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...

This paper adopts quantile regressions to scrutinize the realized stock-bond correlation based upon high frequency returns. The paper provides in-sample and out-of-sample analysis and considers a large number of macro-?nance predictors well-know from the return predictability literature. Strong...

This paper adopts dynamic factor models with macro-fi?nance predictors to revisit the intertemporal risk-return relation in ?five large European stock markets. We identify country specifi?c, Euro area, and global factors to determine the conditional moments of returns considering the role of...

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...

This paper re-examines the joint distribution of equity and bond returns using high frequency data. In particular, we analyze the weekly realized stock bond correlation calculated from 5-minute returns of the futures prices of the S&P 500 and the 10-year Treasury Note. A potentially gradual...

In this paper, we scrutinize the cross-sectional relation between idiosyncratic volatility and stock returns. As a novelty, the idiosyncratic volatility is obtained by conditioning upon macro-finance factors as well as upon traditional asset pricing factors. The macro-finance factors are...