One of the major points of contention in studying and modelling financial returns is whether or not the variance of the returns is finite or infinite (sometimes referred to as the Bachelier-Samuelson Gaussian world versus the Mandelbrot stable world). A different formulation of the question asks...

In this paper, we consider multivariate models for returns on Russian equities based on normal distribution, t-distribution with scalar degrees of freedom parameter and t-distribution with vector degrees of freedom parameter. Our models capture autocorrelation, volatility clustering, dynamic...

A maximum likelihood method for estimating the power-law exponent verifies that the positive and negative tails of the Colombian stock market index (IGBC) and the Colombian peso exchange rate (TRM) approximate a scale-free distribution, whereas none of the heavy tails of a local sovereign...

A maximum likelihood method for estimating the power-law exponent verifies that the positive and negative tails of the Colombian stock market index (IGBC) and the Colombian peso exchange rate (TRM) approximate a scale-free distribution, whereas none of the heavy tails of a local sovereign...

We empirically investigate the possibilities for enhancing value-at-risk predictions by explicit modelling conditional higher order moment dynamics of financial returns. Using one-day-ahead VaR forecasts for 5 highly liquid constituents of the S&P500 index from different industrial sectors, we...

We survey the main applications of algorithmic (Kolmogorov) complexity to the problem of price dynamics in financial markets. We stress the differences between these works and put forward a general algorithmic framework in order to highlight its potential for financial data analysis. This...

We propose to model multivariate volatility processes on the basis of the newly defined conditionally uncorrelated components (CUCs). This model represents a parsimonious representation for matrix-valued processes. It is flexible in the sense that each CUC may be fitted separately with any...

We survey the main applications of algorithmic (Kolmogorov) complexity to the problem of price dynamics in financial markets. We stress the differences between these works and put forward a general algorithmic framework in order to highlight its potential for financial data analysis. This...

Financial returns often present moderate skewness and high kurtosis. As a consequence, it is natural to look for a model that is exible enough to capture these characteristics. The proposal is to undertake inference for a generalized autoregressive conditional heteroskedastic (GARCH) model,...

We derive simple algebraic expressions for score tests of serial correlation in the levels and squares of common and idiosyncratic factors in static factor models with (semi) parametrically specified elliptical distributions even though one must generally compute the likelihood by simulation. We...