A Gravity Model of Mortality Rates for Two Related Populations

Abstract

The mortality rate dynamics between two related but different-sized populations are modeled consistently using a new stochastic mortality model that we call the gravity model. The larger population is modeled independently, and the smaller population is modeled in terms of spreads (or deviations) relative to the evolution of the former, but the spreads in the period and cohort effects between the larger and smaller populations depend on gravity or spread reversion parameters for the two effects. The larger the two gravity parameters, the more strongly the smaller population’s mortality rates move in line with those of the larger population in the long run. This is important where it is believed that the mortality rates between related populations should not diverge over time on grounds of biological reasonableness. The model is illustrated using an extension of the Age-Period-Cohort model and mortality rate data for English and Welsh males representing a large population and the Continuous Mortality Investigation assured male lives representing a smaller related population.     

The Impact of Systematic Trend and Uncertainty on Mortality and Disability in a Multistate Latent Factor Model for Transition Rates

Multiple state functional disability models do not generally include systematic trend and uncertainty. We develop and estimate a multistate latent factor intensity model with transition and recovery rates depending on a stochastic frailty factor to capture trend and uncertainty. We estimate the model parameters using U.S. Health and Retirement Study data between 1998 and 2012 with Monte Carlo maximum likelihood estimation method. The model shows significant reductions in disability and mortality rates during this period and allows us to quantify uncertainty in transition rates arising from the stochastic frailty factor. Recovery rates are very sensitive to the stochastic frailty. There is an increase in expected future lifetimes as well as an increase in future healthy life expectancy. The proportion of lifetime spent in disability on average remains stable with no strong support in the data for either morbidity compression or expansion. The model has widespread application in costing of government-funded aged care and pricing and risk management of long-term-care insurance products.     

两因子随机死亡率状态空间模型及长寿风险测度

引入状态空间模型对传统两因子CBD模型拟合阶段和预测阶段进行联合建模,并基于卡尔曼滤波方法对模型参数进行估计。进一步考虑到死亡率数据的小样本特征,结合Bootstrap仿真技术和生存年金组合折现模型对长寿风险进行测度。利用1996~2011年数据展开实证研究,结果表明:结合模型解释能力、参数估计结果和误差项正态分布检验结果,两因子状态空间模型要优于传统CBD模型;年金组合规模的扩大可以消除微观长寿风险,但不能消除宏观长寿风险和参数风险;宏观长寿风险占据着不可分散风险的主导地位。     

A Two-Factor Model for Stochastic Mortality with Parameter Uncertainty: Theory and Calibration

In this article, we consider the evolution of the post‐age‐60 mortality curve in the United Kingdom and its impact on the pricing of the risk associated with aggregate mortality improvements over time: so‐called longevity risk. We introduce a two‐factor stochastic model for the development of this curve through time. The first factor affects mortality‐rate dynamics at all ages in the same way, whereas the second factor affects mortality‐rate dynamics at higher ages much more than at lower ages. The article then examines the pricing of longevity bonds with different terms to maturity referenced to different cohorts. We find that longevity risk over relatively short time horizons is very low, but at horizons in excess of ten years it begins to pick up very rapidly. A key component of the article is the proposal and development of a method for calculating the market risk‐adjusted price of a longevity bond. The proposed adjustment includes not just an allowance for the underlying stochastic mortality, but also makes an allowance for parameter risk. We utilize the pricing information contained in the November 2004 European Investment Bank longevity bond to make inferences about the likely market prices of the risks in the model. Based on these, we investigate how future issues might be priced to ensure an absence of arbitrage between bonds with different characteristics.     

网络环境对传统会计模式影响的探讨

新技术的迅速发展使网络经济应运而生,网络环境具有知识化、虚拟化两大特性.本文从对会计人员职业判断的要求、会计职能向决策型转变、对会计核算的影响以及会计报表创新等四方面全面论述网络环境对传统会计模式产生的影响.     

