P2.T7. Operational & Integrated Risk Management. Michael Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition
|
|
- Emory Whitehead
- 6 years ago
- Views:
Transcription
1 P2.T7. Operational & Integrated Risk Management Bionic Turtle FRM Practice Questions Michael Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition By David Harper, CFA FRM CIPM
2 CROUHY, CHAPTER 15: MODEL RISK... 3 P2.T MODEL ERROR AND MODEL IMPLEMENTATION RISK
3 Crouhy, Chapter 15: Model Risk P2.T Model error and model implementation risk P2.T Mitigation of model risk P2.T Model error and model implementation risk Learning Objectives: Identify and explain errors in modeling assumptions that can introduce model risk. Explain how model risk can arise in the implementation of a model According to Crouhy, Galai & Mark, JPMorgan's London Whale incident "showed that model risk has no respect for the size or standing of an institution." According to the US Senate's Subcommittee Report, despite portraying itself as an expert in risk management, the bank's Chief Investment Office (CIO) which was charted with managing excess deposits "placed a massive bet on a complex set of synthetic credit derivatives that, in 2012, lost at least $6.2 billion." Which of the following is TRUE as risk management failure that contributed to the loss at JPMorgan's CIO? a) Soon after breaching the bank' and CIO's VaR limit, a new VaR model was adopted (and approved) that reduced the SCP VaR by 50%, enabling the CIO to end its breach b) The CIO switched from its historical practice of marking credit derivative positions at or near the midpoint price in the daily range to assigning the favorable price within the daily price range c) SCP trades routinely breached the limits on all five key metrics used by CIO (ie, VaR, CS01, CSW10%, stress loss, and stop loss), and the breaches were reported to management, but the breaches were largely ignored d) All of the above are true, according to the Senate Subcommittee: the loss was caused by failures in operational risk, model risk, and corporate governance 3
4 Crouhy, Galai & Mark explain that the main cause of model risk are either (i) model error or (ii) implementation. Model error is when "the model might contain mathematical errors or, more likely, be based on simplifying assumptions that are misleading or inappropriate." Implementation is when "the model might be implemented wrongly, either by accident or as part of a deliberate fraud. " Each of the following is a classic example of how model error can be introduced EXCEPT which is the LEAST likely assumption, by itself, to create model error risk? a) To assume an asset's distribution is stationary over time in order to maintain or improve the tractability of the model b) To assume a delta-neutral hedging strategy is risk-free and can be maintained because active re-balancing is unrealistic c) To assume asset returns, follow an empirical distribution simply because the historical data happens to be easily available d) To assume the forward rates--i.e., that are used to value fixed-income instruments--are log normal although interest rates have shifted into a long-term regime of negative territory In regard to model implementation, Crouhy says "even if a model is correct and is being used to tackle an appropriate problem, there remains the danger that it will be wrongly implemented. With complicated models that require extensive programming, there is always a chance that a programming bug may affect the output of the model. Some implementations rely on numerical techniques that exhibit inherent approximation errors and limited ranges of validity. Many programs that seem error-free have been tested only under normal conditions and so may be error-prone in extreme cases and conditions. " With respect to model implementation, which of the following is the BEST pieces of advice? a) Ensure responsibility for data accuracy is clearly assigned b) Remove outliers in all cases because outliers distort skew and kurtosis of the distribution c) Volatility and correlation should be directly observed rather than forecast; if these two inputs cannot be observed, seek an alternative approach d) Seek the maximum length of the sampling period in order to improve the power of statistical tests and reduce estimation errors 4
5 Answers: D. All of the above are TRUE, according to the Senate Subcommittee: the loss was caused by failures in operational risk, model risk, and corporate governance In regard to true (A) which is model risk (emphasis ours): CIO traders, risk personnel, and quantitative analysts frequently attacked the accuracy of the risk metrics, downplaying the riskiness of credit derivatives and proposing risk measurement and model changes to lower risk results for the SCP [Synthetic Credit Portfolio]. In the case of the CIO VaR, after analysts concluded the existing model was too conservative and overstated risk, an alternative CIO model was hurriedly adopted in late January 2012, while the CIO was in breach of its own and the bankwide VaR limit. The bank did not obtain OCC approval as it should have to use the model for the SCP. The CIO s new model immediately lowered the SCP s VaR by 50%, enabling the CIO not only to end its breach, but to engage in substantially more risky derivatives trading. Months later, the bank determined that the model was improperly implemented, requiring error-prone manual data entry and incorporating formula and calculation errors. On May 10, the bank backtracked, revoking the new VaR model due to its inaccuracy in portraying risk, and reinstating the prior model. In regard to true (B) which is an operational risk failure (emphasis ours): "To minimize its reported losses, the CIO began to deviate from the valuation practices it had used in the past to price credit derivatives. In early January, the CIO had typically established the