This document provides an outline and readings for the 2007 FRM Examination. It outlines the five risk-related disciplines covered in the exam, including Quantitative Analysis (10%), Market Risk Measurement and Management (30%), Credit Risk Measurement and Management (25%), Operational and Integrated Risk Management and Legal (25%), and Risk Management and Investment Management (10%). For each discipline, it lists relevant topics and recommended readings to assist candidates in preparing for the exam. It emphasizes that the exam tests both theoretical and practical risk management concepts and how they apply to real-world situations.
The document outlines the syllabus for the Financial Risk Manager (FRM) Exam. It is divided into two parts. Part I covers key risk management concepts like corporate risk governance, portfolio construction, asset pricing models, and risk management frameworks. It tests quantitative analysis techniques, financial products and markets, and valuation and risk models. Part II applies these risk management tools in greater depth to areas like market, credit, operational, and investment risk management. It also addresses current issues in financial markets. The goal is to evaluate candidates' understanding of theoretical and practical applications of risk management principles.
This document discusses various concepts related to market risk, including value at risk (VaR), stress testing, and back testing. It defines VaR as a threshold loss value such that the probability of portfolio loss exceeding this value over a time horizon is a given probability, like 5%. It describes how VaR is calculated using historical, variance-covariance, and Monte Carlo simulation methods. Stress testing and back testing are also introduced as tools to assess risk under unfavorable conditions and test trading strategies on historical data.
Corporate risk management emerged as a way to optimize risk taking for non-financial corporations using book value accounting. It encompasses techniques from both financial risk management and asset-liability management. The main challenges are managing "business risks" like uncertainty in asset values that don't have clear market prices. Some techniques treat business risks like market risks by assigning "economic values," while others focus on risks to earnings and cash flows under book value accounting. Economic value approaches were controversial and criticized after Enron's collapse.
I have given this presentation at the Amsterdam Business School, University of Amsterdam. It is a practical introduction for Master students in Financial Markets about the importance of Risk Management and the tools thereof.
This presentation provides a highlight of the key issues in the management of Market Risk. It touches briefly some of the elements of the Basel 2 Accord with respect to Market Risk
This document provides an overview of an upcoming presentation on asset pricing models. The presentation will cover capital market theory, the capital market line, security market line, capital asset pricing model, and diversification. It will discuss the assumptions and formulas for the capital market line and security market line. The capital market line shows expected returns based on portfolio risk, while the security market line shows expected individual asset returns based on systematic risk. The capital asset pricing model uses the concept of beta to calculate the expected return of an asset based on its risk relative to the market.
The document outlines the syllabus for the Financial Risk Manager (FRM) Exam. It is divided into two parts. Part I covers key risk management concepts like corporate risk governance, portfolio construction, asset pricing models, and risk management frameworks. It tests quantitative analysis techniques, financial products and markets, and valuation and risk models. Part II applies these risk management tools in greater depth to areas like market, credit, operational, and investment risk management. It also addresses current issues in financial markets. The goal is to evaluate candidates' understanding of theoretical and practical applications of risk management principles.
This document discusses various concepts related to market risk, including value at risk (VaR), stress testing, and back testing. It defines VaR as a threshold loss value such that the probability of portfolio loss exceeding this value over a time horizon is a given probability, like 5%. It describes how VaR is calculated using historical, variance-covariance, and Monte Carlo simulation methods. Stress testing and back testing are also introduced as tools to assess risk under unfavorable conditions and test trading strategies on historical data.
Corporate risk management emerged as a way to optimize risk taking for non-financial corporations using book value accounting. It encompasses techniques from both financial risk management and asset-liability management. The main challenges are managing "business risks" like uncertainty in asset values that don't have clear market prices. Some techniques treat business risks like market risks by assigning "economic values," while others focus on risks to earnings and cash flows under book value accounting. Economic value approaches were controversial and criticized after Enron's collapse.
I have given this presentation at the Amsterdam Business School, University of Amsterdam. It is a practical introduction for Master students in Financial Markets about the importance of Risk Management and the tools thereof.
This presentation provides a highlight of the key issues in the management of Market Risk. It touches briefly some of the elements of the Basel 2 Accord with respect to Market Risk
This document provides an overview of an upcoming presentation on asset pricing models. The presentation will cover capital market theory, the capital market line, security market line, capital asset pricing model, and diversification. It will discuss the assumptions and formulas for the capital market line and security market line. The capital market line shows expected returns based on portfolio risk, while the security market line shows expected individual asset returns based on systematic risk. The capital asset pricing model uses the concept of beta to calculate the expected return of an asset based on its risk relative to the market.
1. The document discusses various types of exchange rate risks faced by firms, including transaction risk, translation risk, and economic risk.
2. It presents the Value-at-Risk (VaR) approach as the predominant method for measuring a firm's exchange rate risk exposure. VaR measures the maximum potential loss over a given time period with a certain level of confidence.
3. The document examines exchange rate risk management strategies such as tactical versus strategic hedging and passive versus active hedging. It also outlines best practices for currency risk management, including identifying risk exposures and measuring risks using models like VaR.
Coupling of Market Risk,Credit Risk, and Liquidity RiskGateway Partners
The main risks of any financial product are market risk, credit risk, and liquidity risk. When we reference credit risk, we are including both market-based credit risk, where widening of credit spreads is indicative of credit quality deterioration, as well as counterparty credit risk. This may be caused by the loss in the market value of the portfolio holdings or market illiquidity. Similarly, liquidity risk includes the funding liquidity as well as the market liquidity of different asset classes. In general, these risks are treated separately as if they are totally Independent of each other. That assumption is untrue as any loss in market value impacts both funding costs as well as credit quality loss. Similarly, any loss in liquidity can impact the credit performance risk as well as the market prices of an asset. If we measure the market, credit, and liquidity risk separately, this risk can be significantly understated as the coupling can be highly non-linear, thus increasing the losses several orders of magnitude.
The following presentation discusses this coupling of market, credit, and liquidity risk as well as the difficulties in measuring them in addition to possible solutions to hedge them.
