scholarly journals Variance Risk Premia, Asset Predictability Puzzles, and Macroeconomic Uncertainty

2018 ◽  
Vol 10 (1) ◽  
pp. 481-497 ◽  
Author(s):  
Hao Zhou
Keyword(s):  
Risk Premium ◽  
Risk Premia ◽  
Forward Rate ◽  
Leverage Ratio ◽  
Variance Risk Premium ◽  
Long Run ◽  
Short Run ◽  
Variance Risk ◽  
Asset Pricing Puzzles ◽  
Interest Differential

This article reviews the predictability evidence on the variance risk premium: ( a) It predicts significant positive risk premia across equity, bond, currency, and credit markets; ( b) the predictability peaks at few-month horizons and dies out afterward; ( c) such a short-run predictability is complementary to the long-run predictability offered by the price-to-earnings ratio, forward rate, interest differential, and leverage ratio. Several structural approaches based on the notion of economic uncertainty are discussed for generating these stylized facts about the variance risk premium, which has broad implications for various empirical asset pricing puzzles.

scholarly journals Short-Run Bond Risk Premia

2019 ◽  
Vol 09 (03) ◽  
pp. 1950011
Author(s):  
Philippe Mueller ◽  
Andrea Vedolin ◽  
Hao Zhou
Keyword(s):  
Risk Premium ◽  
Predictive Power ◽  
Risk Premia ◽  
Forward Rates ◽  
Variance Risk Premium ◽  
Bond Risk Premia ◽  
Short Run ◽  
Variance Risk ◽  
Bond Risk ◽  
The One

In the short-run, bond risk premia exhibit pronounced spikes around major economic and financial crises. In contrast, long-term bond risk premia feature cyclical swings. We empirically examine the predictability of the market variance risk premium — a proxy of economic uncertainty — for bond risk premia and we show the strong predictive power for the one-month horizon that quickly recedes for longer horizons. The variance risk premium is largely orthogonal to well-established bond return predictors — forward rates, jumps, and macro variables. We rationalize our empirical findings in an equilibrium model of uncertainty about consumption and inflation which is coupled with recursive preferences. We show that the model can quantitatively explain the levels of bond and variance risk premia as well as the predictive power of the variance risk premium, while jointly matching salient features of other asset prices.

scholarly journals Variance risk premia for agricultural commodities

2019 ◽  
Vol 79 (3) ◽  
pp. 286-303
Author(s):  
Wenwen Xi ◽  
Dermot Hayes ◽  
Sergio Horacio Lence
Keyword(s):  
Risk Premium ◽  
Price Volatility ◽  
Risk Premia ◽  
Content Type ◽  
Risk Premiums ◽  
Variance Risk Premium ◽  
Revenue Insurance ◽  
Risk Neutral ◽  
Variance Risk ◽  
Practical Implications

Purpose The purpose of this paper is to study the variance risk premium in corn and soybean markets, where the variance risk premium is defined as the difference between the historical realized variance and the corresponding risk-neutral expected variance. Design/methodology/approach The authors compute variance risk premiums using historical derivatives data. The authors use regression analysis and time series econometrics methods, including EGARCH and the Kalman filter, to analyze variance risk premiums. Findings There are moderate commonalities in variance within the agricultural sector, but fairly weak commonalities between the agricultural and the equity sectors. Corn and soybean variance risk premia in dollar terms are time-varying and correlated with the risk-neutral expected variance. In contrast, agricultural commodity variance risk premia in log return terms are more likely to be constant and less correlated with the log risk-neutral expected variance. Variance and price (return) risk premia in agricultural markets are weakly correlated, and the correlation depends on the sign of the returns in the underlying commodity. Practical implications Commodity variance (i.e. volatility) risk cannot be hedged using futures markets. The results have practical implications for US crop insurance programs because the implied volatilities from the relevant options markets are used to estimate the price volatility factors used to generate premia for revenue insurance products such as “Revenue Protection” and “Revenue Protection with Harvest Price Exclusion.” The variance risk premia found implies that revenue insurance premia are overpriced. Originality/value The empirical results suggest that the implied volatilities in corn and soybean futures market overestimate true expected volatility by approximately 15 percent. This has implications for derivative products, such as revenue insurance, that use these implied volatilities to calculate fair premia.

scholarly journals Option-Based Estimation of the Price of Coskewness and Cokurtosis Risk

2020 ◽  
pp. 1-27
Author(s):  
Peter Christoffersen ◽  
Mathieu Fournier ◽  
Kris Jacobs ◽  
Mehdi Karoui
Keyword(s):  
Risk Premium ◽  
Risk Premia ◽  
Factor Models ◽  
Option Prices ◽  
Variance Risk Premium ◽  
Market Return ◽  
Price Of Risk ◽  
Variance Risk ◽  
Index Option

Abstract We show that the prices of risk for factors that are nonlinear in the market return can be obtained using index option prices. The price of coskewness risk corresponds to the market variance risk premium, and the price of cokurtosis risk corresponds to the market skewness risk premium. Option-based estimates of the prices of risk lead to reasonable values of the associated risk premia. An analysis of factor models with coskewness risk indicates that the new estimates of the price of risk improve the models’ performance compared with regression-based estimates.

