One of the most important aspects in asset allocation problems is the assumption concerning the probability distribution of asset returns. Financial managers generally suppose normal distribution, even if extreme realizations usually have an higher frequency than in the Gaussian case. The aim of...

We apply sequential Monte Carlo (SMC) to the detection of turning points in the business cycle and to the evaluation of useful statistics employed in business cycle analysis. The proposed nonlinear filtering method is very useful for sequentially estimating the latent variables and the...

This work deals with multivariate stochastic volatility models, which account for a time-varying variance-covariance structure of the observable variables. We focus on a special class of models recently proposed in the literature and assume that the covariance matrix is a latent variable which...

The aim of this paper is to compare three regularized particle filters in an online data processing context. We carry out the comparison in terms of hidden states filtering and parameters estmation, considering a Bayesian paradigm and a univariate stochastic volatility model. We discuss the use...

Have Italian mutual funds been able to generate "extra-return"? Were some of them able to persistently beat the competitors? In this paper we address thee question and provide a detailed and systematic performance and return persistence analysis of the Italian equity mutual funds. We show that,...

We propose a new class of Markov-switching (MS) models for business cycle analysis. As usually done in the literature, we assume that the MS latent factor is driving the dynamics of the business cycle but the transition probabilities can vary randomly over time. Transition probabilities are...

The recent observed decline of business cycle variability suggests that broad macroeconomic risk may have fallen as well. This may in turn have some impact on equity risk premia. We investigate the latent structures in the volatilities of the business cycle and stock market valuations by...

We investigate the latent volatility structures of the fluctuations in the US business cycle and stock market valuations. The technical novelty of this work lies in the estimation of a Markov-switching stochastic-volatility model that allows for Bayesian sequential evaluation on both the...