Factor Demand and Factor Returns
We propose and test a novel mechanism that links mutual funds’ factor demand to the performance of factors in the cross-section. Under this mechanism, a fund’s demand for a given factor is not elastic and induces a rebalancing motive, leading to predictable rebalancing behavior at the stock level. The resulting price pressure generates cross-sectional return predictability: stocks whose characteristics are well-matched with the underlying funds’ factor demand experience more buying pressure and higher returns, whereas mismatched stocks experience more selling and lower returns. We calculate the scale of factor rebalancing and estimate an average factor demand elasticity of -0.23.
2019 RCFS/RAPS Conference at Baha Mar, 2019 CICF, 2019 SGF, 2021 AFA, 2021 MFA, 2021 NFA; Birkbeck (University of London), BlackRock, Cambridge, LSE, Notre Dame, Peking University, USI Lugano, Yale SOM
Rating Agency Beliefs and Credit Market Distortions
The beliefs of credit rating agencies (CRAs) induce mispricing in bond markets which in turn affect firms’ financial and investment decisions. We measure CRA beliefs as the difference in forecasts of future aggregate credit spreads between CRAs and a consensus of other financial institutions. We show that when CRAs are relatively more optimistic, they issue higher credit ratings even though their forecasts do not contain additional information regarding future aggregate yields. Moreover, this optimism leads to lower initial yields and subsequent negative returns for newly issued bonds. In response to this mispricing, firms increase their debt levels, leverage and investment, where the effects are most pronounced among rated firms. Finally, when CRAs are more optimistic, firms are more likely to be rated. Our results are consistent with investors being overly reliant on the beliefs of rating agencies, causing mispricing in credit markets, which firms then take advantage of. Overall, our analysis shows how CRA beliefs drive aggregate financing and investment behavior through mispricing in credit markets.
Under- and Overreaction in Yield Curve Expectations
I document a robust pattern in how Treasury market participants’ yield curve expectations respond to new information: forecasts for short-term rates underreact to news while forecasts for long-term rates overreact. I propose a new explanation of this based on ``autocorrelation averaging,’’ whereby, due to limited processing capacity, forecasters’ estimate of the autocorrelation of a given process is biased toward the average autocorrelation of all related processes. Consistent with this view, forecasters overestimate the autocorrelation of the less persistent term-premium component of interest rates and underestimate the autocorrelation of the more persistent short-rate component; a calibrated model quantitatively matches the documented pattern of misreaction. Moreover, banks’ allocations to Treasuries vary positively with their expectations of bond returns and misreaction proxies can strongly predict future short- and long-term bond returns, respectively.
Hong Kong University of Science and Technology, Cheung Kong Graduate School of Business, University of Hong Kong, National University of Singapore, Chinese University of Hong Kong, Notre Dame, Michigan Ross, University of Florida, Cornerstone Research, Yale SOM, 2021 WFA
Rediscover Predictability: A Duration-Based Approach
16th Paris December Finance Meeting Best Paper Award
The ratio of long- to short-term dividend prices, “price ratio” ($pr_t$), predicts annual market return with an out-of-sample $R^2$ of 19%, subsuming the predictive power of price-dividend ratio ($pd_t$). After controlling for $pr_t$, $pd_t$ predicts dividend growth with an out-of-sample $R^2$ of 30%. Our results hold outside the U.S. An exponential-affine model shows that the key to our findings is the (lack of) persistence of expected dividend growth. We find the expected return is countercyclical and responds strongly to monetary policy shocks. As implied by ICAPM, shocks to $pr_t$, the expected-return proxy, are priced in the cross-section.
LBS Trans-Atlantic Doctoral Conference, Yale SOM, Econometric Society Annual Meeting, 2018 NFA, Fall Finance Conference at UT Dallas, Örebro Workshop on Predicting Asset Returns, 16th Paris December Finance Meeting, HKUST Finance Symposium, 2019 RCFS/RAPS Conference at Baha Mar
Delegation bears an intrinsic form of uncertainty. Investors hire managers for their superior models of asset markets, but delegation outcome is uncertain precisely because managers’ model is unknown to investors. We model investors’ delegation decision as a trade-off between asset return uncertainty and delegation uncertainty. Our theory explains several puzzles on fund performances. It also delivers asset pricing implications supported by our empirical analysis: (1) because investors partially delegate and hedge against delegation uncertainty, CAPM alpha arises; (2) the cross-section dispersion of alpha increases in uncertainty; (3) managers bet on alpha, engaging in factor timing, but factors’ alpha is immune to the rise of their arbitrage capital - when investors delegate more, delegation hedging becomes stronger. Finally, we offer a novel approach to extract model uncertainty from asset returns, delegation, and survey expectations.
ASU Sonoran Winter Finance, CEPR ESSFM Gerzensee, CUHK, European Winter Finance Summit, Geneva Workshop on Financial Stability, INSEAD, 2019 MFA, Stanford SITE, University of Zurich