This document discusses risk and return in finance. It defines risk as the probability that an actual return on an investment will be lower than the expected return. Risk is broadly divided into systematic risk and unsystematic risk. Systematic risk refers to variability in returns caused by factors affecting all securities, like economic or market changes. Unsystematic risk is unique to a specific security. The document also defines return as the money earned from an investment as a percentage of the amount invested. It discusses actual return, expected return, and risk-free return. Finally, it introduces several methods for evaluating portfolio performance, including the Sharpe ratio, Treynor's ratio, and Jensen's measure.
The Markowitz model generates an efficient frontier of optimal portfolios based on expected return and risk. The Capital Asset Pricing Model (CAPM) further develops this by incorporating a risk-free asset, creating the Capital Market Line (CML). The CML represents equilibrium pricing relationships between expected return and risk for all efficient portfolios. According to CAPM, the expected return of any security or portfolio is equal to the risk-free rate plus a risk premium proportional to the security's systematic risk relative to the market.
This document provides an introduction to financial risk management. It defines risk as the uncertainty about future outcomes or events. It categorizes risks as either pure risks, which can be controlled through internal controls or insurance, or speculative risks, which are necessary to make profits but cannot be avoided. The document then discusses various types of risks according to the Turnbull report, including market, credit, liquidity, technological, legal and others. It also covers concepts in risk management such as exposure, risk appetite, risk-based approaches and more. Methods of identifying, assessing, monitoring, controlling and quantifying different types of financial risks are outlined.
Financial Mgt. - Capital Asset Pricing ModelKaustabh Basu
This document presents an overview of the Capital Asset Pricing Model (CAPM). It discusses the key assumptions of CAPM, including that investors hold diversified portfolios and can borrow/lend at the risk-free rate. CAPM represents the relationship between required return and systematic risk using the formula: Ke = Rf + β(Rm - Rf). It also discusses the different degrees of market efficiency, advantages of CAPM in considering only systematic risk, and disadvantages such as its assumptions. The conclusion states that while criticisms exist, CAPM remains a useful model and stands up well to criticism.
The document discusses the Capital Asset Pricing Model (CAPM) and some of its key assumptions and implications. It summarizes Sharpe's (1964) development of CAPM based on Markowitz portfolio theory. Sharpe's model shows how asset prices adjust to create a linear relationship between risk and expected return in equilibrium. However, later studies found some empirical issues with CAPM's assumptions around unlimited borrowing and lending. Black (1972) discusses how relaxing this assumption could change CAPM and better explain observed returns that did not perfectly fit the model.
A new emphasis on enterprise risk management from regulators has heightened awareness among bankers to get educated and adopt these best practices at their institution. In response to this increased focus, the RMA ERM Council developed the ERM framework and associated competencies, which became the foundation for a series of highly practical workbooks for implementing effective ERM.
Capital Structure Theories, Valuation of Shares & Efficient Market HypothesisSwaminath Sam
The presentation contains details on Net Income, Net Operating, Traditional and Modigliani & Miller Approach; valuation of shares i.e., different models for valuation of shares in particular CAPM; Efficient Market Hypothesis (EMH) & forms of hypothesis
The Markowitz model generates an efficient frontier of optimal portfolios that maximize return for a given level of risk. The Capital Asset Pricing Model (CAPM) builds on this by deriving the security market line (SML) which plots the expected return of individual securities based on their beta coefficient in relation to the market portfolio. The capital market line (CML) extends the efficient frontier by including a risk-free asset, demonstrating how investors can optimize the trade-off between risk and return through borrowing and lending at the risk-free rate.
The Capital Asset Pricing Model (CAPM) was developed in the 1960s as a way to determine the expected return of an asset based on its risk. CAPM assumes that investors will be compensated only based on an asset's systematic or non-diversifiable risk as measured by its beta. The model builds on Markowitz's portfolio theory and introduces the security market line, which plots the expected return of an asset against its beta. According to CAPM, the expected return of an asset is equal to the risk-free rate plus a risk premium that is proportional to the asset's beta.
This module discusses key concepts related to investment avenues and portfolio management. It covers mutual funds, investor lifecycles, personal finance, international investing, and portfolio management of funds in banks, insurance companies and pension funds. It also provides an introduction to portfolio management, including the meaning of portfolio management, portfolio analysis, portfolio objectives, and the portfolio management process.
FRM - Level 1 Part 1 - Foundations of Risk ManagementJoe McPhail
Enterprise risk management (ERM) involves identifying risks at an entity level, quantifying exposures, establishing a risk appetite framework, monitoring performance against the framework, and amending the strategy as needed. Key challenges for ERM include clearly communicating all material risks, correctly accounting for interactions between risks, and ensuring risk mitigation strategies do not introduce new risks. Setting an effective risk appetite framework requires qualitative and quantitative articulation of acceptable risk limits along with clear communication and responsibility for risk throughout the organization.
Considering Necessary Details For Credit Risk FRM Part II.For more information on this video, and to sign-up for our 10-day Free CFA Course click here:-http://www.edupristine.com/courses/frm-garp-financial-risk-manager/frm-level-ii-trainings/
To know more about these trainings, do contact us at -M: +91 80800 05533
Rejda chapter 1 slides risk and its treatmentnlmccready
The document defines risk and discusses techniques for managing risk. It defines risk as uncertainty about potential losses and distinguishes between objective and subjective risk. It also defines chance of loss, perils, hazards, and different types of risk like pure risk and diversifiable risk. Major personal and commercial risks are outlined. Techniques for managing risk include risk control methods like loss prevention and risk financing methods like insurance, which transfers risk to an insurer by pooling together many insured individuals and companies.
1. The document discusses various types of exchange rate risks faced by firms, including transaction risk, translation risk, and economic risk.
2. It presents the Value-at-Risk (VaR) approach as the predominant method for measuring a firm's exchange rate risk exposure. VaR measures the maximum potential loss over a given time period with a certain level of confidence.
3. The document examines exchange rate risk management strategies such as tactical versus strategic hedging and passive versus active hedging. It also outlines best practices for currency risk management, including identifying risk exposures and measuring risks using models like VaR.
