金融风险管理(双语)
IMF 金融风险,financial risk,英文版
Effects of Culture on Firm Risk-Taking: A Cross-Country and Cross-Industry Analysis
Roxana Mihet
© 2012 International Monetary Fund
WP/12/
IMF Working Paper Research Department Effects of Culture on Firm Risk-Taking: A Cross-Country and Cross-Industry Analysis Prepared by Roxana Mihet* Authorized for distribution by Stijn Claessens August 2012
* I have benefited especially from detailed discussions with Stijn Claessens and Luc Laeven. I am grateful to Mohsan Bilal for his extensive help with the data. I would like to thank George Akerlof, Christopher Baum, John Beshears, Nathan Nunn, Lev Ratnovski, Fabian Valencia, and Francis Vitek in particular, and participants to 17th International Conference on Cultural Economics for their interesting comments on the topic, and useful and valuable suggestions on this paper. This paper is the winner of the President Prize for the best graduate student paper presented at the ACEI's 17th International Conference on Cultural Economics in Kyoto, Japan.
金融风险管理外文翻译文献
金融风险管理外文翻译文献(文档含英文原文和中文翻译)原文：Enterprise Risk Management in InsuranceEnterprise Risk Management (hereinafter referred as “ERM”) interests a wide range of professions (e.g., actuaries, corporate financial managers, underwriters, accountants,and internal auditors), however, current ERM solutions often do not cover all risks because they are motivated by the core professional ethics and principles of these professions who design and administer them. In a typical insurance company all such professions work as a group to achieve the overriding corporate objectives.Risk can be defined as factors which prevent an organization in achieving its objectives and risks affect organizations holistically. The management of risk in isolation often misses its big picture. It is argued here that a holistic management of risk is logical and is the ultimate destination of all general management activities.Moreover, risk management should not be a separate function of the business process;rather, managing downside risk and taking the opportunities from upside risk should be thekey management goals. Consequently, ERM is believed as an approach to risk management, which provides a common understanding across the multidisciplinary groups of people of the organization. ERM should be proactive and its focus should be on the organizations future. Organizations often struggle to see and understand the full risk spectrum to which they are exposed and as a result they may fail to identify the most vulnerable areas of the business. The effective management of risk is truly an interdisciplinary exercise grounded on a holistic framework.Whatever name this new type of risk management is given (the literature refers to it by diverse names, such as Enterprise Risk Management, Strategic Risk Management, and Holistic Risk Management) the ultimate focus is management of all significant risks faced by the organization. Risk is an integral part of each and every action of the organization in the sense that an organization is a basket of contracts associated with risk (in terms of losses and opportunities). The idea of ERM is simple and logical, but implementation is difficult. This is because its involvement with a wide stakeholder community, which in turn involves groups from different disciplines with different beliefs and understandings. Indeed, ERM needs theories (which are the interest of academics) but a grand theory of ERM (which invariably involves an interdisciplinary concept) is far from having been achieved.Consequently, for practical proposes, what is needed is the development of a framework(a set of competent theories) and one of the key challenges of this thesis is to establish the key features of such a framework to promote the practice of ERM. Multidisciplinary Views of RiskThe objective of the research is to study the ERM of insurance companies. In line with this it is designed to investigate what is happening practically in the insurance industry at the current time in the name of ERM. The intention is to minimize the gap between the two communities (i.e., academics and practitioners) in order to contribute to the literature of risk management.In recent years ERM has emerged as a topic for discussion in the financial community,in particular, the banks and insurance sectors. Professional organizations have published research reports on ERM. Consulting firms conducted extensive studies and surveys on the topic to support their clients. Rating agencies included theERM concept in their rating criteria. Regulators focused more on the risk management capability of the financial organizations. Academics are slowly responding on the management of risk in a holistic framework following the initiatives of practitioners.The central idea is to bring the organization close to the market economy. Nevertheless,everybody is pushing ERM within the scope of their core professional understanding.The focus of ERM is to manage all risks in a holistic framework whatever the source and nature. There remains a strong ground of knowledge in managing risk on an isolated basis in several academic disciplines (e.g., economics, finance, psychology,sociology, etc.). But little has been done to take a holistic approach of risk beyond disciplinary silos. Moreover, the theoretical understanding of the holistic (i.e., multidisciplinary)properties of risk is still unknown. Consequently, there remains a lack of understanding in terms of a common and interdisciplinary language for ERM.Risk in FinanceIn finance, risky options involve monetary outcomes with explicit probabilities and they are evaluated in terms of their expected value and their riskiness. The traditional approach to risk in finance literature is based on a mean-variance framework of portfolio theory, i.e., selection and diversification. The idea of risk in finance is understood within the scope of systematic (non-diversifiable) risk and unsystematic (diversifiable)risk. It is recognized in finance that systematic risk is positively correlated with the rate of return. In addition, systematic risk is a non-increasing function of a firm’s growth in terms of earnings. Another established concern in finance is default risk and it is argued that the performance of the firm is linked to the firm’s default risk. A large part of finance literature deals with severa l techniques of measuring risks of firms’ investment portfolios (e.g., standard deviation, beta, VaR, etc.). In addition to the portfolio theory, Capital Asset Pricing Model (CAPM) was discovered in finance to price risky assets on the perfect capital markets. Finally, derivative markets grew tremendously with the recognition of option pricing theory.Risk in EconomicsRisk in economics is understood within two separate (independent) categories,i.e.,endogenous (controllable) risk and background (uncontrollable) risk. It is recognized that economic decisions are made under uncertainty in the presence of multiple risks.Expected Utility Theory argues that peoples’ risk attitude on the size of risk (small,medium, large) is derived from the utility-of-wealth function, where the utilities of outcomes are weighted by their probabilities. Economists argue that people are risk averse (neutral) when the size of the risks is large (small).Prospect theory provides a descriptive analysis of choice under risk. In economics, the concept of risk-bearing preferences of agents for independent risks was described under the notion of “ standard risk aversion.” Most of the economic research on risk is originated on the study of decision making behavior on lotteries and other gambles. Risk in PsychologyWhile economics assumes an individual’s risk preference is a function of probabilistic beliefs, psychology explores how human judgment and behavior systematically forms such beliefs. Psychology talks about the risk taking behavior (risk preferences).It looks for the patterns of human reactions to the context, reference point,mental categories and associations that influence how people make decisions.The psychological approach to risk draws upon the notion of loss aversion that manife sts itself in the related notion of “regret.” According to Willett; “risk affects economic activity through the psychological influence of uncertainty.” Managers’ attitude of risk taking is often described from the psychological point of view in terms of feelings.Psychologists argue that risk, as a multidisciplinary concept, can not be reduced meaningfully by a single quantitative treatment. Consequently, managers tend to utilize an array of risk measurers to assist them in the decision making process under uncertainty. Risk perception plays a central role in the psychological research on risk, where the key concern is how people perceive risk and how it differs to the actual outcome. Nevertheless, the psychological research on risk provides fundamental knowledge of how emotions are linked to decision making.Risk in SociologyIn sociology risk is a socially constructed phenomenon (i.e., a social problem) and defined as a strategy referring to instrumental rationality. The sociologicalliterature on risk was originated from anthropology and psychology is dominated by two central concepts. First, risk and culture and second, risk society. The negative consequences of unwanted events (i.e., natural/chemical disasters, food safety) are the key focus of sociological researches on risk. From a sociological perspective entrepreneurs remain liable for the risk of the society and responsible to share it in proportion to their respective contributions. Practically, the responsibilities are imposed and actions are monitored by state regulators and supervisors.Nevertheless, identification of a socially acceptable threshold of risk is a key challenge of many sociological researches on risk.Convergence of Multidisciplinary Views of RiskDifferent disciplinary views of risk are obvious. Whereas, economics and finance study risk by examining the distribution of corporate returns, psychology and sociology interpret risk in terms of its behavioral components. Moreover, economists focus on the economic (i.e., commercial) value of investments in a risky situation.In contrast, sociologists argue on the moral value (i.e., sacrifice) on the risk related activities of the firm. In addition, sociologists’ criticism of economists’concern of risk is that although they rely on risk, time, and preferences while describing the issues related to risk taking, they often miss out their interrelationships(i.e., narrow perspective). Interestingly, there appears some convergence of economics and psychology in the literature of economic psychology. The intention is to include the traditional economic model of individuals’ formal rational action in the understanding of the way they actually think and behave (i.e., irrationality).In addition, behavioral finance is seen as a growing discipline with the origin of economics and psychology. In contrast to efficient market hypothesis behaviour finance provides descriptive models in making judgment under uncertainty.The origin of this convergence was due to the discovery of the prospect theory in the fulfillment of the shortcomings of von Neumann-Morgenstern’s utility theory for providing reasons of human (irrational) behavior under uncertainty (e.g., arbitrage).Although, the overriding enquiry of disciplines is the estimation of risk, they comparing and reducing into a common metric of many types of risks are there ultimate difficulty. The key conclusion of the above analysis suggests that there existoverlaps on the disciplinary views of risk and their interrelations are emerging with the progress of risk research. In particular, the central idea of ERM is to obscure the hidden dependencies of risk beyond disciplinary silos.Insurance Industry PracticeThe practice of ERM in the insurance industry has been drawn from the author’s PhD research completed in 2006. The initiatives of four major global European insurers(hereinafter referred as “CASES”) were studied for this purpose. Out of these four insurers one is a reinsurer and the remaining three are primary insurers. They were at various stages of designing and implementing ERM. A total of fifty-one face-to-face and telephone interviews were conducted with key personnel of the CASES in between the end of 2004 and the beginning of 2006. The comparative analysis (compare-and-contrast) technique was used to analyze the data and they were discussed with several industry and academic experts for the purpose of validation. Thereafter,a conceptual model of ERM was developed from the findings of the data.Findings based on the data are arranged under five dimensions. They are understanding;evaluation; structure; challenges, and performance of ERM. Understanding of ERMIt was found that the key distinction in various perceptions of ERM remains between risk measurement and risk management. Interestingly, tools and processes are found complimentary. In essence, meaning that a tool can not run without a process and vice versa. It is found that the people who work with numbers (e.g.,actuaries, finance people, etc.) are involved in the risk modeling and management(mostly concerned with the financial and core insurance risks) and tend to believe ERM is a tool. On the other hand internal auditors, company secretaries, and operational managers; whose job is related to the human, system and compliance related issues of risk are more likely to see ERM as a process.ERM: A ProcessWithin the understanding of ERM as a process, four key concepts were found. They are harmonization, standardization, integration and centralization. In fact, they are linked to the concept of top-down and bottom-up approaches of ERM.The analysis found four key concepts of ERM. They are harmonization,standardization,integration and centralization (in decreasing order of importance). It was also found that a unique understanding of ERM does not exist within the CASES, rather ERM is seen as a combination of the four concepts and they often overlap. It is revealed that an understanding of these four concepts including their linkages is essential for designing an optimal ERM system.Linkages Amongst the Four ConceptsAlthough harmonization and standardization are seen apparently similar respondents view them differently. Whereas, harmonization allows choices between alternatives,standardization provides no flexibility. Effectively, harmonization offers a range of identical alternatives, out of which one or more can be adopted depending on the given circumstances. Although standardization does not offer such flexibility,it was found as an essential technique of ERM. Whilst harmonization accepts existing divergence to bring a state of comparability, standardization does not necessarily consider existing conventions and definitions. It focuses on a common standard, (a “top-down” approach). Indeed, integration of competent policies and processes,models, and data (either for management use, compliance and reporting) are not possible for global insurers without harmonizing and standardizing them. Hence, the research establishes that a sequence (i.e., harmonization, standardization, integration,and then centralization) is to be maintained when ERM is being developed in practice (from an operational perspective). Above all, the process is found important to achieve a diversified risk culture across the organization to allocate risk management responsibilities to risk owners and risk takers.ERM: A ToolViewed as a tool, ERM encompasses procedures and techniques to model and measure the portfolio of (quantifiable) enterprise risk from insurers’ core disciplinary perspective. The objective is to measure a level of (risk adjusted) capital(i.e., economic capital) and thereafter allocation of capital. In this perspective ERM is thought as a sophisticated version of insurers’ asset-liability management.Most often, extreme and emerging risks, which may bring the organization down,are taken into consideration. Ideally, the procedure of calculating economic capital is closely linked to the market volatility. Moreover, the objective is clear, i.e., meetingthe expectation of shareholders. Consequently, there remains less scope to capture the subjectivity associated with enterprise risks.ERM: An ApproachIn contrast to process and tool, ERM is also found as an approach of managing the entire business from a strategic point of view. Since, risk is so deeply rooted in the insurance business, it is difficult to separate risk from the functions of insurance companies. It is argued that a properly designed ERM infrastructure should align risk to achieve strategic goals. Alternatively, application of an ERM approach of managing business is found central to the value creation of insurance companies.In the study, ERM is believed as an approach of changing the culture of the organization in both marketing and strategic management issues in terms of innovating and pricing products, selecting profitable markets, distributing products, targeting customers and ratings, and thus formulating appropriate corporate strategies. In this holistic approach various strategic, financial and operational concerns are seen integrated to consider all risks across the organization.It is seen that as a process, ERM takes an inductive approach to explore the pitfalls (challenges) of achieving corporate objectives for broader audience (i.e.,stakeholders) emphasizing more on moral and ethical issues. In contrast, as a tool,it takes a deductive approach to meet specific corporate objectives for selected audience(i.e., shareholders) by concentrating more on monitory (financial) outcomes.Clearly, the approaches are complimentary and have overlapping elements. 作者：M Acharyya译文：保险业对企业风险管理的实证研究企业风险管理涉及各种行业(如保险精算师、公司财政经理、保险商、会计和内部审计员)，当前企业风险管理解决方案往往不能涵盖所有的风险，因为这些方案取决于决策者和执行则的专业道德和原则。
金融风险管理(financial risk management)
2018/12/2
Teaching Team of Advanced Financial Management
2
Definition of financial risk Definition, features and types of risk Components of corporate business risk Influencing factors and types of financial risk
Procedure of financial risk evaluation Basic methods of financial risk identification Methods of financial risk evaluation
2018/12/2
Teaching Team of Advanced Financial Management
4
Definition, features and types of risk 2. Types of risk include:
（3）controllable risk and
uncontrollable risk
（4）objective risk and subjective cost
（5）macro risk and micro risk
Teaching Team of Advanced Financial Management
14
1. Decomposition method
Decompose a complicated system into several parts or subsystems, and analyze them one by one, to summarize all the varieties of risks influencing the system operations. This is a basic method to identify risk.
