Knowledge that Transforms

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Active and Passive Investing: Understanding Samuelson’s Dictum

The Review of Asset Pricing Studies 2022 12(2), 389-446 open access
We model how investors allocate between asset managers, managers choose portfolios of multiple securities, fees are set, and security prices are determined. Investors are indifferent between higher-cost informed managers and lower-cost uninformed managers, interpreted as passive managers as their portfolio is linked to the " expected market portfolio." We make precise Samuelson's dictum by showing that active investors reduce micro-inefficiencies more than they do macro-inefficiencies. In fact, all inefficiency arises from systematic factors when the number of assets is large. Further, we show how the costs of active and passive investing affect macro- and micro-efficiency, fees, and assets managed by active and passive managers. Our findings help explain the rise of delegated asset management and the resultant changes in financial markets.

Volatility-of-Volatility Risk in Asset Pricing

The Review of Asset Pricing Studies 2022 12(1), 289-335 open access
This paper develops a general equilibrium model and provides empirical support that the market volatility-of-volatility (VOV) predicts market returns and drives the time-varying volatility risk. In asset pricing tests with the market, volatility, and VOV as factors, the risk premium on VOV is statistically and economically significant and robust. Market and volatility risks are not priced in unconditional models, but, consistent with theory, their factor loadings, conditional on VOV, are priced. The pricing impact of VOV strengthens during market crashes, suggesting that VOV is particularly relevant during market turmoil, when investors demand increased compensation for VOV risk. (JEL G11, G12, G13)

Embedded Leverage

The Review of Asset Pricing Studies 2022 12(1), 1-52 open access
Abstract Many financial instruments are designed with embedded leverage, such as options and leveraged exchange-traded funds (ETFs). Embedded leverage alleviates investors’ leverage constraints, and, therefore, we hypothesize that embedded leverage lowers required returns. Consistent with this hypothesis, we find empirically that options and leveraged ETFs provide significant amounts of embedded leverage; this embedded leverage increases return volatility in proportion to the embedded leverage; and higher embedded leverage is associated with lower risk-adjusted returns. The results are statistically and economically significant, and we provide extensive robustness tests and discuss the broader implications of embedded leverage for financial economics. (JEL G02, G11, G12, G13, G14, G20)

Inventory-Constrained Underwriters and Corporate Bond Offerings

The Review of Asset Pricing Studies 2022 12(3), 639-666 open access
Abstract 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)

The Marketing Capability Premium

The Review of Asset Pricing Studies 2022 12(4), 918-959 open access
Abstract 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.

Equity Risk Premium Predictability from Cross-Sectoral Downturns

The Review of Asset Pricing Studies 2022 12(3), 808-842 open access
Abstract 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)

Working Remotely and the Supply-Side Impact of COVID-19

The Review of Asset Pricing Studies 2022 12(1), 53-111 open access
Abstract 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)

What Drives the Size and Value Factors?

The Review of Asset Pricing Studies 2022 12(4), 845-885 open access
Abstract 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)