数学代写|风险管理代写Risk Management代考|OHSS7006 The Regulatory Environment

如果你也在 怎样代写风险管理Risk Management|这个学科遇到相关的难题,请随时右上角联系我们的24/7代写客服。风险管理Risk Management是对风险(在ISO31000中定义为不确定性对目标的影响)的识别、评估和优先排序,然后对资源进行协调和经济的应用,以最小化、监测和控制不幸事件的概率或影响,或最大限度地实现机会。

风险管理Risk Management 可以来自不同的来源,包括国际市场的不确定性、项目失败的威胁(在设计、开发、生产或维持生命周期的任何阶段)、法律责任、信用风险、事故、自然原因和灾难、对手的蓄意攻击,或不确定或不可预测的根源事件。有两种类型的事件,即负面事件可以归类为风险,而正面事件则归类为机会。风险管理标准由不同的机构制定,包括项目管理协会、国家标准和技术研究所、精算协会和ISO标准。方法、定义和目标因风险管理方法是在项目管理、安全、工程、工业流程、金融组合、精算评估或公共健康和安全的背景下而有很大差异。某些风险管理标准被批评为对风险没有可衡量的改善,而对估计和决定的信心似乎有所增加。

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数学代写|Matlab代考|OHSS7006 The Regulatory Environment

数学代写|风险管理代写Risk Management代考|The Regulatory Environment

So far in this chapter, we have explained how the global environment became riskier as the financial markets were liberalized, and we have charted the consequent growth in risk management products in terms of the types of instrument and the volumes traded. Now it is time to turn our attention back to the regulatory environment.

In 1980 the Depository Institutions Deregulation and Monetary Control Act (DIDMCA) marked a major change in regulatory philosophy in the United States. This act was an important step in the deregulation of the banking system, and the liberalization of the economic environment in which banks operate. The act initiated a six-year phase-out period for Regulation $Q$, which had placed a ceiling on the interest rates that banks could offer deposit accounts with check facilities and savings deposits. The act allowed commercial banks to pay interest on accounts with withdrawal rights (the so-called “NOW” accounts).

This trend continued with the 1982 Garn-St. Germain Depository Institution Act (DIA), which allowed banks to offer money market deposit accounts, and the so-called “super-NOW” accounts (i.e., accounts that paid interest but offered limited check-writing privileges).
These regulatory moves opened up the banking industry to further competition from federally chartered thrift institutions, but they also allowed commercial banks to expand by buying failed savings banks. By the late 1970 s and early 1980 s, the numbers of such failed institutions had increased substantially. The main reason was an economic squeeze on banks that held sizable fixed-rate loan portfolios and which had financed these portfolios by means of short-term instruments. The inflationary environment of the 1970 s left such institutions exposed to rising interest rates.

数学代写|风险管理代写Risk Management代考|The Academic Background and Technological Changes

Risk management cannot be understood independently of the body of academic research published on risk management techniques and derivative valuation that has evolved since the early 1950 s. A common deficiency in risk management systems and policy proposals is the lack of a firm theoretical foundation (and therefore consistency).
In this section we review some of the key theories and models, and show how they relate to the development of approaches to risk management in banking. However, it is worth making clear at the outset that the theoretical work on risk management is based on many simplifying assumptions, and that the implementation of theoretical work is not always straightforward. Real life is complicated and is composed of many details that models cannot, and maybe should not, accommodate. Instead, the role of models is often to simplify complicated structures and to highlight the most important factors. A “good” financial model is one that helps the analyst separate out the major explanatory variables from a noisy background.
Milton Friedman, in his seminal article “The Methodology of Positive Economics” (1953), emphasizes that a model can be only evaluated in terms of its predictive power. It cannot be evaluated in terms of the assumptions employed, or in terms of whether the model seems to be sufficiently complicated to capture all the relevant details from “real life.” In other words, a model can be simple, and yet be judged successful if it helps in predicting the future and in improving the efficiency of the decision-making process.

The word “risk” has many meanings and connotations. It is widely used by professional traders, risk managers, and the public. Many articles in newspapers and magazines talk about risky and choppy markets. They warn their readers from investing “too much” in “risky assets,” and they wonder whether financial markets have become “too risky” and volatile. A proliferation of names has emerged to describe the various risks: business risk, financial risk, market risk, liquidity risk, default risk, systematic risk, specific risk, residual risk, credit risk, counterparty risk, operations risk, settlement risk, country risk, portfolio risk, systemic risk, legal risk, reputational risk, and more.

数学代写|Matlab代考|OHSS7006 The Regulatory Environment

风险管理代写

数学代写|风险管理代写Risk Management代考

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微观经济学代写

微观经济学是主流经济学的一个分支,研究个人和企业在做出有关稀缺资源分配的决策时的行为以及这些个人和企业之间的相互作用。my-assignmentexpert™ 为您的留学生涯保驾护航 在数学Mathematics作业代写方面已经树立了自己的口碑, 保证靠谱, 高质且原创的数学Mathematics代写服务。我们的专家在图论代写Graph Theory代写方面经验极为丰富,各种图论代写Graph Theory相关的作业也就用不着 说。

线性代数代写

线性代数是数学的一个分支,涉及线性方程,如:线性图,如:以及它们在向量空间和通过矩阵的表示。线性代数是几乎所有数学领域的核心。



博弈论代写

现代博弈论始于约翰-冯-诺伊曼(John von Neumann)提出的两人零和博弈中的混合策略均衡的观点及其证明。冯-诺依曼的原始证明使用了关于连续映射到紧凑凸集的布劳威尔定点定理,这成为博弈论和数学经济学的标准方法。在他的论文之后,1944年,他与奥斯卡-莫根斯特恩(Oskar Morgenstern)共同撰写了《游戏和经济行为理论》一书,该书考虑了几个参与者的合作游戏。这本书的第二版提供了预期效用的公理理论,使数理统计学家和经济学家能够处理不确定性下的决策。



微积分代写

微积分,最初被称为无穷小微积分或 “无穷小的微积分”,是对连续变化的数学研究,就像几何学是对形状的研究,而代数是对算术运算的概括研究一样。

它有两个主要分支,微分和积分;微分涉及瞬时变化率和曲线的斜率,而积分涉及数量的累积,以及曲线下或曲线之间的面积。这两个分支通过微积分的基本定理相互联系,它们利用了无限序列和无限级数收敛到一个明确定义的极限的基本概念 。



计量经济学代写

什么是计量经济学?
计量经济学是统计学和数学模型的定量应用,使用数据来发展理论或测试经济学中的现有假设,并根据历史数据预测未来趋势。它对现实世界的数据进行统计试验,然后将结果与被测试的理论进行比较和对比。

根据你是对测试现有理论感兴趣,还是对利用现有数据在这些观察的基础上提出新的假设感兴趣,计量经济学可以细分为两大类:理论和应用。那些经常从事这种实践的人通常被称为计量经济学家。



MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中,其中问题和解决方案以熟悉的数学符号表示。典型用途包括:数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发,包括图形用户界面构建MATLAB 是一个交互式系统,其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题,尤其是那些具有矩阵和向量公式的问题,而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问,这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展,得到了许多用户的投入。在大学环境中,它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域,MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要,工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数(M 文件)的综合集合,可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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