Research

Monetary Factor Momentum, Adam Farago, Erik Hjalmarsson, and Hongtao Qiu, coming soon

We document strong persistence in factor returns following Federal Open Market Committee (FOMC) announcements, as factors tend to sustain their performance afterward. This monetary factor momentum is both economically sizable and statistically significant, and it is distinct from previously documented time-series and cross-sectional factor momentum. We interpret these findings through a mispricing channel: price pressure from persistent FOMC-related sentiment demand for factors cannot be fully arbitraged away. Consistent with this channel, factor returns have much stronger autocorrelation in the FOMC cycle and factor performance tends to remain persistent across multiple FOMC meetings. The monetary factor momentum effect also concentrates in FOMC days with high VIX levels, which correspond to times with more severe limits to arbitrage.

Presidential Cycles in PEAD, with Zhi Da and Liyao Wang

Post-earnings announcement drift (PEAD) displays presidential cycles: it earns 4.1% per year during Democratic presidencies but its profitability increases significantly to 14.9% during Republican presidencies. Survey-based evidence also indicates substantial underreaction to earnings news when the US president is Republican. The tax component of firm earnings exhibits significantly higher volatility during Republican periods, likely reflecting higher tax policy uncertainty. Consistently, we find that the PEAD is much stronger for firms with larger exposure to tax policy changes during Republican presidencies. This explanation accounts for the observed presidential cycles in PEAD, whereas existing explanations for PEAD cannot. The cycles are more pronounced among non-microcap firms.

Analysts Are Good at Ranking Stocks , with Adam Farago and Erik Hjalmarsson, R&R at  Journal of Finance

Sell-side analysts' forecasts of stock returns are biased and the consensus forecast is a poor cross-sectional predictor. In sharp contrast, the implicit ranking of stocks by each analyst is highly informative of subsequent returns. Long-short portfolios sorted on these rankings result in large and highly significant excess returns that cannot be explained by previous anomaly characteristics. The strong performance is most easily understood by noting the similarity between rankings and within-analyst demeaned forecasts. The latter are equivalent to removing each analyst's fixed effect and thus controlling for unobservable analyst-specific biases.

Inflation Risk, Ambiguity, and the Cross-Section of Stock Returns, with Guihai Zhao

Inflation premia among individual stocks are moderate on average, yet their magnitude rises by 1.6% to 3.2% per month when ambiguity is high. This finding is consistent with an equilibrium model with ambiguity in which the investor prices stocks using a worst-case inflation model. We show that inflation ambiguity amplifies the magnitude of the inflation premium. Moreover, through a channel complementary to but distinct from the inflation cyclicality, we show that a higher inflation-ambiguity correlation makes stocks with higher inflation betas better hedges for ambiguity. The monthly inflation premium is 0.20% under negative correlation but drops to -1.94% under positive correlation. Therefore, the time-varying inflation premium among individual stocks is largely driven by the ambiguity premium.

Factor MAX and Predictable Factor Returns, with Liyao Wang

Extreme factor returns contain valuable information about future factor performance. Factors with the highest maximum daily returns in the past month outperform those with the lowest maximum returns by 0.32% per month (t = 5.89). The profitability of this factor MAX strategy is not subsumed by factor momentum or by a range of lottery or momentum-related anomalies at the stock-level. Our evidence suggests that investors’ limited attention and resulting underreaction to extreme factor-level news drive the predictive power of factor MAX. Consistent with this mechanism, the MAX strategy is more profitable for factors that receive low investor attention or whose extreme-return dates do not coincide with salient macroeconomic or firm-specific earnings announcements. Further evidence shows that investors appear to overreact to stock-level MAX events yet underreact to factor-level MAX events, which helps reconcile why factor MAX predicts returns in the opposite direction of stock MAX.