This paper proposes and tests an investment-flow based explanation for three empirical findings on return predictability -the persistence of mutual fund performance, the "smart money" effect, and stock price momentum. Since mutual fund managers generally scale up or down their existing positions in response to investment flows, and the portfolios of funds receiving capital generally differ from those that lose capital, investment flows to mutual funds can cause significant demand shocks in individual stocks. Moreover, given that mutual fund flows are largely predictable from past fund performance and past flows, this paper further establishes that flow-induced price pressure is predictable. Finally, this paper shows that such flow-based return predictability can fully account for mutual fund performance persistence and the "smart money" effect, and can partially explain stock price momentum.

We propose a novel measure of arbitrage activity to examine whether arbitrageurs can have a destabilizing effect on the stock market. We focus on stock price momentum, a classic example of a positive-feedback strategy that our theory predicts can be destabilizing. Our measure, dubbed comomentum, is the high-frequency abnormal return correlation among stocks on which a typical momentum strategy would speculate. When comomentum is low, momentum strategies are stabilizing, reflecting an underreaction phenomenon that arbitrageurs correct. When comomentum is high, the returns on momentum stocks strongly revert, reflecting prior overreaction from crowded momentum trading that pushes prices away from fundamentals.

We link investor heterogeneity to the persistence of the overnight and intraday components of returns. We document strong overnight and intraday firm-level return continuation along with an offsetting cross-period reversal effect, all of which lasts for years. We look for a similar tug of war in the returns of 14 trading strategies, finding in all cases that profits are either earned entirely overnight (for reversal and a variety of momentum strategies) or entirely intraday, typically with profits of opposite signs across these components. We argue that this tug of war should reduce the effectiveness of clienteles pursuing the strategy. Indeed, the smoothed spread between the overnight and intraday return components of a strategy generally forecasts time variation in that strategy’s close-to-close performance in a manner consistent with that interpretation. Finally, we link cross-sectional and time-series variation in the decomposition of momentum profits to a specific institutional tug of war.

We exploit information in sovereign CDS spreads and the international trade network to provide causal evidence of the propagation of global economic shocks. We show that trade links are an important source of shock transmission using the natural experiments of the Japanese tsunami and the COVID-19 lockdown in China. We then confirm more general and gradual information flows along the trade network by showing extensive country-level credit/equity cross-sectional return predictability. News about country fundamentals flows primarily from importers to exporters, depends on both direct and indirect links in the trade network, and is magnified by the exporting country's financial vulnerability.

We use granular data from an investment firm and a credible identification strategy to estimate the effect of financial advisors' incentives on client investments. Exploiting a natural experiment triggered by the 2018 implementation of Markets in Financial Instruments Directive II (MiFID II), we find that clients' investments respond strongly to changes in advisor incentives. Advisors react through multiple mechanisms: (i) inducing existing clients to bring in new money, (ii) channeling it to high‐incentive funds, and (iii) attracting more new clients. We also find that the MiFID II reform generated more balanced incentives, which translated into higher portfolio efficiency through lower average fees and stronger portfolio diversification.

We explore a new mechanism by which investors take correlated shortcuts and present evidence that managers—using sales management—take advantage of these shortcuts. Specifically, we exploit a regulatory provision wherein a firm's primary industry is determined by the highest sales segment. Exploiting this regulation, we provide evidence that investors classify operationally nearly identical firms as starkly different depending on their placement around this sales cutoff. Moreover, managers appear to exploit this by manipulating sales to be just over the cutoff in favorable industries. Further evidence suggests that managers engage in activities to realize large, tangible benefits from this opportunistic action.

We study the transmission of financial news and opinions through social interactions among retail investors in the United States. We identify a series of plausibly exogenous shocks, which cause “treated investors” to trade abnormally. We then trace the “contagion” of abnormal trading activity from the treated investors to their neighbors and their neighbors’ neighbors. Coupled with methodology drawn from epidemiology, our setting allows us to estimate the rate of communication and how it varies with the characteristics of the underlying investor population.

Using comprehensive administrative data from the UK, we examine trading by different investor types in government bond markets. Our sample covers virtually all secondary market trading in gilts and contains detailed information on each transaction, including the identities of both counterparties. We find that hedge funds’ daily trading positively forecasts gilt returns in the following one to five days, which is then fully reversed in the following month. A part of this short-term return predictability is due to hedge funds’ ability to predict other investors’ future demand. Mutual fund trading also positively predicts gilt returns, but over a longer horizon of one to two months. This return pattern does not revert in the following year and is partly due to mutual funds’ ability to forecast changes in short-term interest rates.

Using granular data covering both regulated (brokerage‐financed) and unregulated (shadow‐financed) margin accounts in China, we provide novel evidence on retail investors' margin trading behavior and its price implications. We first show that retail investors' decisions to lever up in stock trading despite the hefty borrowing cost is related to their lottery preferences. We then show that margin borrowing affects investors' trading behavior—investors are more likely to liquidate their holdings as they approach margin calls. Finally, we show that margin‐induced trading aggregates to affect asset prices and contributes to shock spillovers across stocks (e.g., from lottery stocks to nonlottery stocks).

Using a novel database that tracks web traffic on the Security Exchange Commission's EDGAR server between 2004 and 2015, we show that institutional investors gather information on a very particular subset of firms and insiders, and their surveillance is very persistent over time. This tracking behavior has powerful implications for their portfolio choice and its information content. An institution that downloaded an insider trading filing by a given firm last quarter increases its likelihood of downloading an insider trading filing on the same firm by more than 41.3 percentage points this quarter. Moreover, the average tracked stock that an institution buys generates annualized alphas of over 12% relative to the purchase of an average non tracked stock. We find that institutional managers tend to track top executives and to share educational and locational commonalities with the specific insiders they choose to follow. Collectively, our results suggest that the information in tracked trades is important for fundamental firm value and is only revealed following the information-rich dual trading by insiders and linked institutions.