contemporaneous stock returns, regardless of the prior levels of disagreement. Because the level of investor disagreement is highly persistent, stocks with high prior levels of disagreement earn lower subsequent returns as disagreements on these stocks remain high or continue to increase. Consequently, changes in investor disagreement and their impact on stock prices, not overvaluation as in Miller (1977), drive the relation between investor disagreement and subsequent stock returns documented in the existing literature. Empirical analyses based on changing short-sale constraints and earnings announcements provide further support to the central role of changing investor disagreement in asset pricing. In my second essay, I emphasize and examine the role of the consensus investor opinion in the relation between heterogeneous investor beliefs and stock prices, which is largely overlooked in the prior empirical literature. I measure investors\u27 opinions based on financial analysts\u27 stock recommendations and study how both investors\u27 opinions and their disagreement jointly affect stock prices. I show that the consensus opinion is at least as important as the dispersion of opinion in predicting stock returns. When the consensus opinion is pessimistic, investor disagreement leads to lower stock returns, but the opposite is true when the consensus opinion is optimistic. Moreover, strong investor agreement predicts stock returns and largely drives the return difference between high- and low-agreement stocks. In supporting evidence, I show that both the investor opinion and its dispersion are related to short-sale constraints and strong optimistic agreement is significantly associated with binding short-sale constraints

Disagreement, underreaction, and stock returns

2016-2017 > Academic research: refereed > Publication in refereed journalbcrcAccepted ManuscriptRGCRGC: 644212Publishe

Disagreement, underreaction, and stock returns

We explore the analyst earnings forecasts data to study the interactive effect between disagreement and underreaction to earnings news on asset prices. We find that (1) changes in the mean of forecasted earnings, as an underreaction measure, predict future returns positively and significantly; that (2) changes in the standard deviation of forecasted earnings, as a disagreement measure, predict future returns negatively and marginally; and more importantly, that (3) changes in the standard deviation predict future returns significantly only when changes in the mean are negative. Our results are robust both in the standard cross-sectional return setting and in the event-study setting around earnings announcements. Our evidence suggests that the return predictability of analyst forecast dispersion measure in Diether, Malloy, and Scherbina (2002) is mainly contributed by the underreaction component in the measure’s deflator rather by the disagreement component in the numerator

Disagreement, underreaction, and stock returns

We explore the analyst earnings forecasts data to study the interactive effect between disagreement and underreaction to earnings news on asset prices. We find that (1) changes in the mean of forecasted earnings, as an underreaction measure, predict future returns positively and significantly; that (2) changes in the standard deviation of forecasted earnings, as a disagreement measure, predict future returns negatively and marginally; and more importantly, that (3) changes in the standard deviation predict future returns significantly only when changes in the mean are negative. Our results are robust both in the standard cross-sectional return setting and in the event-study setting around earnings announcements. Our evidence suggests that the return predictability of analyst forecast dispersion measure in Diether, Malloy, and Scherbina (2002) is mainly contributed by the underreaction component in the measure’s deflator rather by the disagreement component in the numerator