金融操作风险的度量与管理

业界正在努力采取一种系统性的方法去度量并管理风险：借用保险公司的有关工具去量化操作风险，借用市场风险的有关工具去管理操作风险，而且监管当局也将操作风险纳入资本要求之中以便更有效地控制操作风险。本文对操作风险进行了概念界定，并且介绍了操作风险的度量和管理方法。     

我国商业银行操作风险度量方法的选择

操作风险管理是我国商业银行面临的一个严峻课题,影响着商业银行的生存和发展,而其中操作风险的准确度量,是有效管理和防范操作风险的关键环节.国外发达银行和巴塞尔委员会虽然推出了一些操作风险度量的方法和框架,但是直接运用于我国商业银行还存在诸多问题.本文从分析影响我国商业银行操作风险度量方法选择的因素出发,论述了<巴塞尔新资本协议>推荐的几种方法在我国商业银行操作风险度量中的适应性问题,并对我国商业银行发展操作风险度量方法提出了建设性的意见.     

上市公司绩效及风险度量

自从Markowitz于1952年创立了投资组合以来．风险度量和金融资本配置模型的研究一直是金融投资研究的热点之一，到目前为止，金融投资专家和学者已提出很多种不同的度量风险模型。本文回顾了历史上使用过的风险度量方法．并指出了它们的局限性，同时本文提出了修改的构想和一个新的风险度量标准——综合风险偏差。     

金融市场风险度量方法研究

文章首先分析了金融市场风险度量方法的产生与发展,以及金融市场风险度量方法分类的基本框架,并评述了每类风险度量方法的优点与不足,其次,研究了市场风险度量方法的新进展,并按一致风险度量标准,对以分位数为基础的度量方法的特点与实现条件进行了分析比较,最后,对金融市场风险度量方法进行了必要的归类。     

一种度量国家经济安全风险的方法

研究国家经济安全风险是国家战略需要,度量风险可为风险决策和防范提供可靠数据,但现有研究,还缺乏一套行之有效或付诸实践的国家经济安全风险度量方法。鉴于此,在前人研究的基础上,建立了国家经济安全风险度量指标体系,并用故障树和信息熵方法度量国家经济安全风险。利用故障树方法,合理地分解了国家经济安全所涉及的领域,利用信息熵方法,解决了风险度量中各个部分权重分配问题。并通过1985~2011年国家外债统计年鉴数据实证分析了该方法的合理性和有效性。     

涉外企业的汇率风险度量

汇率风险日益成为影响涉外企业价值的重要因素,然而与对利率风险、信用风险的度量研究相比,汇率风险的度量研究相对滞后。本文通过尝试着把主要用来衡量利率风险的VaR方法运用于对涉外企业的汇率风险衡量,以期来推动理论界对汇率风险度量问题的关注。     

证券投资风险度量方法探讨

近年来,世界金融快速发展,然而金融学很多理论尚未形成一个完整的体系,特别是风险理论,在金融发展过程中起步较晚。金融危机的爆发给世界经济的发展带来严重的损害。证券投资风险的管理和防范引起了越来越多人的关注,因此要采用科学合理的证券投资风险度量方法,有效度量和识别证券投资风险。本文简要介绍了证券投资风险和证券投资风险度量,分析了证券投资风险度量方法,阐述了证券投资风险度量方法的思考。     

商业银行操作风险度量建模思路与模型选择研究

由于银行监管和内部经济资本配置的需要，操作风险度量是商业银行操作风险管理的一项重要内容。目前，还没有准确度量操作风险的方法，操作风险度量模型构建要以操作风险的特征为基础，操作风险具有自己的特征。应据此提出建模思路并选择合适模型。     

当前我国商业银行操作风险度量研究

操作风险是银行业三大风险之一,有效控制操作风险是完善银行操作风险管理体系、提高经营管理水平的客观要求:而实现操作风险的准确度量,则是有效防范操作风险的重要前提.目前我国对操作风险的研究还处于探索阶段,今后应在以下五个方面加强研究:(1)制定操作风险管理政策;(2)设计操作风险管理组织架构及再造业务流程;(3)建立内部控制自我评价体系;(4)建立操作风险损失数据库;(5)探索操作风险度量模型.     

