Do analysts who understand accounting conservatism exhibit better forecasting performance?

This study investigates the performance of analysts when they match the asymmetric timeliness of their earnings forecast revisions (i.e., asymmetric forecast timeliness) with the asymmetric timeliness of firms’ reported earnings (i.e., asymmetric earnings timeliness). We find that better timeliness‐matching analysts produce more accurate earnings forecasts and elicit stronger market reactions to their forecast revisions. Further, better timeliness‐matching analysts issue less biased earnings forecasts, more profitable stock recommendations and have more favorable career outcomes. Overall, our results indicate that analysts’ ability to incorporate conditional conservatism into their earnings forecasts is an important reflection of analyst expertise and professional success.     

Can financial statement analysis beat consensus analysts’ recommendations?

We examine whether investors can exploit financial statement information to identify companies with a greater likelihood of future earnings increases and whether stocks of those companies generate 1-year abnormal returns that exceed the abnormal returns from following analysts’ consensus recommendations. Our approach summarizes financial statement information into a “predicted earnings increase score,” which captures the likelihood of 1-year-ahead earnings increases. We find that, within our sample of consensus recommendations, stocks with high scores are much more likely to experience future earnings increases than stocks with low scores. A hedge portfolio strategy that utilizes our approach within each consensus recommendation level generates average annual abnormal returns of 10.9 percent over our 12-year sample period, after controlling for previously identified risk factors. These abnormal returns exceed those available from following analysts’ consensus recommendations. Our results show that share prices and consensus recommendations fail to impound financial statement information that helps predict future earnings changes.     

More than words: Can tone of consumer product reviews help predict firms’ fundamentals?

Although financial market participants are increasingly interested in the financial value of unstructured qualitative information regarding the prospects of a firm, empirical evidence remains sparse on the properties of qualitative content in consumer product reviews and their capital market implications. Using a broad sample of consumer reviews posted on Amazon.com, I examine whether the linguistic tone of aggregate consumer product reviews conveys information that is associated with firms’ sales, earnings, stock returns and risk. I find that aggregate review tone successfully predicts a firm's forthcoming quarterly sales. Moderating analyses show that this predictability is stronger for firms operating in a highly competitive environment. I further find that review tone predicts a firm's quarterly earnings surprises, abnormal stock returns and risk. A path analysis shows that the effect of review tone on stock prices is partially channeled through its effect on firms’ earnings. I finally find that negative review tone is more informative and useful than positive tone in predicting a firm's fundamentals. Importantly, these results hold after controlling for other review characteristics, including review rating, review volumeand review dispersion. Overall, my findings highlight the importance of considering the tone of consumer reviews when evaluating a firm's prospects and value.     

Can credit spreads help predict a yield curve?

In this paper we investigate whether information in credit spreads helps improve the forecasts of government bond yields. To do this, we propose and estimate a joint dynamic Nelson–Siegel (DNS) model of the U.S. Treasury yield curve and the credit spread curve. The model accounts for the possibility of regime changes in yield curve dynamics and incorporates a zero lower bound constraint on yields. We show that our joint model produces more accurate out-of-sample density forecasts of bond yields than does the yield-only DNS model. In addition, we demonstrate that incorporating regime changes and a zero lower bound constraint is essential for forecast improvements.     

Can happiness predict future volatility in stock markets?

In this paper, we use the Twitter based happiness index as a proxy for investor sentiment in order to examine whether happiness influences future market volatility of country VIX indexes. Our sample includes the major stock markets of the USA, Canada, UK, Germany, France, Netherlands, Switzerland, Japan, China, Hong Kong, India, Brazil, South Korea, and South Africa. Using linear and nonlinear causality tests, we find that Twitter happiness significantly causes the future volatility of the sample countries. The robustness checks show no divergence from our primary findings and provide strong evidence of a nonlinear relationship between investor sentiment and future stock market volatility.     

Can dual-currency sovereign CDS predict exchange rate returns?

This paper examines both the time-series and cross-sectional variation in the difference between US dollar and Euro denominated sovereign CDS spreads for a group of Eurozone countries. We find that the spread difference between dual-currency sovereign CDS significantly affects the bilateral exchange rate returns. In addition, the difference could predict the cumulative exchange rate returns up to 10 days. The results strongly suggest that the difference contains important information for the exchange rate dynamics at various phases of the crisis.     

Can margin traders predict future stock returns in Japan?

A growing body of literature suggests that investor sentiment affects stock prices both at the firm level and at the market level. This study examines the relationship between investor behavior and stock returns focusing on Japanese margin transactions using weekly data from 1994 to 2003. Margin trading is dominated by individual investors in Japan. In analysis at the firm level, we find a significant cross-sectional relationship between margin buying and stock returns. Both market-level and firm-level analyses show that margin buying traders follow herding behavior. They seem to follow positive feedback trading behavior for small-firm stocks and negative feedback trading behavior for large firm stocks. Our results show that information about margin buying helps predict future stock returns, especially for small-firm stocks at short horizons. The predictive power does not diminish even after controlling for firm size and liquidity.     

