I study how hedge funds strategically disclose their private information during short-selling campaigns. Using data on hedge funds' voluntary announcements and daily short positions in the EU market, I document the existence of two groups of funds: Announcers and Followers. Announcers, typically small and young, (1) establish short positions, (2) publish research reports about short targets, and (3) realise profits from the falling price within a short time frame. Followers, usually large, enter at the release of the report and increase their short positions even after announcers exit. To understand the strategic interaction among short sellers, I provide a model to explain how size affects a short seller’s incentive and behaviour. Small funds benefit more from disclosing when facing binding leverage constraints. In contrast, large funds profit from others’ private information by offering capital to price discovery. I characterize the effect of such short-selling campaigns on market efficiency and confirm the model prediction that stocks with lower borrowing costs and larger mispricing are more likely to be announced by hedge funds.

Using new data on mutual funds’ equity lending positions, we find that short sellers borrow shares of different stocks from a different but small set of repeated lenders. Through survey and empirical evidence, we argue that this fragmented, persistent lender structure is driven by myriads of lending-side institutional frictions and contributes to limits-to-arbitrage at the lender-stock level. When existing lenders sell their shares, short sellers struggle to find replacement lenders and get partially squeezed, even when conventional measures suggest lending supply is slack. Consequently, lending fees spike, and stocks become more likely to be overpriced. Ex ante, risks implied by lender structure are priced in equity prices. Overall, our findings suggest that lending-side frictions, a class of frictions unconsidered by prior literature, significantly hamper market efficiency.

We show that after the introduction of leverage ratio constraints on bank-affiliated dealers, bond mutual funds have engaged in more liquidity provision in investment-grade corporate bonds and that the performance of funds with liquidity-supplying strategies has benefited. Not only have regulations transferred profits associated with liquidity provision in the corporate bond market to mutual funds, but the liquidity and returns of investment-grade corporate bonds have become more exposed to redemptions from the bond mutual fund industry, suggesting that the regulations may have made investment-grade corporate bonds more volatile. Accordingly, we observe that investment-grade corporate bonds more exposed to leverage ratio constraints experienced a more severe deterioration in liquidity and returns at the onset of the COVID-19 pandemic.

We propose a novel method to impute daily mutual fund trades in individual stocks from daily stock prices and returns and quarterly fund holdings, monthly total net assets and daily fund returns -- so that the method can be applied to standard CRSP mutual fund data. We set up an (underidentified) system of linear equations and solve the underidentification issue with an iterative method that applies random and adaptive constraints on trade incidence. The method produces daily, stock-level trade estimates with associated confidence levels. Validation and simulation analyses using proprietary daily fund trading data show good accuracy, especially for larger trades.

This paper provides empirical evidence that the low volatility anomaly in stock prices, characterized by high alpha and low idiosyncratic volatility, is an externality that results from mutual funds' performance evaluation against benchmark indexes. Using a unique dataset of mutual funds benchmarked exclusively to the S&P 500 index, I show that mutual funds that tend to keep up with performances of other same-benchmark peers have the tendency to deviate the least possible from past peer trades. This study examines mutual fund holdings of non-benchmark stocks. Mutual fund managers invest heavily in certain stocks and create a clustering effect, causing these stocks to experience higher trade volumes compared to other stocks. High trade volumes rapidly reveals all private information about a stock to the market, causing the stock price to quickly converge to its full information equilibrium, and reduces stock volatility. Stocks with high trade volumes also rapidly adjust to marketwide information which increases stock alpha. Capital flows analyses show that the low volatility anomaly is an outcome due to the behaviour of same-benchmark mutual funds. It lasts for three quarters during which the anomaly remains unexploited.

Existing studies, focused primarily on the U.S., show the improved value factor performance when adjusting book values for intangible assets. However, there is little evidence whether this is a U.S. specific, or wider international phenomenon. My findings expand the existing evidence to multiple international regions and suggest that the intangible-adjusted book-to-market ratio better measures the value factor globally. Especially in more recent decades, where the size of intangible assets increased dramatically, the relative outperformance of the intangible-adjusted value factor over the traditional value factor has become stronger. Economically, the adjusted value factor bears additional risk related to liquidity, financial distress and funding constraints.

Whilst the predictability of fund flows based on prior-period returns is empirically well-established in the literature, we extend its insights to tradeable macro ecosystems, where there is anecdotal evidence of distribution divergences between flows and prior-period returns. We study the relative entropy of flows to capture an exogenous price signal, which we hypothesise to represent the aggregate directional positioning of informed investors. We construct and assess factor portfolios and a spectra of unconstrained systematic long-only portfolios to test our hypothesis, in pursuit of demonstrating the informativeness and additionality of the factor in augmenting traditional weighting schemes to produce superior systematic portfolios, and in adding to the discretionary investor’s toolbox a method for identifying the positioning of supposed “smart money” in the aggregate. Our findings indicate that the relative entropy signal demonstrates relevance in predicting future returns and identifying relative value within our designated tradeable macro ecosystem and that, within certain portfolio configurations, it can contribute positively to portfolio construction outcomes based on historical evidence.

Many institutional investors publicly commit to some form of responsible investment. This raises concerns about the credibility of such claims. We use participation in collaborative engagements to identify ``Leaders’’, i.e., institutional investors that are truly committed to improving firms' sustainability outcomes. Despite owning only 2.2% of the average firm, Leaders alone explain the positive relationship between institutional ownership and firms’ environmental and social performance. In line with committed owners facilitating corporate change, engagement campaigns are successful only when targeted firms are substantially owned by Leaders. We also find that these firms are less at risk of experiencing negative incidents.

We propose a new performance attribution framework that decomposes a constrained portfolio's holdings, expected utility, expected returns, variance, and realized returns into components attributable to: (1) the unconstrained mean-variance optimal portfolio; (2) individual static constraints; and (3) information, if any, arising from those constraints. A key contribution of our framework is the recognition that constraints may contain information that is correlated with returns, in which case imposing such constraints can affect performance. The excess return from information is positive (negative) when this correlation is positive (negative) and the constraint is binding. The excess variance of a portfolio is negative when the holdings of a shrinkage portfolio and the holdings attributable to constraints are positively correlated, and the degree to which variance is reduced depends on the squared correlation between returns and constraints. We provide simulated and empirical examples involving constraints on ESG portfolios. Contrary to conventional wisdom, constraints may improve portfolio performance under certain scenarios.

We develop a novel measure of disagreement in voice between active and passive mutual funds using their proxy votes that captures shareholder conflicts in public firms. We show that the disagreement in voice between passive and active mutual funds destroys firm value and suggest that the firm value loss is due to conflicting incentives between the two groups of mutual funds. Using Federal Open Market Committee announcements with press conferences as events that create scope for investors to make informed votes and interpret news differently for individual firms, we show that such value-destroying effect of disagreement is likely causal.