国内风险度量理论研究综述

风险的客观存在及损失的产生使人们对风险的认识不断深入,进而产生了现代风险理论,而现代风险理论的重点是风险管理。风险度量理论是风险管理理论的一个重要组成部分,理清并综述国内风险度量理论研究及其进展对于风险理论的研究具有一定学术价值。     

Expected utility theory and prospect theory: one wedding and a decent funeral

Choice behavior is typically evaluated by assuming that the data is generated by one latent decision-making process or another. What if there are two (or more) latent decision-making processes generating the observed choices? Some choices might then be better characterized as being generated by one process, and other choices by the other process. A finite mixture model can be used to estimate the parameters of each decision process while simultaneously estimating the probability that each process applies to the sample. We consider the canonical case of lottery choices in a laboratory experiment and assume that the data is generated by expected utility theory and prospect theory decision rules. We jointly estimate the parameters of each theory as well as the fraction of choices characterized by each. The methodology provides the wedding invitation, and the data consummates the ceremony followed by a decent funeral for the representative agent model that assumes only one type of decision process. The evidence suggests support for each theory, and goes further to identify under what demographic domains one can expect to see one theory perform better than the other. We therefore propose a reconciliation of the debate over two of the dominant theories of choice under risk, at least for the tasks and samples we consider. The methodology is broadly applicable to a range of debates over competing theories generated by experimental and non-experimental data.     

Expected utility inequalities: theory and applications

Suppose we know the utility function of a risk averse decision maker who values a risky prospect X at a price CE. Based on this information alone I develop upper bounds for the tails of the probabilistic belief about X of the decision maker. In the paper I also illustrate how to use these expected utility bounds in a variety of applications, which include the estimation of risk measures from observed data, option valuation, and the study of credit risk. I would like to thank John Cochrane, Tom Cosimano, Amanda Friedenberg, George Korniotis, Markus Brunermeier and Paul Schultz for helpful discussions and to participants at two Notre Dame seminars, at the 2006 Spring Midwest Economic Theory and International Economics Conference, and at the 2006 Australasian Meeting of the Econometric Society for their very useful comments. I began working on this project during a year-long visit to the Central Bank of Venezuela. I gratefully acknowledge their hospitality and financial support.     

旅游风险认知与测度研究——基于大学生群体入藏旅游的调查

随着人们对旅游出行安全重要性的日益重视,旅游安全研究在学术界得到了更多的关注。在旅游安全研究领域里,对游者风险认知的研究一直属于薄弱环节。在文献分析以及问卷调查基础上,文章提出旅游风险认知的测度应限定在特定的群体与目的地之间的思想,并以此对大学生入藏旅游风险认知进行了系统的研究。文章考察了影响大学生对入藏旅游风险认知的维度,分析了大学生对不同维度与属性风险的认知程度,并且进行了不同特征下大学生群体旅游风险认知的相关研究。研究发现,影响大学生入藏旅游风险认知共有6个维度,包含16个基本属性;大学生群体对不同的维度与属性风险有着不同的认知程度;不同人口统计特征下大学生有着不同的风险认知,对于同一维度的风险,大学生群体内部存在着差异性认知。     

Expected utility theory and experimental utility measurement, 1950–1985. From confidence to scepticism

Abstract

The paper reconstructs the history of the experimental attempts to measure the cardinal utility of money between 1950 and 1985 within the framework provided by expected utility theory (EUT). It is shown that this history displays a definite trajectory: from the confidence in EUT and the EUT-based measurement of utility of the 1950s to the scepticism that, from the mid-1970s, haunted the validity of EUT as well as the significance of the utility measures obtained through it. By exploring the diverse aspects and causes of this trajectory, the paper covers new ground in the history of both decision theory and utility measurement.     