Coupling of Market Risk,Credit Risk, and Liquidity RiskGateway Partners
The main risks of any financial product are market risk, credit risk, and liquidity risk. When we reference credit risk, we are including both market-based credit risk, where widening of credit spreads is indicative of credit quality deterioration, as well as counterparty credit risk. This may be caused by the loss in the market value of the portfolio holdings or market illiquidity. Similarly, liquidity risk includes the funding liquidity as well as the market liquidity of different asset classes. In general, these risks are treated separately as if they are totally Independent of each other. That assumption is untrue as any loss in market value impacts both funding costs as well as credit quality loss. Similarly, any loss in liquidity can impact the credit performance risk as well as the market prices of an asset. If we measure the market, credit, and liquidity risk separately, this risk can be significantly understated as the coupling can be highly non-linear, thus increasing the losses several orders of magnitude.
The following presentation discusses this coupling of market, credit, and liquidity risk as well as the difficulties in measuring them in addition to possible solutions to hedge them.
This document discusses risk and return in finance. It defines risk as the probability that an actual return on an investment will be lower than the expected return. Risk is broadly divided into systematic risk and unsystematic risk. Systematic risk refers to variability in returns caused by factors affecting all securities, like economic or market changes. Unsystematic risk is unique to a specific security. The document also defines return as the money earned from an investment as a percentage of the amount invested. It discusses actual return, expected return, and risk-free return. Finally, it introduces several methods for evaluating portfolio performance, including the Sharpe ratio, Treynor's ratio, and Jensen's measure.
The Markowitz model generates an efficient frontier of optimal portfolios based on expected return and risk. The Capital Asset Pricing Model (CAPM) further develops this by incorporating a risk-free asset, creating the Capital Market Line (CML). The CML represents equilibrium pricing relationships between expected return and risk for all efficient portfolios. According to CAPM, the expected return of any security or portfolio is equal to the risk-free rate plus a risk premium proportional to the security's systematic risk relative to the market.
This document provides an introduction to financial risk management. It defines risk as the uncertainty about future outcomes or events. It categorizes risks as either pure risks, which can be controlled through internal controls or insurance, or speculative risks, which are necessary to make profits but cannot be avoided. The document then discusses various types of risks according to the Turnbull report, including market, credit, liquidity, technological, legal and others. It also covers concepts in risk management such as exposure, risk appetite, risk-based approaches and more. Methods of identifying, assessing, monitoring, controlling and quantifying different types of financial risks are outlined.
Financial Mgt. - Capital Asset Pricing ModelKaustabh Basu
This document presents an overview of the Capital Asset Pricing Model (CAPM). It discusses the key assumptions of CAPM, including that investors hold diversified portfolios and can borrow/lend at the risk-free rate. CAPM represents the relationship between required return and systematic risk using the formula: Ke = Rf + β(Rm - Rf). It also discusses the different degrees of market efficiency, advantages of CAPM in considering only systematic risk, and disadvantages such as its assumptions. The conclusion states that while criticisms exist, CAPM remains a useful model and stands up well to criticism.
The document discusses the Capital Asset Pricing Model (CAPM) and some of its key assumptions and implications. It summarizes Sharpe's (1964) development of CAPM based on Markowitz portfolio theory. Sharpe's model shows how asset prices adjust to create a linear relationship between risk and expected return in equilibrium. However, later studies found some empirical issues with CAPM's assumptions around unlimited borrowing and lending. Black (1972) discusses how relaxing this assumption could change CAPM and better explain observed returns that did not perfectly fit the model.
A new emphasis on enterprise risk management from regulators has heightened awareness among bankers to get educated and adopt these best practices at their institution. In response to this increased focus, the RMA ERM Council developed the ERM framework and associated competencies, which became the foundation for a series of highly practical workbooks for implementing effective ERM.
Capital Structure Theories, Valuation of Shares & Efficient Market HypothesisSwaminath Sam
The presentation contains details on Net Income, Net Operating, Traditional and Modigliani & Miller Approach; valuation of shares i.e., different models for valuation of shares in particular CAPM; Efficient Market Hypothesis (EMH) & forms of hypothesis
The Markowitz model generates an efficient frontier of optimal portfolios that maximize return for a given level of risk. The Capital Asset Pricing Model (CAPM) builds on this by deriving the security market line (SML) which plots the expected return of individual securities based on their beta coefficient in relation to the market portfolio. The capital market line (CML) extends the efficient frontier by including a risk-free asset, demonstrating how investors can optimize the trade-off between risk and return through borrowing and lending at the risk-free rate.
The Capital Asset Pricing Model (CAPM) was developed in the 1960s as a way to determine the expected return of an asset based on its risk. CAPM assumes that investors will be compensated only based on an asset's systematic or non-diversifiable risk as measured by its beta. The model builds on Markowitz's portfolio theory and introduces the security market line, which plots the expected return of an asset against its beta. According to CAPM, the expected return of an asset is equal to the risk-free rate plus a risk premium that is proportional to the asset's beta.
This module discusses key concepts related to investment avenues and portfolio management. It covers mutual funds, investor lifecycles, personal finance, international investing, and portfolio management of funds in banks, insurance companies and pension funds. It also provides an introduction to portfolio management, including the meaning of portfolio management, portfolio analysis, portfolio objectives, and the portfolio management process.
FRM - Level 1 Part 1 - Foundations of Risk ManagementJoe McPhail
Enterprise risk management (ERM) involves identifying risks at an entity level, quantifying exposures, establishing a risk appetite framework, monitoring performance against the framework, and amending the strategy as needed. Key challenges for ERM include clearly communicating all material risks, correctly accounting for interactions between risks, and ensuring risk mitigation strategies do not introduce new risks. Setting an effective risk appetite framework requires qualitative and quantitative articulation of acceptable risk limits along with clear communication and responsibility for risk throughout the organization.
Considering Necessary Details For Credit Risk FRM Part II.For more information on this video, and to sign-up for our 10-day Free CFA Course click here:-http://www.edupristine.com/courses/frm-garp-financial-risk-manager/frm-level-ii-trainings/
To know more about these trainings, do contact us at -M: +91 80800 05533
Rejda chapter 1 slides risk and its treatmentnlmccready
The document defines risk and discusses techniques for managing risk. It defines risk as uncertainty about potential losses and distinguishes between objective and subjective risk. It also defines chance of loss, perils, hazards, and different types of risk like pure risk and diversifiable risk. Major personal and commercial risks are outlined. Techniques for managing risk include risk control methods like loss prevention and risk financing methods like insurance, which transfers risk to an insurer by pooling together many insured individuals and companies.
