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 show that macroeconomic growth at the end of the year (fourth-quarter or December) strongly predicts the returns of the aggregate market, small- and large-cap stocks, portfolios sorted on book-to-market and dividend yields, bond returns, and international stock returns, whereas economic...

We suggest an iterated GMM approach to estimate and test the consumption based habit persistence model of Campbell and Cochrane (1999), and we apply the approach on annual and quarterly Danish stock and bond returns. For comparative purposes we also estimate and test the standard CRRA model. In...

By using a beginning-of-period timing convention for consumption, and by including the Great Depression years in the analysis, we show that on annual data from 1926 to 2009 a standard contemporaneous consumption risk model goes a long way in explaining the size and value premiums in...

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...