金融代写|量化风险管理代写Quantitative Risk Management代考|BUSA90315

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我们提供的量化风险管理Quantitative Risk Management及其相关学科的代写,服务范围广, 其中包括但不限于:

  • Statistical Inference 统计推断
  • Statistical Computing 统计计算
  • Advanced Probability Theory 高等概率论
  • Advanced Mathematical Statistics 高等数理统计学
  • (Generalized) Linear Models 广义线性模型
  • Statistical Machine Learning 统计机器学习
  • Longitudinal Data Analysis 纵向数据分析
  • Foundations of Data Science 数据科学基础
金融代写|量化风险管理代写Quantitative Risk Management代考|BUSA90315

金融代写|量化风险管理代写Quantitative Risk Management代考|Market Risk

Market risk is risk associated with changing asset values. Market risk is most often associated with assets that trade in liquid financial markets, such as stocks and bonds. During trading hours, the prices of stocks and bonds constantly fluctuate. An asset’s price will change as new information becomes available and investors reassess the value of that asset. An asset’s value can also change due to changes in supply and demand.

All financial assets have market risk. Even if an asset is not traded on an exchange, its value can change over time. Firms that use mark-to-market accounting recognize this change explicitly. For these firms, the change in value of exchange-traded assets will be based on market prices. Other assets will either be marked to model -that is, their prices will be determined based on financial models with inputs that may include market prices-or their prices will be based on broker quotes – that is, their prices will be based on the price at which another party expresses their willingness to buy or sell the assets. Firms that use historical cost accounting, or book value accounting, will normally only realize a profit or a loss when an asset is sold. Even if the value of the asset is not being updated on a regular basis, the asset still has market risk. For this reason, most firms that employ historical cost accounting will reassess the value of their portfolios when they have reason to believe that there has been a significant change in the value of their assets.

For most financial instruments, we expect price changes to be relatively smooth and continuous most of the time, and large and discontinuous rarely. Because of this, market risk models often involve continuous distribution. Market risk models can also have a relatively high frequency (i.e., daily or even intraday). For many financial instruments, we will have a large amount of historical market data that we can use to evaluate market risk.

金融代写|量化风险管理代写Quantitative Risk Management代考|Credit Risk

Credit risk is the risk that one party in a financial transaction will fail to pay the other party. Credit risk can arise in a number of different settings. Firms may extend credit to suppliers and customers. Credit card debt and home mortgages create credit risk. One of the most common forms of credit risk is the risk that a corporation or government will fail to make interest payments or to fully repay the principal on bonds they have issued. This type of risk is known as default risk, and in the case of national governments it is also referred to as sovereign risk. Defaults occur infrequently, and the simplest models of default risk are based on discrete distributions. Although bond markets are large and credit rating agencies have been in existence for a long time, default events are rare. Because of this, we have much less historical data to work with when developing credit models, compared to market risk models.

For financial firms, counterparty credit risk is another important source of credit risk. While credit risk always involves two counterparties, when risk managers talk about counterparty credit risk they are usually talking about the risk arising from a significant long-term relationship between two counterparties. Prime brokers will often provide loans to investment firms, provide them with access to emergency credit lines, and allow them to purchase securities on margin. Assessing the credit risk of a financial firm can be difficult, time consuming, and costly. Because of this, when credit risk is involved, financial firms often enter into long-term relationships based on complex legal contracts. Counterparty risk specialists help design these contracts and play a lead role in assessing and monitoring the risk of counterparties.

Derivatives contracts can also lead to credit risk. A derivative is essentially a contract between two parties, that specifies that certain payments be made based on the value of an underlying security or securities. Derivatives include futures, forwards, swaps, and options. As the value of the underlying asset changes, so too will the value of the derivative. As the value of the derivative changes, so too will the amount of money that the counterparties owe each other. This leads to credit risk.