The document provides information about the Financial Risk Manager (FRM) certification program, which involves passing two exams to demonstrate knowledge of financial risk management. It details the requirements to obtain the FRM charter, including work experience and education qualifications. Key details are provided around the exam dates and locations, registration fees, course structure and duration, and payment options for an upcoming training program in India to prepare candidates for the FRM exams.
This module discusses risk management and insurance. It covers topics such as risks and risk management, different types of risks, methods of handling risks including avoiding, controlling, accepting and transferring risks. It also discusses the basic concepts of insurance including risk pooling, law of large numbers, requirements of insurable risks, advantages and disadvantages of insurance. Additionally, it covers personal risk management process, objectives of risk management pre-loss and post-loss, insurance market dynamics and underwriting cycle. Finally, it discusses some key legal principles of insurance contracts such as offer and acceptance, consideration, insurable interest, subrogation and utmost good faith.
This document provides course information for the Master of Business Administration program at Anna University in Chennai, India. It outlines the curriculum, courses, credits, and electives for full-time students over four semesters and part-time students over six semesters. The curriculum covers topics such as accounting, economics, finance, human resources, marketing, operations, and more. Students are required to complete courses in these functional areas as well as internships, labs, and a final project to earn a total of 96 credits to graduate.
Insurance is defined both functionally and contractually. Functionally, it is a cooperative device to spread risk over multiple individuals exposed to the same risk. Contractually, it is an agreement where an insurer takes on the risk of a large loss in exchange for regular premium payments. The primary functions of insurance are providing protection from economic loss, collective risk bearing by sharing losses among policyholders, evaluating risks, and providing certainty. Secondary functions include preventing losses, covering larger risks with small capital contributions, and facilitating development of large industries. Insurance also serves as a savings/investment tool, earns foreign exchange, enables risk-free trade, and provides indemnification for unanticipated losses.
Chapter 01 concepts and principles of insuranceiipmff2
The document defines insurance as a social device where individuals transfer risk to an insurer who pools losses to make statistical predictions and provide payments from premium contributions. Legally, it is a contract where an insurer provides security to an insured against specified events in exchange for a premium proportionate to the risk. Key elements are risk transfer from insured to insurer, insurance as a business to meet costs and make profit, and an insurance contract as a legally enforceable agreement. Fundamental principles include utmost good faith, indemnity, subrogation, contribution, and proximate cause. There are various types of insurance and governing laws regulate the insurance sector in India.
This document outlines a course on risk management and derivatives. The course aims to provide knowledge on measuring and hedging various risks through 4 modules covering risk analysis in capital budgeting, investment risks and derivatives, hedging with futures contracts, and options basics and strategies. The course objectives are to orient students on risk types, provide knowledge on risk measurement and evaluation, and risks associated with investments and hedging strategies using derivatives like futures and options.
This document discusses approaches for measuring and managing systemic risk from an economic perspective. It outlines network analysis, portfolio modeling using market data, and macro stress testing approaches. It also discusses plausible mitigation strategies like hedging, collateral management, and central clearing counterparties. Specific examples are provided on modeling local contagion, ranking financial institutions by systemic risk under baseline and stressed scenarios, and assessing the impact of sovereign defaults. Collateral management strategies like haircut valuation under baseline and stressed conditions are also examined.
This document outlines courses in a Basics of Financial Analysis program. The courses cover topics such as economics, accounting, corporate finance, financial markets, investments, banking, risk management, and insurance. Some key courses include Fundamentals of Financial Statements, Capital Budgeting, Security Analysis and Portfolio Management, Derivatives, Credit Management, and Risk Management in Banks, Mutual Funds, and Insurance Companies. The document lists recommended textbooks for each subject area.
This document provides an overview of model risk and model risk management. It defines a model, discusses what model risk is using examples from NAB and JPMorgan, and describes the key aspects of model risk management including validation, quantification, and a control framework. It also discusses two case studies of model risk issues at NAB and JPMorgan, the value of model risk management, what it's like to work in the field, and regulators' increasing focus on it.
An analysis of credit risk with risky collateral a methodology for haircut de...hasare
This document presents an analysis of credit risk when collateral is involved. It aims to develop a methodology for determining haircut levels on collateral. The document provides context on the growth of credit risk in financial markets and the increased use of collateralization to manage it. It notes that while credit risk pricing models exist, little attention has been paid to the impact of risky collateral. The analysis examines credit risk valuation in situations with stochastic collateral, bond collateral with interest rate risk, and both continuous and discrete collateral margining. The goal is to understand how haircut levels should depend on the risks of the collateral and underlying assets, as well as their correlation.
Model Risk Management | How to measure and quantify model risk?Genest Benoit
The aim of this paper is to present model risk situations and a methodology to measure and quantify the associated risk at model level, with different types of assumptions. Then, considering that in practice, a model risk management at model level is hardly feasible, this paper also outlines a method to measure and quantify model risk at risk category level (ex: Credit Risk).
In fact, one of the overarching drivers of this paper is to provide a model risk “value” which will enable you to analyse if the model risk is sufficiently covered. Indeed, although banks already allocate funds regarding this risk (portion of RWA attributed to conservative margins for credit risk, portion of Op risk Value at Risk, etc.), assessing the appropriateness of those funds remain complicated
The document is a study guide for the 2012 Financial Risk Manager (FRM) Examination. It outlines the topics covered on the exam and provides recommended readings to prepare. The exam tests risk management concepts and their real-world application. It is divided into two parts, with Part I covering foundations of risk management, quantitative analysis, financial markets and products, and valuation and risk models. Part II covers market risk measurement and management, and credit risk measurement and management. The study guide provides detailed outlines of the topics covered within each part, as well as the exam weighting for each topic, to help candidates focus their exam preparation.
This document provides an overview of the course content for Operations Research and Operations Management.
The Operations Research course covers topics like linear programming, transportation problems, assignment problems, network analysis, queuing theory, and game theory. The Operations Management course covers operations planning and control, production scheduling, quality control, materials management, and stores management.
Both courses discuss quantitative and analytical techniques for decision-making in business operations and supply chain management. The goal is to introduce conceptual frameworks and mathematical models to optimize resource allocation, maximize efficiency, and minimize costs across different operational functions and processes.
