Graphical models have shown remarkable performance in uncovering the conditional dependence structure across a set of given variables. In this paper, we introduce two new graphical modelling approaches - called Gslope and Tslope - to the portfolio selection literature for directly estimating the...

In this paper, we show that the availability of multiple price series for the same asset can be exploited to estimate its integrated variance. We use a vector error correction model for those prices and its common trend representation to estimate the efficient price of the asset. Because the...

We introduce a novel weighted least squares approach to estimate daily realized covariation and microstructure noise variance using high-frequency data. We provide an asymptotic theory and conduct a comprehensive Monte Carlo simulation to demonstrate the desirable statistical properties of the...

Graphical models have shown remarkable performance in uncovering the conditional dependence structure across a set of given variables. In this paper, we introduce two new graphical modelling approaches—called Gslope and Tslope—to the portfolio selection literature for directly estimating the...

We introduce the ambiguity towards risk, defined as the variance of signals, as a source of investors’ uncertainty to supplement risk. When public signals arrive, all traders are informed, but they react diversely. We propose a piecewise optimal demand schedule for ambiguity-averse investors,...