Stock Return Predictability and Variance Risk Premia: Statistical Inference and International Evidence

Abstract

Recent empirical evidence suggests that the variance risk premium predicts aggregate stock market returns. We demonstrate that statistical finite sample biases cannot "explain" this apparent predictability. Further corroborating the existing evidence of the United States, we show that country-specific regressions for France, Germany, Japan, Switzerland, the Netherlands, Belgium, and the United Kingdom result in quite similar patterns. Defining a "global" variance risk premium, we uncover even stronger predictability and almost identical cross-country patterns through the use of panel regressions.

Forecasting International Index Returns Using Option-Implied Variables

“…International evidence for VRP's usefulness is limited, however. Bollerslev, Marrone, Xu and Zhou (2014) run predictive regressions using VRP for international equity indexes and find results that are similar to the S&P for most countries in their sample (see also Londono, 2015). Both U.S. and international studies, however, use monthly-sampled data.…”

“…This literature has usually adopted a monthly frequency and has reported a peak in predictability at the quarterly horizon (Bollerslev, Tauchen and Zhou, 2009;Bollerslev et al, 2014). Shorter horizons are, however, of considerable interest, as risk management practices are often focused on short-run measures [e.g., Brown (2001); Brownlees, Engle and Kelly (2014); Christoffersen and Diebold (2000)].…”

“…where VRP is the variance risk premium defined as risk-neutral variance minus realized variance from intraday returns; RNS t and RNK t are respectively the third and fourth moments of the risk-neutral distribution at time t; and FH t is the Foster-Hart measure of riskiness computed from the risk-neutral distribution. Following Bollerslev et al (2014), we use bootstrapped critical values to evaluate standard errors. We use a simulation design based on the VAR (1) GARCH(1,1) DCC model (Engle, 2002) suggested in Bollerslev et al (2014) to compute bootstrapped critical values for the Newey-West tstatistics for each of the four predictive variables in the regression analysis.…”

“…In accordance with the literature, simulations are performed on the critical points of our tests to account for persistence in cumulative returns (Bollerslev et al, 2014;. Then, we conduct out-of-sample forecasts, compute the 2 , and use forecasting tests to assess the significance of the forecast improvements (Clark and MacCracken, 2005).…”

Variance Premium and Implied Volatility in a Low-Liquidity Option Market

“…Bollerslev, Marrone, Xu, & Zhou (2014) finds that the variance premium is a strong predictor of stock returns in France, Germany, Switzerland, The Netherlands, Belgium, the UK and, marginally, in Japan. Our results confirm Bollerslev et al (2014) findings for the Brazilian market. To the best of our knowledge, our study is the first to show this for an emerging economy.…”