金融风险管理英文版本教材
金融风险管理英文版本教材Financial Risk Management TextbookTitle: Financial Risk Management: A Comprehensive Guide Author: [Your Name]Edition: 1st EditionPublisher: [Publishing Company]Publication Year: [Year]ISBN: [ISBN number]Table of Contents:1. Introduction to Financial Risk Management1.1 Definition and Importance of Financial Risk Management 1.2 Types of Financial Risks1.3 Objectives of Financial Risk Management2. Market Risk Management2.1 Concept and Measurement of Market Risk2.2 Market Risk Models (Value at Risk, Expected Shortfall)2.3 Hedging Techniques for Market Risk3. Credit Risk Management3.1 Introduction to Credit Risk3.2 Credit Risk Assessment and Evaluation3.3 Credit Risk Mitigation Techniques4. Liquidity Risk Management4.1 Understanding Liquidity Risk4.2 Liquidity Risk Measurement and Monitoring4.3 Liquidity Risk Management Strategies5. Operational Risk Management5.1 Overview of Operational Risk5.2 Identification and Assessment of Operational Risks5.3 Operational Risk Measurement and Control6. Interest Rate Risk Management6.1 Understanding Interest Rate Risk6.2 Measurement and Management of Interest Rate Risk6.3 Strategies for Interest Rate Risk Mitigation7. Foreign Exchange Risk Management7.1 Introduction to Foreign Exchange Risk7.2 Tools and Techniques for Foreign Exchange Risk Management7.3 Currency Hedging Strategies8. Enterprise Risk Management8.1 Overview of Enterprise Risk Management8.2 Framework for Implementing Enterprise Risk Management8.3 Integration of Different Risk Management Approaches9. Risk Management in Financial Institutions9.1 Risk Management in Banks9.2 Risk Management in Insurance Companies9.3 Risk Management in Investment Firms10. Regulatory and Legal Aspects of Financial Risk Management 10.1 Regulatory Environment for Risk Management10.2 Compliance and Legal Issues in Risk Management11. Case Studies in Financial Risk Management11.1 Real-life Risk Management Scenarios11.2 Analysis and Solutions for Risk Management Cases12. Emerging Trends and Challenges in Financial Risk Management12.1 Impact of Technology on Risk Management12.2 Future Challenges and OpportunitiesAppendix: Glossary of Financial Risk Management Terms BibliographyIndexNote: This textbook is intended for educational purposes and provides a comprehensive overview of various aspects of financial risk management. It covers key concepts, theories, and practical strategies to effectively manage and mitigate financial risks in different sectors. The case studies included further enhance the understanding and application of risk management principles.。
金融风险管理(双语)
中国海洋大学本科生课程大纲一、课程介绍1.课程描述（中英文）：随着金融一体化和经济全球化的发展，金融风险日趋复杂化和多样化，金融风险管理的重要性愈加突出。
由于金融风险对经济、金融乃至国家安全的消极影响，在国际上，许多大型企业、金融机构和组织、各国政府及金融监管部门都在积极寻求金融风险管理的技术和方法。
通过本课程的学习使学生掌握金融风险管理的基本方法、基础知识和基本原理，掌握识别金融风险、计量金融风险、化解金融风险，以及防范金融风险的基本理论和基本措施。
As the financial industry becomes increasingly competitive and concerned about managing risk, it is important to look at the robust financial risk management frameworks that satisfy compliance demands, contribute to better decision making, and enhance performance. This course provides a thorough introduction to sources of risk and describes the tools, techniques, systems, processes and strategies necessary for managing risks in banks and insurance companies. It also examines the critical importance of personal skills in implementing effective risk management and the need for commitment at all organizational levels.2.设计思路：本课程引导学生了解金融风险的产生机理，传递路径，评估技术以及控制方法，从而在投资决策中更好的管理风险。
金融市场的风险管理英文版
Lecture 2 - The Universal Principle of Risk Management: Pooling and the Hedging of RisksOverview:Statistics and mathematics underlie the theories of finance. Probability Theory and various distribution types are important to understanding finance. Risk management, for instance, depends on tools such as variance, standard deviation, correlation, and regression analysis. Financial analysis methods such as present values and valuing streams of payments are fundamental to understanding the time value of money and have been in practice for centuries.Reading assignment:Jeremy Siegel, Stocks for the Long Run, chapter 1 and Appendix 2, p. 12Financial Markets: Lecture 2 TranscriptJanuary 16, 2008Professor Robert Shiller: Today I want to spend--The title of today's lecture is: The Universal Principle of Risk Management, Pooling and the Hedging of Risk. What I'm really referring to is what I think is the very original, the deep concept that underlies theoretical finance--I wanted to get that first. It really is probability theory and the idea of spreading risk through risk pooling. So, this idea is an intellectual construct that appeared at a certain point in history and it has had an amazing number of applications and finance is one of these. Some of you--This incidentally will be a more technical of my lectures and it's a little bit unfortunate that it comes early in the semester. For those of you who have had a course in probability and statistics, there will be nothing new here. Well, nothing in terms of the math. The probability theory is new. Others though, I want to tell you that it doesn't--if you're shopping--I had a student come by yesterday and ask--he's a little rusty in his math skills--if he should take this course. I said, "Well if you can understand tomorrow's lecture--that's today's lecture--then you should have no problem."I want to start with the concept of probability. Do you know what a probability is? We attach a probability to an event. What is the probability that the stock market will go up this year? I would say--my personal probability is .45. That's because I'm a bear but--Do you know what that means? That 45 times out of 100 the stock market will go up and the other 55 times out of 100 it will stay the same or go down. That's a probability. Now, you're familiar with that concept, right? Ifsomeone says the probability is .55 or .45, well you know what that means. I want to emphasize that it hasn't always been that way and that probability is really a concept that arose in the 1600s. Before that, nobody ever said that.Ian Hacking, who wrote a history of probability theory, searched through world literature for any reference to a probability and could find none anywhere before 1600. There was an intellectual leap that occurred in the seventeenth century and it became very fashionable to talk in terms of probabilities. It spread throughout the world--the idea of quoting probabilities. But it was--It's funny that such a simple idea hadn't been used before. Hacking points out that the word probability--or probable--was already in the English language. In fact, Shakespeare used it, but what do you think it meant? He gives an example of a young woman, who was describing a man that she liked, and she said, I like him very much, I find him very probable. What do you think she means? Can someone answer that? Does anyone know Elizabethan English well enough to tell me? What is a probable young man? I'm asking for an answer. It sounds like people have no idea. Can anyone venture a guess? No one wants to venture a guess?Student: fertile?Professor Robert Shiller: That he can father children? I don't think that's what she meant but maybe. No, what apparently she meant is trustworthy. That's a very important quality in a person I suppose.So, if something is probable you mean that you can trust it and so probability means trustworthiness. You can see how they moved from that definition of probability to the current definition. But Ian Hacking, being a good historian, thought that someone must have had some concept of probability going before, even if they didn't quote it as a number the way--it must have been in their head or in their idea. He searched through world literature to try to find some use of the term that preceded the 1600s and he concluded that there were probably a number of people who had the idea, but they didn't publish it, and it never became part of the established literature partly because, he said, throughout human history, there has been a love of gambling and probability theory is extremely useful if you are a gambler. Hacking believes that there were many gambling theorists who invented probability theory at various times in history but never wrote it down and kept it as a secret.He gives an example--I like to--he gives an example from a book that--or it's a collection--I think, a collection of epic poems written in Sanskrit that goes back--it was actually written over a course of 1,000 years and it was completed in the fourth century. Well, there's a story--there's a long story in the Mahabarahta about an emperor called Nala and he had a wife named Damayanti and he was a very pure and very good person. There was an evil demon called Kali who hated Nala and wanted to bring his downfall, so he had to find a weakness of Nala. He found finally some, even though Nala was so pure and so perfect--he found one weakness and that was gambling. Nala couldn't resist the opportunity to gamble; so the evil demon seduced him into gambling aggressively. You know sometimes when you're losing and you redouble and you keep hoping to win back what you've lost? In a fit of gambling, Nala finally gambled his entire kingdom and lost--it's a terrible story--and Nala then had to leave the kingdom and his wife. They wandered foryears. He separated from her because of dire necessity.They were wandering in the forests and he was in despair, having lost everything. But then he meets someone by the name of--we have Nala and he meets this man, Rituparna, and this is where a probability theory apparently comes in. Rituparna tells Nala that he knows the science of gambling and he will teach it to Nala, but that it has to be done by whispering it in his ear because it's a deep and extreme secret. Nala is skeptical. How does Rituparna know how to gamble? So Rituparna tries to prove to him his abilities and he says, see that tree there, I can estimate how many leaves there are on that tree by counting leaves on one branch. Rituparna looked at one branch and estimated the number of leaves on the tree, but Nala was skeptical. He stayed up all night and counted every leaf on the tree and it came very close to what Rituparna said; so he--the next morning--believed Rituparna. Now this is interesting, Hacking says, because it shows that sampling theory was part of Nala's theory. You don't have to count all the leaves on the tree, you can take a sample and you count that and then you multiply.Anyway, the story ends and Nala goes back and is now armed with probability theory, we assume. He goes back and gambles again, but he has nothing left to wager except his wife; so he puts her and gambles her. But remember, now he knows what he's doing and so he really wasn't gambling his wife--he was really a very pure and honorable man. So he won back the entire kingdom and that's the ending.Anyway, that shows that I think probability theory does have a long history, but--it not being an intellectual discipline--it didn't really inform a generation of finance theory. When you don't have a theory, then you don't have a way to be rigorous. So, it was in the 1600s that probability theory started to get written down as a theory and many things then happened in that century that, I think, are precursors both to finance and insurance.One was in the 1600s when people started constructing life tables. What is a life table? It's a table showing the probability of dying at each age, for each age and sex. That's what you need to know if you're going to do life insurance. So, they started to do collecting of data on mortality and they developed something called actuarial science, which is estimating the probability of people living. That then became the basis for insurance. Actually, insurance goes back to ancient Rome in some form. In ancient Rome they had something called burial insurance. You could buy a policy that protected you against your family not having the money to bury you if you died. In ancient culture people worried a great deal about being properly buried, so that's an interesting concept. They were selling that in ancient Rome; but you might think, but why just for burial? Why don't you make it into full-blown life insurance? You kind of wonder why they didn't. I think maybe it's because they didn't have the concepts down. In Renaissance Italy they started writing insurance policies--I read one of the insurance policies, it's in the Journal of Risk and Insurance--and they translate a Renaissance insurance policy and it's very hard to understand what this policy was saying. I guess they didn't have our language, they didn't--they were intuitively halfway there but they couldn't express it, so I think the industry didn't get really started. I think it was the invention of probability theory that really started it and that's why I think theory is very important in finance.Some people date fire insurance with the fire of London in 1666. The whole city burned down, practically, in a terrible fire and fire insurance started to proliferate right after that in London. But you know, you kind of wonder if that's a good example for fire insurance because if the whole city burns down, then insurance companies would go bankrupt anyway, right? London insurance companies would because the whole concept of insurance is pooling of independent probabilities. Nonetheless, that was the beginning.We're also going to recognize, however, that insurance got a slow start because--I believe it is because--people could not understand the concept of probability. They didn't have the concept firmly in mind. There are lots of aspects to it. In order to understand probability, you have to take things as coming from a random event and