This paper presents a novel theoretical framework to model the evolution of a dynamic portfolio (i.e., a portfolio whose weights vary over time), considering a given investment policy. The framework is based on graph theory and the quantum probability. Embedding the dynamics of a portfolio into...

The aim of this work is to investigate whether the combination of forecasts plays an important role in the improvement of forecast accuracy Particular attention is paid to: (a) the methods of forecasting (the methods compared are neural networks, fuzzy logic, GARCH models, switching regime and...

Identification of financial bubbles and crisis is a topic of major concern since it is important to prevent collapses that can severely impact nations and economies. Our analysis deals with the use of the recently proposed ‘delay vector variance’ (DVV) method, which examines local...

A novel procedure to test for linearity and unit root in a nonlinear framework is proposed by introducing a new model–the MT-STAR model–which has similar properties of the ESTAR model but reduces the effects of the identification problem and can also account for asymmetry in the adjustment...

We propose a generalization of the Dynamic Conditional Correlation multivariate GARCH model of Engle [R.F. Engle, Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroskedasticity models, Journal of Business and Economic Statistics 20...

We propose a transparent way of establishing a turning point chronology for the euro area business cycle. Our analysis is achieved by exploiting the concept of recurrence plots, in particular distance plots, to characterise and detect turning points of the business cycle. Firstly, we apply the...

We propose several econometric measures of systemic risk to capture the interconnectedness among the monthly returns of hedge funds, banks, brokers, and insurance companies based on principal components analysis and Granger-causality tests. We find that all four sectors have become highly...

We propose a new approach for detecting turning points and forecasting the level of economic activity in the business cycle. We make use of coincident indicators and of nonlinear and non-Gaussian latent variable models. We thus combine the ability of nonlinear models to capture the asymmetric...

This paper aims at the production of a chronology for the EU15 business cycle by comparing parametric and non-parametric procedures on monthly and quarterly data as well in a combined approach. The main innovation is the joint use of the monthly series for the EU15 Gross Domestic Product (GDP)...