In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data, taking the logarithm of the squared returns to obtain a linear state space model. A well-known series representation links the correlations between elements of the observation...

In the analysis of multivariate stochastic volatility models, many estimation procedures begin by transforming the data, taking the logarithm of the squared returns to obtain a linear state space model. A well-known series representation links the correlations between elements of the observation...

Theoretical part of this article examines the impact of information on the stochastic model of generating returns of assets (vector autoregressive model) on the optimal structure of assets allocation of the investment portfolio. Article includes theoretical basis for construction and...

Se presenta un modelo de dos factores para estimar el riesgo de crédito de un portafolio de acciones. La especificación de los rendimientos incluye un factor local (IPC) y un factor global (S&P500) cuya estructura de correlaciones sigue un proceso DCC (Dynamic Conditional Correlations). Las...

Empirical techniques to assess market comovements are numerous from cointegration to dynamic conditional correlations. This paper uses the fractal properties of asset returns and presents estimations of Markov switching multifractal models [as MSM] to give new insights about short and long run...