This document outlines the course information, learning outcomes, transferable skills, course description, content, scheme of work, assessment, references, assignment format, referencing format, presentation format, and instructor details for the course "Risk Management in Islamic Finance". The course is a 3-credit hour core diploma course that introduces students to risk management principles and applications in Islamic finance. Topics covered include risk and uncertainty, risk profiles of Islamic financial institutions, and risk management frameworks in Islamic banks, takaful, and capital markets. Student assessment includes assignments, presentations, tests, and a final exam.
This document outlines a course on Risk Management in Islamic Finance. The course aims to provide students with an understanding of risk management principles and applications within Islamic financial institutions. Over 3 credit hours and 36 contact hours, the course will cover topics such as risk and uncertainty in Islam, risk profiles of Islamic banks and capital markets, and the risk management framework and processes used in Islamic financial sectors. Assessment is comprised of group assignments, individual presentations, tests, and a final exam. The course references a main text on risk management in Islamic financial institutions and provides formatting guidelines for student work.
This document discusses risk management in banks. It outlines the major types of risks banks face: credit risk, market risk, and operational risk. Credit risk is the potential that a bank borrower fails to meet obligations and can take the form of outright default or deterioration in credit quality. Market risk includes liquidity risk, interest rate risk, foreign exchange risk, and country risk due to fluctuations in market values. Operational risk is the risk of loss from inadequate internal processes or systems. The Basel Accords provide capital adequacy guidelines for banks to manage unexpected losses from risks based on their risk profiles. Risk management in banks involves identifying, measuring, monitoring, and controlling various risks to ensure sufficient capital levels are maintained.
This document provides information about an upcoming Risk Management Workshop Plus (RMWP) event, including instructor biographies and workshop descriptions. Four instructors are listed: Xuping Zhang from BMO Financial Group who will discuss model validation; Warren Cai from Manulife Financial covering the risk management lifecycle; Jonathan Zhang from Sun Life Investment Management on interest rate risk management; and Wei Jiang from Scotiabank discussing retail credit risk. The workshops will cover topics such as risk frameworks, valuation models, market risk, and customer risk. Participants can choose from case study, soft skills, or full packages covering industry overview, case studies, and resume/interview preparation.
This document outlines the modules and topics covered in the course "Entrepreneurship Development". The 8 modules cover a range of topics including entrepreneur characteristics, creativity and innovation, business planning, institutions supporting entrepreneurs, family business, international entrepreneurship opportunities, venture capital, and managing growth. Recommended and reference books are also listed to provide further reading on entrepreneurship concepts. The course aims to equip students with knowledge on developing entrepreneurial skills and establishing new business ventures.
This document discusses commercial bank risk management based on interviews with various financial institutions. It finds that banks actively manage three types of risks: (1) risks that can be avoided through business practices, (2) risks that can be transferred to other parties, and (3) risks that must be managed internally. For risks in the third category, banks employ a four part risk management process involving (i) setting standards and reporting requirements, (ii) establishing position limits and rules, (iii) outlining investment guidelines and strategies, and (iv) implementing incentive-based compensation schemes. The document evaluates current industry practices and identifies areas for improvement in commercial bank risk management.
This document provides information about the Certified in Finance (CFR) certification program from the American Academy of Finance Management (AAFM). It includes the table of contents, descriptions of financial risk management functions and objectives, and the syllabus for the Finance Risk Management certification. The syllabus covers topics like interest rate risk, foreign exchange risk, liquidity risk, and risk measurement. It also provides background on AAFM, its board of standards, and international recognition.
Value-at-Risk (VaR) has been adopted as the cornerstone and commonlanguage of risk management by virtually all major financial institutions and regulators. However, this risk measure has failed to warn the market participants during the financial crisis. In this paper, we show this failure may come from the methodology that we use to calculate VaR and not necessarily for VaR measure itself. we compare two different methods for VaR calculation, 1)by assuming the normal distribution of portfolio return, 2)
by using a bootstrap method in a nonparametric framework. The Empirical exercise is implemented on CAC 40 index, and the results show us that the first method will underestimate the market risk - the failure of VaR measure occurs. Yet, the second method overcomes the shortcomings of the first method and provides results that pass the tests of VaR evaluation.
Research:What is the banking risk managementMahad Qaasim
This document is a report submitted by the GURMAD GROUP on the topic of banking risk management for a Money and Banking course. It discusses the types of risks banks face, including credit risk, liquidity risk, market risk, operational risk, reputation risk, and legal risk. It also provides tips for how banks can work to reduce these risks, such as by documenting loan upgrades, conducting stress testing to uncover vulnerabilities, developing a stress testing framework, and setting deadlines for risk assessment processes. The group aims to explain what risk management is, why it is important for banks, and some methods used in risk management.
Commercial banking & bank management[1]dvdoshi0904
This document provides information about the Commercial Banking & Bank Management course offered at Flame School of Business. The 3-sentence summary is:
The course provides a framework for students to understand banking institutions and their role as financial intermediaries, focusing on statutes governing banks, operational risk management, and new banking products. Students will learn about universal banking, banker-customer relationships, credit facilities, asset liability management, and innovative banking products. Evaluation incorporates class participation, group submissions, quizzes, a term exam, and case studies/assignments related to topics like retail banking, financial sector reforms, and international trade finance.
Carry out a systematic literature review on the application of macTawnaDelatorrejs
Carry out a systematic literature review on the application of machine learning in Banking risk management building on the work of Leo et al., 2019 (attached).
· 12-13 pages (excluding title page and reference pages)
· References must not be older than 2 years.
· APA 7.0
Carry out a
systematic
literature review on the application of machine learning in
Banking risk
management
building on the work of Leo et al., 2019 (attached).
·
1
2
-
1
3
pages (excluding title page and reference pages)
·
References must not be older t
han 2 years.
·
APA 7.0
Carry out a systematic literature review on the application of machine learning in
Banking risk management building on the work of Leo et al., 2019 (attached).
12-13 pages (excluding title page and reference pages)
References must not be older than 2 years.
APA 7.0
risks
Article
Machine Learning in Banking Risk Management:
A Literature Review
Martin Leo * , Suneel Sharma and K. Maddulety
SP Jain School of Global Management, Sydney 2127, Australia; [email protected] (S.S.);
[email protected] (K.M.)
