We introduce tractable models for commodity derivatives pricing with inventory and volatility effects, and illustrate with applications to the oil market. We contribute to the existing literature in several respects. First, whereas the previous literature uses futures data for investigating the...

We investigate the long-run stock-bond correlation using a novel model that combines the dynamic conditional correlation model with the mixed-data sampling approach. The long-run correlation is affected by both macro-finance variables (historical and forecasts) and the lagged realized...

In this paper we show that the long-run stock and bond volatility and the long-run stock-bond correlation depend on macroeconomic uncertainty. We use the mixed data sampling (MIDAS) econometric approach. The findings are in accordance with the flight-to-quality phenomenon when macroeconomic...

We introduce the Simplified Component GARCH (SC-GARCH) option pricing model, show and discuss sufficient conditions for non-negativity of the conditional variance, apply it to low-frequency and high-frequency financial data, and consider the option valuation, comparing the model performance with...

A new semiparametric estimator for an empirical asset pricing model with general nonparametric risk-return tradeoff and a GARCH process for the underlying volatility is introduced. The estimator does not rely on any initial parametric estimator of the conditional mean function, and this feature...

In this paper a new GARCH–M type model, denoted the GARCH-AR, is proposed. In particular, it is shown that it is possible to generate a volatility-return trade-off in a regression model simply by introducing dynamics in the standardized disturbance process. Importantly, the volatility in the...