Theoretical risk factors underlying time-variations of risk premium across asset classes are typically unobservable or hard to measure by construction. Important examples include risk factors in Long Run Risk [LRR] structural models (Bansal and Yaron 2004) as well as stochastic volatility or...

Expected returns vary when investors face time-varying investment opportunities. Longrun risk models (Bansal and Yaron 2004) and no-arbitrage affine models (Duffie, Pan, and Singleton 2000) emphasize sources of risk that are not observable to the econometrician. We show that, for both classes of...

We introduce the Homoscedastic Gamma [HG] model where the distribution of returns is characterized by its mean, variance and an independent skewness parameter under both measures. The model predicts that the spread between historical and risk-neutral volatilities is a function of the risk...

Expected returns vary when investors face time-varying investment opportunities. Longrun risk models (Bansal and Yaron 2004) and no-arbitrage affine models (Duffie, Pan, and Singleton 2000) emphasize sources of risk that are not observable to the econometrician. We show that, for both classes of...

We introduce the Homoscedastic Gamma [HG] model where the distribution of returns is characterized by its mean, variance and an independent skewness parameter under both measures. The model predicts that the spread between historical and risk-neutral volatilities is a function of the risk...

We introduce the Homoscedastic Gamma [HG] model where the distribution of returns is characterized by its mean, variance and an independent skewness parameter under both measures. The model predicts that the spread between historical and risk-neutral volatilities is a function of the risk...

Expected returns vary when investors face time-varying investment opportunities. Longrun risk models (Bansal and Yaron 2004) and no-arbitrage affine models (Duffie, Pan, and Singleton 2000) emphasize sources of risk that are not observable to the econometrician. We show that, for both classes of...

We introduce the Homoscedastic Gamma [HG] model where the distribution of returns is characterized by its mean, variance and an independent skewness parameter under both measures. The model predicts that the spread between historical and risk-neutral volatilities is a function of the risk...

Expected returns vary when investors face time-varying investment opportunities. In theory, structural long-run risk models (Bansal and Yaron, 2004) and no-arbitrage affine models (Duffie, Pan, and Singleton, 2000) emphasize sources of risk that are not observable to the econometrician. We show...

Many studies have documented that daily realized volatility estimates based on intraday returns provide volatility forecasts that are superior to forecasts constructed from daily returns only. We investigate whether these forecasting improvements translate into economic value added. To do so we...