Contrary to the common wisdom that asset prices are barely possible to forecast, we show that high and low prices of equity shares are largely predictable. We propose to model them using a simple implementation of a fractional vector autoregressive model with error correction (FVECM). This model...

Within an asset allocation framework, when the number of assets is larger than the sample dimension, mean-variance approaches cannot be used due to the limited number of degrees of freedom. In such a situation, performance measures could be used to rank assets, and then select a subset of them...

This paper proposes structured parametrizations for multivariate volatility models, which use spatial weight matrices induced by economic proximity. These structured specifications aim at solving the curse of dimensionality problem, which limits feasibility of model-estimation to small...

We extend the Dynamic Conditional Correlation multivariate GARCH specification to investigate the dynamic contemporaneous relationship between correlations and variances of the underlying assets. We present a generalization of the DCC model where the dynamic behavior depends on the assets...