Expected stock return and mixed frequency variance risk premium data
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ORIGINAL RESEARCH
Expected stock return and mixed frequency variance risk premium data Ruobing Liu1 · Jianhui Yang1 · Chuanyang Ruan2,3 Received: 10 June 2019 / Accepted: 26 September 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract Motivated by the research of the variance risk premium (VRP) and MIDAS model, we employ the VRP with different maturities and the ADL-MIDAS regression model to forecast the expected stock return in Standard & Poor 500 market. The VRP is defined as the difference between the realized variance and the implied variance of the options. By using Standard & Poor 500 index options, we provide the empirical tests of the forecasting performance provided by the VRP with different maturities to the expected stock returns in the Standard & Poor 500 stock index market. Based on the empirical results, we know the VRP with 1-month and 2-month maturities can provide the best out-of-sample forecast. Keywords ADL-MIDAS model · Variance risk premium · Forecast combination · Expected stock return
1 Introduction The predictability of the stock return is a vital question that researchers concern. Many researchers provide empirical research that the difference between implied and realized variance can explain a nontrivial fraction of the expected stock return (see Bollerslev et al. (2009), (2014)). The difference between ‘model-free’ implied variance and realized variance is termed as variance risk premium (VRP) (see Carr and Wu (2009), Bollerslev et al. (2011)). Former research (see Carr and Wu (2009), Corte et al. (2016), Gonzalez-Urteaga and Rubio (2016), Bekaert and Hoerova (2014), Bollerslev et al. (2009)) focuses on the research with VPR which is expressed as a nonlinear
* Chuanyang Ruan [email protected] Ruobing Liu [email protected] Jianhui Yang [email protected] 1
School of Business Administration, South China of Technology, Guangzhou 510640, China
2
School of Business Administration, Guangdong University of Finance &Economics, Guangzhou 510320, China
3
Antai College of Economics and Management, Shanghai Jiao Tong University, Shanghai 200240, China
function of the short-term aggregate degree of risk aversion in the market. According to the research of Bollerslev et al. (2009), the VRP with 1-month maturity can serve as an useful predictor of the expected stock return. Bekaert and Hoerova (2014) provide more evidence on the predictive power of VRP on the stock return. These studies illustrate the forecasting performance of VRP with 1-month maturity. The forecasting performance of the VRP with different maturities is still unexplored. VRP can measure the aggregate market risk aversion. The VRP with different maturities can be seen as a nonlinear function of the aggregate degree of risk aversion at the different horizon. How the long-term aggregate market risk aversion affects future variation in expected returns? This paper employs the panel data of VRP with maturities ranging from 1-month to 3-year as the independent variable to forecast t
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