daily value of a credit derivative by marking it at or near the midpoint price in the daily range of prices (bid-ask spread) offered in the market place. Using midpoint prices had enabled the CIO to comply with the requirement that it value its derivatives using prices that were the most representative of fair value. But later in the first quarter of 2012, instead of marking near the midpoint, the CIO began to assign more favorable prices within the daily price range (bid-ask spread) to its credit derivatives. The more favorable prices enabled the CIO to report smaller losses in the daily profit/ loss (P& L) reports that the SCP filed internally within the bank. In regard to true (C), which is a case of poor corporate governance: In contrast to JPMorgan Chase s reputation for best-in-class risk management, the whale trades exposed a bank culture in which risk limit breaches were routinely disregarded, risk metrics were frequently criticized or downplayed, and risk evaluation models were targeted by bank personnel seeking to produce artificially lower capital requirements. The CIO used five key metrics and limits to gauge and control the risks associated with its trading activities, including the Value-at-Risk (VaR) limit, Credit Spread Widening 01 (CS01) limit, Credit Spread Widening 10% (CSW10%) limit, stress loss limits, and stop loss advisories. During the first three months of 2012, as the CIO traders added billions of dollars in complex credit derivatives to the SCP, the SCP trades breached the limits on all five risk metrics. In fact, from January 1 through April 30, 2012, CIO risk limits and advisories were breached more than 330 times. The SCP s many breaches were routinely reported to JPMorgan Chase and CIO management, risk personnel, and traders. The breaches did not, however, spark an in-depth review of the SCP or require immediate remedial actions to lower risk. Instead, the breaches were largely ignored or ended by raising the relevant risk limit. 5
6 C. FALSE: To assume asset returns follow an empirical distribution (simply because the historical data happens to be easily available) is considered an advantage over "theoretical" (ie, parametric) distributions. In regard to (A), (B) and (D), each is cited as an example of model error that can create model risk. In regard to true (A), Crouhy et al say "the most frequent error in model building is to assume that the distribution of the underlying asset is stationary (i.e., unchanging) when in fact it changes over time. The case of volatility is particularly striking. " In regard to true (B), Crouhy et al say "As a practical example, most derivative pricing models are based on the assumption that a delta-neutral hedging strategy can be put in place for the instruments in question i.e., that the risk of holding a derivative can be continually offset by holding the underlying asset in an appropriate proportion (hedge ratio). In practice, a deltaneutral hedge of an option against its underlying asset is far from being completely risk-free, and keeping such a position delta-neutral over time often requires a very active rebalancing strategy. Banks rarely attempt the continuous rebalancing that pricing models assume. For one thing, the theoretical strategy implies the execution of an enormous number of transactions, and trading costs are too large for this to be feasible. Nor is continuous trading possible, even disregarding transactions costs: markets close at night, on national holidays, and on weekends." In regard to true (D), Crouhy et al say "A model can be found to be mathematically correct and generally useful and yet be misapplied to a given situation. For example, some term structure models that are widely used to value fixed-income instruments depend upon the assumption that forward rates are log normal that is, that their rates of change are normally distributed. This model seems to perform relatively well when applied to most of the world s markets with the exception of Japan for the last 10 years and the United States and Europe in the immediate post-crisis years (because central banks implemented quantitative easing monetary policies and flooded the markets with huge amount of liquidity). Post-crisis markets were characterized by very low interest rates, and Japan sometimes exhibited negative rates; in these conditions, different statistical tools (e.g., Gaussian and square root models) for interest rates work much better. " 6
7 A. TRUE: Ensure responsibility for data accuracy is clearly assigned. It's easy to underestimate the importance of data governance, but this seemingly mundane piece of advice is important: if nobody has responsibility, then some of the other rules and guidelines won't be nearly as relevant. In regard to false (B), Crouhy et al say "All statistical estimators are subject to estimation errors involving the inputs to the pricing model. A major problem in the estimation procedure is the treatment of outliers, or extreme observations. Are the outliers really outliers, in the sense that they do not reflect the true distribution? Or are they important observations that should not be dismissed? The results of the estimation procedure will be vastly different depending on how such observations are treated. Each bank, or even each trading desk within a bank, may use a different estimation procedure to estimate the model parameters. " In regard to false (C), Crouhy says "Volatilities and correlations are the hardest input parameters to judge accurately. For example, an option s strike price and maturity are fixed, and asset prices and interest rates can easily be observed directly in the market but volatilities and correlations must be forecast... Throughout the history of the derivatives markets, the fact that model parameters such as volatility and correlation cannot be observed directly has given rise to many