A semi-parametric approach to estimating the operational risk and Expected Shortfall

In this article, we propose improvements to the peak-over-threshold (POT) method and apply this improved method for modelling US business operational losses and estimating operational risks (ORs). In the widely used traditional POT method, the generalized Pareto distribution (GPD) is fitted to severity losses, while an empirical distribution is fitted to small to medium losses. Then, the Expected Loss and the 99.9% operational value-at-risk (OpVaR) are estimated. Additionally, the Expected Shortfall (ES) – a coherent risk measure – is estimated in this article as an alternative to OpVaR. These risk measures constitute the levels of regulatory and economic capitals to cover risks. With the improved POT method, the risks can be estimated more accurately than with the traditional POT method. The results indicate that the OpVaR are much lower than the ES and that the larger the tail losses the greater the difference between these two risk measures. Our findings imply that the ES would provide higher levels of capitals to cover risks than would the OpVaR, particularly during crises, and they have implications for the efficient OR management and regulators.     

Is hedging successful at reducing financial risk exposure?

This article analyses whether firms use risk management instruments for hedging or speculative purposes. First, by analysing the relationship between the firm’s stock returns and financial risks in 567 Euronext firms, we measure the firm’s exposure to risk. Next, we investigate the effect of hedging in such exposures, addressing simultaneously the endogeneity of hedging decision through a treatment effect methodology. We have found that firms in our sample display higher percentages of exposure, when weighed against preceding studies, and confirmed that hedging reduces the level of the underlying financial exposure, concluding that firms use risk management instruments with hedging purposes.     

外汇风险的多维分析

本文采用数量分析的方法对外汇风险进行解析，在明确外汇风险的构成（三要素：外汇暴露，汇率的不确定性被动和持有期）的基础上，对外汇风险的概念做出相对完善的描述，在此基础上再展开封外汇风险的衡量及组成要素的针对性管理的探讨。     

国家风险测评方法研究

国家风险是指因债务人(或投资对象)其所处国家经济、政治或社会等方面的变化而使外国债权人(或外国投资者)蒙受损失的可能性。分析、评估国家风险大致可分为定性分析模式和定量分析模式,两种模式从不同的侧重角度、应用不同的评估方法对于跨国授信中面临的国家风险提供了系统的分析范式。     

Mixed data sampling expectile regression with applications to measuring financial risk

To avoid information loss or measurement error in traditional methods dealing with mixed frequency data, we develop a novel mixed data sampling expectile regression (MIDAS-ER) model to measure financial risk. We construct the MIDAS-ER model by introducing a MIDAS structure into expectile regressions. This enables us to perform an expectile regression on raw mixed frequency data directly. We apply the proposed MIDAS-ER model to estimate two popular financial risk measures, namely, Value at Risk and Expected Shortfall, with both simulated data and four stock indices, and compare the model's performance with those of several popular models. The outstanding performance of our model demonstrates that high-frequency information helps to improve the accuracy of risk measurement. In addition, the numerical results also imply that our model can be a significant tool for risk-averse investors to control risk losses and for financial institutions to implement robust risk management.     

Precautionary savings of agents with heterogeneous risk aversion

This article focuses on the estimation of the importance of the precautionary motive in the wealth accumulation decision. We use the micro data set of the De Nederlandsche Bank (DNB) Household Survey (DHS) (CentERdata, Tilburg University), a Dutch household survey containing information on wealth, a subjective measure of income uncertainty and subjective qualitative measures of risk aversion. We find that only a small share of wealth is accumulated for the precautionary motive by the Dutch households. This share of wealth is constant across assets with different degrees of liquidity. The economic downturn of the period 2008 to 2010 seems to affect risk attitudes and precautionary saving. Our findings also suggest that the more risk-averse individuals are those who hold less savings.