Obaid and Pukthuanthong (2022) find that daily market return is negatively related to the previous day’s (lag 1) value of their pessimistic sentiment measure derived from Wall Street Journal news photos for the period from August 2008 to September 2020. The authors replicate their results and show that the statistical significance of the lag 1 photo pessimism measure depends on the inclusion of year 2011 data – indeed, more specifically, on 20 observations (from 2011) out of 3,044 total observations. Oddly, with the removal of 2011 data, the lag 2 photo pessimism measure maintains its positive statistical significance.
Over 70% of the $15tn in cumulative acquisition value around the world in the past two decades accrue to firms that engage in serial acquisitions. Golubov et al. (2015) find that serial acquirers domiciled in the experience persistent returns up to five years into their streams of acquisition activity. The same, however, is not true for non-US firms, which account for two-thirds of all serial acquirers. The authors find the differences are concentrated among the highest quintiles of serial acquirers by returns - the "extraordinary" acquirers - and among those serial acquisition deals in the high-technology industry in the USA.
Within the growing market for exchange-traded funds (ETFs), the authors identify many dominated ETFs with returns that are highly correlated with those of cheaper, more liquid competitors. Both retail and institutional investors overallocate to dominated funds with nonindex strategies. The authors estimate the aggregate excess fees paid by investors to dominated equity ETFs to be $4.7bn from 2000 to 2018. This cost is growing over time as newly listed ETFs claim unique strategies despite high correlations with cheap, well-established index ETFs. Dominated ETFs survive and thrive even without advisor incentive misalignments, suggesting limitations on the potential benefits of expanding fiduciary standards.
This paper successfully replicates Kosowski, Naik and Teo (2007) and Jagannathan, Malakhov and Novikov (2010), two seminal studies of hedge fund performance persistence. The authors show that top funds continue to persist in a more recent sample, even when using novel "real-time" data that approximates an investor's actual information set. The persistence available to investors has substantially weakened, however, and is only observed when using Kosowski et al.'s Bayesian alpha to predict performance. The authors identify the econometric source of the superiority of Kosowski et al.'s methodology and show that the decline in performance persistence is associated with decreasing returns to scale for superior funds.
The authors examine when firms choose to issue green or sustainability-linked bonds (SLBs), and how these bonds are priced. The authors hypothesize that firms are likely to issue green bonds when credit spreads are high ("reaching for features"). Using data from 2019 to 2023 on corporate bond issues in dollars, yen, and euros, the authors estimate a trivariate probit model and find evidence consistent with this hypothesis. Furthermore, higher emission firms are more likely to issue both green bonds and SLBs, while companies that do not disclose emissions are less likely to issue these bonds. The authors consider matching, OLS, and using a heteroskedasticity-based instrument to see how green and securities are priced. Regression methods suggest sustainability-linked bond spreads were issued with 29-46 basis point lower spreads than regular bonds. Green bonds were also priced with lower spreads than regular bonds, although this difference is not always statistically significant.
Kumar et al. (2015) report that mutual fund managers with foreign-sounding names attract less investor flow, a pattern which is consistent with taste-based discrimination. While I can reproduce their main finding using their sample, the result does not hold under independent sample construction, alternative name classifications and outlier-robust methods. My analysis finds that the original result is sensitive to a small number of extreme observations and classification decisions. This highlights how routine empirical choices can affect replicability and inference, and underscores the importance of economically motivated design strategies, particularly in filtering and classification.
This study is critical of implausible stock return effects. Among these are studies linking stock returns to extreme climate variables, outer space, politics, religious observances, sports results, weather conditions and other peculiar phenomena. The author argues that these effects are just predetermined outcomes of endogenous treatment assignments, not true causal effects. To demonstrate, The author "discovers" a new implausible effect called the big league effect. Win-loss records of NY's two professional baseball teams predict excess returns on well-known anomaly strategies. New critical values are calculated by Monte Carlo simulation where the treatment assignment follows a Bernoulli distribution with endogenous success probability. These new critical values expose the big league effect as just an artifact of the sample selection mechanism.
Recent studies find poor out-of-sample performance for volatility-managed portfolios. I propose a simple improved strategy based on Moreira and Muir (2017)'s formation of volatility management. The improved volatility management features effective risk scaling, conditional expected return, and intercept from conditional risk-return tradeoff. Using this strategy for a comprehensive set of 197 risk factors and anomaly portfolios, I document significant real-time performance improvements including 148 Sharpe ratio increases and 165 positive abnormal returns. The performance survives robustness checks of leverage constraints, transaction costs and different design choices.
This paper aims to compare the forecasting and hedging performance of 11 market beta estimators across 53 international stock markets in six geographical regions. The Welch (2022) age-decayed slope-winsorized beta estimator produces the highest R-squares in predicting future realized betas in 45 markets and is always within the top three performers. It also forecasts future realizations of its competitors well and performs the best when hedging market risk exposures in 42 markets. On the practical side, it significantly outperforms commonly available market betas on Bloomberg, Yahoo! Finance and Google Finance. Market participants can greatly improve their beta estimations in both developed and emerging markets with this easy-to-implement slope-winsorized beta estimator.