opportunities for both genuine mistakes and deliberate tampering that can be countered only through robust control procedures and independent vetting." Finally, Crouhy also writes: "The most frequent problems in estimating values, on the one hand, and assessing the potential errors in valuation, on the other, are: Inaccurate data. Most financial institutions use internal data sources as well as external databases. The responsibility for data accuracy is often not clearly assigned. It is therefore very common to find data errors that can significantly affect the estimated parameters. Inappropriate length of sampling period. Adding more observations improves the power of statistical tests and tends to reduce the estimation errors. But the longer the sampling period, the more weight is given to potentially stale and obsolete information. Especially in dynamically changing financial markets, old data can become irrelevant and may introduce noise into the estimation process. Problems with liquidity and the bid/ ask spread. In some markets, a robust market price does not exist. The gap between the bid and ask prices may be large enough to complicate the process of finding a single value. Choices made about the price data at the time of data selection can have a major impact on the output of the model." Discuss in forum here: 7
P2.T6. Credit Risk Measurement & Management. Michael Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition
P2.T6. Credit Risk Measurement & Management Bionic Turtle FRM Practice Questions Michael Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition By David Harper, CFA FRM CIPM
More informationP2.T5. Market Risk Measurement & Management. Bruce Tuckman, Fixed Income Securities, 3rd Edition
P2.T5. Market Risk Measurement & Management Bruce Tuckman, Fixed Income Securities, 3rd Edition Bionic Turtle FRM Study Notes Reading 40 By David Harper, CFA FRM CIPM www.bionicturtle.com TUCKMAN, CHAPTER
More informationLinda Allen, Jacob Boudoukh and Anthony Saunders, Understanding Market, Credit and Operational Risk: The Value at Risk Approach
P1.T4. Valuation & Risk Models Linda Allen, Jacob Boudoukh and Anthony Saunders, Understanding Market, Credit and Operational Risk: The Value at Risk Approach Bionic Turtle FRM Study Notes Reading 26 By
More informationDowd, Measuring Market Risk, 2nd Edition
P2.T7. Operational & Integrated Risk Management Dowd, Measuring Market Risk, 2nd Edition Bionic Turtle FRM Study Notes Reading 53 By David Harper, CFA FRM CIPM www.bionicturtle.com DOWD CHAPTER 14: ESTIMATING
More informationBasel III: The Liquidity Coverage Ratio and Liquidity Risk Monitoring Tools
P2.T7. Operational & Integrated Risk Management Basel III: The Liquidity Coverage Ratio and Liquidity Risk Monitoring Tools Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com
More informationP2.T5. Market Risk Measurement & Management. BIS # 19, Messages from the Academic Literature on Risk Measuring for the Trading Books
P2.T5. Market Risk Measurement & Management BIS # 19, Messages from the Academic Literature on Risk Measuring for the Trading Books Bionic Turtle FRM Study Notes Reading 38 By David Harper, CFA FRM CIPM
More informationP2.T5. Market Risk Measurement & Management. Bruce Tuckman, Fixed Income Securities, 3rd Edition
P2.T5. Market Risk Measurement & Management Bruce Tuckman, Fixed Income Securities, 3rd Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Tuckman, Chapter 6: Empirical
More informationP2.T8. Risk Management & Investment Management
P2.T8. Risk Management & Investment Management Constantinides, Harris & Stulz, Handbook of the Economics of Finance Fung & Hsieh, Chapter 17: Hedge Funds Bionic Turtle FRM Study Notes Reading 72 By David
More informationP2.T8. Risk Management & Investment Management. Jorion, Value at Risk: The New Benchmark for Managing Financial Risk, 3rd Edition.
P2.T8. Risk Management & Investment Management Jorion, Value at Risk: The New Benchmark for Managing Financial Risk, 3rd Edition. Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM and Deepa Raju
More informationKevin Dowd, Measuring Market Risk, 2nd Edition
P1.T4. Valuation & Risk Models Kevin Dowd, Measuring Market Risk, 2nd Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Dowd, Chapter 2: Measures of Financial Risk
More informationP2.T6. Credit Risk Measurement & Management. Michael Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition
P2.T6. Credit Risk Measurement & Management Michael Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com
More informationAllen, Financial Risk Management: A Practitioner s Guide to Managing Market & Credit Risk
P1.T1. Foundations of Risk Bionic Turtle FRM Practice Questions Reading 4 Allen, Financial Risk Management: A Practitioner s Guide to Managing Market & Credit Risk By David Harper, CFA FRM CIPM www.bionicturtle.com
More informationP2.T8. Risk Management & Investment Management. Zvi Bodie, Alex Kane, and Alan J. Marcus, Investments, 10th Edition
P2.T8. Risk Management & Investment Management Zvi Bodie, Alex Kane, and Alan J. Marcus, Investments, 10th Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Bodie,
More informationP2.T5. Market Risk Measurement & Management. Bionic Turtle FRM Practice Questions Sample
P2.T5. Market Risk Measurement & Management Bionic Turtle FRM Practice Questions Sample Hull, Options, Futures & Other Derivatives By David Harper, CFA FRM CIPM www.bionicturtle.com HULL, CHAPTER 20: VOLATILITY
More informationHull, Options, Futures & Other Derivatives
P1.T3. Financial Markets & Products Hull, Options, Futures & Other Derivatives Bionic Turtle FRM Study Notes Sample By David Harper, CFA FRM CIPM and Deepa Raju www.bionicturtle.com Hull, Chapter 1: Introduction
More informationModel Risk. Alexander Sakuth, Fengchong Wang. December 1, Both authors have contributed to all parts, conclusions were made through discussion.