金融代写|量化风险管理代写Quantitative Risk Management代考|Enterprise Risk

The enterprise risk management group of a firm, as the name suggests, is responsible for the risk of the entire firm. At large financial firms, this often means overseeing market, credit, liquidity, and operations risk groups, and combining information from those groups into summary reports. In addition to this aggregation role, enterprise risk management tends to look at overall business risk. Large financial companies will often have a number of business units (e.g., capital markets, corporate finance, commercial banking, retail banking, asset management, etc.). Some of these business units will work very closely with risk management (e.g. capital markets, asset management), while others may have very little day-to-day interaction with risk (e.g. corporate finance). Regardless, enterprise risk management would assess how each business unit contributes to the overall profitability of the firm in order to assess the overall risk to the firm’s revenue, income, and capital.

Operational risk is risk arising from all aspects of a firm’s business activities. Put simply, it is the risk that people will make mistakes and that systems will fail. Operational risk is a risk that all financial firms must deal with.

Just as the number of activities that businesses carry out is extremely large, so too are the potential sources of operational risk. That said, there are broad categories on which risk managers tend to focus. These include legal risk (most often risk arising from contracts, which may be poorly specified or misinterpreted), systems risk (risk arising from computer systems) and model risk (risk arising from pricing and risk models, which may contain errors, or may be used inappropriately).

As with credit risk, operational risk tends to be concerned with rare but significant events. Operational risk presents additional challenges in that the sources of operational risk are often difficult to identify, define, and quantify.

金融代写|量化风险管理代写Quantitative Risk Management代考|BUSA90315


金融代写|量化风险管理代写Quantitative Risk Management代考|Market Risk


所有金融资产都有市场风险。即使资产不在交易所交易,其价值也会随着时间而变化。使用盯市会计的公司明确认识到这一变化。对于这些公司,交易所交易资产的价值变化将基于市场价格。其他资产将被标记为模型 – 也就是说,它们的价格将基于可能包括市场价格的输入的金融模型确定 – 或者它们的价格将基于经纪人报价 – 也就是说,它们的价格将基于价格另一方表示愿意购买或出售资产。使用历史成本会计或账面价值会计的公司通常只会在出售资产时实现损益。即使资产的价值没有定期更新,该资产仍有市场风险。出于这个原因,大多数采用历史成本会计的公司会在有理由相信其资产价值发生重大变化时重新评估其投资组合的价值。


金融代写|量化风险管理代写Quantitative Risk Management代考|Credit Risk




金融代写|量化风险管理代写Quantitative Risk Management代考|Enterprise Risk





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术语 广义线性模型(GLM)通常是指给定连续和/或分类预测因素的连续响应变量的常规线性回归模型。它包括多元线性回归,以及方差分析和方差分析(仅含固定效应)。



有限元是一种通用的数值方法,用于解决两个或三个空间变量的偏微分方程(即一些边界值问题)。为了解决一个问题,有限元将一个大系统细分为更小、更简单的部分,称为有限元。这是通过在空间维度上的特定空间离散化来实现的,它是通过构建对象的网格来实现的:用于求解的数值域,它有有限数量的点。边界值问题的有限元方法表述最终导致一个代数方程组。该方法在域上对未知函数进行逼近。[1] 然后将模拟这些有限元的简单方程组合成一个更大的方程系统,以模拟整个问题。然后,有限元通过变化微积分使相关的误差函数最小化来逼近一个解决方案。





随机过程,是依赖于参数的一组随机变量的全体,参数通常是时间。 随机变量是随机现象的数量表现,其时间序列是一组按照时间发生先后顺序进行排列的数据点序列。通常一组时间序列的时间间隔为一恒定值(如1秒,5分钟,12小时,7天,1年),因此时间序列可以作为离散时间数据进行分析处理。研究时间序列数据的意义在于现实中,往往需要研究某个事物其随时间发展变化的规律。这就需要通过研究该事物过去发展的历史记录,以得到其自身发展的规律。


多元回归分析渐进(Multiple Regression Analysis Asymptotics)属于计量经济学领域,主要是一种数学上的统计分析方法,可以分析复杂情况下各影响因素的数学关系,在自然科学、社会和经济学等多个领域内应用广泛。


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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