Political Uncertainty and the US Market Risk Premium

2020 ◽  
Author(s):  
Richard Paul Gregory
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Richard P. Gregory

PurposeThe purpose of this study is to examine the bi-directional causality between political uncertainty and the market risk premium in the US.Design/methodology/approachI use a theoretical model to motivate signs and then check signs based on a vector autoregression.FindingsI find that political uncertainty has a small positive, delayed effect on the market risk premium. The market risk premium, on the other hand, has a large permanent, negative effect on political uncertainty.Originality/valueThis is the first research paper to consider the bi-directional effects of political uncertainty on the market risk premium and vice versa. It also finds interesting empirical results.


2019 ◽  
Vol 14 (7) ◽  
pp. 160
Author(s):  
Antonio Salvi ◽  
Emanuele Teti ◽  
Anastasia Giakoumelou

This paper investigates the relationship between leveraged buyouts (LBOs) and initial public offerings (IPOs) with the market risk premium in the European market. We expand our study to the period spanning from the first quarter of 1999 to the fourth quarter of 2016. Our longitudinal analysis finds evidence of an inverse relationship between market risk premium and the volume of LBOs, as well as a direct relationship between the latter and the stock index STOXX Europe 600. Additionally, our analysis of IPO operations confirms the significance of all factors considered in predicting the IPO trends in Europe, with a persisting accentuated impact generated by the market risk premium and the stock index STOXX Europe 600, also in this case. While previous analyses majorly focused on the US market, this paper is among first attempts to examine the topic of interest in the European context.


2011 ◽  
Vol 47 (1) ◽  
pp. 115-135 ◽  
Author(s):  
Mariano González ◽  
Juan Nave ◽  
Gonzalo Rubio

AbstractThis paper explores the cross-sectional variation of expected returns for a large cross section of industry and size/book-to-market portfolios. We employ mixed data sampling (MIDAS) to estimate a portfolio’s conditional beta with the market and with alternative risk factors and innovations to well-known macroeconomic variables. The market risk premium is positive and significant, and the result is robust to alternative asset pricing specifications and model misspecification. However, the traditional 2-pass ordinary least squares (OLS) cross-sectional regressions produce an estimate of the market risk premium that is negative, and significantly different from 0. Using alternative procedures, we compare both beta estimators. We conclude that beta estimates under MIDAS present lower mean absolute forecasting errors and generate better out-of-sample performance of the optimized portfolios relative to OLS betas.


2014 ◽  
Vol 23 (2) ◽  
pp. 51-58 ◽  
Author(s):  
Austin Murphy ◽  
Liang Fu ◽  
Terry Benzschawel

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