Model Risk Alexander Sakuth, Fengchong Wang December 1, 2012 Both authors have contributed to all parts, conclusions were made through discussion. 1 Introduction Models are widely used in the area of financial
More informationBrooks, Introductory Econometrics for Finance, 3rd Edition
P1.T2. Quantitative Analysis Brooks, Introductory Econometrics for Finance, 3rd Edition Bionic Turtle FRM Study Notes Sample By David Harper, CFA FRM CIPM and Deepa Raju www.bionicturtle.com Chris Brooks,
More informationP2.T5. Market Risk Measurement & Management. Jorion, Value-at Risk: The New Benchmark for Managing Financial Risk, 3 rd Edition
P2.T5. Market Risk Measurement & Management Jorion, Value-at Risk: The New Benchmark for Managing Financial Risk, 3 rd Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM and Deepa Raju
More informationP2.T5. Market Risk Measurement & Management. Hull, Options, Futures, and Other Derivatives, 9th Edition.
P2.T5. Market Risk Measurement & Management Hull, Options, Futures, and Other Derivatives, 9th Edition. Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Hull, Chapter 9:
More informationStulz, Governance, Risk Management and Risk-Taking in Banks
P1.T1. Foundations of Risk Stulz, Governance, Risk Management and Risk-Taking in Banks Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Stulz, Governance, Risk Management
More informationAmath 546/Econ 589 Introduction to Credit Risk Models
Amath 546/Econ 589 Introduction to Credit Risk Models Eric Zivot May 31, 2012. Reading QRM chapter 8, sections 1-4. How Credit Risk is Different from Market Risk Market risk can typically be measured directly
More informationP2.T6. Credit Risk Measurement & Management. Giacomo De Laurentis, Renato Maino, and Luca Molteni, Developing, Validating and Using Internal Ratings
P2.T6. Credit Risk Measurement & Management Giacomo De Laurentis, Renato Maino, and Luca Molteni, Developing, Validating and Using Internal Ratings Bionic Turtle FRM Practice Questions By David Harper,
More informationHull, Options, Futures & Other Derivatives, 9th Edition
P1.T3. Financial Markets & Products Hull, Options, Futures & Other Derivatives, 9th Edition Bionic Turtle FRM Study Notes Reading 19 By David Harper, CFA FRM CIPM www.bionicturtle.com HULL, CHAPTER 1:
More informationP2.T5. Market Risk Measurement & Management. Jorion, Value-at Risk: The New Benchmark for Managing Financial Risk, 3 rd Edition
P2.T5. Market Risk Measurement & Management Jorion, Value-at Risk: The New Benchmark for Managing Financial Risk, 3 rd Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com
More informationP2.T6. Credit Risk Measurement & Management. Jonathan Golin and Philippe Delhaise, The Bank Credit Analysis Handbook
P2.T6. Credit Risk Measurement & Management Jonathan Golin and Philippe Delhaise, The Bank Credit Analysis Handbook Bionic Turtle FRM Study Notes Reading 42 By David Harper, CFA FRM CIPM www.bionicturtle.com
More informationP2.T5. Tuckman Chapter 9. Bionic Turtle FRM Video Tutorials. By: David Harper CFA, FRM, CIPM
P2.T5. Tuckman Chapter 9 Bionic Turtle FRM Video Tutorials By: David Harper CFA, FRM, CIPM Note: This tutorial is for paid members only. You know who you are. Anybody else is using an illegal copy and
More informationP2.T6. Credit Risk Measurement & Management. Jonathan Golin and Philippe Delhaise, The Bank Credit Analysis Handbook
P2.T6. Credit Risk Measurement & Management Jonathan Golin and Philippe Delhaise, The Bank Credit Analysis Handbook Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Golin,
More informationGaps and the Open. June 23, 2014 Adam Grimes, CIO, Waverly Advisors
Gaps and the Open June 23, 2014 Adam Grimes, CIO, Waverly Advisors Outline: Definitions: What is an opening gap? What is gap closure? Why do markets gap on the open? How might the world be changing? Are
More informationUse of Internal Models for Determining Required Capital for Segregated Fund Risks (LICAT)
Canada Bureau du surintendant des institutions financières Canada 255 Albert Street 255, rue Albert Ottawa, Canada Ottawa, Canada K1A 0H2 K1A 0H2 Instruction Guide Subject: Capital for Segregated Fund
More informationP1.T6. Credit Risk Measurement & Management
Bionic Turtle FRM Practice Questions P1.T6. Credit Risk Measurement & Management Global Topic Drill By David Harper, CFA FRM CIPM www.bionicturtle.com GLOBAL TOPIC DRILL: CREDIT RISK MEASUREMENT & MANAGEMENT...
