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...

Vector-autoregressive models are used to decompose housing returns in 18 OECD countries into cash ?ow (rent) news and discount rate (return) news. Only for two countries - Germany and Ireland - do changing expectations of future rents play a dominating role in explaining housing return...

We investigate the predictive power of the rent-to-price ratio for future real estate returns and rent growth in 18 OECD countries over the period 1970 to 2011. First, we document that in most countries returns are signi?cantly predictable by the rent-price ratio. An increase (decrease) in the...

We extend the VAR based intertemporal asset allocation approach from Campbell et al. (2003) to the case where the VAR parameter estimates are adjusted for small-sample bias. We apply the analytical bias formula from Pope (1990) using both Campbell et al.'s dataset, and an extended dataset with...

Based on Chen and Zhao's (2009) criticism of VAR based return decompositions, we explain in detail the various limitations and pitfalls involved in such decompositions. First, we show that Chen and Zhao's interpretation of their excess bond return decomposition is wrong: the residual component...

We analyze and compare the properties of various methods for bias-correcting parameter estimates in vector autoregressions. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study, we show that this simple...

This paper presents a new framework for coping with problems often encountered when modeling seasonal high frequency data containing both flow and stock variables. The idea is to apply a multivariate weekly representation of a daily periodic model and to exploit the possible cointegration and...

Relations between economic variables can often not be exploited for forecasting, suggesting that predictors are weak in the sense that estimation uncertainty is larger than bias from ignoring the relation. In this paper, we propose a novel bagging predictor designed for such weak predictor...

This paper considers asymptotic inference in the multivariate BEKK model based on (co-)variance targeting (VT). By defi?nition the VT estimator is a two-step estimator and the theory presented is based on expansions of the modifi?ed likelihood function, or estimating function, corresponding to...