people don't clearly have that in their mind from an intuitive standpoint. They have maybe a sense that I can influence events by willing or wishing and if I think that--if I have kind of a mystical side to me, then probabilities don't have a clear meaning. It has been shown that even today people seem to think that. They don't really take, at an intuitive level, probabilities as objective. For example, if you ask people how much they would be willing to bet on a coin toss, they will typically bet more if they can toss the coin or they will bet more if the coin hasn't been tossed yet. It could have been already tossed and concealed. Why would that be? It might be that there's just some intuitive sense that I can--I don't know--I have some magical forces in me and I can change things.The idea of probability theory is that no, you can't change things, there are all these objective laws of probability out there that guide everything. Most languages around the world have a different word for luck and risk--or luck and fortune. Luck seems to mean something about you: like I'm a lucky person. I don't know what that means--like God or the gods favor me and so I'm lucky or this is my lucky day. Probability theory is really a movement away from that. We then have a mathematically rigorous discipline.Now, I'm going to go through some of the terms of probability and--this will be review for many of you, but it will be something that we're going to use in the--So I'll use the symbol P or I can sometimes write it out as prob to represent a probability. It is always a number that lies between zero and one, or between 0% and 100%. "Percent" means divided by 100 in Latin, so 100% is one. If the probability is zero that means the event can't happen. If the probability is one, it means that it's certain to happen. If the probability is--Can everyone see this from over there? I can probably move this or can't I? Yes, I can. Now, can you now--you're the most disadvantaged person and you can see it, right? So that's the basic idea.One of the first principles of probability is the idea of independence. The idea is that probability measures the likelihood of some outcome. Let's say the outcome of an experiment, like tossing a coin. You might say the probability that you toss a coin and it comes up heads is a half, because it's equally likely to be heads and tails. Independent experiments are experiments that occur without relation to each other. If you toss a coin twice and the first experiment doesn't influence the second, we say they're independent and there's no relation between the two.One of the first principles of probability theory is called the multiplication rule. That says that ifyou have independent probabilities, then the probability of two events is equal to the product of their probabilities. So, the Prob(A and B) = Prob(A)*Prob(B). That wouldn't hold if they're not independent. The theory of insurance is that ideally an insurance company wants to insure independent events. Ideally, life insurance is insuring people--or fire insurance is insuring people--against independent events; so it's not the fire of London. It's the problem that sometimes people knock over an oil lamp in their home and they burn their own house down. It's not going to burn any other houses down since it's just completely independent of anything else. So, the probability that the whole city burns down is infinitesimally small, right? This will generalize to probability of A and B and C equals the probability of A times the probability of B times the probability of C and so on. If the probability is 1 in 1,000 that a house burns down and there are 1,000 houses, then the probability that they all burn down is 1/1000 to the 1000th power, which is virtually zero. So insurance companies then–Basically, if they write a lot of policies, then they have virtually no risk. That is the fundamental idea that may seem simple and obvious to you, but it certainly wasn't back when the idea first came up.Incidentally, we have a problem set, which I want you to start today and it will be due not in a week this time, because we have Martin Luther King Day coming up, but it will be due the Monday following that.If you follow through from the independent theory, there's one of the basic relations in probability theory--it's called the binomial distribution. I'm not going to spend a whole lot of time on this but it gives the probability of x successes in n trials or, in the case of insurance x, if you're insuring against an accident, then the probability that you'll get x accidents and n trials. The binomial distribution gives the probability as a function of x and it's given by the formula where P is theprobability of the accident: ()()()()!!1xnnppx fxnx--=-. That is the formula that insurancecompanies use when they have independent probabilities, to estimate the likelihood of having a certain number of accidents. They're concerned with having too many accidents, which might exhaust their reserves. An insurance company has reserves and it has enough reserves to cover them for a certain number of accidents. It uses the binomial distribution to calculate the probability of getting any specific number of accidents. So, that is the binomial distribution. I'm not going to expand on this because I can't get into--This is not a course in probability theory but I'm hopeful that you can see the formula and you can apply it. Any questions? Is this clear enough? Can you read my handwriting?Another important concept in probability theory that we will use a lot is expected value, the mean, or average--those are all roughly interchangeable concepts. We have expected value, mean or average. We can define it in a couple of different ways depending on whether we're talking about sample mean or population mean. The basic definition--the expected value of some random variable x--E(x)--I guess I should have said that a random variable is a quantity that takes on value. If you have an experiment and the outcome of the experiment is a number, then a random variable is the number that comes from the experiment. For example, the experiment could be tossing a coin; I will call the outcome heads the number one, and I'll call the outcome tails the number zero,so I've just defined a random variable. You have discrete random variables, like the one I just defined, or there are also--which take on only a finite number of values--and we have continuous random variables that can take on any number of values along a continuum. Another experiment would be to mix two chemicals together and put a thermometer in and measure the temperature. That's another invention of the 1600s, by the way--the thermometer. And they learned that concept--perfectly natural to us--temperature. But it was a new idea in the 1600s. So anyway, that's continuous, right? When you mix two chemicals together, it could be any number, there's an infinite number of possible numbers and that would be continuous.For discrete random variables, we can define the expected value, or µx --that's the Greek letter mu--as the summation i = 1 to infinity of. [P(x=xi) times (xi)]. I have it down that there might be an infinite number of possible values for the random variable x. In the case of the coin toss, there are only two, but I'm saying in general there could be an infinite number. But they're accountable and we can list all possible values when they're discrete and form a probability weighted average of the outcomes. That's called the expected value. People also call that the mean or the average. But, note that this is based on theory. These are probabilities. In order to compute using this formula you have to know the true probabilities. There's another formula that applies for a continuous random variables and it's the same idea except that--I'll also call it µx, except that it's an integral. We have the integral from minus infinity to plus infinity of F(x)*x*dx, and that's really--you see it's the same thing because an integral is analogous to a summation.Those are the two population definitions. F(x) is the continuous probability distribution for x. That's different when you have continuous values--you don't have P (x = xi) because it's always zero. The probability that the temperature is exactly 100° is zero because it could be 100.0001° or something else and there's an infinite number of possibilities. We have instead what's called a probability density when we have continuous random variables. You're not going to need to know a lot about this for this course, but this is--I wanted to get the basic ideas down. These are called population measures because they refer to the whole population of possible outcomes and they measure the probabilities. It's the truth, but there are also sample means. When you get--this is Rituparna, counting the leaves on a tree--you can estimate, from a sample, the population expected values. The population mean is often written "x-bar." If you have a sample with n observations, it's the summation i = 1 to n of xi/n--that's the average. You know that formula, right? You count n leaves--you count the number of leaves. You have n branches on the tree and you count the number of leaves and sum them up. One would be--I'm having a little trouble putting this into the Rituparna story, but you see the idea. You know the average, I assume. That's the most elementary concept and you could use it to estimate either a discreet or continuous expected value.In finance, there's often reference to another kind of average, which I want to refer you to and which, in the Jeremy Siegel book, a lot is made of this. The other kind of average is called the geometric average. We'll call that--I'll only show the sample version of it G(x) = the product i = 1 to n of (xi )^(1/n). Does everyone--Can you see that? Instead of summing them and dividing by M, I multiply them all together and take the nth root of them. This is called the geometric average and it's used only for positive numbers. So, if you have any negative numbers you'd have a problem, right? If you had one negative number in it, then the product would be a negative number and, ifyou took a root of that, then you might get an imaginary number. We don't want to use it in that case.There's an appendix to one of the chapters in Jeremy Siegel's book where he says that one of the most important applications of this theory is to measure how successful an investor is. Suppose someone is managing money. Have they done well? If so, you would say, "Well, they've been investing money over a number of different years. Let's take the average over all the different years." Suppose someone has been investing money for n years and xi is the return on the investment in a given year. What is their average performance? The natural thing to do would be to average them up, right? But Jeremy says that maybe that's not a very good thing to do. What he says you should do instead is to take the geometric average of gross returns. The return on an investment is how much you made from the investment as a percent of the money invested. The gross return is the return plus one. The worst you can ever do investing is lose all of your investment--lose 100%. If we add one to the return, then you've got a number that's never negative and we can then use geometric returns.Jeremy Siegel says that in finance we should be using geometric and not arithmetic averages. Why is that? Well I'll tell you in very simple terms, I think. Suppose someone is investing your money and he announces, I have had very good returns. I have invested and I've produced 20% a year for nine out of the last ten years. You think that's great, but what about the last year. The guy says, "Oh I lost 100% in that year." You might say, "Alright, that's good." I would add up 20% a year for nine years and than put in a zero–no, 120 because it's gross return for nine years--and put in a zero for one year. Maybe that doesn't look bad, right? But think about it, if you were investing your money with someone like that, what did you end up with? You ended up with nothing. If they have one year when they lose everything, it doesn't matter how much they made in the other years. Jeremy says in the text that the geometric return is always lower than the arithmetic return unless all the numbers are the same. It's a less optimistic version. So, we should use that, but people in finance resist using that because it's a lower number and when you're advertising your return you want to make it look as big as possible.We also need some measure of--We've been talking here about measures of central tendency only and in finance we need, as well, measures of dispersion, which is how much something varies. Central tendency is a measure of the center of a probability distribution of the--Central tendency is a measure--Variance is a measure of how much things change from one observation to another. We have variance and it's often represented by σ², that's the Greek letter sigma, lower case, squared. Or, especially when talking about estimates of the variance, we sometimes say S² or we say standard deviation². The standard deviation is the square root of the variance. For population variance, the variance of some random variable x is defined as the summation i = 1 to infinity of the Prob (x = xi) times (xi - µx)2. So mu is the mean--we just defined it of x--that's the expectation of x or also E(x), so it's the probability weighted average of the squared deviations from the mean. If it moves a lot--either way from the mean--then this number squared is a big number. The more x moves, the bigger the variance is.There's also another variance measure, which we use in the sample--or also Var is