A well known macroeconometric model of the Italian economy is updated to produce forecasts at 1974.

In econometric models specified as systems of simultaneous equations, forecast errors can be regarded as random variables whose variances can be investigated, analyzed and estimated. This book summarizes results available in the literature for linear and nonlinear econometric models, when...

Problems related to deterministic solution of nonlinear econometric models are well known in the literature. The use of mean (average) stochastic simulation results has been usually proposed to solve the problem of bias. This raises however other types of problems, like possible non-coherent...

Country risk and sovereign risk are two of the most important topics in risk management. The first part of this work introduces these concepts and shows the differences between them. The following chapters fit linear and ordinal regression models to a data-set with more than 100 countries, where...

Nonlinear time series models can exhibit components such as long range trends and seasonalities that may be modeled in a flexible fashion. The resulting unconstrained maximum likelihood estimator can be too heavily parameterized and suboptimal for forecasting purposes. The paper proposes the use...

In this paper we address the issue of forecasting Value–at–Risk (VaR) using different volatility measures: realized volatility, bipower realized volatility, two scales realized volatility, realized kernel as well as the daily range. We propose a dynamic model with a flexible trend...

La psicologia mostra che la probabilità soggettiva associata ad eventi economici futuri viene distorta in modo sistematico, rispetto a quella oggettiva, da elementi psicologici diffusi e persistenti. Lo stesso vale per l'interpretazione retrospettiva dei fatti economici. In particolare, si...

The frequency of crashes and the magnitude of crises in international financial markets are growing more severe over time. Recent financial crises are not singular events portrayed in recent accounts, rather, they erupt in circumstances that are very similar to the economic and financial...

Many ways exist to measure and model financial asset volatility. In principle, as the frequency of the data increases, the quality of forecasts should improve. Yet, there is no consensus about a "true" or "best" measure of volatility. In this paper we propose to jointly consider absolute daily...

We analyze several measures of volatility (realized variance, bipower variation and squared daily returns) as estimators of integrated variance of a continuous time stochastic process for an asset price. We use a Multiplicative Error Model to describe the evolution of each measure as the product...