Abstract: I propose an asset-pricing model with preference shocks and contemporaneous cash-flow risk that can explain key asset-pricing patterns related to business cycle. In this consumption-based model with preference shocks, contemporaneous cash-flow risk of equities drives the cross section of risk premia in bad times, i.e. during periods with a high recession probability, relatively more than in good times. This model makes new predictions about the conditional relevance of cash flow risk for asset prices that are confirmed in data. Unlike in models with external habits or long-run risks, a model with preference shocks correlated with business-cycle shocks further implies that reasonable quantities of contemporaneous cash-flow risk have a significant effect on conditional risk premia of assets and return volatility.
Presented at: MFA Conference in 2020, University of Iowa, Melbourne University, Aarhus University, NOVA University, Vrije University, Oxford Finance Job Market Workshop (Saïd Business School), 31st Australasian Finance and Banking Conference in Sydney, Macquarie University in Sydney, the 9th FMCG in Melbourne, the EFMA conference in Milan.
Abstract: Are managerial incentives to innovate affected by financial crises? We document that awarding CEOs with stock options in bad times increases their incentives to invest in risky projects and produce innovation. We find that an exogenous increase in CEO option pay awarded during times of high bank distress is associated with an increase in both the quantity and quality of innovation produced by the CEO’s firm. In contrast, the same increase in option pay awarded during normal times does not have a significant effect on firm innovation. We rationalize our results using the Schumpeter’s theory of creative destruction where managers exploit unique growth opportunities that arise during crises. We argue that, during crises, growth opportunities that stem from exploiting innovative projects dominate managerial risk aversion and `skin-in-the-game’ concerns. This result is the strongest among firms with high market power (incumbents) or less financially-constrained firms. Exogenous variation in option compensation is identified using pre-negotiated multiyear option plans.
Presented at: 28th Finance Forum, University of Iowa.
(with Umang Khetan)
Abstract: We characterize the demand function of multi-national corporations in foreign exchange (FX) markets and assess its impact on asset prices. Our findings suggest that corporate order flow does not consistently predict future returns, it is highly auto-correlated and, in contrast to pure noise, it strongly responds to realized asset returns. Further, we find compelling evidence of a positive impact of corporations’ net order imbalance on the post-execution volatility of currency returns. Using settlement breaks to instrument for quasi-exogenous shocks to liquidity-motivated trading, we show that a one standard-deviation drop in traded volume decreases return volatility by 38%. This effect dissipates within a trading day. We document that order imbalance also impacts dealers’ price spreads to corporations, but observable currency and trade characteristics explain less than 1% of the variation. Based on these empirical facts, we propose a dynamic model of price determination between a dealer and an uninformed agent in a setting with asymmetric information, multi-period relationships and search frictions.
Presented at: WFA 2022, 4th Future of Financial Information Conference in Stockholm, University of Iowa, 2021 FMA New Ideas Session.
Explaining the Idiosyncratic Volatility Puzzle with a Bayesian-Updating Model
(with Xuhui (Nick) Pan, Bharat Raj Parajuli)
Abstract: We document that the idiosyncratic volatility (IVOL) puzzle exists only among firms that underperform their benchmark or release negative earnings surprises. We explain these findings using a Bayesian updating model with asymmetric signal precision in which agents observe noisy signals about future cash flows. In this setting, negative news are associated with relatively lower signal precision, negative momentum, and low subsequent returns. After controlling for relative performance (our proxy of news) and signal precision, the IVOL puzzle disappears. This performance- and signal-precision-based explanation alone can account for up to 83% of the IVOL puzzle, which is more than other existing theories combined.
Presented at: University of Iowa, University of Oklahoma.