Does the bond‐stock earnings yield differential model predict equity market corrections better than high P/E models?

We extend the literature on crash prediction models in three main ways. First, we explicitly relate crash prediction measures and asset pricing models. Second, we present a statistical significance test for crash prediction models. Finally, we propose a definition and a measure of robustness for these models. We apply our statistical test and measure the robustness of selected model specifications of the Price‐Earnings (P/E) ratio and Bond Stock Earning Yield Differential (BSEYD) measures. This analysis shows that the BSEYD and P/E ratios, were statistically significant robust predictors of corrections on the US equity market over the period 1964 to 2014.     

Are two heads better than one? Evidence from the thrift crisis

We employ a natural experiment from the 1980s, predating the ubiquitous clamor for independence influenced corporate governance structures, to examine which governance mechanisms are associated with firm survival and failure. We find that thrifts were more likely to survive the thrift crisis when their CEO also chaired the firm’s board of directors. On average, chair-holding CEOs undertook less aggressive lending policies than their counterparts who did not chair their boards. Consequently, taxpayer interests were protected by thrifts that bestowed both leadership posts to one person. This is an important policy issue, because taxpayers become the residual claimants for depository institutions that fail as a result of managers adopting risky strategies to exploit underpriced deposit insurance. Our findings corroborate recent evidence that manager-dominated firms resist shareholder pressure to adopt riskier investment strategies to exploit underpriced deposit insurance.     

Can historical returns-earnings relations predict price responses to earnings news?

The main purpose of this study is to examine the usefulness of pooled and firm-specific returns-earnings models in predicting price responses to future earnings news. The question addresses whether earnings response coefficients (ERCs) (i.e., slope coefficients obtained from regressions of market-adjusted returns on earnings surprises) are helpful in predicting price responses to future earnings surprises. In other words, are historical returns-earnings relations (as captured by ERCs) useful in predicting future returns-earnings relations? Surprisingly, we find that ERCs from firm-specific regressions provide less accurate predictions of price responses to future earnings surprises than ERCs from pooled regressions. In addition, out-of-sample predictions from actual-firm-specific regressions are no more accurate than those from pseudo-firm-specific regressions. This is despite the fact that our pseudo firms are created through random draws of returns-earnings data. Therefore, they have no economic characteristics that extend beyond the period over which the coefficients are estimated.     

Do German security analysts herd?

We employ an innovative methodology suggested by Bernhardt et al. (J. Financ. Econ. 80:657–675, 2006) to examine the herding (or anti-herding) behavior of German analysts regarding earnings forecasts. This methodology avoids well-known shortcomings often encountered in related studies, such as correlated information signals, unexpected common shocks to earnings, systematic optimism or pessimism, or forecast target mismeasurement. Our findings suggest that German analysts anti-herd, that is, they systematically issue earnings forecasts that are further away from the consensus forecast than their private information indicates. Furthermore, we analyze the association between herding behavior and different characteristics, including the size of the brokerage, general or firm-specific experience, and the coverage of firms on the Neuer Markt. We mainly confirm findings for the United States, for example, that anti-herding is more severe in cases of higher competition among analysts. Contrary to anecdotal evidence, we also find anti-herding behavior in earnings forecasts for Neuer Markt firms during the “new economy” bubble.

Can SRI funds better resist global financial crisis? Evidence from Japan

This paper compared Socially Responsible Investment (SRI) funds and conventional funds in the Japanese market with respect to the impact of the global financial crisis in 2008. Taking the bankruptcy of Lehman Brothers as a particular event, we estimated the average cumulative abnormal returns of both funds by event study methodology using a Fama–French three-factor model and EGARCH model. Our results suggest that SRI funds better resisted the bankruptcy of the Lehman Brothers than conventional funds. We also found that this result can be attributed to the existence of international funds, possibly because investors might evaluate the CSR activities of international firms more than those of domestic firms. Alternatively, it can be interpreted that the universe of domestic SRI funds is too limited to enjoy risk diversification.     

Do analysts affect bad news timeliness?

I investigate the effect of analysts on the speed with which bad news is reflected in earnings. Intuitively, the more analysts that cover a firm, the more costly it will be for the firm to keep bad news suppressed. Thus, analyst coverage should positively affect bad news timeliness (BNT) (but not necessarily the differential timeliness of bad news over good news, or conditional conservatism). Using brokerage house mergers as a natural experiment with a difference-in-differences design, I find that an exogenous decrease in analyst coverage decreases BNT; that is, analysts positively affect BNT. The decrease in BNT is robust to controlling for unobserved firm heterogeneity, using a propensity score matched sample, persists for up to three years after the brokerage house merger, and is stronger for firms with relatively low analyst coverage before the merger. The result improves our understanding of how analysts affect a firm's information environment.     

