In this study we develop a multi-factor extension of the family of Lee-Carter stochastic mortality models. We build upon the time, period and cohort stochastic model structure to extend it to include exogenous observable demographic features that can be used as additional factors to improve...

The pricing of life insurance products depends critically on the ability to model and forecast three core stochastic drivers. Firstly, the ability to accurately forecast expected mortality rates by age group for a given population in order to construct estimates of the life expectancy required...

Modelling and forecasting of asset volatility and covariance is of prime importance in the construction of portfolios. In this paper, we present a generalised multi-factor model that incorporates heteroskedasticity and dependence in the idiosyncratic error terms. We apply this model to...

With the exception of naive methods for portfolio selection, such as the equal weighted approaches, all other methods of portfolio allocation are more or less sensitive to the quality of the inputs considered in constructing the models and risk measures utilised in the allocation framework. The...

This paper explores and develops alternative statistical representations and estimation approaches for dynamic mortality models. The framework we adopt is to reinterpret popular mortality models such as the Lee-Carter class of models in a general state-space modelling methodology, which allows...

The focus of this work involves a comparison of the performance of a covariance regression model (CovReg) and a vector heterogeneous autoregressive (VHAR) model for the development of a dynamic portfolio allocation framework in equity index strategies. The performance of each method is assessed...