Deposit Insurance and Risk Management of the U.S. Banking System: What is the Loss Distribution Faced by the FDIC?

We examine the question of deposit insurance through the lens of risk management by constructing the loss distribution faced by the Federal Deposit Insurance Corporation (FDIC). We take a novel approach by arguing that the risk management problem faced by the FDIC is similar to that of a bank managing a loan portfolio, only in the FDIC’s case the risk arises from the potential for loss of the individual banks in its portfolio. We explicitly estimate the cumulative loss distribution of FDIC insured banks using two variations of the Merton model and find that reserves are sufficient to cover roughly 99.85% of the loss distribution, corresponding to about a BBB+ rating. However, under different stress scenarios (higher correlations, fat-tailed bank returns, increased loss severity) that level can be much lower: approximately 96% corresponding to about a B+ rating.JEL classification: G210, G280.Any views expressed represent those of the author only and not necessarily those of the Federal Reserve Bank of New York or the Federal Reserve System.     

On a Class of Asymptotically Risk-Efficient Sequential Procedures

A class of sequential procedures is developed for the point estimation of the parameter(s) of a population under a family of loss functions plus cost function of the general form. Condition on the initial sample size is determined which ensures the asymptotic ‘risk-efficiency’ of the proposed class. By means of various examples, it is shown that many sequential point estimation problems can be handled with the help of the proposed class.     

Gibbs posterior inference on value-at-risk

ABSTRACT

Accurate estimation of value-at-risk (VaR) and assessment of associated uncertainty is crucial for both insurers and regulators, particularly in Europe. Existing approaches link data and VaR indirectly by first linking data to the parameter of a probability model, and then expressing VaR as a function of that parameter. This indirect approach exposes the insurer to model misspecification bias or estimation inefficiency, depending on whether the parameter is finite- or infinite-dimensional. In this paper, we link data and VaR directly via what we call a discrepancy function, and this leads naturally to a Gibbs posterior distribution for VaR that does not suffer from the aforementioned biases and inefficiencies. Asymptotic consistency and root-n concentration rate of the Gibbs posterior are established, and simulations highlight its superior finite-sample performance compared to other approaches.     

损失分布模型在操作风险中的应用分析

随着巴塞尔协议的公布,操作风险(Operational Risk)的量化模型已经成为银行业目前研究的主要课题。本文按照巴塞尔协议规定,利用损失分布方法(Loss Distribution Approach,LDA)来度量操作风险,这种方法的优点在于分别度量损失事件发生频度以及损失幅度,然后利用组合分布方法来研究一段时间内的累积损失分布。本文主要讨论在商业银行内部如何执行LDA以及引入操作风险在险值(Valueat Risk,VaR)的概念,并且介绍了能够反映损失分布的分布函数。同时按照巴塞尔协议公布的方法和策略,从损失事件类型、业务部门以及损失分布额度的估计方法探讨利用高级度量方法的可能性和现实性以及操作中的现实问题。     

基于拓扑数据模型的车险操作风险度量

以机动车辆保险为研究对象,分析车险核心业务流程中操作风险的表现形式,借助拓扑数据模型及Monte Carlo模拟对其风险进行度量.结果显示:损失强度表现出较强的厚尾性,事件频率具有高频性,但总损失额分布的厚尾特征不明显,这些结果为操作风险进行经济资本配置及管理提供了依据.     

Extremes on the discounted aggregate claims in a time dependent risk model

This paper presents an extension of the classical compound Poisson risk model for which the inter-claim time and the forthcoming claim amount are no longer independent random variables (rv's). Asymptotic tail probabilities for the discounted aggregate claims are presented when the force of interest is constant and the claim amounts are heavy tail distributed rv's. Furthermore, we derive asymptotic finite time ruin probabilities, as well as asymptotic approximations for some common risk measures associated with the discounted aggregate claims. A simulation study is performed in order to validate the results obtained in the free interest risk model.     

The surplus prior to ruin and the deficit at ruin for a correlated risk process

This paper presents an explicit characterization for the joint probability density function of the surplus immediately prior to ruin and the deficit at ruin for a general risk process, which includes the Sparre-Andersen risk model with phase-type inter-claim times and claim sizes. The model can also accommodate a Markovian arrival process which enables claim sizes to be correlated with the inter-claim times. The marginal density function of the surplus immediately prior to ruin is specifically considered. Several numerical examples are presented to illustrate the application of this result.     

Default prediction with dynamic sectoral and macroeconomic frailties

This paper extends the macroeconomic frailty model to include sectoral frailty factors that capture default correlations among firms in a similar business. We estimate sectoral and macroeconomic frailty factors and their effects on default intensity using the data for Japanese firms from 1992 to 2010. We find strong evidence for the presence of sectoral frailty factors even after accounting for the effects of observable covariates and macroeconomic frailty on default intensity. The model with sectoral frailties performs better than that without. Results show that accounting for the sources of unobserved sectoral default risk covariations improves the accuracy of default probability estimation.     

Market Risk of Developed and Emerging Countries During the Global Financial Crisis

This study compares the performance of the widely used risk measure, value at risk (VaR), across a large sample of developed and emerging countries. The performance of VaR is assessed using both the unconditional and conditional tests of Kupiec and Christoffersen, respectively, as well as the quadratic loss function. The results indicate that VaR performs much more poorly when measuring the risk of developed countries than of emerging ones. One possible reason might be the deeper initial impact of the global financial crisis on developed countries. The results also provide evidence of the decoupling of the market risk of emerging and developed countries during the global financial crisis.