Are better governed funds better monitors?

Using Morningstar mutual fund stewardship grade data, we find that the governance mechanisms of mutual funds play a key role in their monitoring of portfolio firms and in their investment decisions. Mutual funds with better governance practices tend to vote responsibly on corporate governance proposals of their portfolio firms and also provide better return performance. Furthermore, these funds tend to avoid investing in poorly governed firms. The results suggest that funds with quality governance are more likely to act in the interest of their investors, and that costs associated with funds' monitoring of their portfolio firms do not adversely affect their return performance.     

Measuring discretionary accruals: are ROA-matched models better than the original Jones-type models?

Discretionary accruals estimated from Jones-type models are elevated or depressed for firms with extreme performance. Kothari et al. (J Acc Econ 39:163–197, 2005) propose performance matching to address the issue, that is, to difference discretionary accruals estimated from Jones-type models for treatment and control firms matched on current ROA. This study shows (1) performance matching will systematically cause discretionary accruals of either sign to be underestimated, and (2) the measurement error will be negatively correlated with the true discretionary accruals. As a result, using discretionary accruals estimated with performance matching to test whether certain events induce earnings management will increase the frequency of Type II errors, and using them as the dependent or an independent variable in regression analysis will bias the regression coefficient toward zero. The results of our empirical tests are consistent with these predictions.     

Can energy predict the regional prices of carbon emission allowances in China?

The carbon emission trading is an important market-oriented tool in the process of China's carbon neutrality, which makes companies face tremendous pressure to reduce emissions while having strong energy demands. In order to evaluate whether energy prices can be robust predictors of the prices of emission allowances, this study perform extreme bounds analysis (EBA) in four representative markets. The empirical results reveal that energy prices can indeed predict the prices of emission allowances, but the robustly predictive capabilities of different energy prices vary with regions. Among them, thermal coal is the robustly positive predictor for Guangdong, Hubei and Shanghai market; natural gas is the robustly negative predictor for all the four chosen regions; and crude oil can only positively predict Hubei market with robustness. Meanwhile, the horizons that predictions from energy to emission allowance can be performed as well as the predictive coefficients also vary with energy types and regions. And some trading implications are also provided alongside.     

Litigating crashes? Insights from security class actions

Investors tend to litigate large stock price declines, i.e., file ‘stock-drop lawsuits’. However, it is less clear whether the ex-ante threat of security class actions can deter stock price crashes in the first place. To answer this question, we exploit the 1999 ruling of the Ninth Circuit Court of Appeals that discourages security class actions as a quasi-exogenous shock, and find that reducing the threat of security class actions leads to a significant increase in stock price crash risk measured by negative skewness of stock returns. We reveal that the main effect is partially driven by a reduction in the timeliness of bad news disclosure and worsened earnings quality, which is consistent with the view that bad news hoarding serves as the key factor in the formation of a stock price crash. Our overall findings highlight the importance of security class actions in deterring the occurrence of firm-level negative tail events on the financial market.     

Do large-cap exchange-traded funds perform better than their small-cap counterparts in extreme market conditions?

This study proposes a new threshold model that differentiates between the size and sign-dependent responses of large- and small-cap exchange-traded funds (ETFs) to changes in extreme market conditions. The asymmetric returns in extreme upsides, extreme downsides, and “in-between” markets are estimated using three sets of betas. Findings support the notion that small-cap ETFs in all seven countries fall more in extreme downturns than they rise in extreme upturns. By contrast, six out of nine large-cap ETFs climb up in upside more than they fall in downswing. Therefore, investors should be cautious when assigning excessive weights to small-cap ETFs in their portfolio.     

Do investment banks listen to their own analysts?

To what extent conflicts of interest affect the investment value of sell-side analyst research is an ongoing debate. We approach this issue from a new direction by investigating how asset-management divisions of investment banks use stock recommendations issued by their own analysts. Based on holdings changes around initiations, upgrades, and downgrades from 1993 to 2003, we find that these bank-affiliated investors follow recommendations from sell-side analysts in general, increasing (decreasing) their relative holdings following positive (negative) recommendations. More importantly, these investors respond more strongly to recommendations issued by their own analysts than to those issued by analysts affiliated with other banks, especially for recommendations on small and low-analyst-coverage firms. Thus, we find that investment banks “eat their own cooking,” showing that these presumably sophisticated institutional investors view sell-side recommendations as having investment value, particularly when the recommendations come from their own analysts.