usedsometimes--and this is ∑². There's also another variance measure, which is for the sample. When we have n observations it's just the summation i = 1 to n of (x - x bar)²/n. That is the sample variance. Some people will divide by n–1. I suppose I would accept either answer. I'm just keeping it simple here. They divide by n-1 to make it an unbiased estimator of the population variance; but I'm just going to show it in a simple way here. So you see what it is--it's a measure of how much x deviates from the mean; but it's squared. It weights big deviations a lot because the square of a big number is really big. So, that's the variance.So, that completes central tendency and dispersion. We're going to be talking about these in finance in regards to returns because--generally the idea here is that we want high returns. We want a high expected value of returns, but we don't like variance. Expected value is good and variance is bad because that's risk; that's uncertainty. That's what this whole theory is about: how to get a lot of expected return without getting a lot of risk.Another concept that's very basic here is covariance. Covariance is a measure of how much two variables move together. Covariance is--we'll call it--now we have two random variables, so I'll just talk about it in a sample term. It's the summation i = 1 to n of [(x – x-bar) times (y – y-bar)]/n. So x is the deviation for the i-subscript, meaning we have a separate xi and yi for each observation. So we're talking about an experiment when you generate--Each experiment generates both an x and a y observation and we know when x is high, y also tends to be high, or whether it's the other way around. If they tend to move together, when x is high and y is high together at the same time, then the covariance will tend to be a positive number. If when x is low, y also tends to be low, then this will be negative number and so will this, so their product is positive. A positive covariance means that the two move together. A negative covariance means that they tend to move opposite each other. If x is high relative to x-bar--this is positive--then y tends to be low relative to its mean y-bar and this is negative. So the product would be negative. If you get a lot of negative products, that makes the covariance negative.Then I want to move to correlation. So this is a measure--it's a scaled covariance. We tend to use the Greek letter rho. If you were to use Excel, it would be correl or sometimes I say corr. That's the correlation. This number always lies between -1 and +1. It is defined as rho= [cov(xiyi)/SxSy] That's the correlation coefficient. That has kind of almost entered the English language in the sense that you'll see it quoted occasionally in newspapers. I don't know how much you're used to it--Where would you see that? They would say there is a low correlation between SAT scores and grade point averages in college, or maybe it's a high correlation. Does anyone know what it is? But you could estimate the corr--it's probably positive. I bet it's way below one, but it has some correlation, so maybe it's .3. That would mean that people who have high SAT scores tend to get higher grades. If it were negative--it's very unlikely that it's negative--it couldn't be negative. It couldn't be that people who have high SAT scores tend to do poorly in college. If you quantify how much they relate, then you could look at the correlation.I want to move to regression. This is another concept that is very basic to statistics, but it has particular use in finance, so I'll give you a financial example. The concept of regression goes back to the mathematician Gauss, who talked about fitting a line through a scatter of points. Let's draw a line through a scatter of points here. I want to put down on this axis the return on the stock。
Financial Risk Management C1&2
1. Financial Risk1.1IntroductionFinancial risk management has been a part of financial management for a long time and it was believed that (financial) risks were manageable.In financial accounting, it often seems that the amounts that the accountants work with are certainties. However, they are not. Reported revenues, costs and income do not equal the cash flows a company generates. Accounting data reflect the past, while investors are looking forward. Investors are interested in future performance and return on their investment. And in regard with the future, companies and private investors - and as we now know also governments and ultimately the taxpayers – are exposed to financial risk. In this course – Financial Instruments and Derivatives and Financial Risk Management – we will elaborate on the several types of financial risk and the instruments used to – as far as possible – manage it .Since you started your studies, in the passed few years you have seen risk at work:∙Homes and real estate market crisis, hand in hand with∙Collapse of the market of mortgage based investment vehicles and derivatives, leading to∙Stock market crisis∙Credit crisis∙Economic crisis∙Sovereign debt crisis∙Currency market volatility∙Pension crisisThis is on a macroeconomic scale. On a microeconomic scale it meant the disappearance (by bankruptcy or take-overs) or nationalization of banks and other financial institutions. Three of the five major American investment banks disappeared (Lehman Bros bankrupt, Merill Lynch taken over by Bank of America, Bears Stearns taken over by JP Morgan Chase) with Morgan Stanley and Goldman Sachs remaining.What started as a panic in the American subprime mortgage market has spread over the global financial system.When bundling and securitizing “sub-prime” (= high risk) mortgages in“collateralized debt obligations” and selling those to investors who againrestructure and resell them or borrow against these “assets”, only the highreturn but not the high risk was considered. By securitizing and spreading(“portfolio diversification”) and insuring these mortgages, in theory the risk is spread and diminished. In less than ten years the market for these structuredfinance investment products became a multi trillion dollar market – before itcollapsed two years ago.This time in the real world theory did not hold. When defaults on mortgagepayments started to rise, investors discovered that the risk had becomeuntraceable, so not measurable and as a consequence almost untradeable. This brought part of the interbank money market and credit market to a halt. Quite suddenly there was (and to a lesser extent in 2010 still is) is a credit crunch even though there is money in abundance. Central banks pump money in thefinancial system by the billions by buying debt paper and interest rates are close to zero. A number of banks and investment funds still are on the brink ofbankruptcy and are kept afloat by capital injections (from governments andstate-funds from oil exporting countries and the Far East, mainly China) or even nationalization.Recent history is filled with cases where financial risk has led to calamities. Some because of outright fraud, some caused by not understanding the risk involved in instruments used:∙US Savings & Loans Banks (1980s, junk bonds, $ multiple billions)∙Volkswagen (1986, trading fraud with dollar options, DEM 0,5 bn)∙BCCI (1991, fraud, over $ 5 bn )∙Bank of England (1992, speculation against GBP after entering ERM, £ 3,4 bn, of which $ 1bn to George Soros alone)∙Metallgesellschaft (1993, trading fraud energy futures, $ 1,4 bn)∙Kashima Oil (1994, foreign exchange forwards, $1,5 bn)∙Orange County, Cal. (1994, reverse RPs and structured notes, $ 1,6 bn)∙Daiwa Bank (1995, bonds, 1,1 bn)∙Barings Bank (1995, fraud with stock index futures, $ 1,4 bn)∙Sumitomo (1996, effort to corner copper market with futures, $ 1,8 bn)∙Enron (2001, accounting fraud, tens of bn $)∙Worldcom (2003, accounting fraud, $ 11 bn)∙Ahold (2003, accounting fraud, overstating profits by $ 800 mln)∙Societe General (2008, trading fraud € 4,9 bn)∙Bernard Madoff’s investment funds (2009, Ponzi scheme, up to $ 50 bn)∙AIG (2008, credit default swaps, $ 400(?) bn)∙The global financial system (2008-2009, structured instruments/CDOs, IMF-estimate of losses over $ 2 tln)It is clear from all these examples that badly managed financial risk can easily lead to financial disaster. However, risk taking also offers opportunities, it may increase returns on investment, it lies at the heart of entrepreneurship and as such contributes to economic growth.And where mega-losses make the headlines, on the other side of the deal are winners. The billions Nick Leeson (Barings Bank) and Jerome Kerviel (Societe General) lost, are profits for their counterparties in the trades.Moreover, the derivatives markets that we will be discussing are places where risk is traded. Risk taking is a way of making money. Risk averse companies transfer their risk to risk-takers, “speculators” and pay a price. This doesn’t mean this is a sure bet for the speculator, he may end up making or loosing a lot of money. Jobs as market maker, futures or option trader are very popular with young people. Trading becomes a game, “b eating the market” often gets addictive.Uncertainty about the weather in France when your holiday is in Austria is not risk in this sense, since being in Austria you are not exposed to rain in France. Also, jumping from a plane at 10.000 feet without a parachute is not risky at all.Uncertainty is measured using mathematical/statistical techniques. Since the 1990s a much used risk measure is VAR: Value at Risk. Simply stated as the question: What is the most a company - with a say 95% level of confidence - can expect to lose in dollars over the next day or week or month? More on VAR later.However, probability distributions used are perceived distributions, they may be not (fully) correct. And empirically determined probabilities are based on historical data, while it is the future that we should worry about.This course will be aimed at-understanding financial risks and your (company’s) attitude towards risk taking (risk averse or risk preference)-knowledge of financial instruments and derivatives and how to use them-arbitrage relations between underlying instruments and their derivatives and pricing.Risk taking by itself is not a bad thing, only one has to be beware of the risk, understand it and measure it:-risk needs to be recognized, identified-once recognized, the risk has to be qualified-and – as far as possible – it must be measured with numbers, financial or non-financial; the risk has to be quantified.-This syllabus is only a short summary and doesn’t cover all there is in the field. More reading and practising have to be done by the student him- or herself. In the library meters of books on financial risk management and financial derivatives are available. And for the modern student the internet is an inexhaustible source, to start with the exchanges where financial derivatives are traded.During this course, for every subject there are some assignments, mostly to be worked out in a spreadsheet.1.2Risk qualificationModern companies, enterprises, whether in manufacturing or service, exist bythe virtue of risk taking. Just taking your market for granted may work for adairy or wheat farmer, but most companies have to innovate constantly toremain in business. Introducing and marketing new products meansuncertainty about profitability. This is entrepreneurial risk and is outside thescope of this course. Here we concentrate on financial risk.There are, broadly, four different types of financial risk that companies haveto manage:∙Market risk: the possible values of an asset or liability at some point in the future (and the probabilities of these values occurring). We willelaborate on interest rate risk (the risk of falling income flows fromfalling rates and rising costs from rising rates), price or value risk (causedby changes in market interest rates that result in price or value changes offinancial instruments and their derivatives) and further discuss stockmarket and foreign currency exchange rate risk; ∙Liquidity risk: over what period of time and at what price can a position be closed;∙Counterparty risk or credit risk: the probability of default of the counterparty to a deal and, in the event of default, the likelyrecovery rate;∙Operational risk: losses through fraud, malfeasance or operational error.1.3Financial Leverage and RiskA first step is studying the balance sheet to see where the value risk of acompany comes from.As you of course know, o n a company’s balance sheetthe asset side shows the capital that creates an income flowthe liability side shows the financial structure by which the asset side isfinanced and the degree of financial leverage:Plant & EquipmentCommon stock 15Retained earnings /reserves 75The composition of the liability-side is called the financial (or capital)structure of a company: how much debt of one type or other and how much owner’s equity is used for the financing.The more debt compared to owners equity, the higher the financial leverage or financial gearing of the company:As long as the return on the total investment in assets (=the balance sheet total, in short return on assets or ROA) exceeds the cost of borrowing, higherleverage leads to a higher return on equity (ROE). Compare two identicalcompanies, with the only difference their financial structure (for simplicity no depreciation and no taxes):EBIT100 EBIT 100 interest 15interest 35 profit 85profit65ROA = 10%ROA = 10% ROE = 12%ROE = 22%If EBIT rises by 20%, the ROE of company A rises by 24%, the ROE of company B is leveraged more and rises by 31% (check yourself!).As has been taught for decades and is experienced now: leverage works in the other direction just as well . Highly leveraged or