融资模式对商业银行风险的影响:一个文献综述

次贷危机前,随着金融脱媒的快速发展,西方国家商业银行的融资模式已经发生变化,零售存款的比重逐渐下降,非存款融资占比不断提高,商业银行越来越倾向于以货币市场和资本市场金融创新为支撑的短期批发融资。本文对商业银行融资模式及其对银行风险影响的文献进行梳理,厘清商业银行融资模式的内涵和分类,分析融资模式对银行风险影响的机理,综述现有实证研究的不同研究方法和结论,以期对我国商业银行融资模式变化及对银行风险的影响提供参考。     

Statistical Inference for Lee-Carter Mortality Model and Corresponding Forecasts

Although the Lee-Carter model has become a benchmark in modeling mortality rates, forecasting mortality risk, and hedging longevity risk, some serious issues exist on its inference and interpretation in the actuarial science literature. After pointing out these pitfalls, this article proposes a modified Lee-Carter model, provides a rigorous statistical inference, and derives the asymptotic distributions of the proposed estimators and unit root test when the mortality index is nearly integrated and errors in the model satisfy some mixing conditions. After a unit root hypothesis is not rejected, future mortality forecasts can be obtained via the proposed inference. An application of the proposed unit root test to U.S. mortality rates rejects the unit root hypothesis for the female and combined mortality rates but does not reject the unit root hypothesis for the male mortality rates.     

网络虚拟货币对货币供求的影响及效应分析

虚拟货币不是真正的货币。只要真实货币与虚拟货币处于两个不同的市场,虚拟货币就不可能引发现实的通货膨胀,虚拟货币的发行也不会对货币发行产生严重冲击。但是,目前虚拟货币已经不满足于"虚拟"世界,逐渐进入现实流通领域。我们应当正视虚拟货币对货币供求的负面影响。中央银行需要构建专门应用于网络虚拟货币的新型交易平台,建立网络消费者虚拟资金存款账户,保证中央银行调控网络虚拟货币的力度和弹性。     

A General Procedure for Constructing Mortality Models

Recently a large number of new mortality models have been proposed to analyze historic mortality rates and project them into the future. Many of these suffer from being over-parametrized or have terms added in an ad hoc manner that cannot be justified in terms of demographic significance. In addition, poor specification of a model can lead to period effects in the data being wrongly attributed to cohort effects, which results in the model making implausible projections. We present a general procedure for constructing mortality models using a combination of a toolkit of functions and expert judgment. By following the general procedure, it is possible to identify sequentially every significant demographic feature in the data and give it a parametric structural form. We demonstrate using U.K. mortality data that the general procedure produces a relatively parsimonious model that nevertheless has a good fit to the data.     

A Re-Examination of the Joint Mortality Functions

Abstract

Mortality analysis involving multiple lives is easily one of the more complicated aspects in the theory of life contingencies. In this paper, we re-investigate joint mortality functions and in particular, we examine an assertion that relates the joint-life and last-survivor random variables. This common assertion states that the sum of the lifetimes of the joint-life and the last-survivor statuses is equal to the sum of the lifetimes of the single statuses. However, we show that this assertion is not precisely correct. We therefore offer a modification to the statuses definitions so that this common assertion holds.     

极端死亡率债券的运行机制与定价模型

极端死亡率债券是票息或面值与极端死亡概率相关的债券,能够将寿险公司所面临的极端死亡率风险转移到资本市场。本文阐述了极端死亡率债券的市场发展,包括发行规模、触发机制、债券期限、债券分层、债券评级等,分析了以 Tartan 债券为代表的本金赔付累积型极端死亡率债券的运行机制,并给出了考虑极端死亡率风险的跳跃性特征下的本金赔付累积型极端死亡率债券 Wang 转换定价的解析式。     

基于自由现金流管理视角的创值动因解析模型研究

以创值为目标、(自由)现金流为对象的现金流创值财务学要解决的主要问题是企业如何从(自由)现金流的角度进行财务管理从而实现价值最大化的目标。本文借鉴拉巴波特模型和杜邦分析系统的思想构建自由现金流管理视角的创值动因解析模型,为企业精细化地进行现金流管理提供一个有价值的分析工具。依据创值动因解析模型的分析结果,企业可以有针对性的采取相应的财务管理措施,实现价值创造。     

