Knowledge that Transforms

We investigate the impact of Exchange-Traded Funds (ETFs) on the comovements of their constituent securities using a novel identification that exploits the switch from synthetic to physical replication of a large French ETF. After the switch, constituent stocks experience greater commonality, in both returns and liquidity. For both the full sample of ETF constituents and the least liquid ETF constituents, a larger part of the variation in individual stock returns or liquidity is explained by market-wide variations. We present evidence that ETF creation and redemption is the transmission mechanism of the comovements. Moreover, we show that the comovements do not appear excessive.

We develop a novel measure to identify short squeezes triggered by sharp price increases. These “market squeezes” drive short sellers to close their positions early. To provide a comprehensive analysis of short squeeze dynamics, we also examine lender squeezes, identified through share recalls. We find that stock-day short-squeeze events are rare and short-lived. However, the quarterly proportion of unique stocks experiencing market squeezes is 9.9% (12.3%) in the US (EU), compared to 8.7% (5.4%), for lender squeezes. Our analysis shows that market and lender squeezes are driven by different determinants. We find that market squeezes impair price discovery, consistent with significant declines in short interest after these events. This contrasts with lender squeezes, after which short interest remains stable or increases, and price discovery remains unaffected.

In this study, we examine how political information quality influences the predictive effects of investor sentiment and risk aversion on stock market returns. Our analysis reveals that low-quality information significantly diminishes the predictive power of investor sentiment while amplifying that of risk aversion. Moreover, incorporating a proxy for political information quality into predictive regression models significantly enhances their explanatory power. Overall, our results provide compelling evidence that the quality of information plays a critical role in shaping the dynamics of financial markets.

The performance of corporate bond mutual funds tends to be estimated using models with limited empirical validation. We survey the literature to determine the models in use and develop a representative set of models. Testing that set of models, we find considerable variation in quality, with the most effective models sharing common traits. We recommend, among the tested models, the four-factor model proposed by Jones and Mo (2021). Regarding the stylized facts of corporate bond fund performance, our recommended model produces notable deviations from the prior literature and other models, including less evidence of positive alphas not attributable to luck.

Using state-level data from the United States covering the period 1980 to 2020, we explore the effect of right-to-work (RTW) laws on venture capital (VC) investment. Employing a difference-in-differences strategy, we find that the passage of right-to-work laws increases venture capital investment. The results are robust to omitted variable bias, reverse causality and unobservable local economic conditions. We find that the positive effect of RTW laws on VC investments remains significant in states that are highly unionized and technological. • Right to work laws encourage Venture Capital Investment. • Uses state-level data from the United States covering the period 1980 to 2020. • Employs a difference-in-differences strategy. • The passage of right-to-work law increases Venture Capital investment by 80%.

Using a proprietary, hand-collected database of 251 sanctions issued by national and international authorities on 109 European banks, we investigate the deterrent effect of governance effectiveness at the country level on detected bank misconduct from 2009 to 2019. We also examine the impact of detected bank misconduct on depositor behavior to investigate how customer reaction is shaped by media coverage. Our empirical strategy based on probit and panel fixed effects shows the existence of a deterrent effect exerted by country governance effectiveness. Moreover, the instrumental regressions show that depositors react to detected bank misconduct by withdrawing their funds and that this reaction is stronger when news coverage is high.

We provide a new theory of exchange access fees that explains why fees relatively reduce the probability of execution and increase the limit order queue length on “maker-taker” platforms. Nonetheless, the limit order subsidy greatly improves market depth, together with market efficiency and trading volume. Moreover, fee structures never “wash out” regardless of the minimum tick. The regulatory requirement that trading and order flow depend only on raw (nominal) spreads and prices underpins the multi-billion-dollar subsidy to limit orders. So long as a platform remains competitive, elimination of the fee structure does not alter the raw spread, but it does lower the cum fee spread. We test these implications with a unilateral maker-taker fee/rebate reduction using NASDAQ's “quasi-natural” $1.9 trillion experiment to find support for our theory.

We model the dynamic evolution of the attention process over the duration of climate change news events as a Brownian motion with an absorbing barrier, where attention to the news event ceases. In this framework, the duration of the underlying news event is a random variable whose probability distribution is the Inverse Gaussian (IG). We show that the IG distribution of news duration can be used to predict the response time of asset prices to climate news risk. We test the empirical validity of our model by constructing two novel climate news duration data sets: a daily duration and an hour-by-hour intra-news duration. At the daily frequency, our model predicts the response time of green versus brown firms’ stock prices to climate news risk. We demonstrate how this response time can enhance the precision of conventional risk management statistics, e.g., Value at Risk and expected shortfall, and in consequence improves the efficiency of managing firms’ exposures to such risk. At the high frequency, we extend the autoregressive conditional duration (ACD) model and show that, in an IG-ACD-GARCH framework, climate change news arrivals contribute to the volatility of green (but not brown) firms’ returns. This finding is attributed to public and investors’ concerns about climate change or to their belief that climate transition policies are ineffective in combating climate change.

Based on a non-linear structural banking sector model, we show that the impact of changes in bank capital requirements on lending is strongly state-dependent. When banks make profits or maintain voluntary capital buffers, the impact on lending works through a “pricing channel” which is small: 0.1% less loans for a 1pp capital requirement increase. When banks are capital-constrained, the impact on lending works through a “quantity channel” which is large: 10% more loans for a 1pp capital requirement reduction. Our results provide a theoretical justification for building up a positive neutral countercyclical capital buffer in “normal” macro-financial environments.

We propose a new measure of price discovery, New Leadership Share (NLS), that attributes permanent information flow to individual markets using a uniquely identified structural moving average model. NLS quantifies each market’s contribution to permanent price innovations as a proportion of total informational leadership and offers key technical advantages, including uniqueness and adherence to standard statistical asymptotics. We derive closed-form solutions and analytical standard errors for bivariate markets and provide a framework that extends naturally to multiple markets without the variable ordering problem. Simulation results show that NLS consistently outperforms three widely used benchmarks. Empirical analysis of 2023 data finds that exchange-traded funds and front-month futures markets share equal leadership relative to the S&P 500 spot index.