Expected Stock Returns and Variance Risk Premia
TL;DR: This article found that the difference between implied and realized variances, or the variance risk premium, is able to explain more than fifteen percent of the ex-post time series variation in quarterly excess returns on the market portfolio over the 1990 to 2005 sample period, with high premia predicting high (low) future returns.
read more
Abstract: We find that the difference between implied and realized variances, or the variance risk premium, is able to explain more than fifteen percent of the ex-post time series variation in quarterly excess returns on the market portfolio over the 1990 to 2005 sample period, with high (low) premia predicting high (low) future returns. The magnitude of the return predictability of the variance risk premium easily dominates that afforded by standard predictor variables like the P/E ratio, the dividend yield, the default spread, and the consumption-wealth ratio (CAY). Moreover, combining the variance risk premium with the P/E ratio results in an R 2 for the quarterly returns of more than twenty-five percent. The results depend crucially on the use of “modelfree”, as opposed to standard Black-Scholes, implied variances, and realized variances constructed from high-frequency intraday, as opposed to daily, data. Our findings suggest that temporal variation in risk and risk-aversion both play an important role in determining stock market returns.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Figures

Table 5 Annual return regressions 
Table 4 Quarterly return regressions 
Figure 1 Model-implied slopes and R2s The figure shows the population slope coefficients and R2s from regressions of the scaled h-period returns on the variance difference implied by the equilibrium model. The four different lines refer to the four different parameter configurations discussed in the main text. 
Table 2 Variance premium return regressions 
Table 3 Monthly return regressions
Citations
Anxiety in Returns
Uta Pigorsch,Sebastian Schäfer +1 more
TL;DR: Risk-averse investors exhibit anxiety towards stocks with realized losses, yielding lower subsequent returns, and this anxiety predicts cross-sectional returns in out-of-sample tests, supporting convex risk aversion and empirical risk premia.
2
Ambiguity and asset pricing: An empirical investigation for an emerging market
Seza Danışoğlu,Baki Cem Sahin +1 more
TL;DR: This article explored the impact of ambiguity on returns of both individual stocks and stock portfolios in an emerging market setting and found that stocks with a high (low) sensitivity to ambiguity generate higher (lower) excess returns.
2
Predicting the Equity Market with Option-Implied Variables
TL;DR: In this paper, the authors comprehensively analyze the predictive power of several option-implied variables for monthly S&P 500 excess returns and realized variance, and reveal that statistical evidence of predictability does not necessarily lead to economic gains.
q-Gaussian Model of Default: Valuation of CDS Spreads
TL;DR: In this article, a simple formula for a term-structure of CDS spreads is derived based on the generalized Merton distance to default, the risk neutral recovery rate, and the Tsallis entropic parameter q.
2
Equity Portfolio Management Using Option Price Information
Peter Christoffersen,Xuhui Pan +1 more
TL;DR: The authors survey the recent academic literature that uses option-implied information to construct equity portfolios and show that using information in individual equity options, exposure to information in market index options, and exposure to crude oil option information can also help construct better mean-variance portfolios and better estimates of market beta.
References
Common risk factors in the returns on stocks and bonds
Eugene F. Fama,Kenneth R. French +1 more
TL;DR: In this article, the authors identify five common risk factors in the returns on stocks and bonds, including three stock-market factors: an overall market factor and factors related to firm size and book-to-market equity.
29.7K
A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix
Whitney K. Newey,Kenneth D. West +1 more
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
The Cross‐Section of Expected Stock Returns
Eugene F. Fama,Kenneth R. French +1 more
TL;DR: In this paper, Bhandari et al. found that the relationship between market/3 and average return is flat, even when 3 is the only explanatory variable, and when the tests allow for variation in 3 that is unrelated to size.
15.9K
•Posted Content
A Simple, Positive Semi-Definite, Heteroskedasticity and Autocorrelationconsistent Covariance Matrix
TL;DR: In this article, a simple method of calculating a heteroskedasticity and autocorrelation consistent covariance matrix that is positive semi-definite by construction is described.
15.6K
A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options
TL;DR: In this paper, a closed-form solution for the price of a European call option on an asset with stochastic volatility is derived based on characteristi c functions and can be applied to other problems.