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...

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 factors constructed from a large number of macro-finance predictors well-known from the return...

This paper explores the time variation in the stock–bond correlation using high-frequency data. Gradual transitions between regimes of negative and positive stock–bond correlation are well accommodated by the smooth transition regression (STR) model. We find that the regimes are...

This paper develops an open-economy intertemporal growth model with We provide evidence on the sources of co-movement in monthly US and UK stock returns by investigating the role of macroeconomic and financial variables in a model with time-varying correlations. Cross-country communality in...

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We use historical data that cover more than one century on real GDP for industrial countries and employ the Pesaran panel unit root test that allows for cross-sectional dependence to test for a unit root on real GDP. At first, we find strong evidence against the unit root null. Our results seem...

We use historical data that cover more than one century on real GDP for industrial countries and employ the Pesaran panel unit root test that allows for cross-sectional dependence to test for a unit root on real GDP. At first, we find strong evidence against the unit root null. Our results seem...

This article proposes time-varying nonparametric and semiparametric estimators of the conditional cross-correlation matrix in the context of portfolio allocation. Simulations results show that the nonparametric and semiparametric models are best in DGPs with substantial variability or structural...