Macroeconomic Uncertainty and Time-Varying Short-Horizon Return Predictability

Abstract A factor stochastic volatility model estimates the common component to output gap estimates produced by the staff of the Federal Reserve, its time-varying volatility, and time-varying, horizon-specific forecast uncertainty. The output gap estimates are uncertain even well after the fact. Nevertheless, the common component is clearly procyclical, and positive innovations to the common component produce movements in macroeconomic variables consistent with an increase in aggregate demand. Heightened macroeconomic uncertainty, as measured by the common component's volatility, leads to persistently negative economic responses.

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Variance risk in aggregate stock returns and time-varying return predictability

Journal of Financial Economics ◽

10.1016/j.jfineco.2018.10.002 ◽

2019 ◽

Vol 132 (1) ◽

pp. 150-174 ◽

Cited By ~ 12

Author(s):

Sungjune Pyun

Keyword(s):

Stock Returns ◽

Return Predictability ◽

Time Varying ◽

Variance Risk

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Bond Risk Premiums with Machine Learning

Review of Financial Studies ◽

10.1093/rfs/hhaa062 ◽

2020 ◽

Cited By ~ 3

Author(s):

Daniele Bianchi ◽

Matthias Büchner ◽

Andrea Tamoni

Keyword(s):

Machine Learning ◽

Yield Curve ◽

Return Predictability ◽

Time Varying ◽

Short Term ◽

Risk Premiums ◽

Machine Learning Methods ◽

Yield Information ◽

Bond Return ◽

Bond Risk

Abstract We show that machine learning methods, in particular, extreme trees and neural networks (NNs), provide strong statistical evidence in favor of bond return predictability. NN forecasts based on macroeconomic and yield information translate into economic gains that are larger than those obtained using yields alone. Interestingly, the nature of unspanned factors changes along the yield curve: stock- and labor-market-related variables are more relevant for short-term maturities, whereas output and income variables matter more for longer maturities. Finally, NN forecasts correlate with proxies for time-varying risk aversion and uncertainty, lending support to models featuring both channels.

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Time varying stock return predictability: Evidence from US sectors

Finance Research Letters ◽

10.1016/j.frl.2012.07.002 ◽

2013 ◽

Vol 10 (1) ◽

pp. 34-40 ◽

Cited By ~ 15

Author(s):

Massimo Guidolin ◽

David G. McMillan ◽

Mark E. Wohar

Keyword(s):

Stock Return ◽

Return Predictability ◽

Time Varying ◽

Stock Return Predictability

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Time-varying stock return predictability: the Eurozone case

Notas Económicas ◽

10.14195/2183-203x_41_3 ◽

2015 ◽

pp. 28-38

Author(s):

Nuno Silva

Keyword(s):

Statistical Tests ◽

Economic Value ◽

Return Predictability ◽

Time Varying ◽

Stock Return Predictability ◽

Varying Coefficients ◽

Time Varying Parameters ◽

Constant Coefficients ◽

Time Varying Coefficients ◽

Better Than

In this paper, we test the existence of predictability in eleven Eurozone stock markets, using both regressions with constant coefficients and with time-varying coefficients. Our results show that there is statistical evidence of predictability in some countries. The economic value of the forecasting models is much stronger than what could be inferred, based on the statistical tests. A meanvariance investor could have obtained substantial utility gains in most countries. Overall, models with time-varying parameters perform slightly better than models with constant coefficients.http://dx.doi.org/10.14195/2183‑203X_41_4

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Disappointment Aversion, Term Structure, and Predictability Puzzles in Bond Markets

Management Science ◽

10.1287/mnsc.2020.3757 ◽

2020 ◽

Author(s):

Patrick Augustin ◽

Roméo Tédongap

Keyword(s):

Interest Rates ◽

Term Structure ◽

Dynamic Equilibrium ◽

Time Varying ◽

State Variables ◽

Expectations Hypothesis ◽

Macroeconomic Uncertainty ◽

Disappointment Aversion ◽

Nominal Interest Rates ◽

Continuous State

We solve a dynamic equilibrium model with generalized disappointment-aversion preferences and continuous state-endowment dynamics. We apply the framework to the term structure of interest rates and show that the model generates an upward-sloping term structure of nominal interest rates and a downward-sloping term structure of real interest rates and that it accounts for the failure of the expectations hypothesis. The key ingredients are preferences with disappointment aversion, preference for early resolution of uncertainty, and an endowment economy with three state variables: time-varying macroeconomic uncertainty, time-varying expected inflation, and inflation uncertainty. This paper was accepted by Karl Diether, finance.

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