More informationP2.T8. Risk Management & Investment Management
P2.T8. Risk Management & Investment Management Mirabile, Hedge Fund Investing: A Practical Approach to Understanding Investor Motivation, Manager Profits, and Fund Performance Bionic Turtle FRM Study Notes
More informationValidation of Nasdaq Clearing Models
Model Validation Validation of Nasdaq Clearing Models Summary of findings swissquant Group Kuttelgasse 7 CH-8001 Zürich Classification: Public Distribution: swissquant Group, Nasdaq Clearing October 20,
More information13.1 Quantitative vs. Qualitative Analysis
436 The Security Risk Assessment Handbook risk assessment approach taken. For example, the document review methodology, physical security walk-throughs, or specific checklists are not typically described
More informationIEOR E4602: Quantitative Risk Management
IEOR E4602: Quantitative Risk Management Basic Concepts and Techniques of Risk Management Martin Haugh Department of Industrial Engineering and Operations Research Columbia University Email: martin.b.haugh@gmail.com
More informationP2.T5. Market Risk Measurement & Management. Kevin Dowd, Measuring Market Risk, 2nd Edition
P2.T5. Market Risk Measurement & Management Kevin Dowd, Measuring Market Risk, 2nd Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Dowd Chapter 3: Estimating Market
More informationHull, Options, Futures & Other Derivatives Exotic Options
P1.T3. Financial Markets & Products Hull, Options, Futures & Other Derivatives Exotic Options Bionic Turtle FRM Video Tutorials By David Harper, CFA FRM 1 Exotic Options Define and contrast exotic derivatives
More informationP2.T5. Market Risk Measurement & Management
P2.T5. Market Risk Measurement & Management Kevin Dowd, Measuring Market Risk Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM and Deepa Raju www.bionicturtle.com Dowd Chapter 3: Estimating
More informationINVESTMENT SERVICES RULES FOR RETAIL COLLECTIVE INVESTMENT SCHEMES
INVESTMENT SERVICES RULES FOR RETAIL COLLECTIVE INVESTMENT SCHEMES PART B: STANDARD LICENCE CONDITIONS Appendix VI Supplementary Licence Conditions on Risk Management, Counterparty Risk Exposure and Issuer
More informationP2.T8. Risk Management & Investment Management. Grinold, Chapter 14: Portfolio Construction
P2.T8. Risk Management & Investment Management Grinold, Chapter 14: Portfolio Construction Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com Grinold, Chapter 14: Portfolio
More informationFIN FINANCIAL INSTRUMENTS SPRING 2008
FIN-40008 FINANCIAL INSTRUMENTS SPRING 2008 The Greeks Introduction We have studied how to price an option using the Black-Scholes formula. Now we wish to consider how the option price changes, either
More informationNOTES ON THE BANK OF ENGLAND OPTION IMPLIED PROBABILITY DENSITY FUNCTIONS
1 NOTES ON THE BANK OF ENGLAND OPTION IMPLIED PROBABILITY DENSITY FUNCTIONS Options are contracts used to insure against or speculate/take a view on uncertainty about the future prices of a wide range
More informationThe Greek Letters Based on Options, Futures, and Other Derivatives, 8th Edition, Copyright John C. Hull 2012
The Greek Letters Based on Options, Futures, and Other Derivatives, 8th Edition, Copyright John C. Hull 2012 Introduction Each of the Greek letters measures a different dimension to the risk in an option
More informationFINANCIAL INSTITUTIONS
FINANCIAL INSTITUTIONS Quality Of Trading Risk Management Practices Varies In Financial Institutions Primary Credit Analysts: Prodyot Samanta New York (1) 212-438-2009 prodyot_samanta@ standardandpoors.com
More informationPortfolio Rebalancing:
Portfolio Rebalancing: A Guide For Institutional Investors May 2012 PREPARED BY Nat Kellogg, CFA Associate Director of Research Eric Przybylinski, CAIA Senior Research Analyst Abstract Failure to rebalance
More informationIASB Exposure Drafts Financial Instruments: Classification and Measurement and Fair Value Measurement. London, September 10 th, 2009
International Accounting Standards Board First Floor 30 Cannon Street, EC4M 6XH United Kingdom Submitted via www.iasb.org IASB Exposure Drafts Financial Instruments: Classification and Measurement and
More informationP2.T6. Credit Risk Measurement & Management. Jon Gregory, The xva Challenge: Counterparty Credit Risk, Funding, Collateral, and Capital
P2.T6. Credit Risk Measurement & Management Jon Gregory, The xva Challenge: Counterparty Credit Risk, Funding, Collateral, and Capital Bionic Turtle FRM Study Notes Sample By David Harper, CFA FRM CIPM
More informationP2.T7. Operational & Integrated Risk Management
P2.T7. Operational & Integrated Risk Management Bionic Turtle FRM Practice Questions Marcelo G. Cruz, Gareth W. Peters, and Pavel V. Shevchenko, Fundamental Aspects of Operational Risk and Insurance Analytics:
More informationCredit Risk Modelling: A Primer. By: A V Vedpuriswar
Credit Risk Modelling: A Primer By: A V Vedpuriswar September 8, 2017 Market Risk vs Credit Risk Modelling Compared to market risk modeling, credit risk modeling is relatively new. Credit risk is more
More information2. Criteria for a Good Profitability Target
Setting Profitability Targets by Colin Priest BEc FIAA 1. Introduction This paper discusses the effectiveness of some common profitability target measures. In particular I have attempted to create a model
More informationReconsidering long-term risk quantification methods when routine VaR models fail to reflect economic cost of risk.