* Correspondence: [email protected]; Tel.: +65-9028-9209
Received: 25 January 2019; Accepted: 27 February 2019; Published: 5 March 2019
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Abstract: There is an increasing influence of machine learning in business applications, with many
solutions already implemented and many more being explored. Since the global financial crisis,
risk management in banks has gained more prominence, and there has been a constant focus around
how risks are being detected, measured, reported and managed. Considerable research in academia
and industry has focused on the developments in banking and risk management and the current
and emerging challenges. This paper, through a review of the available literature seeks to analyse
and evaluate machine-learning techniques that have been researched in the context of banking risk
management, and to identify areas or problems in risk management that have been inadequately
explored and are potential areas for further research. The review has shown that the application of
machine learning in the management of banking risks such as credit risk, market risk, operational
risk and liquidity risk has been explored; however, it doesn’t appear commensurate with the current
industry level of focus on both risk management and machine learning. A large number of areas
remain in bank risk management that could significantly benefit from the study of how machine
learning can be applied to address specific problems.
Keywords: risk management; bank; machine learning; credit scoring; fraud
1. Introduction
Since the global financial crisis, risk management in banks has gained more prominence, and
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Considerable research (Van Liebergen 2017; Deloitte University Press 2017; Helbekkmo et al. 2013;
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1. 2007 FRM Examination
Study Guide
Topic Outline, Readings, Test Weightings
The Study Guide sets forth primary topics and subtopics under the five risk-related
disciplines covered in the FRM exam. The topics were selected by the FRM Committee
as being representative of the theories and concepts utilized by risk management
professionals as they address current issues. The topics are reviewed yearly to ensure
the FRM exam is kept timely and relevant.
FRM Examination Approach
The FRM exam is a practice-oriented examination. Its questions are derived from a
combination of theory, as set forth in the readings, and “real-world” work experience.
Candidates are expected to understand risk management concepts and approaches and
how they would apply to a risk manager’s day-to-day activities.
The FRM examination is also a comprehensive examination, testing a risk professional
on a number of risk management concepts and approaches. It is very rare that a risk
manager will be faced with an issue that can immediately be slotted into one
category. In the real world, a risk manager must be able to identify any number of
risk-related issues and be able to deal with them effectively.
Readings
Questions for the FRM examination are derived from the readings listed under each
topic outline. These readings were selected by the FRM Committee to assist
candidates in their review of the subjects covered by the exam. It is strongly
suggested that candidates review these readings in depth prior to sitting for the exam.
The Financial Risk Manager Handbook, 4th edition, by Philippe Jorion (New York:
Wiley, 2007), covers most of the FRM examination topics at the appropriate level.
However, FRM candidates must remember that the handbook is not a textbook. It is
only designed to help candidates review the material. Alone, it is not sufficient to
prepare a candidate to pass the examination. An interactive CD with questions and
answers from previous FRM exams, and an FRM Readings CD are also available to assist
candidates with their exam preparation.
2. Study Outline, Test Weightings, Readings
I. Quantitative Analysis – 10%
Estimating parameters of distributions
Extreme value theory; basic principles
Hypothesis testing
Linear regression and correlation
Mean, standard deviation, correlation, skewness, and kurtosis
Monte Carlo analysis
Probability distributions
Statistical properties and forecasting of correlation, covariance, and volatility
Quantitative Analysis Readings:
1. Linda Allen, Jacob Boudoukh, Anthony Saunders, Understanding Market, Credit and
Operational Risk: The Value At Risk Approach (Oxford: Blackwell Publishing, 2004).
Chapter 2 – Quantifying Volatility in VaR Models
2. John Hull, Options, Futures, and Other Derivatives, 6th ed. (New York: Prentice
Hall, 2006).
Chapter 19 – Estimating volatilities and correlations
3. Philippe Jorion, Value at Risk: The New Benchmark for Managing Financial Risk, 3rd
ed. (New York: McGraw-Hill, 2007).
Chapter 9 – Forecasting risk and correlations
Chapter 12 – Monte Carlo Methods
4. Lampros Kalyvas and Ioannis Akkizidis, Integrated Market, Credit and Operational
Risk: A Complete Guide for Bankers and Risk Professionals (London: Risk Books, 2006).
Chapter 4 – Extreme Value Theory and in Risk Management
5. Murray R. Spiegel, John Schiller, and R. Alu Srinivasan, Probability and Statistics,
Schaum’s Outlines, 2nd ed. (New York: McGraw-Hill, 2000).
Chapter 1 – Basic Probability
Chapter 2 – Random Variables and Probability Distributions
Chapter 3 – Mathematical Expectation
Chapter 4 – Special Probability Distributions
Chapter 5 – Sampling Theory
3. Chapter 6 – Estimation Theory
Chapter 7 – Tests of Hypotheses and Significance
Chapter 8 – Curve Fitting, Regression, and Correlation
NOTE: Candidates should not memorize formulas of distributions but should
understand when it is appropriate to use a particular type of distribution.
II. Market Risk Measurement and Management – 30%
Derivatives on fixed-income securities, interest rates, foreign exchange, equities,
and commodities
Emerging market risks including currency crises
Identifying and measuring risk exposures
Interest rate, foreign exchange, equity, and commodity risks
Interest rates and bond pricing
Measuring and managing corporate exposures, including cash flow at risk
Risk budgeting
Stress testing
Valuation and risk analysis of futures, forwards, swaps, and options
Value-at-Risk:
1. definition, delta-normal, historical simulation, Monte Carlo
2. implementation
3. limitations and alternative risk measures, e.g., conditional Value-at-Risk
Cash-flow-at-risk, earnings-at-risk
Market Risk Measurement and Management Readings:
1. Allen, Boudoukh, and Saunders, Understanding Market, Credit and Operational Risk.
Chapter 1 – Introduction to Value at Risk (VaR)
Chapter 3 – Putting VaR to Work
2. Hull, Options, Futures, and Other Derivatives, 6th ed.
Chapter 3 – Hedging Strategies using Futures
Chapter 5 – Determination of Forward and Futures Prices
Chapter 6 – Interest Rate Futures
Chapter 7 – Swaps
4. Chapter 9 – Properties of Stock Options
Chapter 10 – Trading Strategies Involving Options
Chapter 11 – Binomial Trees
Chapter 13 – The Black-Scholes-Merton Model
Chapter 15 – The Greek Letters
Chapter 16 – Volatility Smiles
Chapter 22 – Exotic Options
3. Jorion, Value-at-Risk, 3rd ed.
Chapter 10 – VaR Methods
Chapter 11 – VaR Mapping
Chapter 14 – Stress Testing
4. Robert L. McDonald, Derivatives Markets, (Boston: Addison-Wesley, 2003).
Chapter 6 – Commodity Forwards and Futures
5. Anthony Saunders, Financial Institutions Management, 5th ed. (New York: McGraw-
Hill, 2005).
