### 金融代写|量化风险管理代写Quantitative Risk Management代考|FINC6023

statistics-lab™ 为您的留学生涯保驾护航 在代写量化风险管理Quantitative Risk Management方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写量化风险管理Quantitative Risk Management代写方面经验极为丰富，各种代写量化风险管理Quantitative Risk Management相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (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|OVERVIEW OF FINANCIAL RISK MANAGEMENT

Imagine you are a chef at a restaurant. You’ve just finished preparing eggs benedict for a customer. The eggs are cooked perfectly, the hollandaise sauce has just the right mix of ingredients, and it all sits perfectly on the plate. The presentation is perfect! You’re so proud of the way this has turned out that you decide to deliver the dish to the customer yourself. You place the plate in front of the customer, and she replies, “This looks great, but I ordered a filet mignon, and you forgot my drink.”

Arguably, the greatest strength of modern financial risk management is that it is highly objective. It takes a scientific approach, using math and statistics to measure and evaluate financial products and portfolios. While these mathematical tools can be very powerful, they are simply that-tools. If we make unwarranted assumptions, apply models incorrectly, or present results poorly – or if our findings are ignored – then the most elegant mathematical models in the world will not help us. The eggs might be perfect, but that’s irrelevant if the customer ordered a steak.

This is not a new idea, Vitruvius, a famous Roman architect wrote, “Neque enim ingenium sine disciplina aut disciplina sine ingenio perfectum artificem potest efficere”, which roughly translates to “Neither genius without knowledge, nor knowledge without genius, will make a perfect artist.” Applying this to risk management, we might say, “Neither math without knowledge of financial markets, nor knowledge of financial markets without math, will make a perfect risk manager.”

Before we get to the math and statistics, then, we should take a step back and look at risk management more broadly. Before delving into the models, we explore the following questions: What is risk management? What is the proper role for a risk manager within a financial organization? What do risk managers actually do on a day-to-day basis?

We end this chapter with a brief history of risk management. As you will see, risk management has made many positive contributions to finance, but it is far from being a solved problem.

## 金融代写|量化风险管理代写Quantitative Risk Management代考|WHAT IS RISK

Before we can begin to describe what financial risk managers do, we need to understand what financial risk $i$. In finance, risk arises from uncertainty surrounding future profits or returns. There are many ways to define risk, and we may change the definition slightly, depending on the task at hand.

In everyday speech, the word risk is associated with the possibility of negative outcomes. For something to be risky, the final outcome must be uncertain and there must be some possibility that the final outcome will have negative consequences. While this may seem obvious, some popular risk measures treat positive and negative outcomes equally, while others focus only negative outcomes. For this reason, in order to avoid any ambiguity when dealing specifically with negative outcomes, risk managers will often talk about downside risk.
Risk is often defined relative to expectations. If we have one investment with a $50 / 50$ chance of earning $\$ 0$or$\$200$, and a second investment with a $50 / 50$ chance of earning $\$ 400$or$\$600$, are both equally risky? The first investment earns $\$ 100$on average, and the second$\$500$, but both have a $50 / 50$ chance of being $\$ 100$above or below this expected value. Because the deviations from expectations are equal, many risk managers would consider the two investments to be equally risky. By this logic, the second investment is more attractive because it has a higher expected return, not because it is less risky. It is also important to note that risk is about possible deviations from expectations. If we expect an investment to make$\$1$ and it does make $\$ 1$, the investment was not necessarily risk free. If there were any possibility that the outcome could have been something other than$\$1$, then the investment was risky.

## 金融代写|量化风险管理代写Quantitative Risk Management代考|Absolute, Relative, and Conditional Risk

There may be no better way to understand the limits of financial risk management-why and where it may fail or succeed – than to understand the difference between absolute, relative, and conditional risk.

Financial risk managers are often asked to assign probabilities to various financial outcomes. What is the probability that a bond will default? What is the probability that an equity index will decline by more than $10 \%$ over the course of a year? These types of predictions, where risk managers are asked to assess the total or absolute risk of an investment, are incredibly difficult to make. As we will see, assessing the accuracy of these types of predictions, even over the course of many years, can be extremely difficult.

It is often much easier to determine relative risk than to measure risk in isolation. Bond ratings are a good example. Bond ratings can be used to assess absolute risk, but they are on much surer footing when used to assess relative risk. The number of defaults in a bond portfolio might be much higher or lower next year depending on the state of the economy and financial markets. No matter what happens, though, a portfolio consisting of a large number of AAA-rated bonds will almost certainly have fewer defaults than a portfolio consisting of a large number of C-rated bonds. Similarly, it is much easier to say that emerging market equities are riskier than U.S. equities, or that one hedge fund is riskier than another hedge fund.
What is the probability that the S\&P 500 will be down more than $10 \%$ next year? What is the probability that a particular U.S. large-cap equity mutual fund will be down more than $8 \%$ next year? Both are very difficult questions. What is the probability that this same mutual fund will be down more than $8 \%$, if the S\&P 500 is down more than $10 \%$ ? This last question is actually much easier to answer. What’s more, these types of conditional risk forecasts immediately suggest ways to hedge and otherwise mitigate risk.

Given the difficulty of measuring absolute risk, risk managers are likely to be more successful if they limit themselves to relative and conditional forecasts, when possible. Likewise, when there is any ambiguity about how a risk measure can be interpreted —as with bond ratings – encouraging a relative or conditional interpretation is likely to be in a risk manager’s best interest.

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## MATLAB代写

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