In this paper we consider two cases of pairs trading strategies: a conditional statistical arbitrage method and an implicit statistical arbitrage method. We use a simulation-based Bayesian procedure for predicting stable ratios, defined in a cointegration model, of pairs of stock prices. We show...

We investigate the direct connection between the uncertainty related to estimated stable ratios of stock prices and risk and return of two pairs trading strategies: a conditional statistical arbitrage method and an implicit arbitrage one. A simulation-based Bayesian procedure is introduced for...

In several scientific fields, like bioinformatics, financial and macro-economics, important theoretical and practical issues exist that involve multimodal data distributions. We propose a Bayesian approach using mixtures distributions to approximate accurately such data distributions. Shape and...

Multimodal empirical distributions arise in many fields like Astrophysics, Bioinformatics, Climatology and Economics due to the heterogeneity of the underlying populations. Mixture processes are a popular tool for accurate approximation of such distributions and implied mode detection. Using...

In several scientific fields, such as finance, economics and bioinformatics, important theoretical and practical issues exist involving multimodal and asymmetric count data distributions due to heterogeneity of the underlying population. For accurate approximation of such distributions we...

This chapter proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH-type models. The emphasis is put on a novel efficient procedure named AdMitIS. The methodology automatically constructs a mixture of Student-t distributions as an approximation to...

This paper presents the R package bayesGARCH which provides functions for the Bayesian estimation of the parsimonious but effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids the time-consuming and difficult task of tuning a sampling...

A novel simulation-based methodology is proposed to test the validity of a set of marginal time series models, where the dependence structure between the time series is taken "directly" from the observed data. The procedure is useful when one wants to summarize the test results for several time...