Reconsidering long-term risk quantification methods when routine VaR models fail to reflect economic cost of risk. Executive Summary The essay discusses issues and challenges of long-term risk measurement
More informationWeek 2 Quantitative Analysis of Financial Markets Hypothesis Testing and Confidence Intervals
Week 2 Quantitative Analysis of Financial Markets Hypothesis Testing and Confidence Intervals Christopher Ting http://www.mysmu.edu/faculty/christophert/ Christopher Ting : christopherting@smu.edu.sg :
More informationAlgorithmic Trading Session 4 Trade Signal Generation II Backtesting. Oliver Steinki, CFA, FRM
Algorithmic Trading Session 4 Trade Signal Generation II Backtesting Oliver Steinki, CFA, FRM Outline Introduction Backtesting Common Pitfalls of Backtesting Statistical Signficance of Backtesting Summary
More informationMarket Risk Analysis Volume IV. Value-at-Risk Models
Market Risk Analysis Volume IV Value-at-Risk Models Carol Alexander John Wiley & Sons, Ltd List of Figures List of Tables List of Examples Foreword Preface to Volume IV xiii xvi xxi xxv xxix IV.l Value
More informationP1.T4.Valuation Tuckman, Chapter 5. Bionic Turtle FRM Video Tutorials
P1.T4.Valuation Tuckman, Chapter 5 Bionic Turtle FRM Video Tutorials By: David Harper CFA, FRM, CIPM Note: This tutorial is for paid members only. You know who you are. Anybody else is using an illegal
More informationFRBSF ECONOMIC LETTER
FRBSF ECONOMIC LETTER 2010-19 June 21, 2010 Challenges in Economic Capital Modeling BY JOSE A. LOPEZ Financial institutions are increasingly using economic capital models to help determine the amount of
More informationGN47: Stochastic Modelling of Economic Risks in Life Insurance
GN47: Stochastic Modelling of Economic Risks in Life Insurance Classification Recommended Practice MEMBERS ARE REMINDED THAT THEY MUST ALWAYS COMPLY WITH THE PROFESSIONAL CONDUCT STANDARDS (PCS) AND THAT
More informationERM and ORSA Assuring a Necessary Level of Risk Control
ERM and ORSA Assuring a Necessary Level of Risk Control Dave Ingram, MAAA, FSA, CERA, FRM, PRM Chair of IAA Enterprise & Financial Risk Committee Executive Vice President, Willis Re September, 2012 1 DISCLAIMER
More informationAlgorithmic Trading Session 12 Performance Analysis III Trade Frequency and Optimal Leverage. Oliver Steinki, CFA, FRM
Algorithmic Trading Session 12 Performance Analysis III Trade Frequency and Optimal Leverage Oliver Steinki, CFA, FRM Outline Introduction Trade Frequency Optimal Leverage Summary and Questions Sources
More informationArnaud de Servigny and Olivier Renault, Measuring and Managing Credit Risk
P1.T4. Valuation & Risk Models Arnaud de Servigny and Olivier Renault, Measuring and Managing Credit Risk Bionic Turtle FRM Study Notes Reading 33 By David Harper, CFA FRM CIPM www.bionicturtle.com DE
More informationIt doesn't make sense to hire smart people and then tell them what to do. We hire smart people so they can tell us what to do.
A United Approach to Credit Risk-Adjusted Risk Management: IFRS9, CECL, and CVA Donald R. van Deventer, Suresh Sankaran, and Chee Hian Tan 1 October 9, 2017 It doesn't make sense to hire smart people and
More informationCatastrophe Reinsurance Pricing
Catastrophe Reinsurance Pricing Science, Art or Both? By Joseph Qiu, Ming Li, Qin Wang and Bo Wang Insurers using catastrophe reinsurance, a critical financial management tool with complex pricing, can
More informationHull, Options, Futures, and Other Derivatives, 9 th Edition
P1.T4. Valuation & Risk Models Hull, Options, Futures, and Other Derivatives, 9 th Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM and Deepa Sounder www.bionicturtle.com Hull, Chapter
More informationCABARRUS COUNTY 2008 APPRAISAL MANUAL
STATISTICS AND THE APPRAISAL PROCESS PREFACE Like many of the technical aspects of appraising, such as income valuation, you have to work with and use statistics before you can really begin to understand
More informationWeek 1 Quantitative Analysis of Financial Markets Distributions B
Week 1 Quantitative Analysis of Financial Markets Distributions B Christopher Ting http://www.mysmu.edu/faculty/christophert/ Christopher Ting : christopherting@smu.edu.sg : 6828 0364 : LKCSB 5036 October
More informationDo You Really Understand Rates of Return? Using them to look backward - and forward
Do You Really Understand Rates of Return? Using them to look backward - and forward November 29, 2011 by Michael Edesess The basic quantitative building block for professional judgments about investment
More informationWHY PORTFOLIO MANAGERS SHOULD BE USING BETA FACTORS
Page 2 The Securities Institute Journal WHY PORTFOLIO MANAGERS SHOULD BE USING BETA FACTORS by Peter John C. Burket Although Beta factors have been around for at least a decade they have not been extensively
More informationObtaining Predictive Distributions for Reserves Which Incorporate Expert Opinions R. Verrall A. Estimation of Policy Liabilities