geared companies or investments are very sensitive to falling earnings and rising interest rates. Earnings can be leveraged, but risk is leveraged too:if EBIT plummets by 50%, the ROE of A falls by 60%, that of B by 77%(check!). Then, if interest rates also go up by 3%, look what happens then:equity 700 equity 300 EBIT 50 EBIT 50interest 24 interest 56profit 26 profit − 6ROA = 5,0% down 50% ROA = 5,0% down 50%ROE = 3,7% down 69% ROE = − 2,0% down 109%Company A can, company B cannot service its debt from the cash flow from assets. As can be seen, in bad times as well as good times the financial risk is leveraged.1.4 A special case: risk of traditional bankingLet’s look at a bank’s balance sheet. There is a mismatch between the funding (mainly short term: personal or salary accounts, short term saving accounts, money market borrowings) and the lending (mainly long term: mortgage loans, loans to companies):Balance sheet of B-Bank in mln €This mismatch is the source of income of traditional banking: in a normal yield curve (to be discussed later) environment (long term rates higher than short term rates) the bank earns the interest rate spread between funding cheaper short term rate and lending at higher long term rate.Suppose B-Bank borrows short term @ 2% and long term @ 4% while it lends short term @ 4% and long term @ 6% and its operational cost is € 400m. The income statement then is (check!):Interest received 1.100Interest paid 440Interest margin 660operational expenses 400profit 260ROE 17%However, this is a double cutting knife causing an interest rate risk and a price risk: an interest rate rise leads to∙the cost of (short term) funding to rise,∙the (present) value of outstanding (long term) loans to falls (and vice versa of course)To see the effect, now suppose rates rise by 2% across the board and B-Bank maintains its interest rate spreads. The income statement becomes (when checking, mind that long term rates are fixed!):Interest received 1.200Interest paid 740Interest margin 460operational expenses 400depreciation of assets and liabilities 913profit ― 853ROE ―145%The drop in the interest margin is obvious (if you did your calculation right), but where does the depreciation cost come from?This will be explained in the next chapter, you must accept for now that the rise in interest rates of 2% causes the long term loans and debt to decrease by about 8% in value. IFRS and US GAAP require companies to revalue there assets and liabilities accordingly.As you can imaging, this can be even more painful in the case that the yield curve turns from normal to inverted with short term interest rates rising over long term interest rates.Not only banks, but also non-bank companies usually run such a maturity mismatch risk.This form of interest rate risk can be determined by∙Simulation: given interest rate sensitive positions and expected liquidity flows, a computer program calculates the effect of interest rate changes∙Gap Analysis: netting asset and liabilities within the same maturity-intervals, producing the net exposure in these maturity-intervals.∙Duration analysis: calculate the duration of all items on the balance sheet, giving the overall duration. Duration is the weighted remaining time to maturity of a cash flow, a good approximation of the basis point value of financial instruments. It can be weighted, summed and netted, though at the cost of some precision. The concept of duration is explained later.Back to the balance sheet: there are two more risks that have recently lead to a credit crunch:∙on the left hand side of the balance sheet banks have increasingly added structured finance products with supposedly higher returns than plain vanilla mortgage and corporate loans. The value of these instruments has dropped like a stone∙on the right hand side − because the drop in the value of the bank’s assets − the short term loans that finance the investments cannot be rolled over (= renewed)To add another list to make the picture complete: bankers usually distinguish between six basic risk categories:o Credit risk: counterpart exposureo Market risk: change in price/value of financial instruments. This not only depends on economic factors, but also on the depth (or liquidity) of the market. With a lack of demand it is hard to sell without lowering the offer price.o Interest rate risk: earnings and returns fluctuate with change in interest rateso Liquidity risk: sufficient cash available to meet financial commitments?Liquidity shortfall in one single institution can have system widerepercussions (as has been obvious since 2008)o Operational risk: information, communication, transaction processing, settlement, procedures, fraudo Cross-border risk or country risk: partly operational, partly price risk, in particular foreign exchange riskIn this course we will not elaborate on credit risk management, which briefly summarized involves:o Screening before loan is giveno Monitoring during loan periodo Long term customer relationshipo Loan commitment by banko Collateral, compensating balanceso Credit rationingo In case of moratorium or default: what is the relative bargaining position, access to and availability and value of collateral, seniority of debt,secured or not? Multiple creditors?Liquidity risk management:Until halfway 2007 liquidity risk seemed to be well in control. For banks central banks handle strict liquidity standards and the interbank money market made liquidity readily available. Until securitized structured finance instruments (consisting of portfolios of subprime mortgage loans, car loans, credit card loans, student loans, etc) were discovered to be very risky rather than very profitable. Not only these securities themselves, but also the holders (banks) became high risk for their counterparts and were locked out of the interbank credit market so by the end of the summer or 2008 this market had all but stopped functioning and after the fall of investment bank Lehman totally evaporated. Central banks provided 10s of billions of $ and € to keep credit available, but this was mainly used to strengthen the asset side of balances at no risk, so investing in riskless instruments like US T-bills. Thespread between interbank deposit rates and T-bill rates (referred to as the TED-spread) which in normal circumstances is below 50 basispoints, widened to 450 bpts, fell back to 250 after European and the US governments started guaranteeing interbank credits and has been back to “normal” from 2009. Since last year the world economy suffers from a sovereign debt crisis (the PIIGS in Euroland) and central banks still keep pumping liquidity in the banking system.Operational risk is the field of administrative organization and controlling.Probably there always will be new Nick Leesons and Jerome Kerviels. Even if risk managers give warnings, chief traders up to CEOs do not want to finish the goose that seems to be laying golden eggs. Until it’s too late.Probably a lot of fraud that is discovered is never publicised.Interest rate risk, price risk and foreign exchange risk are dealt with throughout the syllabus.2. Quantifying financial risk2.1Value: Discounting of cash flows and present valueBack to the basics. The Anglo-American or Anglo-Saxon paradigm we have lived by the last half century is that a corporation’s goal is to create shareholders value. The value of a company, so the value of the shares of a company, depends on:∙the (market) value of its assets and its debt, but mostly on∙the expected future income flows, or rather cash flows the company generates, and∙the cost of capitalThe asset value is only of real importance in the case of liquidation of (part of) a company. Private equity funds have the habit of buying companies and then after reorganization and cost cutting to split them up and sell the parts. Sometimes the real estate of a company (the office buildings for instance) has a higher current market value than the present value of the estimated future cash flows. In this case, shareholders value is increased by closing the company. Needless to say that other stakeholders, to start with the employees, will not agree and fight to keep ´their´ company open.In our analysis we will follow the main stream paradigm that in the end investors only invest when they can expect a decent return on investment. Thus the value of a company is the present value of the expected free cash flows it generates, where the discount rate is a weighted average of the market cost of equity and debt capital.Corporations´ shares are bought and sold in stock markets based on the expected return for shareholders.The cash flow of a company are the euros or dollars flowing into the company as a result of its operation: i.e. producing and selling cars, restaurant mealsor accounting services.Traditionally, a company’s cash flow is defined as the after tax profit plus depreciation. But a growing company automatically needs more working capital (growth induced investment in inventories and accounts receivable minus accounts payable) and fixed capital (autonomous investment). The financing of this investment will (partly) come from the company’s cash flow. What is left of the cash flow after these investments is called the company’s free cash flow from assets. It is distributed betweenthe holders of debt (cash flow to creditors) and the owners or shareholders of the company (cash flow to stockholders).Shareholders may decide to have this cash to be paid out or to reinvest (part of) their earnings in the company (= retained earnings, expectedly leading to higher future cash flows).The value of a security is the present value of the expected future cash flows from that security, discounted at the appropriate market rate of return for comparable securities.Why present value instead of just value?The answer is to be found in time preference and risk aversion of investors: the value of a sum of money credited to your bank account today is greater than the value of the same sum credited to your bank account in a year’s time. Postponed spending asks for a reward: interest.Put € 1000 in a savings account at a rate of 4% per year now and have € 1040 = 1000 x (1+0,04) in your account after one year.So the present value of € 1040 to be received (or paid) next year is € 1000 = 1040 / (1 + 0,04)Again put € 1000 in a saving s account at a rate of 4% per year, now for three years, add the interest received to the principal each year and have€ 1124,86 = 1000 x (1+0,04)3 in your account after three years.So the present value of € 1124,86 to be received or paid after three years is € 1000 = 1124,86 / (1+0,04)3Question: how much is the value of € 1000 to be received 3 years from now when the relevant interest rate is 4%?Example of the value of a simple cash flow:An ordinary bullet bond has the following basic features:- a principal amount,- a term- a couponlike $1000 principal, 15 years till maturity, 5% coupon. “Bullet” means the redemption takes place in full at the maturity date of the bond. The yearly cash flow from the bond is the yearly interest income of $50, + at maturity $1000.The value of a bond at any moment depends on the going market interest rate: it is the present value at the current market interest rate of the coupon income flow during the remaining time to maturity plus the redemption of the principal amount at maturity.If this bond was issued (just over) 11 years ago – so 4 more years to go till redemption – and the market interest rate for this maturity presently is 6%, the value of this bond would be $ 965,35 (check!).2.2Financial risk measurement: basis point valueFor long term fixed income instruments like bonds, the price risk of an interest rate change increases with∙the remaining time to maturity∙the coupon rate compared to the market rateExampleCompare the effect of an interest rate rise from 4,0% to 4,1% for two bonds A and B with both a face value of €1000 and a coupon of 5%, only bond A h as 4 years till maturity and B 12 yearsExampleCompare the effect of an interest rate rise from 6,0% to 6,1% for two bonds C and D with both a face value of € 1000 and 7 years till maturity, only C has a coupon of 3% and D of 12%In both of the examples above, the values of the bonds change (by different amounts) because of an interest rate rise of 0,1% or 10 basis points.The change in value caused by a one basis point ( = 1/100 of 1%)interest change is called the basis point value of a bond (or any other interest sensitive instrument). It is a much used measure for the price or value risk of interest rate changes.The basis point values (bpvs) of the bonds with face value € 1000 in the examples above are A: € 0,371 , B: € 0,987 , C: € 0,497 and D: € 0,675.This doesn’t seem a lot, but the bpv of a position of € 1 bn in bond B (not overly much for a pension fund) is almost € 1 mln. If rates rise by 0,5%, this would mean a value drop of € 50 mln.2.3Financial risk measurement: DurationFor bonds, an interest rate rise is on the one hand value-eroding, on the other hand the interest payments can then be reinvested at a higher rate, partly compensating for the loss of the value of the bond. Bond investors (and traders and dealers) look at the duration as “... the magic moment in a bond’s life at which the return to investors would be about the same no matter whether interest rates had risen or fallen.” (as quoted from the Wall Street Journal). Roughly speaking this is a bonds remaining economic lifetime, or more cryptically, the value weighted time the bond (still) generates cash flows. The nearer the bond’s maturity, the shorter (or smaller) its durationDuration is widely used by bond traders and investors as a measure of the price risk, so linked with the bond’s basispoint value.Duration