The microstructural approach to the exchange rate market claims that order flows on a currency can accurately reflect the short-run dynamics its exchange rate. In this paper, instead of focusing on order flows analysis we employ an alternative microstructural approach: we focus on investors'...

The magnitude of the recent financial crisis, which started from the U.S. and expanded in Europe, change the perspective on banking supervision. The recent consensus is that to preserve a healthy and stable banking network, the monitoring of all financial institutions should be under a single...

The 2006 sudden and immense downturn in U.S. House Prices sparked the 2007 global financial crisis and revived the interest about forecasting such imminent threats for economic stability. In this paper we propose a novel hybrid forecasting methodology that combines the Ensemble Empirical Mode...

This paper introduces several new Bayesian nonparametric models suitable for capturing the unknown conditional distribution of realized covariance (RCOV) matrices. Existing dynamic Wishart models are extended to countably infinite mixture models of Wishart and inverse-Wishart distributions. In...

In this paper, we investigate the forecasting ability of the yield curve in terms of the U.S. real GDP cycle. More specifically, within a Machine Learning (ML) framework, we use data from a variety of short (treasury bills) and long term interest rates (bonds) for the period from 1976:Q3 to...

The relationship between risk and return is one of the most studied topics in finance. The majority of the literature is based on a linear, parametric relationship between expected returns and conditional volatility. This paper models the contemporaneous relationship between market excess...

We investigate the R&D portfolio of a monopolist investing in cost-reducing and quality enhancing R&D. Incentives along the two directions are inversely related to the size of market demand, and independent of each other. The stability analysis shows the existence of a unique stable steady state...

This paper discusses estimation of US inflation volatility using time varying parameter models, in particular whether it should be modelled as a stationary or random walk stochastic process. Specifying inflation volatility as an unbounded process, as implied by the random walk, conflicts with...

The time-varying parameter vector autoregressive (TVP-VAR) model has been used to successfully model interest rates and other variables. As many short interest rates are now near their zero lower bound (ZLB), a feature not included in the standard TVP-VAR specification, this model is no longer...

This article develops a new econometric methodology for performing stochastic model specification search (SMSS) in the vast model space of time-varying parameter VARs with stochastic volatility and correlated state transitions. This is motivated by the concern of over-fitting and the typically...