Multi-population mortality forecasting using tensor decomposition

ABSTRACT

In this paper, we formulate the multi-population mortality forecasting problem based on 3-way (age, year, and country/gender) decompositions. By applying the canonical polyadic decomposition (CPD) and the different forms of the Tucker decomposition to multi-population mortality data (10 European countries and 2 genders), we find that the out-of-sample forecasting performance is significantly improved both for individual populations and the aggregate population compared with using the single-population mortality model based on rank-1 singular value decomposition (SVD), or the Lee–Carter model. The results also shed lights on the similarity and difference of mortality among different countries. Additionally, we compare the variance-explained method and the out-of-sample validation method for rank (hyper-parameter) selection. Results show that the out-of-sample validation method is preferred for forecasting purposes.     

农村信用社可控信贷风险管理研究——以AHP法为基础

近年来,我国商业银行发展突飞猛进,成为金融活动的中坚力量,商业银行的信贷业务更是其生存发展的根本,信贷风险的存在具有客观性,但又具有可控性,因此,合理控制商业银行信贷风险,关系我国整个金融行业的稳定发展,更与我国国民经济息息相关,对我国社会主义市场经济的进一步发展完善同样起到至关重要的作用.本文从可控风险视角进行分析,...     

Utility maximization in a stochastic affine interest rate and CIR risk premium framework: a BSDE approach

Decisions in Economics and Finance - This paper investigates optimal investment problems in the presence of stochastic interest rates and stochastic volatility under the expected utility...