Asymmetric Impact of Oil Price Shock on Stock Market in China: A Combination Analysis Based on SVAR Model and NARDL Model

This article integrates the SVAR model and nonlinear ARDL (NARDL) model to analyze the long-run and short-run asymmetric effect of structural oil price shocks on the Chinese stock market. We reveal that the demand-side shocks of oil price have a significant impact on the Chinese stock market in both short and long run, but the supply shock is an exception. In terms of asymmetric nature, there is no evidence of asymmetric impact when it refers to the supply shock and the oil-specific demand shock on stock market, and only the aggregate demand shock has asymmetric effect in short run.     

Analyzing determinants of bond yield spreads with Bayesian Model Averaging

This paper analyzes determinants of country default risk in emerging markets, reflected by sovereign yield spreads. The results reported so far in the literature are heterogeneous with respect to significant explanatory variables. This could indicate a high degree of uncertainty about the “true” regression model. We use Bayesian Model Averaging as the model selection method in order to find the variables which are most likely to determine credit risk. We document that total debt, history of recent default, currency depreciation, and growth rate of foreign currency reserves as well as market sentiments are the key drivers of yield spreads.     

A Neural Network Approach for Analyzing Small Business Lending Decisions

In this paper, we apply the neural network method to small business lending decisions. We use the neural network to classify the loan applications into the groups of acceptance or rejection, and compare the model results with the actual decisions made by loan officers. Data were collected from a leading bank in Central New York. The sample contains important financial statement and business information of borrowers and the loan officers' decisions. We conduct the network training on the data sample and find that the neural network has a stronger discriminating power for classifying the acceptance and rejection groups than traditional parametric and nonparametric classifiers. The results show that the neural network model has a high predictive ability. Our findings suggest that neural networks can be a very useful tool for enhancing small-business lending decisions and reducing loan processing time and costs.     

The Processing of Non-Anticipated Information in Financial Markets: Analyzing the Impact of Surprises in the Employment Report

This paper delineates the simultaneous impact of non-anticipated information on mean and variance of the intraday return process by including appropriate variables accounting for the news flow into both the mean and the variance function. This allows us to differentiate between the consistent price reaction to surprising news and the traders' uncertainty about the precise price impact of this information. Focussing on the US employment report, we find that headline information is almost instantaneously incorporated into T-bond futures prices. Nevertheless, large surprises, and `bad' news in particular, create considerable uncertainty. In contrast, if surprises in related headlines cross-validate each other, less room for differences of opinion is left and hence volatility is decreased.     

实质性披露还是选择性披露:企业环境表现对环境信息披露质量的影响

环境信息披露是企业向政府、社会公众传递企业履行环境保护责任情况的重要方式。企业公开的环境信息是对企业环境表现的实质性披露还是选择性披露,决定了企业环境信息披露的质量。本文以2012-2016年沪深两市A股重污染行业上市公司为样本,从披露载体和披露方式两个维度衡量环境信息披露质量,探究企业环境表现对环境信息披露质量的影响。实证结果表明:企业环境表现与环境信息定性披露呈负相关,与单独披露程度和定量披露呈正相关;外部环境管制压力相较于内在企业声誉动力对企业环境表现与环境信息披露质量之间的关系具有更显著的促进作用;环境管制的促进作用对国有企业更显著,而提高企业声誉的激励作用对非国有企业更显著。本文进一步研究还发现:高质量的实质性环境信息披露能够降低企业风险,促进企业可持续发展。     

中国商业银行经营效率分析——三阶段DEA之应用

本文首次运用Fried et al.(2002)所提出的三阶段DEA分析法对2001~2006年中国商业银行效率体系进行实证研究,调整环境变量与随机干扰等因素的影响,以期能对中国商业银行的经营效率进行更准确的评估。在此基础上,分析了其整体经营效率的动态变化并比较分析了商业银行在调整服务品质量变量与去除统计影响前后运行效率之间的差异。分析发现我国商业银行整体入世以来,不论是在规模扩张上,还是在理财产品创新与服务方面等经营效率上都取得了明显的进步。