Chapter 10 – Market Risk
Chapter 15 – Foreign Exchange Risk
6. René Stulz, Risk Management & Derivatives (Mason, Ohio: South-Western, 2003).
Chapter 4 – A Firm-Wide Approach to Risk Management
Chapter 8 – Identifying and Managing Cash Flow Exposures
Chapter 15 – The Demand and Supply for Derivative Products
7. Bruce Tuckman, Fixed Income Securities, 2nd ed. (Hoboken: John Wiley & Sons,
Inc., 2002).
Chapter 1 – Bond Prices, Discount Factors, and Arbitrage
Chapter 2 – Bond Prices, Spot Rates, and Forward Rates
Chapter 3 – Yield to Maturity
Chapter 4 – Generalizations and Curve Fitting
Chapter 5 – One-Factor Measures of Price Sensitivity
Chapter 6 – Measures of Price Sensitivity Based on Parallel Yield Shifts
Chapter 7 – Key Rate and Bucket Exposures
Chapter 9 – The Science of Term Structure Models
Chapter 21 – Mortgage-Backed Securities
5. III. Credit Risk Measurement and Management – 25%
Analyzing special purpose vehicles and securitizations
Bankruptcy including offsets and priority rules
Contingent claim approach and the KMV Model
Counterparty risks:
1. exposures
2. recovery rates
3. risk mitigation techniques including rating triggers, collateral, and seniority clauses
Credit derivatives
1. Collateralized debt obligations
2. Collateralized default swaps
Credit ratings
Credit risk management models
Credit spreads
Default probabilities
Interest rates and yields
Margining
Netting
Portfolio credit risk
Settlement risk
Credit Risk Measurement and Management Readings:
1. Eduardo Canabarro and Darrell Duffie, “Measuring and Marking Counterparty Risk”
in ALM of Financial Institutions, ed. Leo Tilman (London: Euromoney Institutional
Investor, 2003). Copy of article is available at the GARP Digital Library website,
www.GARPDigitalLibrary.org.
2. Christopher Culp, Structured Finance and Insurance: The Art of Managing Capital
and Risk (Hoboken: John Wiley & Sons, Inc., 2006).
Chapter 16 – Securitization
3. Arnaud de Servigny and Olivier Renault, Measuring and Managing Credit Risk, (New
York: McGraw-Hill, 2004).
Chapter 2 – External and Internal Ratings
6. Chapter 3 – Default Risk: Quantitative Methodologies
Chapter 4 – Loss Given Default
Chapter 6 – Credit Risk Portfolio Models
Chapter 7 – Credit Risk Management and Strategic Capital Allocation
4. Ashish Dev, Economic Capital, (London: Risk Books, 2004).
Chapter 7 – Economic Capital for Counterparty Credit Risk, by Evan Picoult and David
Lamb.
5. Gunter Meissner, Credit Derivatives, Application, Pricing and Risk Management,
(Malden, MA: Blackwell Publishing, 2005).
Chapter 2 – Credit Derivatives Products
Chapter 3 – Synthetic Structures
Chapter 4 – Application of Credit Derivatives
Chapter 6 – Risk Management with Credit Derivatives
6. Saunders, Financial Institutions Management, 5th ed.
Chapter 11 – Credit Risk: Individual Loan Risk
Chapter 12 – Credit Risk: Loan Portfolio and Concentration Risk
Chapter 16 – Sovereign Risk
Chapter 27 – Loan Sales and Other Credit Risk Management Techniques
7. Stulz, Risk Management & Derivatives.
Chapter 18 – Credit Risks and Credit Derivatives
IV. Operational and Integrated Risk Management, Legal – 25%
Aggregated distributions
Allocation of risk capital across the firm
Basel II Accord
1. the three pillars
2. the internal ratings-based approach (foundation and advanced IRB)
3. operational risk (foundation and advanced approach)
Correlations across market, credit, and operational risk
Definition of risk capital
7. Differences between market and operational VaRs
Evaluating the performance of risk management systems
Hedging operational risk using financial engineering
Implementation risks of risk management
Internal models approach for market risk
Insuring operational risk
Legal risk
Liquidity risk
Measuring firm-wide risk
Benefits and costs of firm-wide risk management
Severity and frequency distributions for operational risk
Types of operational risk
Workflow in financial institutions
Operational and Integrated Risk Management, Legal Readings:
1. Allen, Boudoukh, and Saunders, Understanding Market, Credit and Operational Risk:
The Value At Risk Approach.
Chapter 5 – Extending the VaR Approach to Operational Risk
2. Michael Crouhy, Dan Galai, and Robert Mark, Risk Management (New York: McGraw-
Hill, 2001).
Chapter 14 – Capital Allocation and Performance Measurement
3. Christopher L. Culp, The Risk Management Process: Business Strategy and Tactics
(Hoboken: John Wiley & Sons, Inc, 2001).
Chapter 17 – Identifying, Measuring, and Monitoring Liquidity Risk
4. Ellen Davis, ed., The Advanced Measurement Approach to Operational Risk,
(London: Risk Books, 2006).
Chapter 3 – Operational Risk Economic Capital Measurement: Mathematical Models
for Analysing Loss Data, by Gene Alvarez
5. de Servigny, Renault, Measuring and Managing Credit Risk.
Chapter 10 – Regulation
6. Kevin Dowd, Measuring Market Risk, 2nd ed., (West Sussex: John Wiley & Sons, Inc.,
2005).
