Long memory in volatility is a stylized fact found in most financial return series. This paper empirically investigates the extent to which interdependence in emerging markets may be driven by conditional short and long range dependence in volatility. We fit copulas to pairs of raw and filtered...

In this paper we study the accumulated claim in some fixed time period, skipping the classical assumption of mutual independence between the variables involved. Two basic models are considered: Model 1 assumes that any pair of claims are equally correlated which means that the corresponding...

The main goal of this article is to generalize the bivariate lack-of-memory property introduced in Marshall & Olkin (1967). Several characterizations of bivariate continuous distributions possessing such a property are established and illustrated by examples.

In this paper, a simple relation between the Leimkuhler curve and the mean residual life is established. The result is illustrated with several models commonly used in informetrics, such as exponential, Pareto and lognormal. Finally, relationships with some other reliability concepts are also...

Volatility plays an important role when managing risks, composing portfolios, and pricing financial instruments. However it is not directly observable, being usually estimated through parametric models such as those in the GARCH family. A more natural empirical measure of daily returns...

Purpose – Proposes a new covariance matrix robust estimator able to capture the correct orientation of the data and the large unconditional variance caused by occasional high volatility periods. Design/methodology/approach – Derives easy-to-compute estimates for the center and covariance...

This paper analyzes the forecast performance of emerging market stock returns using standard autoregressive moving average (ARMA) and more elaborated autoregressive conditional heteroskedasticity (ARCH) models. Our results indicate that the ARMA and ARCH specifications generally outperform...

This paper extends the evolution equation of Patton (2006) for the time variation of the copula parameters by specifying an autoregressive fractionally integrated term. For any copula parameter there is a suitable one-to-one transformation so that the maximum likelihood estimation method may be...