Using a modified DCC-MIDAS specification that allows the long-term correlation component to be a function of multiple … explanatory variables, we show that the stock-bond correlation in the US, the UK, Germany, France, and Italy is mainly driven by … portfolios in terms of portfolio risk. While optimal daily weights minimize portfolio risk, we find that portfolio turnover and …

the presence of microstructure noises and asynchronous trading, the covariance estimator is guaranteed to be positive …This paper proposes a novel covariance estimator via a machine learning approach when both the sampling frequency and … covariance dimension are large. Assuming that a large covariance matrix can be decomposed into low rank and sparse components …

The stock-bond correlation is a cornerstone of every asset allocation decision, but estimating it reliably can prove to … supervised machine learning techniques, this article presents a new approach for identifying key determinants of the correlation … growth, and inflation uncertainty, predict changes in correlation dynamics overtime. Relative to the existing literature, the …