Pre-Refunding Announcement Gains in U.S. Treasurys (2024)
Quantpedia Awards 2024 – 1st Place
Abstract
Each quarter, the Treasury Department unveils its refunding plan, detailing the following quarter’s treasury issuances in terms of size and maturity composition. We document substantial positive returns on long-term Treasurys on the day before these Treasury Refunding Announcements (TRAs), a pattern persisting since the 1990s and intensifying over the last two decades amidst growing Federal deficits. These pre-TRA gains are distinct from known end-of-month pricing patterns and account for a sizable fraction of annual yield and term premium changes. Implementing a trading strategy focused solely on these four days per year yields a Sharpe ratio of over 4. We provide evidence of uncertainty reduction and associated information production around TRAs as a potential mechanism. Finally, we discuss implications for some documented bond market patterns and the pre-FOMC drift in the equities market.
Factor Rebalancing (2024)
CFAM-ARX Paper Award, Finance Down Under Conference, 2022
Chicago Quantitative Alliance Academic Competition Second Prize, 2022
Abstract
When a mutual fund has persistent demand for a priced factor, the fund needs to rebalance its portfolio’s exposure to that factor as stock characteristics change over time. We establish this behavior of “factor rebalancing” and examine its implications for return predictability. We show that factor rebalancing is prevalent in mutual funds’ holding changes, and this behavior poses a source of predictable price pressure that operates independently from the passive trading induced by retail flows. Consistent with factor rebalancing, stocks whose characteristics are misaligned with underlying funds’ factor demand subsequently have lower returns, while wellaligned stocks subsequently have higher returns. We rule out alternative explanations based on private information, skills, and herding.
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Quantity, Risk, and Return (2024)
Financial Markets and Corporate Governance Conference Runner-up for Best Paper
Abstract
We propose a new model of expected stock returns that incorporates quantity information from market trading activities into the factor pricing framework. We posit that the expected return of a stock is determined by not only its factor risk exposures (beta) but also the factor’s quantity fluctuations (q) induced by trading flows, and hence term the model beta times quantity (BTQ). The rationale is that sophisticated investors should require a greater factor premium when they are more exposed to that factor after noise traders sell lots of stocks with high exposures to that factor. The BTQ model provides a compelling risk-based explanation for stock returns, which is otherwise obscured without considering the quantity information. The cross-sectional risk-return association, which is nearly flat unconditionally, strongly depends on the quantity variable. The structured BTQ model reliably predicts monthly stock returns out of sample, and addresses the factor zoo problem by selecting a small number of factors.
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Rediscover Predictability: Information from the Relative Prices of Long-term and Short-term Dividends (2019)
16th Paris December Finance Meeting Best Paper Award
Abstract
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.
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Delegation Uncertainty (2019)
Abstract
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.
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