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 a novel setting in which the same piece of information affects two sets of firms: one set of firms requires straightforward processing to update prices, while the other set requires more complicated analyses to incorporate the same piece of information into prices. We document substantial return predictability from the set of easy-to-analyze firms to their more complicated peers. Specifically, a simple portfolio strategy that takes advantage of this straightforward vs. complicated information processing classification yields returns of 118 basis points per month before transaction costs. Consistent with processing complexity driving the return relation, we further show that the more complicated the firm, the more pronounced the return predictability. In addition, we find that sell-side analysts are subject to these same information processing constraints, as their forecast revisions of easy-to-analyze firms predict their future revisions of more complicated firms.

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.

UK government bond yields tend to drift upwards before scheduled news such as monetary policy announcements and labour market data releases. This effect is particularly pronounced during periods of UK bond issuance and is linked to higher term premia. Financial intermediary constraints play a role as dealers avoid accumulating inventory in pre-news windows following issuance. The composition of liquidity providers also shifts: hedge funds buy a large share of the bond issuance outside pre-news windows, but more passive investors – such as foreign central banks and pension funds – provide liquidity in pre-news windows. We outline a simple model to rationalize these findings.

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 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.