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Author:Chen, Andrew Y. 

Discussion Paper
Has the Inflation Risk Premium Fallen? Is it Now Negative?

In this note, we examine the theoretical determinants of one important component of inflation compensation, the inflation risk premium, and argue that a secular decline in the inflation risk premium may be responsible for a substantial portion of the decline in inflation compensation in recent years.
FEDS Notes , Paper 2016-04-04

Working Paper
Precautionary Volatility and Asset Prices

Many theories of asset prices assume time-varying uncertainty in order to generate time-varying risk premia. This paper generates time-varying uncertainty endogenously, through precautionary saving dynamics. Precautionary motives prescribe that, in bad times, next period's consumption should be very sensitive to news. This time-varying sensitivity results in time-varying consumption volatility. Production makes this channel visible, and external habit preferences amplify it. An estimated model featuring this channel quantitatively accounts for excess return and dividend predictability ...
Finance and Economics Discussion Series , Paper 2014-59

Working Paper
Habit, Production, and the Cross-Section of Stock Returns

Solutions to the equity premium puzzle should inform us about the cross-section of stock returns. An external habit model with heterogeneous firms reproduces numerous stylized facts about both the equity premium and the value premium. The equity premium is large, time-varying, and linked with consumption volatility. The cross-section of expected returns is log-linear in B/M, and the slope matches the data. The explanation for the value premium lies in the interaction between the cross-section of cash flows and the time-varying risk premium. Value firms are temporarily low productivity firms, ...
Finance and Economics Discussion Series , Paper 2014-103

Working Paper
The Limits of p-Hacking : A Thought Experiment

Suppose that asset pricing factors are just p-hacked noise. How much p-hacking is required to produce the 300 factors documented by academics? I show that, if 10,000 academics generate 1 factor every minute, it takes 15 million years of p-hacking. This absurd conclusion comes from applying the p-hacking theory to published data. To fit the fat right tail of published t-stats, the p-hacking theory requires that the probability of publishing t-stats < 6.0 is infinitesimal. Thus it takes a ridiculous amount of p-hacking to publish a single t-stat. These results show that p-hacking alone cannot ...
Finance and Economics Discussion Series , Paper 2019-016

Working Paper
Zeroing in on the Expected Returns of Anomalies

We zero in on the expected returns of long-short portfolios based on 120 stock market anomalies by accounting for (1) effective bid-ask spreads, (2) post-publication effects, and (3) the modern era of trading technology that began in the early 2000s. Net of these effects, the average anomaly's expected return is a measly 8 bps per month. The strongest anomalies return only 10-20 bps after accounting for data-mining with either out-of-sample tests or empirical Bayesian methods. Expected returns are negligible despite cost optimizations that produce impressive net returns in-sample and the ...
Finance and Economics Discussion Series , Paper 2020-039

Working Paper
A Likelihood-Based Comparison of Macro Asset Pricing Models

We estimate asset pricing models with multiple risks: long-run growth, long-run volatility, habit, and a residual. The Bayesian estimation accounts for the entire likelihood of consumption, dividends, and the price-dividend ratio. We find that the residual represents at least 80% of the variance of the price-dividend ratio. Moreover, the residual tracks most recognizable features of stock market history such as the 1990's boom and bust. Long run risks and habit contribute primarily in crises. The dominance of the residual comes from the low correlation between asset prices and consumption ...
Finance and Economics Discussion Series , Paper 2017-024

Working Paper
Publication Bias and the Cross-Section of Stock Returns

We develop an estimator for publication bias and apply it to 156 hedge portfolios based on published cross-sectional return predictors. Publication bias adjusted returns are only 12% smaller than in-sample returns. The small bias comes from the dispersion of returns across predictors, which is too large to be accounted for by data-mined noise. Among predictors that can survive journal review, a low t-stat hurdle of 1.8 controls for multiple testing using statistics recommended by Harvey, Liu, and Zhu (2015). The estimated bias is too small to account for the deterioration in returns after ...
Finance and Economics Discussion Series , Paper 2018-033

Working Paper
Open Source Cross-Sectional Asset Pricing

We provide data and code that successfully reproduces nearly all crosssectional stock return predictors. Our 319 characteristics draw from previous meta-studies, but we differ by comparing our t-stats to the original papers' results. For the 161 characteristics that were clearly significant in the original papers, 98% of our long-short portfolios find t-stats above 1.96. For the 44 characteristics that had mixed evidence, our reproductions find t-stats of 2 on average. A regression of reproduced t-stats on original longshort t-stats finds a slope of 0.90 and an R2 of 83%. Mean returns ...
Finance and Economics Discussion Series , Paper 2021-037

Discussion Paper
The Stock Market–Real Economy "Disconnect": A Closer Look

Between March and September 2020, broad equity price indexes around the world experienced a historic rally. Although this rally followed a significant decline in stock prices, it appears difficult to explain due to continuing concerns about the global pandemic and national economies running far below their potentials.
FEDS Notes , Paper 2020-10-14-2

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