The authors revisit the asset pricing tests conducted in Lettau and Ludvigson (2001) (LL). Contrary to LL's claim, their conditional models based on cay do not explain the dispersion in risk premia among the size/book-to-market portfolios. The pricing performance is either very poor (conditional CAPM/Consumption-CAPM) or quite modest (conditional Human-capital-CAPM), with all models largely underperforming the Fama-French model. Furthermore, the risk price estimates for the scaled factors are insignificant in several cases. When the zero-beta-rate is unrestricted, the authors obtain average pricing errors that are similar or above the raw average risk premia. Alternatively, LL's extreme intercept estimates are inconsistent with the equity premium puzzle. Using alternative test portfolios and evaluating the identification of the risk prices substantially reinforces the negative outlook on their results. LL's models also perform poorly out-of-sample. Overall, LL's wrong conclusions stem from a combination of incorrect empirical choices and a misinterpretation of their results.
This paper revisits the relative pricing of Palm and 3Com shares in 2000. We offer a simple rational explanation of the Palm/3Com price relationship before Palm’s spinoff is completed. Lending fees and spin-off uncertainty are crucially important to understanding the relative levels and co-movement of Palm and 3Com share prices. We use Palm’s post-spinoff forward prices (calculated from the market prices of calls and puts) and model the spin-off uncertainty in valuing 3Com. Considering forward pricing and spin-off uncertainty resolves various pricing puzzles and explains the observed empirical evidence, including a sharp change in relative price behavior once the spinoff uncertainty is resolved on May 8, 2000.
We examine the relative scientific impact of new research in finance and find it declined steadily during the period 2002 to 2019, more than 60% cumulatively, reaching the lowest level in four decades. We also find declining incidence of "home-run" papers during this period. In contrast, the papers published in the period 1985 to 1999 have strong initial and long-lasting impact collectively. Comparisons to other disciplines, including economics, show that the proliferation of research that advance the finance field only marginally in the past two decades is not typical across research fields. Our findings support the necessity to remove the obstacles hindering innovative research and scientific progress in finance that many prolific researchers and editors of leading journals indicate.
Chen et al. (2010) report that, for "commodity currencies", the exchange rate predicts the country's commodity index but not vice versa, consistent with the Engel-West model where the country's key export prices act as the fundamentals. Predictability is assessed "against a variety of benchmarks" (the random walk, the random walk with drift, and an AR(1) process). One snag is that, commodity prices being AR(1), only that third model is valid. Deleting inappropriate benchmarks and correcting a programming error, only one out-of-sample case remains significant, not thirteen, and even that one is not robust to the test statistic. When we use a larger sample the relation becomes non-robust, at best. Commodity prices appear to be no worse than exchange rates at digesting information.
An emerging line of research based on Appel (2019) finds that firms incorporated in Universal Demand (UD) law adopting states experience an increase in the use of entrenchment provisions. Our granular investigation shows that the empirical link between UD laws and management entrenchment is not supported by the evidence. We instead find that the results in Appel (2019) are driven by a small number of firms adopting poison pill and golden parachute provisions after substantial long-term drops in market value. Using hand-collected data, we additionally find that the vast majority of changes in the use entrenchment provisions among affected firms were in fact announced before the enactment of UD laws. The evidence calls into question the existence of a cause-and-effect link between UD laws and management entrenchment.
Predictable biases in analysts' earnings forecasts, whether correlated or uncorrelated with anomalies, signal abnormal next-month returns, but only for firms that are hard to value. This finding is consistent with the plausible hypothesis that stock prices are distorted by investors who rely on predictably inaccurate forecasts by analysts. Moreover, the profitability of most anomaly strategies largely disappears once we account for analyst bias. If discernible earnings forecast biases elicits valuation mistakes, the greater prevalence of optimistic forecasts among stocks that are hard to value emerges as a common thread linking anomaly-generating firm characteristics to subsequent negative alphas.
The paper checks the Bilson-Fama regression for discrete points of structural change. We find greater instability than previous studies and a forward rate bias that is more often insignificant or positive than negative as widely reported. We also find considerably more evidence of a time-varying risk premium. Systematic forecasting errors also play a key role, but the correlations are unstable and switch sign across many of the subperiods. The results present a challenge for the view that currency markets are systematically irrational.
Over the past generation of market returns, factors only matter for (2021) q5-factor models are commonly used to measure the performance of stock return portfolios. Importantly, I find that most of the Fama and French and q5-factor firm-level characteristics have not worked for large capitalization firms for quite a long time (i.e., 1983-2021). Small firms comprising less than 8% of the total market capitalization drive the patterns of the factor models. This paper also reexamines equity issuer performance within the context of the factor firm-level characteristics.
Alpha depends on the return measurement horizon, particularly as the horizon becomes long. We introduce a procedure to estimate long-horizon alphas from short-horizon returns. Among those sample mutual funds with positive alphas estimated from monthly returns, nearly half have negative alpha estimates when returns are measured at the 10-year horizon. Among sample funds with positive monthly alpha estimates and monthly beta estimates that exceed one, over 70% have negative alpha estimates at the decade horizon. Alphas estimated from short-horizon returns can be uninformative or misleading regarding fund performance for both active and passive investors over longer horizons.
We present evidence of a persistent violation of the law of one price in the U.S. stock market. Using a hand collected dataset which corrects for the data errors in SDC, we find that the value of the parent's ownership in the subsidiary can exceed the parent firm's total market value consistent with prior literature. Contrary to what efficient capital markets would suggest, this price aberration is persistent, and we show that it is possible to profitably trade by taking advantage of the price discrepancy.
We criticize ad-hoc tests of return predictability, like those presented by Li and Wang (2025), which are purely motivated by statistical associations. Without ex-ante hypotheses grounded in theory or evidence on portfolio choice, it is difficult to say what we learn from such correlation exercises. We then discuss how convincing progress can be made in uncovering the foundations of portfolio choice and asset pricing, drawing on our own experimental research for illustration.
