Optimal asset allocation for participating contracts with mortality risk under minimum guarantee

Abstract

We investigate an optimal investment problem of participating insurance contracts with mortality risk under minimum guarantee. The insurer aims to maximize the expected utility of the terminal payoff. Due to its piecewise payoff structure, this optimization problem is a non-concave utility maximization problem. We adopt a concavification technique and a Lagrange dual method to solve the problem and derive the representations of the optimal wealth process and trading strategies. We also carry out some numerical analysis to show how the portfolio insurance constraint impacts the optimal terminal wealth.     

客观化创造力测量工具:《中文远距联想测验》编制

依循Mednick远距联想测验(RAT)思路和我国台湾学者任纯慧等编制的中文远距联想测验(CRAT)的观点,并依据北京语言大学《汉语常用词词频表》,编制了符合中国大陆学生语言习惯的《中文远距联想测验》。通过预测验,对题库题目进行难度、区分度分析,选出优质题项与吴静吉等人(1999)编制的《新编创造思考测验》一起对筛选样本进行施测。施测结果表明,《中文远距联想测验》的内部一致性信度较高,Cronbach’α系数为0.734;其效标效度也较好,与《新编创造思考测验》的流畅性、变通性和独创性分数相关非常显著。该测验已被应用于大学自主招生考试,效果良好。     

新时代青年劳动教育的逻辑、特征与发展进路

新时代青年劳动教育是有着鲜明的内在逻辑的,它体现在以世界各国青年劳动教育经验为历史之镜,以马克思主义劳动观为理论指导,以几千年来形成的我国优秀劳动文化为深厚底蕴,以新时代青年劳动教育的现实问题和历史重任为实践源头.新时代青年劳动教育是把劳动价值观教育作为核心内容,其价值旨归是促进人的全面发展,而全社会的协同共育是坚实的机制保障.在开展新时代青年劳动教育的过程中,应当进一步推动劳动教育的本土化发展、专业化发展以及制度化发展,充分发挥劳动教育在立德树人方面的重要作用.     

Test of parameter changes in a class of observation-driven models for count time series

Abstract

This paper investigates the parameter-change tests for a class of observation-driven models for count time series. We propose two cumulative sum (CUSUM) test procedures for detection of changes in model parameters. Under regularity conditions, the asymptotic null distributions of the test statistics are established. In addition, the integer-valued generalized autoregressive conditional heteroskedastic (INGARCH) processes with conditional negative binomial distributions are investigated. The developed techniques are examined through simulation studies and also are illustrated using an empirical example.     

德国选择党——疑欧势力的崛起与前景

德国选择党这支疑欧势力在现有的政党谱系中无法对号入座,却在德国政坛迅速崛起。本文分析该党目前的发展现状,从政党纲领、组织结构和政治动员等多方面探讨其成功原因,进而从政党生命周期理论出发,揭示这一新兴政党所处发展阶段及其对现有政党体制、尤其是右翼阵营的冲击,并研判该党的发展前景与制约因素。     

On the Status and Function of Judicial Justice in Social Governance Innovation

Social governance innovation is a basic requirement of China's socialist construction, and an important guarantee that people can live and work in peace and enjoy long-term stability and order. Strengthening and innovating social governance has great significance for the modernization of the national governance system and governance capacity, and this is where judicial justice plays a unique role at the level of government, society, and the individual. That is, judicial justice is the key to transforming governmental functions; the guarantee of a new-type social construction; and the guide to upgrading autonomy at the grass-roots level. To achieve judicial justice, we must popularize the idea of the rule of law, improve judicial work style and innovate judicial institutions.     

HDDA: DataSifter: statistical obfuscation of electronic health records and other sensitive datasets

There are no practical and effective mechanisms to share high-dimensional data including sensitive information in various fields like health financial intelligence or socioeconomics without compromising either the utility of the data or exposing private personal or secure organizational information. Excessive scrambling or encoding of the information makes it less useful for modelling or analytical processing. Insufficient preprocessing may compromise sensitive information and introduce a substantial risk for re-identification of individuals by various stratification techniques. To address this problem, we developed a novel statistical obfuscation method (DataSifter) for on-the-fly de-identification of structured and unstructured sensitive high-dimensional data such as clinical data from electronic health records (EHR). DataSifter provides complete administrative control over the balance between risk of data re-identification and preservation of the data information. Simulation results suggest that DataSifter can provide privacy protection while maintaining data utility for different types of outcomes of interest. The application of DataSifter on a large autism dataset provides a realistic demonstration of its promise practical applications.