Chapter 16 - Model Risk
8. 7. Reto Gallati, Risk Management and Capital Adequacy (New York: McGraw-Hill,
2003).
Chapter 6 – Case Studies
8. Kalyvas and Akkizidis, Integrated Market, Credit and Operational Risk: A Complete
Guide for Bankers and Risk Professionals (London: Risk Books, 2006).
Chapter 3 – Operational Risk
9. Andrew Kuritzkes, Til Schuermann and Scott M. Weiner. "Risk Measurement, Risk
Management and Capital Adequacy in Financial Conglomerates." Brookings-Wharton
Papers on Financial Services: 2003. Ed. Robert E. Litan and Richard Herring.
Washington D.C.: Brookings Institutional Press, 2003. Copy of article is available at the
GARP Digital Library website, www.GARPDigitalLibrary.org.
10. Brian W. Nocco and René M. Stulz, 2006, “Enterprise Risk Management: Theory and
Practice,” Journal of Applied Corporate Finance 18 (4), 8 – 20. Copy of the article is
available at the GARP Digital Library website, www.GARPDigitalLibrary.org.
11. Saunders, Financial Institutions Management, 5th ed.
Chapter 14 – Technology and Other Operational Risks
12. Stulz, Risk Management & Derivatives.
Chapter 2 – Investors and Risk Management
Chapter 3 – Creating Value with Risk Management
13. Counterparty Risk Management Policy Group II, July 2005. “Toward Greater
Financial Stability: A Private Sector Perspective. The Report of the Counterparty Risk
Management Policy Group II”. Copy of the full report is available at the GARP Digital
Library website, www.GARPDigitalLibrary.org.
Section I: Introduction
Section II: Executive Summary and Recommendations
Section III: Risk Management and Risk-Related Disclosure Practices
Basel Reference Readings:
Candidates are expected to understand the objective and general structure of the
Basel II Accord and general application of the various approaches for calculating
minimum capital requirements. Candidates are not expected to memorize specific
9. details such as risk weights for different assets.
1. “Basel II: International Convergence of Capital Measurement and Capital Standards:
A Revised Framework – Comprehensive Version” (Basel Committee on Banking
Supervision Publication, June 2006). Copy of the article is available at the GARP
Digital Library website, www.GARPDigitalLibrary.org.
2. “Studies on credit risk concentration: an overview of the issues and a synopsis of
the results from the Research Task Force project” (Basel Committee on Banking
Supervision Publication, November 2006). Copy of the article is available at the GARP
Digital Library website, www.GARPDigitalLibrary.org.
3. “An Explanatory Note on the Basel II IRB Risk Weight Functions” (Basel Committee
on Banking Supervision Publication, July 2005). Copy of the article is available at the
GARP Digital Library website, www.GARPDigitalLibrary.org.
4. Marc R. Saidenberg and Til Schuermann, "The New Basel Accord and Questions for
Research" (May 2003). Wharton Financial Institutions Center Working Paper No. 03-14.
Copy of the article is available at the GARP Digital Library website,
www.GARPDigitalLibrary.org.
Note: This article provides an effective overview of the motivation, objective and
structure of the Basel II Accord and potential issues with its implementation. Specific
details may differ from the final version of the Accord listed above.
V. Risk Management and Investment Management – 10%
Traditional investment risk management
Return metrics (Sharpe ratio, information ratio, VaR, relative VaR, tracking error,
survivorship bias)
Implementing VaR
Benchmarking asset mixes
Risk decomposition and performance attribution
Risk budgeting
10. Tracking error
Setting risk limits
Risk of alpha transfer strategies
Risk management issues of pension funds
Hedge fund risk management
Risk-return metrics specific to hedge funds (drawdown, Sortino ratio)
Risks of specific strategies (fixed-income arbitrage, merger arbitrage, convert
arbitrage, equity long/short-market neutral, macro, distressed debt, emerging
markets)
Asset illiquidity, valuation, and risk measurement
The use of leverage and derivatives and the risks they create
Problems in measuring exposures to risk factors (dynamic strategies, leverage,
derivatives, style drift)
Correlations among hedge funds and between hedge funds and other assets
Risk Management and Investment Management Readings;
1. Noel Amenc and Veronique Le Sourd, Portfolio Theory and Performance Analysis
(West Sussex: Wiley, 2003).
Chapter 4 – The Capital Asset Pricing Model and Its Application to Performance
Measurement
Chapter 6 – Multi-Factor Models and Their Application to Performance Measurement
Chapter 8 – Fixed Income Security Investment
2. Ludwig B. Chincarini, “The Amaranth Debacle: A Failure of Risk Measures or a
Failure of Risk Management?” December 2006. Copy of the article is available at the
GARP Digital Library website, www.GARPDigitalLibrary.org.
3. William Fung and David Hsieh, 2002, “The Risk in Fixed-Income Hedge Fund
Strategies”, Journal of Fixed Income 12, 6-27. Copy of the article is available at the
GARP Digital Library website, www.GARPDigitalLibrary.org.
4. Lars Jaeger, ed., The New Generation of Risk Management for Hedge Funds and
Private Equity Investments, (London: Euromoney Institutional Investor, 2003).
Chapter 6 – Funds of Hedge Funds, by Sohail Jaffer
Chapter 27 – Style Drifts: Monitoring, Detection and Control, by Pierre-Yves Moix
5. Lars Jaeger, Through the Alpha Smoke Screens: A Guide to Hedge Fund Return
11. Sources, (New York: Euromoney Institutional Investor, 2005).
Chapter 5 – Individual Hedge Fund Strategies
Chapter 9 – Benchmarking Hedge Fund Performance
6. Jorion, Value at Risk, 3rd ed.
Chapter 7 – Portfolio Risk: Analytical Methods
Chapter 17 – VaR and Risk Budgeting in Investment Management
7. President’s Working Group on Financial Markets, “Agreement among PWG and U.S.
Agency Principals on Principles and Guidelines Regarding Private Pools of Capital”,
February 2007. Copy of the article is available at the GARP Digital Library website,
www.GARPDigitalLibrary.org.
8. Stulz, René M., "Hedge Funds: Past, Present and Future". Forthcoming in the Journal
of Economic Perspectives, Spring 2007. Copy of the article is available at the GARP
Digital Library website, www.GARPDigitalLibrary.org.