"Eu quase que nada não sei. Mas desconfio de muita coisa."
– Guimarães Rosa in "Grande Sertão: Veredas"
Asymmetric Violations of the Spanning Hypothesis - JMP - Updated frequently!
(joint with Gustavo Freire)
We document that the Spanning Hypothesis, which most macro-finance term structure models imply, is violated asymmetrically along the U.S. nominal yield curve. Using an interpretable reduced-form representation of yields and different Machine Learning techniques, we find that macroeconomic variables enhance the predictability of yields only for the shorter end of the yield curve, with no evidence of improvements for the longer end. Such asymmetry leads to higher predictability of bond returns for shorter maturities and economic gains to a mean-variance investor, adding nuance to the debat`e about yield curve predictability. We provide evidence that this extra predictability comes from more accurate predictions of the path of short rates and not from the term premia. We further show that moments in which the Federal Reserve deviates from the Taylor Rule are associated with sharper increases in the predictability of the short end when conditioning on macro data.
How much unspanned volatility can different shocks explain?
(Runner-up prize for best Quantitative Finance paper at the 2024 Brazilian Finance Society Meeting)
Affine term structure models generate sharp predictions about the time series evolution of bond prices. In special, they tie the quadratic variation of yields to the cross-section of average yields. I study these conditions for arbitrary portfolios of bonds in a flexible jump-diffusion setting and use jump-robust estimators of volatility to formally test these restrictions. My approach is more general than previous techniques because it does not constrain the dynamics of underlying factors under the physical measure. I also show that two thirds of all unspanned volatility can be captured by a single factor. I investigate if this factor is related to different shocks, such as monetary policy shocks, oil price shocks, and fiscal policy shocks in the US. I find that forward-guidance-type shocks fuel unspanned volatility, although such surprises can explain less than 10% of the unspanned volatility factor. Oil price shocks and unexpected tax changes also drive unspanned volatility, but only a small part of it.
Subjective Beliefs, Disagreement, and Market Return Predictability - Submitted on Aug, 2024
(joint with Felipe Iachan)
We jointly evaluate the ability of consensus beliefs about long-term earnings growth and analyst disagreement to predict stock market returns. We bridge the gap between the strands of literature testing theories of belief extrapolation and disagreement-fueled over-pricing. Using IBES analyst forecast data from 1982-2022 and conducting both in-sample and out-of-sample analyses, we find limited evidence that these measures of subjective beliefs predict returns. Our analyses across specifications and sample periods highlight the fragility of prior findings after including relevant controls or extending sample periods.
Intraday cross-sectional distributions of systematic risk - Journal of Econometrics, 2023
(joint with Torben Andersen, Martin Thyrsgaard and Viktor Todorov)
Bates-White Prize for the Best Paper at 2022 Annual Meeting of the Society for Financial Econometrics (SoFiE)
We develop a test for the detection of intraday changes in the cross-sectional distribution of assets’ exposure to observable factors. The test is constructed for a panel of high-frequency asset returns, with the size of the cross-section and the sampling frequency increasing simultaneously. It is based on a comparison of the empirical characteristic functions of estimates of the assets’ factor loadings at different parts of the trading day, formed from local blocks of asset returns and the corresponding factor realizations. The limiting behavior of the test statistic is governed by unobservable latent factors in the asset prices. The critical values of the test are constructed on the basis of a novel simulation-based procedure. Empirical implementation of the test to stocks in the S&P 500 index and the five Fama–French factors, as well as the momentum factor, reveals different intraday behavior of the factor loadings: assets’ exposure to size, market and value risks vary systematically over the trading day while the three remaining factors do not exhibit statistically significant intraday variation. Moreover, we find diverse, and for some factors large, reactions in the assets’ factor loadings to major economic or firm specific news releases. Finally, we document that time-varying correlations between the observable risk factors drive a wedge between the time-of-day pattern of market betas, estimated with and without control for the other observable risk factors.