Obtaining Predictive Distributions for Reserves Which Incorporate Expert Opinions R. Verrall A. Estimation of Policy Liabilities LEARNING OBJECTIVES 5. Describe the various sources of risk and uncertainty
More informationAlternative VaR Models
Alternative VaR Models Neil Roeth, Senior Risk Developer, TFG Financial Systems. 15 th July 2015 Abstract We describe a variety of VaR models in terms of their key attributes and differences, e.g., parametric
More informationMathematics of Financial Derivatives
Mathematics of Financial Derivatives Lecture 8 Solesne Bourguin bourguin@math.bu.edu Boston University Department of Mathematics and Statistics Table of contents 1. The Greek letters (continued) 2. Volatility
More informationINVESTMENT PERFORMANCE COUNCIL ADOPTION OF THE GUIDANCE STATEMENT ON THE TREATMENT OF SIGNIFICANT CASH FLOWS
INVESTMENT PERFORMANCE COUNCIL ADOPTION OF THE GUIDANCE STATEMENT ON THE TREATMENT OF SIGNIFICANT CASH FLOWS SUMMARY: In July 2001, the Association for Investment Management and Research (AIMR ) released
More informationWorking Paper October Book Review of
Working Paper 04-06 October 2004 Book Review of Credit Risk: Pricing, Measurement, and Management by Darrell Duffie and Kenneth J. Singleton 2003, Princeton University Press, 396 pages Reviewer: Georges
More informationCopyright by Profits Run, Inc. Published by: Profits Run, Inc Beck Rd Unit F1. Wixom, MI
DISCLAIMER: Stock, forex, futures, and options trading is not appropriate for everyone. There is a substantial risk of loss associated with trading these markets. Losses can and will occur. No system or
More informationBack- and Side Testing of Price Simulation Models
Back- and Side Testing of Price Simulation Models Universität Duisburg Essen - Seminarreihe Energy & Finance 23. Juni 2010 Henrik Specht, Vattenfall Europe AG The starting point Question: How do I know
More informationSpread Risk and Default Intensity Models
P2.T6. Malz Chapter 7 Spread Risk and Default Intensity Models Bionic Turtle FRM Video Tutorials By: David Harper CFA, FRM, CIPM Note: This tutorial is for paid members only. You know who you are. Anybody
More informationTestimony Before The Financial Services Committee Subcommittee on Financial Institutions and Consumer Credit U.S. House of Representatives
1399 New York Avenue, NW Washington, DC 20005-4711 Telephone 202.434.8400 Fax 202.434.8456 www.bondmarkets.com 360 Madison Avenue New York, NY 10017-7111 Telephone 646.637.9200 Fax 646.637.9126 St. Michael
More informationAiming at a Moving Target Managing inflation risk in target date funds
Aiming at a Moving Target Managing inflation risk in target date funds Executive Summary This research seeks to help plan sponsors expand their fiduciary understanding and knowledge in providing inflation
More informationGIPS Workshop. Laura Jirele-Borleske, CFA, CIPM, IACCP Jed Schneider, CIPM, FRM
GIPS Workshop Laura Jirele-Borleske, CFA, CIPM, IACCP Jed Schneider, CIPM, FRM Agenda GIPS Reasons for Compliance GIPS Upcoming Guidance Statements and GIPS 20:20 GIPS Hot Topics Recent SEC Actions GIPS
More informationGuidance paper on the use of internal models for risk and capital management purposes by insurers
Guidance paper on the use of internal models for risk and capital management purposes by insurers October 1, 2008 Stuart Wason Chair, IAA Solvency Sub-Committee Agenda Introduction Global need for guidance
More informationP2.T6. Credit Risk Measurement & Management. Moorad Choudhry, Structured Credit Products: Credit Derivatives & Synthetic Sercuritization, 2nd Edition
P2.T6. Credit Risk Measurement & Management Moorad Choudhry, Structured Credit Products: Credit Derivatives & Synthetic Sercuritization, 2nd Edition Bionic Turtle FRM Study Notes By Nicole Seaman and David
More informationTHE PANEL ON TAKEOVERS AND MERGERS DEALINGS IN DERIVATIVES AND OPTIONS
RS 2005/2 Issued on 5 August 2005 THE PANEL ON TAKEOVERS AND MERGERS DEALINGS IN DERIVATIVES AND OPTIONS STATEMENT BY THE CODE COMMITTEE OF THE PANEL FOLLOWING THE EXTERNAL CONSULTATION PROCESSES ON DISCLOSURE
More informationP1.T1. Foundations of Risk. Bionic Turtle FRM Practice Questions. Zvi Bodie, Alex Kane, and Alan J. Marcus, Investments, 10th Edition
P1.T1. Foundations of Risk Bionic Turtle FRM Practice Questions Zvi Bodie, Alex Kane, and Alan J. Marcus, Investments, 10th Edition By David Harper, CFA FRM CIPM www.bionicturtle.com Bodie, Chapter 10:
More informationCambridge, Ontario Tuesday, May 6, 2008 CHECK AGAINST DELIVERY. For additional information contact:
Remarks by Superintendent Julie Dickson Office of the Superintendent of Financial Institutions Canada (OSFI) to the Langdon Hall Financial Services Forum Cambridge, Ontario Tuesday, May 6, 2008 CHECK AGAINST
More informationJohn Hull, Risk Management and Financial Institutions, 4th Edition
P1.T2. Quantitative Analysis John Hull, Risk Management and Financial Institutions, 4th Edition Bionic Turtle FRM Video Tutorials By David Harper, CFA FRM 1 Chapter 10: Volatility (Learning objectives)
