CARLO AMBROGIO FAVERO

ABSTRACT: 

Aggregate stock prices and aggregate consumption share a common stochastic trend. We estimate this long-run relation in real time and recover a price--consumption cycle that captures transitory deviations of stock prices from their consumption-implied value. These deviations mean-revert over business-cycle horizons and predict future returns on the aggregate market and characteristics-sorted portfolios, both in- and out-of-sample, from one quarter to two years ahead. The cycle does not forecast consumption growth, but contains information about future dividend growth, and its return-predictive power disappears when consumption is excluded from the long-run relation. A simple model with permanent and transitory consumption shocks rationalizes these findings and the time variation in the estimated price--consumption loading. The evidence identifies consumption as a macroeconomic anchor for asset prices and departures from this anchor as a source of time-varying expected returns. 

KEYWORDS: Consumption Levels, Cointegration, Time-Varying Equity Premium, Return Predictability. 

JEL CODES: C22, E32, E44, G12.

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ABSTRACT

This paper examines the influence of mispricing proxies on stock return dynamics within the framework of Fama--French five-factor models. Specifically, we assess the role of mispricing proxies derived from cointegration between asset prices and factor prices, as well as sentiment indicators extracted from quarterly earnings conference calls.  Using quarterly data from 1980 to 2023 for the cross-section of DJIA-listed firms, our empirical analysis shows that deviations from long-run trends, driven by factor prices, have predictive power for stock returns after controlling for the five Fama--French factors. Stock-specific sentiment further enhances predictability. The additional predictability generated by mispricing proxies is fully explained by a nonlinear model in which sentiment determines the speed of adjustment toward the long-run trend identified by cointegration analysis when stock prices are above it. 

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This Revision July 2023

According to no-arbitrage, risk-adjusted returns should be unpredictable. Using several prominent factor models and a large cross-section of anomalies, we uncover a striking fact: past pricing errors predict future risk-adjusted anomaly returns. We show that past pricing errors can be interpreted as deviations of an anomaly price from the mean-variance efficient portfolio. Price deviations constitute an anomaly-specific predictor, endogenous to the given factor model, thus providing direct evidence for conditional misspecification. A zero-cost investment strategy using price deviations generates positive alphas.
     Our findings suggest that cross-sectional models should incorporate information in prices to capture the time-series dynamics of returns.

Keywords: Factor Models, Return Predictability, Conditional Misspecification, Mean-Variance
Portfolio, SDF
JEL codes: C38, G12, G17.

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ABSTRACT

We provide, calibrate and test a realistic model of the spread of SARS-Cov-2 in an
economy with different risks related to age and sectors. The model considers hospital
congestion and response of individuals adjusting their behavior to the virus' spread.
We measure precisely the size of these effects using real data for Italy on intensive care
capacity and mobility decisions; thus our claim is that the tradeoffs we estimate are
quantitatively, rather than qualitatively, approximately correct.
We characterize the policies of containment of the epidemic that are efficient with
respect to number of fatalities and GDP loss. Prudent policies of gradual return to
work may save many lives with limited economic costs, as long as they differentiate
by age group and risk sector. More careful behavior of individuals induced by the
perceived cost of infection may contribute to further reduce fatalities.

 JEL-Code: I12, I18, D6, H84

 Keywords: Covid-19,SARS-Cov-2 SEIR model, post lockdown policies.
 

Press coverage: Il Foglio; Promarket; Bloomberg;  Liberioltre; Sole24ore; Politico; Corriere della sera; Financecue

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This Version November 2022

ABSTRACT

We study the effects of fiscal consolidations in the United States and their propagation in the production network. We use a narrative approach to identify fiscal adjustments which are exogenous to output fluctuations. Then we apply spatial econometric techniques to separate the total effect of fiscal adjustments into a direct and network component. We find that fiscal adjustments based on increased taxation  are more recessionary than those based on spending cuts. Moreover, one quarter of the difference in their total output effect is explained by the stronger network propagation of taxes relative to government spending.

Keywords: industrial networks, fiscal adjustment plans, output growth, applied spatial econometrics.

JEL codes : E60, E62.

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This revision July 2018

Abstract: We investigate the macroeconomic effects of fiscal consolidations based upon government spending cuts, transfers cuts and tax hikes. We extend a narrative dataset of fiscal consolidations, finding details on over 3500 measures. Government spending and transfer cuts are much less harmful than tax hikes. Standard New Keynesian models match our results when fiscal shocks are persistent. Wealth effects on aggregate demand mitigates the impact of a persistent spending cut. Static distortions caused by persistent tax hikes cause larger shifts in aggregate supply under sticky prices. This channel explains different sizes of multipliers found in fiscal stimuli compared to consolidation plans.

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