is calculated as the weighted remaining time to maturity of a cash flow, with the weights being the present value of each period as share of the total present value.The duration D of a cash flow cf1 in year 1 to cf T to year T isD = w1x 1 + … + w T x TWhere w t = cf t / (1+i) t∑ (cf t / (1+i)t)and i is the interest rate used for discounting the cash flows.For bonds, beside quotations of price, current yield, yield to maturity often the duration is given. It appears that the duration of a bond (= a series of cash flows) is a good approximation of the rate sensitivity of the value of this bond (or for that matter of anything else that generates cash flows), so of the basis point value of the bond.A better measure of a bond’s price sensitivity is the modified duration:D mod = D / (1+i)Although the modified duration practically equals the basis point value, because of different bonds having different discount rates to arrive at their (present) value, the D mod of different bonds may not be added just like that to arrive at a portfolio’s p rice sensitivity. Choosing between the use of the duration or the modified duration is a choice between ease and precision.Matching the durations of the asset and liability side of a balance sheet –be it a company’s or an investor’s – is a way of eliminating the market interest rate risk.ExampleLet’s again take bonds A and B with both a face value of €1000 and a coupon of 5%, bond A having 4 years till maturity and B 12 years while the market rate for both is 4%. First the duration and modified duration are calculated and from that the basis point value.Compare the basispoint values found with those found in paragraph 2.2As for the B-Bank-example in given 1.4. The short term investment and funding have a duration of (near to) 0 so they do not (hardly) react to the rate rise. The € 15.000 of 5 yr investment on the asset side has a duration of 4,0 and the € 3500 5 yr loan on the liability side 4,1 (check!). With rates rising by 2%, the value of the investment falls by 8% (4,0*2%) or € 1200 and the value of the debt by 8,2% = € 287, a net loss of € 913 so the equity falls to € 587.2.4Market risk measurement: Value at RiskValue at Risk(VAR) is an estimation of the maximum loss on a portfolio over a given time interval at a given probability based on historical price series.“The daily VAR of a of trading portfolio is € 100 mln at a 99% confidence level” means: there is a 1% chance that (under normal market conditions) at any day the loss will exceed € 100 mln.VAR is very dependent on assumptions about the distribution of price changes (is it normal? Is it stable over time? Is there a correlation between price changes? How long should the period taken be?).The easiest VAR calculations are based on a normal distribution of daily or weekly returns (= %-price changes).If the price of an instrument changes from 90 to 95, the %-change is +5,6%. If the price then falls to 92, the %-change is ―3,2%.The normal distribution is defined by the mean µ and the standard deviation σ. Graphically you know it as the “bell curve” (Graph courtesy Wikipedia):You should remember some properties:∙The distribution is symmetric, with about∙68% of the values drawn from a normal distribution are les then one standard deviation (σ) away from the mean (µ)∙95% of the values drawn are less then 2 times σ away from µ∙99,7% of the values drawn are less then 3 times σ away from µThis is known as the 3-sigma rule or 68-95-99,7 rule.From a statistical point of view heads or tails (when throwing a coin) are equally risky: 50% probability each. But from a financial point of view, if head is up € 1mln and tail down € 1 mln, we see throwing tails as the risk and concentrate on managing that.Value at Risk calculations only look at the loss side of the distribution. So: ∙84% (50%, the right hand side of the curve +0,5%*68% on the left hand side of the curve) of the values drawn from a normal distribution are less then 1 times σ below µ∙97,5% of the values are less then 2 times σ below µ∙99,85% of the values are less then 3 times σ below µ(and of course you can calculate anything in-between if you use the formula of the normal distribution, as is possible in exel).Example:Over the past 10 years the average weekly return of a € 100 mln portfolio was +0,1% and the standard deviation was 0,5%. A normal distribution is assumed.The VAR at a 84% confidence level then is slightly over € 0,4 mln(€100m*(0,1%-0,5%) or stated otherwise, the expected value of the portfolio next week is € 100,1 mln, but there is a 16% probability the value will fall to or below € 99,6 mln (€ 100m-0,4m or €100,1m*(1-0,5%)).。
企业风险管理(中英文)
• At each payment date, only the net value of cash flows is exchanged 只在每个交割日交易净现金流
• The cash flows are based on a notional principal or notional amount 现金流基于名义本金交易量进行计算
– Gibson Greetings – Barings Bank 巴林银行 – Orange County, California 橙县，加州
• Model failure 金融模型失败
– Long Term Capital Management 长期资本管理
• Accounting improprieties 不适当做账
不恰当地管理金融衍生物
• Financial model failures 金融模型失败 • Improper accounting for derivatives
对于衍生物的不适当的会计记账手段
Mismanagement of Financial Risk
金融风险的不妥当管理 • Mismanagement of derivatives 衍生物的不善管理
最初致力于避免衍生工具带来的灾难
– Developing into optimizing firm value
发展到最优化公司价值
• Chief Risk Officer 设立首席风险执行官 • Sarbanes-Oxley Act in the U. S. – 2002 SOX法案 • Increased focus on risk models
出售者有义务应购买者要求履行期权合约
金融市场的风险管理(英文版)剖析
可编辑修改精选全文完整版金融市场的风险管理(英文版)Risk Management in Financial MarketsIntroductionRisk management is a crucial aspect of the financial markets. It involves the identification, assessment, and mitigation of potential risks that may impact an organization's financial well-being. The dynamic nature of financial markets makes effective risk management imperative to ensure stability and sustainability. This article aims to explore the various aspects of risk management in financial markets.Types of RisksFinancial markets face various types of risks, each with its unique characteristics. The most common types of risks in financial markets include credit risk, market risk, liquidity risk, operational risk, and systemic risk.Credit risk refers to the potential loss arising from a borrower's inability to repay a loan or meet its contractual obligations. Financial institutions employ credit risk management techniques, such as credit scoring models and credit derivatives, to assess and mitigate this risk.Market risk encompasses the potential loss due to fluctuating market prices of financial instruments. It includes risks associated with interest rates, currencies, equities, commodities, and derivatives. Market risk management involves using techniqueslike portfolio diversification, hedging, and stress testing to mitigate potential losses.Liquidity risk arises when an institution is unable to fulfill its financial obligations due to an insufficient availability of liquid assets. Effective liquidity risk management involves maintaining adequate liquidity buffers, developing contingency funding plans, and regularly monitoring and stress testing liquidity positions.Operational risk involves the risk of financial loss due to inadequate or failed internal processes, systems, or human error. It includes risks associated with technology failures, fraud, legal and regulatory compliance, and vendor management. Operational risk management involves implementing robust internal controls, conducting regular audits, and training staff on risk awareness.Systemic risk refers to the risk of widespread disruptions or failures in the financial system that could have a significant impact on the overall economy. It can arise from interconnectedness and interdependencies among financial institutions, such as in the case of a financial crisis. Systemic risk management involves regulatory oversight, stress testing, and contingency planning at both the institutional and systemic levels.Risk Assessment and MitigationEffective risk management starts with a thorough and comprehensive risk assessment. This involves identifying and analyzing risks, including their potential impacts and likelihoods of occurrence. Risk assessment enables organizations to prioritize risks and allocate resources accordingly.Once risks are identified, appropriate risk mitigation strategies can be implemented. These strategies may include risk avoidance, risk reduction, risk transfer, or risk acceptance. Risk avoidance involves refraining from activities that pose significant risks. Risk reduction involves implementing measures to minimize the likelihood or impact of risks. Risk transfer involves transferring risks to another party, such as through insurance or hedging. Risk acceptance involves acknowledging and accepting certain risks if their potential impact is deemed acceptable.Risk management frameworks and tools can also assist in the overall risk management process. These frameworks provide a structured approach to managing risks and can help organizations establish appropriate risk management policies, procedures, and controls. Examples of risk management tools include risk registers, risk appetite statements, risk and control self-assessment, and key risk indicators.Continual Monitoring and ReviewRisk management is an ongoing process that requires continuous monitoring and review. Financial institutions need to establish effective risk monitoring systems to detect and assess emerging risks promptly. Regular risk reporting and analysis help organizations stay informed about their risk profiles and take necessary actions.Risk management frameworks should also be periodically reviewed and updated to ensure their effectiveness in addressing evolving risks. As technology advances and market conditionschange, risk management practices need to keep pace to effectively manage emerging risks.ConclusionRisk management is a critical component of the financial markets. The proper identification, assessment, and mitigation of risks are essential for maintaining stability and sustainability. By implementing robust risk management practices, financial institutions can navigate the challenges and uncertainties of financial markets effectively. Continued commitment to risk management ensures the soundness and integrity of the overall financial system.Sure, here's some additional content on the topic:Risk measurement and monitoring are key aspects of risk management in financial markets. Organizations use various metrics and tools to quantify and monitor risks. These include value-at-risk (VaR), stress testing, scenario analysis, and sensitivity analysis. VaR measures the potential loss in a portfolio or position under normal market conditions, with a specified confidence level. Stress testing, on the other hand, involves assessing the impact of extreme and hypothetical market scenarios on a portfolio's value. Scenario analysis involves analyzing the potential outcomes of specific events or market conditions. Sensitivity analysis assesses how changes in underlying factors, such as interest rates or exchange rates, affect the value of a portfolio.Risk management practices also extend to regulatory compliance. Financial institutions need to comply with various regulations and guidelines set by regulatory authorities. These regulations aim tosafeguard the stability and integrity of the financial system and protect consumers. Risk management frameworks help organizations ensure compliance by providing guidelines on risk assessment, reporting, and governance. Regulatory frameworks, such as Basel III, require banks to maintain adequate capital buffers to absorb potential losses and to have robust risk management systems in place.Technology plays a significant role in modern risk management. Advanced analytics tools and algorithms enable organizations to better analyze and understand risks. Artificial intelligence and machine learning can identify patterns and detect anomalies that may indicate potential risks. Risk management systems can also be automated to facilitate real-time monitoring and reporting. Technology-driven risk management helps organizations to improve risk assessment accuracy, increase efficiency, and enable faster decision-making.In addition to external risks, organizations also need to consider internal risks. Internal risks can arise from poor governance, inadequate internal controls, or unethical behaviors. Risk management frameworks often include internal control systems to ensure the effective mitigation of internal risks. These systems involve procedures and policies that promote transparency, accountability, and ethical behavior within the organization. Regular internal audits help assess the effectiveness of internal controls and identify areas for improvement.Risk management is a collective effort that involves all stakeholders in the financial markets. Regulators, financialinstitutions, investors, and market participants all play a role in identifying, assessing, and mitigating risks. Effective risk management requires collaboration and information sharing among these stakeholders. Regulatory authorities set standards and guidelines, financial institutions implement risk management practices, investors conduct due diligence, and market participants adhere to market rules and regulations.In conclusion, risk management in financial markets is vital to ensure stability, sustainability, and trust in the financial system. It involves identifying, assessing, and mitigating various types of risks, including credit risk, market risk, liquidity risk, operational risk, and systemic risk. Risk assessment and mitigation strategies are informed by robust risk management frameworks and tools. Continual monitoring and review of risks help organizations stay informed and responsive to emerging risks. Technology and regulatory compliance also play significant roles in effective risk management. By prioritizing risk management, financial institutions can safeguard their financial well-being and contribute to the overall stability of the financial system.。
