We propose new neighbouring prediction models for mortality forecasting. For each mortality rate at age x in year t, denoted as mx,t, we construct images of neighbourhood mortality data around mx,t, i.e., ℇmx,t (x1, x2, s), which includes mortality information for ages in [x − x1, x + x2],...

We propose a new machine learning-based framework for long-term mortality forecasting. Based on ideas of neighbouring prediction, model ensembling, and tree boosting, this framework can significantly improve the prediction accuracy of long-term mortality. In addition, the proposed framework...

One of the most important risks in the actuarial industry is the longevity risk. The accurate prediction of mortality rates plays a crucial role in the management of the aforementioned risk. Such predictions are performed by modelling the mortality rates using mortality models. Aiming at...

Multi-population mortality forecasting has become an increasingly important area in actuarial science and demography, as a means to avoid long-run divergence in mortality projection. This paper aims to establish a unified state-space Bayesian framework to model, estimate and forecast mortality...

We present the methodology for developing a predictive model for identifying homeless persons likely to have high future costs for public services. It was developed by linking administrative records from 2007 through 2012 for seven Santa Clara County agencies and identifying 38 demographic,...

In recent years, the international community has been increasing its efforts to reduce the human footprint on air pollution and global warming. Total CO2 emissions are a key component of global emissions, and as such, they are closely monitored by national and supranational entities. This study...

The paper attempts to determine regional unemployment rates for NUTS 2 regions based on data available on a regular basis from Eurostat and ILO. In the first part it is shown how the evolution of regional unemployment rates is determined by national unemployment rates by industry and the...

Penalized quantile regressions are proposed for the combination of Value-at-Risk forecasts. The primary reason for regularization of the quantile regression estimator with the elastic net, lasso and ridge penalties is multicollinearity among the standalone forecasts, which results in poor...

Based on the 2012 Version of the Romanian Macromodel, the first section of this paper discusses the evolution of the Romanian economy in 2014. The previous simulations were revised taking into account the changes in the internal and external socio-economic conjuncture or in the available...

The objective of this study is to examine the performance of default prediction model: the Z-score model using discriminant analysis, and to propose a new prediction model on a data set of 30 defaulted and 30 solvent companies. Financial ratios obtained from corporate balance sheets are used as...