This study considers the forecasting of mortality rates in multiple populations. We propose a model that combines … mortality forecasting and functional data analysis (FDA). Under the FDA framework, the mortality curve of each year is assumed … to be a smooth function of age. As with most of the functional time series forecasting models, we rely on functional …

shows better forecasting accuracy than the Lee-Carter and Bayesian vector autoregressive (BVAR) models without regime …-switching and while retaining the advantages of BVAR. MSBVAR provides more reliable estimates for parameter uncertainty and more …We apply a Markov-switching Bayesian vector autoregression (MSBVAR) model to mortality forecasting. MSBVAR has not …

We introduce a multistep-ahead forecasting methodology that combines empirical mode decomposition (EMD) and support … vector regression (SVR). This methodology is based on the idea that the forecasting task is simplified by using as input for …

This paper investigates the risk exposure for options and proposes MaxVaR as an alternative risk measure which captures … the risk better than Value-at-Risk especially. While VaR is a measure of end-of-horizon risk, MaxVaR captures the interim … risk exposure of a position or a portfolio. MaxVaR is a more stringent risk measure as it assesses the risk during the risk …

While a lot of research concentrates on the respective merits of VaR and TCE, which are the two most classic risk …. In this paper, we introduce a new risk indicator that extends TCE to take into account higher-order risks. We compare the …

One of the key components of financial risk management is risk measurement. This typically requires modeling …, estimating and forecasting tail-related quantities of the asset returns’ conditional distribution. Recent advances in the …

trend risk and population basis risk. In particular, the cross- and auto-correlations between the innovations of the latent … uncorrelated. This permits us to disentangle trend risk and population basis risk, thereby sparing us from the need to use a …

This paper proposes a new framework to reduce the variance and uncertainty in the risk assessment process. Today, this … and a simulation of the risk assessment process, and the improvement in reducing the variance is significant. …