Expected Returns and the Business Cycle: Heterogeneous Goods and Time-Varying Risk Aversion

2008 ◽  
Author(s):  
Lars A. Lochstoer
Keyword(s):  
Business Cycle ◽  
Risk Aversion ◽  
Expected Returns ◽  
Time Varying ◽  
Heterogeneous Goods ◽  
The Business Cycle

Getting Paid to Hedge: Why Don’t Investors Pay a Premium to Hedge Downturns?

2018 ◽  
Vol 54 (3) ◽  
pp. 1157-1192
Author(s):  
Nishad Kapadia ◽  
Barbara Bennett Ostdiek ◽  
James P. Weston ◽  
Morad Zekhnini
Keyword(s):  
Gross Domestic Product ◽  
Business Cycle ◽  
Expected Returns ◽  
Firm Characteristics ◽  
Cycle Frequency ◽  
Gross Domestic Product Growth ◽  
Market Index ◽  
Ex Ante ◽  
Out Of Sample ◽  
The Business Cycle

Stocks that hedge sustained market downturns should have low expected returns, but they do not. We use ex ante firm characteristics and covariances to construct a tradable safe minus risky (SMR) portfolio that hedges market downturns out of sample. Although downturns (peaks to troughs in market index levels at the business-cycle frequency) predict significant declines in gross domestic product growth, SMR has significant positive average returns and 4-factor alphas (both around 0.8% per month). Risk-based models do not explain SMR’s returns, but mispricing does. Risky stocks are overpriced when sentiment is high, resulting in subsequent returns of -0.9% per month.

scholarly journals Modeling time-variation over the business cycle (1960–2017): an international perspective

2018 ◽  
Vol 22 (5) ◽  
Author(s):  
Enrique Martínez-García
Keyword(s):  
Business Cycles ◽  
Business Cycle ◽  
International Business ◽  
Linear Models ◽  
Trade Openness ◽  
Form Solution ◽  
Reduced Form ◽  
Time Varying ◽  
Time Varying Parameter ◽  
The Business Cycle

AbstractIn this paper, I explore the changes in international business cycles with quarterly data for the eight largest advanced economies (US, UK, Germany, France, Italy, Spain, Japan, and Canada) since the 1960s. Using a time-varying parameter model with stochastic volatility for real GDP growth and inflation allows their dynamics to change over time, approximating nonlinearities in the data that otherwise would not be adequately accounted for with linear models [Granger, Clive W.J., Timo Teräsvirta, and Heather M. Anderson. 1991. “Modeling Nonlinearity over the Business Cycle.”In NBER book Business Cycles, Indicators and Forecasting (1993), edited by James H. Stock and Mark W. Watson, University of Chicago Press.; Granger, Clive W.J. 2008. “Non-Linear Models: Where Do We Go Next – Time Varying Parameter Models?”Studies in Nonlinear Dynamics and Econometrics12 (3): 1–11.]. With that empirical model, I document a period of declining macro volatility since the 1980s, followed by increasing (and diverging) inflation volatility since the mid-1990s. I also find significant shifts in inflation persistence and cyclicality, as well as in macro synchronization and even forecastability. The 2008 global recession appears to have had an impact on some of this. I ground my empirical strategy on the reduced-form solution of the workhorse New Keynesian model and, motivated by theory, explore the relationship between greater trade openness (globalization) and the reported shifts in international business cycle. I show that globalization has sizeable (yet nonlinear) effects in the data consistent with the implications of the model – yet globalization’s contribution is not a foregone conclusion, depending crucially on more than the degree of openness of the international economy.

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