In this paper we analyse the properties of hierarchical Archimedean copulas. This classis a generalisation of the Archimedean copulas and allows for general non-exchangeable dependencystructures. We show that the structure of the copula can be uniquely recovered from all bivariate margins.We...

Using data for six OECD countries, this paper studies the effect of macroeconomic conditions on the mortality index kt in the well-known Lee-Carter model. Significant correlations are found with real GDP growth rates in Australia, Canada, and the United States, and with unemployment rate changes...

Systemic weather risk is a major obstacle for the formation of private (non-subsidized) crop insurance. This paper explores the possibility of spatial diversication ofinsurance by estimating the joint occurrence of unfavorable weather conditions in dierentlocations. For that purpose copula...

Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the recurrent SVR is compared with three competing methods,...

In this paper we provide a review of copula theory with applications to finance. We illustrate the idea on the bivariate framework and discuss the simple, elliptical and Archimedean classes of copulae. Since the copulae model the dependency structure between random variables, next we explain the...

This article provides a comprehensive econometric analysis of factors driving aggregate mortality rates over time. It differs from previous studies in this field by simultaneously considering an extensive set of macroeconomic, socio-economic and ecological factors as explanatory variables....

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...

A huge body of empirical and theoretical literature has emerged on the relationship between foreign exchange (FX) uncertainty and international trade. Empirical findings about the impact of FX uncertainty on trade figures are at best weak and often ambiguous with respect to its direction. Almost...

In the ideal Black-Scholes world, financial time series are assumed 1) stationary (time homogeneous) and 2) having conditionally normal distribution given the past. These two assumptions have been widely-used in many methods such as the RiskMetrics, one risk management method considered as...