Knowledge that Transforms

This paper explains that anticipated market liquidity is an important concern for arbitrageurs considering entry into a market, a concern that can generate self-fulfilling asset prices. In the model, fixed investment costs turn a market illiquid and generate an arbitrage opportunity. The worst-case return on pledged collateral constrains arbitrageurs’ leverage. The interaction between this return and arbitrageurs’ capital makes entry decisions complementary and can create multiple equilibria. When arbitrageurs enter with capital, the market becomes more liquid; the worst-case return rises; and more arbitrageurs enter with capital. When arbitrageurs withhold capital, the market stays illiquid; the worst-case return falls; and other arbitrageurs stay out. (JEL D84, G11, G12) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We empirically study how inventory constraints of underwriters affect corporate bond offerings. Using underwriter-insurer-level transaction data, we find that a more constrained underwriter is more likely to place a bond and increases the allocation in the primary market to an insurer with a stronger preexisting relationship. The same underwriter is also more likely to buy back part of an allocation from the same insurer within 6 to 12 months after an offering. Overall, by “parking” inventory to relationship investors in the primary market, underwriters mitigate the effect of their inventory constraints on firms’ bond financing costs. (JEL G12, G32)

We exploit detailed transaction and position data for a sample of long-short equity hedge funds to study the trading activity of fundamental investors. We find that hedge funds exhibit skill in opening positions, but that they close their positions too early, thereby forgoing about one-third of the trades’ potential profitability. We explain this behavior with the limits of arbitrage: hedge funds close positions early in order to reallocate their capital to more profitable investments and/or to accommodate tightened financial constraints. Consistent with this view, we document that hedge funds leave more money on the table after opening new positions, negative returns, or increases in funding constraints and volatility. (JEL G11, G12, G14, G15)

Using proprietary data from a major fund data provider, we analyze the screening activity of investment consultants (ICs). We find that ICs frequently shortlist funds using threshold screens clustered at $500MM for AUM, 0% for benchmark-adjusted return, and quartiles for return percentile rank screens. Funds just above the $500MM AUM threshold get 14%–18% more page views and 5–9 pp greater flows over the next year compared to similar funds just below the threshold. Our results are consistent with ICs using a two-stage consider-then-choose decision-making process and cognitive reference numbers in selecting screening thresholds. (JEL G41, G11, G14, G29) Received January 8, 2021; editorial decision September 3, 2021. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Marketing capability refers to a firm’s ability to optimally deploy and integrate different marketing inputs to achieve high sales at low cost. This paper examines whether the value of marketing capability is incorporated into stock returns. High-level marketing capability predicts better future operating performance and stock returns. A marketing capability-based long-short portfolio strategy earns an average annual return of 5.16%, a substantial portion of which is earned over subsequent earnings announcements. The return predictability is stronger in stocks with higher valuation uncertainty and lower investor attention. Investors underreact to the value-relevant, but difficult to process, information embedded in marketing capability. (JEL G12, G14, G10, M30) Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We illustrate the role of left tail dependence—left tail mean (LTM)—in equity risk premium (ERP) predictability. LTM measures the average of pairwise left tail dependency among major equity sectors incorporating shocks imperceptible at the aggregate level. LTM, as well as the variance risk premium, significantly predicts the ERP in and out of sample, which is not the case with commonly used predictors. We find this predictability is the result of procyclical shocks’ reversals in a stable business cycle. This paper contributes to the ongoing debate on ERP predictability. (JEL G10, G12, G14)

We study the extent of cross-asset learning in financial markets by examining the spillover effects around mutual fund fire sales, which lead to a well-documented impact-reversal pattern in returns. We find that the returns of fire sale stocks spill over onto the stock returns of economic peers with a magnitude of around one-third of the original effect. These spillovers extend to liquidity and are not explained by common funding shocks or the hedging activity of liquidity providers. We conclude that they represent information spillovers due to learning from prices, thus identifying cross-asset learning as an important driver for the commonality in returns and liquidity. (JEL G11, G12, G14, G23) Received July 1, 2021; editorial decision August 30, 2021. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

We analyze the supply-side disruptions associated with COVID-19. We find that sectors in which a higher fraction of the workforce is not able to work remotely experienced greater declines in employment and expected revenue growth, worse stock market performance, and higher likelihood of default. The stock market overweights low-exposure industries. Thus, our findings cast light on the disconnect between stock market indices and aggregate outcomes. We combine these ex ante heterogeneous industry exposures with daily financial market data to create a stock return portfolio that tracks news about the supply-side disruptions resulting from the pandemic. (JEL G12, D22, H25, J20, E00)

This paper evaluates whether economic uncertainty is consistent with the Merton (1973) intertemporal CAPM (ICAPM) theory. The economic uncertainty index of Jurado, Ludvigson and Ng (2015) consistently predicts a significant increase in stock market volatility. However, its innovation carries a statistically insignificant price of covariance risk in the cross-section, thereby failing to satisfy the Maio and Santa-Clara (2012) sign restrictions associated with the ICAPM. I also find robust evidence by using the level of the economic uncertainty index (JEL G10, G11, G12). Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

I find that approximately 30% of price fluctuations in the Fama-French size and value factors are nonfundamental price pressures driven by correlated fund flows, which generate price movements that revert over time. Is this really demand-based price pressure? I show that the price effects happen exclusively in periods when mutual funds place trades, a fact that is difficult to explain using traditional mechanisms such as unobserved investor preference changes. The estimated price elasticity is also consistent with other studies. Overall, my findings show that a sizable fraction of size and value factor movements do not represent economic risk. (JEL G10, G12, G23, G40)