scholarly journals Inflation Risk Premia, Yield Volatility, and Macro Factors

2018 ◽  
Vol 17 (3) ◽  
pp. 397-431 ◽  
Author(s):  
Andrea Berardi ◽  
Alberto Plazzi
Keyword(s):  
Term Structure ◽  
Risk Premium ◽  
Implied Volatility ◽  
Risk Premia ◽  
Output Growth ◽  
Inflation Risk ◽  
Variance Risk Premium ◽  
Real Risk ◽  
Variance Risk ◽  
Inflation Risk Premia

Abstract We incorporate a latent stochastic volatility factor and macroeconomic expectations in an affine model for the term structure of nominal and real rates. We estimate the model over 1999–2016 on U.S. data for nominal and TIPS yields, the realized and implied volatility of T-bonds, and survey forecasts of GDP growth and inflation. We find relatively stable inflation risk premia averaging at 40 basis points at the long-end, and which are strongly related to the volatility factor and conditional mean of output growth. We also document real risk premia that turn negative in the post-crisis period, and a non-negligible variance risk premium.

Portfolio allocation across variance risk premia

2019 ◽  
Vol 20 (5) ◽  
pp. 556-593
Author(s):  
Julien Chevallier ◽  
Dinh-Tri Vo
Keyword(s):  
Risk Premium ◽  
Regime Switching ◽  
Realized Volatility ◽  
Risk Premia ◽  
Covariance Matrices ◽  
Management Style ◽  
Portfolio Performance ◽  
Content Type ◽  
Variance Risk Premium ◽  
Variance Risk

Purpose In asset management, what if clients want to purchase protection from risk factors, under the form of variance risk premia. This paper aims to address this topic by developing a portfolio optimization framework based on the criterion of the minimum variance risk premium (VRP) for any investor selecting stocks with an expected target return while minimizing the risk aversion associated to the portfolio according to “good” and “bad” times. Design/methodology/approach To accomplish this portfolio selection problem, the authors compute variance risk-premium as the difference from high-frequencies' realized volatility and options' implied volatility stemming from 19 stock markets, estimate a 2-state Markov-switching model on the variance risk-premia and optimize variance risk-premia portfolios across non-overlapping regions. The period goes from March 16, 2011, to March 28, 2018. Findings The authors find that optimized portfolios based on variance-covariance matrices stemming from VRP do not consistently outperform the benchmark based on daily returns. Several robustness checks are investigated by minimizing historical, realized or implicit variances, with/without regime switching. In a boundary case, accounting for the realized variance risk factor in portfolio decisions can be seen as a promising alternative from a portfolio performance perspective. Practical implications As a new management “style”, the realized volatility approach can, therefore, bring incremental value to construct the conditional covariance matrix estimates. Originality/value The authors assess the portfolio performance determined by the variance-covariance matrices that are derived by four models: “naive” (Markowitz returns benchmark), non-switching VRP, maximum likelihood regime-switching VRP and Bayesian regime switching VRP. The authors examine the best return-risk combination through the calculation of the Sharpe ratio. They also assess another different portfolio strategy: the risk parity approach.

OUT-OF-SAMPLE STOCK RETURN PREDICTION USING HIGHER-ORDER MOMENTS

2018 ◽  
Vol 21 (06) ◽  
pp. 1850043 ◽  
Author(s):  
JOSÉ AFONSO FAIAS ◽  
TIAGO CASTEL-BRANCO
Keyword(s):  
Stock Returns ◽  
Cross Section ◽  
Risk Premium ◽  
Risk Premia ◽  
Market Returns ◽  
Variance Risk Premium ◽  
Stock Return Prediction ◽  
Out Of Sample ◽  
The Cross ◽  
Variance Risk

We analyze variance, skewness and kurtosis risk premia and their option-implied and realized components as predictors of excess market returns and of the cross-section of stock returns. We find that the variance risk premium is the only moment-based variable to predict S&P 500 index excess returns, with a monthly out-of-sample [Formula: see text] above 6% for the period between 2001 and 2014. Nonetheless, all aggregate moment-based variables are effective in predicting the cross-section of stock returns. Self-financed portfolios long on the stocks least exposed to the aggregate moment-based variable and short on the stocks most exposed to it achieve positive and significant Carhart 4-factor alphas and a considerably higher Sharpe ratio than the S&P 500 index, with positive skewness.

scholarly journals Risk, Uncertainty, and Expected Returns

2016 ◽  
Vol 51 (3) ◽  
pp. 707-735 ◽  
Author(s):  
Turan G. Bali ◽  
Hao Zhou
Keyword(s):  
Stock Returns ◽  
Risk Premium ◽  
Risk Premia ◽  
Expected Returns ◽  
Cross Sectional ◽  
Asset Pricing Model ◽  
Variance Risk Premium ◽  
Equity Portfolios ◽  
Variance Risk ◽  
Highly Correlated

AbstractA conditional asset pricing model with risk and uncertainty implies that the time-varying exposures of equity portfolios to the market and uncertainty factors carry positive risk premia. The empirical results from the size, book-to-market, momentum, and industry portfolios indicate that the conditional covariances of equity portfolios with market and uncertainty predict the time-series and cross-sectional variation in stock returns. We find that equity portfolios that are highly correlated with economic uncertainty proxied by the variance risk premium (VRP) carry a significant annualized 8% premium relative to portfolios that are minimally correlated with VRP.

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