外文翻译--在金融机构的有效风险管理
原文：Effective risk management in financial institutions Abstract：Risk management is more important in the financial sector than in other parts of the economy. But it is difficult. The basis of banking and similar financial institutions is taking risk in conditions of uncertainty. Describes how the Turnbull report, for which the author was project director, created a new underlying approach to risk. Provides a guide to the way in which the various Turnbull ideas have become the bedrock of risk management and suggests how they can be developed.There can be few, if any, parts of the economy in which risk management is more important than the financial sector. Financial institutions account for a sizeable number of the world’s leading companies and have a criti cal role to play in the economics of every country and thus in world economic order as a whole. Their whole business is centred on taking risks in conditions of uncertainty. The Turnbull Report on risk management and internal control, which is applicable to all listed companies in the UK and which has been widely disseminated internationally, fully recognises this fundamental point. Its focus is on effective risk management and not the elimination of risk. In a modern competitive market economy, business organisations that are risk averse are unlikely to earn satisfactory returns. On the other hand, highly volatile returns are unlikely to find favour with capital markets anxious not to be surprised, particularly by bad news. Moreover, Turnbull is as much about doing the right things and not missing strategic opportunities, as it is about doing things right, essential if a company is to achieve its full potential. Applying Turnbull’s approach may lead to some financial institutions realising that they are not taking enough risk; perhaps a new market can be identified and while there may be clear risks in being the first to enter there may equally be significant first-mover advantages to be gained.A framework, not a rule bookThe Turnbull Report also recognises the dynamic nature of markets in which an organisation operates and seeks to encourage companies to create risk managementsystems that can continually adapt to changing circumstances. To avoid particular controls being seen as an end in themselves even once their usefulness has ceased, the guidance places internal controls firmly in their broader business context: they are only of value to the extent that they help businesses to control the risks that threaten the achievement of their business objectives. In summary, Turnbull offers a framework, rather than a rulebook, which each organisation can apply to its own circumstances to develop an appropriate internal control system.The importance of sound judgementThe fact that Turnbull eschews a tick-box approach has been well received by the business community; however, it does mean that judgement plays a vital role in establishing an effective internal control system, starting at board level. Making sure that judgement is sound is perhaps the greatest single challenge involved in risk management. No system and no amount of internal controls will prevent losses if the judgement on which business decisions are based is poor.Judgement comes into play in initially establishing clearly defined business objectives, identifying the risks to achieving those objectives, prioritising how great a threat those risks pose and then determining appropriate responses in the form of developing internal control systems.Judgement is also called for in terms of applying cost-benefit analysis to the merits of adopting specific controls. It is clearly worthwhile for a bank to undertake credit checks before granting loans but a cost-benefit approach will promote systems that focus staff time on the potentially high risk loans and on developing early warning systems when loans are not performing rather than selecting a one size fits all approach.Identification issuesRisks that threaten a financial institution’s objectives will often range from highly function-specific risks through to strategic, big picture issues. Consider the foreign exchange trading activity in a major bank. There is clearly a risk that an individual trader, left to operate free of internal controls, can run up significant losses. This risk is located in a define d area of the bank’s activities but its potentialwide-ranging impact should not be underestimated. As Barings so visibly demonstrated, operational problems in a financial institution can be life-threatening probably to a greater extent than operational problems in many other businesses.At the other end of the spectrum lie a whole range of market-related strategic risks, for example, the threat that supermarkets will increasingly capitalise on their existing customer relationships to gain a larger share of the retail financial services market, or that closing down bank branches in rural locations will trigger accusations of a lack of social concern and damage the bank’s public image and possibly its brand value even though the decision may be financially supportable. With market concentration growing at national, regional and global levels, it is also essential in many cases not only to select the right strategic partner for growth but also to ensure relevant deals can be successfully concluded. Identifying the take-over candidate or strategic alliance partner is but the start of the process. Care needs to be taken to manage the risk associated with regulatory intervention and to avoid the emergence of a hostile bidder to an agreed deal. As a number of British financial institutions have discovered in recent years, the price in terms of continued independence of a high profile abortive deal can be high.Keep control of your reputationReputational risk is a major issue for the entire financial services sector, given the fundamental need for customers to believe in the stability and security of an organisation’s operations if they are to continue trusting it to handle their affairs. Furthermore, as the pensions mis-selling affair demonstrated there is a need for trust both in the individual institution and in the sector as a whole of which it forms part. This therefore calls on some occasions for collaborative as opposed to solely competitive risk management strategies as may also be the case in, for example, combating credit card fraud or on some IT security issues. In retail banking the reputation of individual banks could become much more of an issue in the years ahead with customers being increasingly tempted to consider the advantages of switching between high street banks, both as a result of the costs of switching being reduced and due to the influx of new market entrants. The recent questioning of the independenceof analysts’ forecasts will also need to be addressed robustly if long-term reputational repercussions are to be avoided.Assessing the importance of risksIdentifying the existence of potential risks does not necessarily mean that action is required to mitigate all of them. Risks must be prioritised, by means of assessing the likelihood of their occurring and the extent of their impact – high likelihood and high impact suggesting high priority for action.Verifying your judgementsWhen identifying and prioritising risks, financial institutions need to have regard to the concept of “verifiability”; in other words, if a different group of people were making the same decisions about the importance of those risks, would they be likely to come to the same conclusion? This is obviously more likely to be the case if a wide range of people from a broad cross-section of the business, both laterally and vertically, is involved in the risk identification and assessment process and if there are no “taboo” subjects which prevent conventional wisdom within the organisation being challenged when necessary.External views of risk must also be fed into the identification and assessment process. What is the market’s view of interest rate developments? How are personal investments expected to change in the coming years? In the case of regulated areas such as financial s ervices, the organisation’s perceived view of how its principal regulator views it will be of interest but also an assessment will be needed of how the overall regulatory environment is likely to develop, including in competition terms, and the impact of international developments such as those being brought about by the Lampfalussy report in the EU.Change managementOne of the key challenges running across the entire process of identifying and assessing risks is that the business and financial world is in a constant state of flux. How is the emergence of Internet banking changing the way that retail customers interact with their bank? How important is 24-hour access to account details? What does this mean for the maintenance of IT systems? Do people really want to be able tochange their bank details using their mobile phone? How do you manage call centres effectively to ensure that this new form of bank/customer interface maintains the bank’s brand values?Some new or changing market conditions will develop gradually over time, while others may sweep the market quickly. Given this dynamic background, the internal control framework must be regularly reviewed and adjusted to take account of changing market conditions. It is management’s role to recommend poli cies for managing risk, the board’s role to review and approve them, and management’s role once more to implement them and report back on their operation.Coping with risk in the midst of change is particularly key when an industry is going through a period of consolidation. Merger and acquisition activity brings inevitable disruption as previously distinct cultures and systems are consolidated into a new combined entity. The risk management implications of such proposals need to be carefully considered before, during and after the merger process.Embedding risksThe ability to respond to changing conditions largely relies on the internal control system being embedded in the bank’s operations. This is a complex process involving a range of activities including the effective communication of, and reporting on, the bank’s risk management policies at all levels, the development of risk training courses, the involvement of staff in responding to early warning systems, channels for reporting suspected control breaches and generally the creation of a positive risk management culture.The process of embedding risks should not, however, be allowed to lead to complacency or passivity within the organisation. The fact that systems are in place, a control manual exists and staff have been trained in risk management as part of their daily activities does not mean that systems are infallible as they will always be dependent, at least to some extent, on the people operating them and, for example, when staff morale is low more mistakes, accidentally or deliberately, are likely to occur.Cultural challengesCulture is also key in terms of creating an environment where dealing losses and real or suspected control breaches can and will be reported. If the prevailing culture is one of blame without just cause, then there is a high chance that individuals will see it as in their own self-interest to try to cover up problems. Many organisations are also now developing “whistleblowing” procedures to ensure concerns can be reported confidentially.Remuneration issuesThe bank’s remuneration policies have an important role in reinforcing or undermining the internal control environment. Take the bonuses paid out at the end of each year. The factors determining the size of the payout are likely, indeed intended, to shape employees’ behaviour. Consider the trader who has had a bad patch and whose bonus is under threat. He/she might react by taking increasingly greater risks in the attempt to reach his/her target. Alternatively, he/she might lose interest in his/her performance until the start of the next bonus period. Either way, the bank’s overall performance could be affected by his/her actions. However, if the bonus is based on long-term performance, then he/she is far more likely to maintain an optimal effort level over the longer term.Management, not eliminationThe Turnbull approach emphasises risk management, not risk elimination. Financial institutions must take risk, but they must do so consciously. Establishing the appropriate cultural framework needs the support of all staff in the process of identifying, monitoring and controlling risks. Risk management must be seen as an ongoing and valued activity with the board setting the example. It is without doubt a challenging agenda.Source: Anthony Carey, 2001.“Effective risk management in financial institutions”. Journal of Risk Finance. February.pp.24-27.译文：在金融机构的有效风险管理摘要：风险管理在金融部门中比经济的其他部分更重要。
新编金融英语教程 Chapter14 Risk Management
• Level 1 represents assets that are highly liquid (generally those risk-weighted at 0% under the Basel III standardized approach for capital) and receives no haircut.
14.2 Key Points
14.2.3 Financial Risk Management
Leverage ratio
Basel III introduced a minimum “leverage ratio”. This is a non-risk-based leverage ratio and is calculated by dividing Tier 1 capital by the bank’s average total consolidated assets (sum of the exposures of all assets and non-balance sheet items). The banks are expected to maintain a leverage ratio in excess of 3% under Basel III.