More informationApplication of Conditional Autoregressive Value at Risk Model to Kenyan Stocks: A Comparative Study
American Journal of Theoretical and Applied Statistics 2017; 6(3): 150-155 http://www.sciencepublishinggroup.com/j/ajtas doi: 10.11648/j.ajtas.20170603.13 ISSN: 2326-8999 (Print); ISSN: 2326-9006 (Online)
More informationXSG. Economic Scenario Generator. Risk-neutral and real-world Monte Carlo modelling solutions for insurers
XSG Economic Scenario Generator Risk-neutral and real-world Monte Carlo modelling solutions for insurers 2 Introduction to XSG What is XSG? XSG is Deloitte s economic scenario generation software solution,
More informationBest Practices for Model Portfolio Performance
Best Practices for Model Portfolio Performance L. Todd Juillerat, CFA Managing Director XXXXXX 0000 Acknowledgements The CFA Institute United States Investment Performance Committee (USIPC) Suggested Practices:
More informationThree Components of a Premium
Three Components of a Premium The simple pricing approach outlined in this module is the Return-on-Risk methodology. The sections in the first part of the module describe the three components of a premium
More informationMarch 9, 2017 PORTFOLIO PROTECTION TECHNIQUES By Mike Halloran, CFA Investment Strategist
March 9, 2017 PORTFOLIO PROTECTION TECHNIQUES By Mike Halloran, CFA Investment Strategist The stock market has been on a historic run higher since last fall. The good news is that global economic growth
More informationBruce Tuckman, Angel Serrat, Fixed Income Securities: Tools for Today s Markets, 3rd Edition
P1.T3. Financial Markets & Products Bruce Tuckman, Angel Serrat, Fixed Income Securities: Tools for Today s Markets, 3rd Edition Bionic Turtle FRM Study Notes By David Harper, CFA FRM CIPM www.bionicturtle.com
More informationFRTB. NMRF Aggregation Proposal
FRTB NMRF Aggregation Proposal June 2018 1 Agenda 1. Proposal on NMRF aggregation 1.1. On the ability to prove correlation assumptions 1.2. On the ability to assess correlation ranges 1.3. How a calculation
More informationDerivatives Valuation
yale program on financial stability case study 2014-2b-v1 december 1, 2014 JPMorgan Chase London Whale B: 1 Derivatives Valuation Arwin G. Zeissler 2 Andrew Metrick 3 Abstract After consistently producing
More informationAsset allocation FOR PROFESSIONAL CLIENTS ONLY NOT FOR RETAIL USE OR DISTRIBUTION
Asset allocation FOR PROFESSIONAL CLIENTS ONLY NOT FOR RETAIL USE OR DISTRIBUTION Plotting a path to retirement success In defined contribution (DC) plans, making effective asset allocation decisions
More informationCrisis and Risk Management
THE NEAR CRASH OF 1998 Crisis and Risk Management By MYRON S. SCHOLES* From theory, alternative investments require a premium return because they are less liquid than market investments. This liquidity
More informationCHAPTER II LITERATURE STUDY
CHAPTER II LITERATURE STUDY 2.1. Risk Management Monetary crisis that strike Indonesia during 1998 and 1999 has caused bad impact to numerous government s and commercial s bank. Most of those banks eventually
More informationTAXATION CONSIDERATIONS IN ECONOMIC DAMAGES CALCULATIONS
TAXATION CONSIDERATIONS IN ECONOMIC DAMAGES CALCULATIONS By Jonathan S. Shefftz Abstract Present value cash flow calculations for economic damages should be performed on an after-tax basis, regardless
More informationA whale in shallow waters: JPMorgan Chase, the London Whale and the organisational catastrophe of 2012
A whale in shallow waters: JPMorgan Chase, the London Whale and the organisational catastrophe of 2012 François Valérian General Engineer of the Mines, General Council for the Economy, Associate Professor
More informationLWord. The. Go beyond the boundaries of leverage ratios to understand hedge fund risk. Hedge fund trading strategies
The LWord Go beyond the boundaries of leverage ratios to understand hedge fund risk. by Peter KleIn There are few practices that are as subject to preconceived notions as the L word. In modern finance
More informationAMA Implementation: Where We Are and Outstanding Questions
Federal Reserve Bank of Boston Implementing AMA for Operational Risk May 20, 2005 AMA Implementation: Where We Are and Outstanding Questions David Wildermuth, Managing Director Goldman, Sachs & Co Agenda
More informationMORNING SESSION. Date: Thursday, November 1, 2018 Time: 8:30 a.m. 11:45 a.m. INSTRUCTIONS TO CANDIDATES
Quantitative Finance and Investment Advanced Exam Exam QFIADV MORNING SESSION Date: Thursday, November 1, 2018 Time: 8:30 a.m. 11:45 a.m. INSTRUCTIONS TO CANDIDATES General Instructions 1. This examination
More informationFinal draft RTS on the assessment methodology to authorize the use of AMA
Management Solutions 2015. All rights reserved. Final draft RTS on the assessment methodology to authorize the use of AMA European Banking Authority www.managementsolutions.com Research and Development
More information