Chapter 14
Risk Management
CONTENTS
14.1 L e a d - i n 14.2 K e y Po i n t s 14.3 L a n g u a g e N o t e s 14.4 F o l l o w - u p Ta s k s 14.5 E x t e n d e d Ta s k s
金融风险管理
金融风险管理小题：1汇率风险——英国雷克航空公司的破产汇率风险是由于汇率的变动而导致行为主体未来收益变化的不确定性。
可细分为交易风险和折算风险：前者是指因汇率的变动影响日常交易的收入，后者是因汇率的变动影响资产负债表中的资产价值和负债成本。
2案例二：利率风险——美国储蓄信贷协会的遭遇3.案例三：衍生品价格风险——巴林银行事件（详见第五节）4市场风险金融市场风险（Financial Market Risk）是指由于金融市场变量的变化或波动而引起的资产组合未来收益的不确定性。
金融市场变量(也称市场风险因子，MarketRisk Factor)，主要包含股票价格、汇率、利率以及衍生品价格等。
所以，金融市场风险也常被称为金融资产价格风险(Price Risk of Financial Assets)，本课程简称市场风险。
市场风险除具有前文所述的金融风险共有的特性之外，还具有以下特点：主要由证券价格、利率、汇率等市场风险因子的变化引起；种类众多、影响广泛、发生频繁，是各个经济主体所面临的最主要的基础性风险；常常是其它金融风险的驱动因素；相对其他类型的金融风险而言，市场风险的历史信息和历史数据的易得性较高。
5信用风险(Credit Risk) ：由于借款人或交易对手不能或不愿履行合约而给另一方带来损失的可能性，以及由于借款人的信用评级变动和履约能力变化导致其债务市场价值的变动而引发损失的可能性。
信用风险主要取决于交易对手的财务状况与风险状况。
信用风险不仅仅包含传统的信贷风险，实际上可以将存在于诸如贷款、承诺、证券投资、金融衍生工具等各种表内和表外业务中所有与违约或信用有关的风险都包含在内。
6经营风险(Managing Risk)是指企业在运营过程中，由于某些因素的不确定性变化导致经营管理出现失误而造成损失的可能性。
经营风险与各类金融风险紧密交织，所包含的主要金融风险类型有：操作风险、决策风险(Decision-making Risk)、财务风险(Financing Risk)、道德风险(Moral Risk)专家调查法(Method of Specialist Investigation)，是利用专家的集体智慧辨识金融风险的方法。
金融机构管理一种风险管理方法FinancialInstitutions
公司债券和抵押贷款 市政债券、公司债券和股票、美国联邦政府证券 公司债券和股票
股份 商业票据、股票、债券 股份 股份
证券承销、经纪和自营业务 消费者信贷和工商信贷 股票、债券 货币市场工具
金融机构风险
What?
Which?
先讲几个故事：
巴林银行破产案
1995-02-26, 有233年历史的巴林银行破 产 尼古拉斯· 利森, 我如何搞垮了巴林银行
契约型金融机构 投资型金融机构
金融机构的类型与其主要资产和负债
金融机构类型 存款型机构（银行） 商业银行 储蓄贷款协会 互相储蓄银行 信用社 契约型储蓄机构 人寿保险公司 火灾和事故保险公司 养老基金、政府退休基金 投资金融中介机构 投资银行 金融公司 互相基金 货币市场互助基金 主要负债（资金来源） 存款 存款 存款 存款 保费 保费 雇员和雇主缴款 主要资产（资金运用） 工商信贷和消费者信贷、抵押贷款联邦政府证券 和市场债券 抵押贷款 抵押贷款 消费者信贷
看好日经225指数, 大量买入日经225股指期 货
在大阪交易所, 持仓量达20亿美元 在新加坡交易所, 持仓量达50亿美元
日经225指数下跌, 利森损失13亿美元
一个职员竟能短期内毁灭一家老牌银行，究其各种复杂原因，其中，不恰当的利用期货"杠杆效应"，并知错不改，以赌博的方式 对待期货，是造成这一"奇迹"的关键。
结构化金融、金融工程、金融创新：金融风险管理的 新要求（流动性风险管理、表外业务、金融监管与透明度）
(2)学科发展的需要
课程主题
金融机构： 金融机构风险： 金融机构的风险衡量： 金融机构的风险管理：
《金融风险管理》PPT课件
信用风险衡量及管理Credit Risk Measurement and Management
Actuarial approach and CreditRisk+ Contingent claim approach and the KMV Model Counterparty rsuring firm-wide risk Severity and frequency distributions for operational risk Types of operational risk Workflow in financial institutions
1. exposures 2. recovery rates 3. risk mitigation techniques including rating triggers, collateral, and seniority clauses
Credit derivatives
风险及投资管理Risk Management and Investment Management
Traditional investment risk management
1. Return metrics (Sharpe ratio, information ratio, VaR, relative VaR, tracking error, survivorship bias) 2. Implementing VaR 3. Benchmarking asset mixes 4. Risk decomposition and performance attribution 5. Risk budgeting 6. Tracking error 7. Setting risk limits 8. Risk of alpha transfer strategies 9. Risk management issues of pension funds
第8章金融风险管理--BaselIII
➢ 由于系统重要性银行的特殊地位，在实施时间和达标时间 上，新协议要求上述系统重要性银行从2013年开始实施该 资本要求，2018年达标。
➢ 在新协议的压力下，大机构面临要么分拆，要么再融资并 充实资本的压力。
从2013年1月1日至2017年1月1日的最低杠杆率为3%。以此降 低银行资本充足率的顺周期性。
计算杠杆比率时，所有的表外资产必须通过一定的系数转化 计算，同时衍生金融资产也需要计入。
银行应从2015 年开始公布其杠杆水平，巴塞尔委员会将结合 测试的结果，于2017年上半年进行最终调整，杠杆比率上限 将于2018 年最终确定，并逐步纳入到新协议的第一支柱部分。
流动性覆盖率主要描述短期（30天以内）特定压力情境下 ， 银行所持有的无变现障碍的、高质量的流动性资产数量，以 此应对资金流失的能力。
一般情况下，主动负债（发行债券、对央行负债、对金融机 构负债 ）流失较快，而非主动负债（存款 ）流失相对较慢。 因此，该指标不鼓励同业资金往来。
2、净稳定融资比率（Net Stable Funding Ratio，NSFR）
虽然《巴塞尔协议III》允许商业银行继续使用自己 的风险模型，但巴塞尔委员会已提议对它们使用的 参数加强控制。
《巴塞尔协议III》对资本的定义更加严格，要求银 行在持有某些风险较大的资产时预留更多的准备金。
《巴塞尔协议Ⅲ》加强了对宏观审慎监管的强调， 更加注重整体金融体系的安全与稳定。
新的巴塞尔协议无论在银行资本构成、资产质量还 是在资本充足率以及其他流动性指标方面都大幅度 甚至成倍地提升了监管要求，从协议的内容看，这 可以称之为最近30年来全球银行业在监管方面进行 的最大规模的改革。
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中国海洋大学本科生课程大纲
一、课程介绍
1.课程描述（中英文）：
随着金融一体化和经济全球化的发展，金融风险日趋复杂化和多样化，金融风险管理的重要性愈加突出。
由于金融风险对经济、金融乃至国家安全的消极影响，在国际上，许多大型企业、金融机构和组织、各国政府及金融监管部门都在积极寻求金融风险管理的技术和方法。
通过本课程的学习使学生掌握金融风险管理的基本方法、基础知识和基本原理，掌握识别金融风险、计量金融风险、化解金融风险，以及防范金融风险的基本理论和基本措施。
As the financial industry becomes increasingly competitive and concerned about managing risk, it is important to look at the robust financial risk management frameworks that satisfy compliance demands, contribute to better decision making, and enhance performance. This course provides a thorough introduction to sources of risk and describes the tools, techniques, systems, processes and strategies necessary for managing risks in banks and insurance companies. It also examines the critical importance of personal skills in implementing effective risk management and the need for commitment at all organizational levels.
2.设计思路：
本课程引导学生了解金融风险的产生机理，传递路径，评估技术以及控制方法，从而在投资决策中更好的管理风险。
课程内容包括六部分：金融风险概述、风险监管、市场风险、信用风险、流动性风险、操作风险。
六个部分由面及点，首先使学生了解金融风险管理的整体框架，然后具体至特定的金融风险。
课程设
置覆盖金融风险的整体范畴以及风险管理的全过程。
此外，课程内容设置也部分借鉴金融风险管理师（FRM）资格认证考试的内容，课堂及课后习题部分来源于FRM试题。
金融风险概述是金融风险管理的理论基础，主要包括风险及风险管理的一般理论、金融风险的界定与分类、金融风险管理的变革以及现代金融风险管理架构。
风险监管是金融风险管理的重要内容，尤其伴随金融监管的日益严格，了解与掌握金融机构风险监管政策具有重要的现实意义。
主要内容包括巴塞尔协议Ⅰ、Ⅱ、Ⅲ。
市场风险主要涉及与股票、利率、汇率、大宗商品价格等市场因素相关的金融风险。
主要内容包括希腊值的计算、风险价值度(VAR)、相关性与COPULA函数、波动率、利率风险。
信用风险主要涉及与违约、降级相关的金融风险。
主要内容包括违约概率估计与信用风险价值度。
操作风险主要内容包括损失频率与损失程度的计算、操作风险资本金的分配以及《萨班斯-奥克斯利法案》
流动性风险主要内容包括交易流动性风险与融资流动性风险。
3. 课程与其他课程的关系：
先修课程：商业银行经营学、金融工程（双语）、金融市场与股权投资（双语）
二、课程目标
本课程主要针对高年级金融学专业学生开设，通过基础理论与方法的学习，强化学生对金融机构尤其是商业银行金融风险的认识，能够利用所学的知识正确的识别风险、评价风险以及控制风险。
到本课程结束时，学生应能够：（1）了解金融风险内部控制体系与外部监管法规、熟悉商业银行风险管理流程、掌握金融风险管理的一般策略。
（2）了解风险价值度的内涵，掌握风险价值度在不同风险类别下的计算，能够基于风险价值度管理相应风险。
（3）掌握金融风险的量化管理技巧，能够利用量化计算技术识别风险、评价风险，适应金融领域量化投资的发展趋势。
（4）掌握FRM一级考试内容，使有此类需求的学生可以顺利通过FRM资格认证考试。
三、学习要求
要完成所有的课程任务，学生必须：
（1）按时上课,上课认真听讲，积极参与课堂讨论、随堂练习和测试。
本课程将包含较多的随堂练习、讨论等课堂活动，课堂表现和出勤率是成绩考核的组成部分。
（2）按时完成常规练习作业。
这些作业要求学生按书面形式提交，只有按时提交作业，才能掌握课程所要求的内容。
延期提交作业需要提前得到任课教师的许可。
（3）完成教师布置的一定量的文献阅读和背景资料等作业，其中大部分内容要求以小组合作形式完成。
这些作业能加深对课程内容的理解、促进同学间的相互学习、并能引导对某些问题和理论的更深入探讨。
四、教学进度
五、参考教材与主要参考书
1. 选用教材
Risk Management and Financial Institutions, 5th Edition, John Hull
2. 参考用书
Financial Risk Manager Handbook, 6th Edition，Philippe Jorion, John Wiley& Sons, Inc., Hoboken, New Jersey, 2011.
金融风险管理(第二版)，张金清，复旦大学出版社，2011.
金融风险管理，王勇，隋鹏达，关晶奇，机械工业出版社，2014.
六、成绩评定
（一）考核方式 A ：A.闭卷考试 B.开卷考试 C.论文 D.考查 E.其他（二）成绩综合评分体系：
七、学术诚信
学习成果不能造假，如考试作弊、盗取他人学习成果、一份报告用于不同的课程等，均属造假行为。
他人的想法、说法和意见如不注明出处按盗用论处。
本课程如有发现上述不良行为，将按学校有关规定取消本课程的学习成绩。
八、大纲审核
教学院长：院学术委员会签章：。