Pragya the best FRM revision course! FRM 2017 Part 2 Book 2 Credit Risk Measurement and Management

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1 Pragya the best FRM revision course! FRM 2017 Part 2 Book 2 Credit Risk Measurement and Management

2 Pragya the best FRM revision course!

3 CREDIT DECISION Reading: The Credit Decision (Chapter 1, Jonathan Golin and Philippe Delhaise, The Bank Credit Analysis Handbook (Hoboken, NJ: John Wiley & Sons, 2013)) 1. Credit Risk: It is the probability that the borrower will not repay the loan in accordance to the terms of agreement 2. Components of Credit Risk: a. The capacity and willingness to repay of obligor b. External environment (Operating conditions, country risk, etc.) c. Characteristic of relevant credit instrument (Product, facility, issue etc.) d. Quality and sufficiency of any credit risk mitigants (Collateral, Guarantees, Credit enhancements etc.) 3. Qualitative & Quantitative Techniques: a. Qualitative technique are primarily used to assess the borrowers willingness to repay the loan and quantitative techniques are used to assess the ability to repay b. Gathering information from different sources, face to face interviews, past loan information etc. are used as some qualitative techniques c. Analyzing financial statements is the primary quantitative technique 4. Measures to evaluate credit risk: a. PD (Probability of default): Likelihood that borrower will default b. LGD (Loss Given default): Likely percentage loss in case of default c. EAD(Exposure at Default): Amount outstanding at time of default d. EL (Expected Loss): PD x LGD x EAD 5. Bank Solvency: Bank insolvency does not mean that bank failure. A bank maybe insolvent but avoid failure as long as it has sources of liquidity like the Federal Reserve.

4 CREDIT ANALYST Reading: The Credit Analyst (Chapter 2, Jonathan Golin and Philippe Delhaise, The Bank Credit Analysis Handbook (Hoboken, NJ: John Wiley & Sons, 2013)) 1. Credit Analyst Roles: a. Consumer Credit Analyst: Works with individual consumer mortgages, with key objective being detailed documentation b. Credit Modelling Analyst: Focused on electronic scoring system, roles include developing, testing, implementing and updating various credit scoring systems c. Corporate Credit Analyst: Scope of analyst is limited to corporations. d. Counterparty Credit Analyst: Analyze two-way counterparties, performs credit reviews, approves limits, develops/ updates credit policies and procedures 2. Functions: a. Counterparty Credit Analyst: Perform risk evaluation of a given entity on a transaction by transaction basis or through annual review. Additionally, she may be required for compliance tasks related to Basel 2 and 3 b. Fixed Income and Equity Analyst: Provide recommendations whether to buy, sell or hold securities. Fixed income analysts focus on determining relative value while equity analyst focus on return on equity 3. Basic Skills: a. Able to read and interpret financial statements b. Background in statistical concepts and macroeconomics 4. Sources of Information: a. Corporation websites, internet, rating agencies report, regulatory filings etc.

5 KEY CONCEPTS OF CREDIT RISK Reading: Classifications and Key Concepts of Credit Risk (Chapter 2, Giacomo De Laurentis, Renato Maino, and Luca Molteni, Developing, Validating and Using Internal Ratings (West Sussex, UK: John Wiley & Sons, 2010)) 1. Definitions: a. Credit Ratings: They are a measure of borrower s credit worthiness b. Default Risk: Counterparty risk or default risk relates to a borrower s inability to make promised payments. i. Recovery Risk: Recovered amount in the event of default is less than full amount ii. Exposure Risk: Credit exposure at time of default increases relative to its current exposure c. Valuation Risk: i. Migration Risk: Credit quality and market value of an asset position could deteriorate over time ii. Spread Risk: Spreads may change during adverse market conditions iii. Liquidity Risk: Asset liquidity and value deteriorate during adverse market conditions d. Marginal VaR: calculated incremental portfolio risk from an individual exposure e. Economic Value Add: Measures economic profit and looks at additional returns generated relative to cost of capital 2. Probability of Default: It can be determined using the following: a. Analyzing historical default frequencies of a borrower s homogenous asset class b. Using mathematical and statistical tools c. Using a hybrid approach d. Extracting implicit default probabilities from market prices of publicly listed counterparties 3. Issues with VaR(Value at Risk) and EL(Expected Loss) a. Do not account for concentration risk

6 RATING ASSIGNMENT Reading: Ratings Assignment Methodologies (Chapter 3, Giacomo De Laurentis, Renato Maino, and Luca Molteni, Developing, Validating and Using Internal Ratings (West Sussex, UK: John Wiley & Sons, 2010)) 1. Definitions: a. Migration frequency: describes how often ratings change from one class to another b. Annualized Default Rate: A multi-year cumulative default rate can be broken down into a yearly ADR c. LDA (Linear Discriminant Analysis): Reduced form model to develop scores to mae accept or reject decision d. LOGIT (Logistic Regression): Model use to predict default based on relationships between independent and dependent variables e. Cluster Analysis: Identifies groups of similar data sets helping aggregate and segregate borrowers f. Cash Flow Analysis: Used to assign ratings to companies that don t have historical data g. Heuristic methods: Predict default by mirroring human decision making process 2. Good Rating system: a. Objectivity and Homogeneity: Ratings are comparable across market and only on credit risk b. Specificity: It measures distance to default while ignoring other elements not tied to default c. Measurability and verifiability: ratings are back tested and provide correct expectation of default 3. Default: Probability of Default (PD) Cumulative PD Marginal PD PD k = defaulted t t+k total number t PD k = i=t+k i=t defaulted total number t i PD marginal k = PD cumulative cumulative t+k PD t 4. ADR (Annualized Default Rate): t cumulative a. Discrete ADR: 1 1 PD t b. Continuous ADR: ln (1 PD t cumulative ) t 5. Structural approach vs. reduced form approach a. Structural approach (Merton model): Building a model involves estimating formal relationships that link relevant variables of the model

7 b. Reduced form models(statistical or numerical): use variables that are statistically suitable without factoring in theoretical relationships among variables 6. Merton Model (Distance to Default): DtD = standard deviation of asset value ln V ln F where F is face value of debt, V is asset value σ is σ A

8 CREDIT RISK AND DERIVATIVES Reading: Default Risk: Credit Risks and Credit Derivatives (Chapter 18, René Stulz, Risk Management & Derivatives (Florence, KY: Thomson South-Western, 2002)) 1. Merton Model: Refer previous chapter for notes 2. Credit Spreads: It is the difference between the yield on risk bond and risk free bond. As the time to maturity increases credit spreads tend to widen. As risk free rate increases, value of firm increases, which in turn decreases risk of default 3. Firm Volatility: Delta is the rate of change of the call option relative to change in value of the underlying asset. Changes in Delta indicate the value of equity volatility is not constant ad I referred to as volatility smirk. The nonconstant volatility is a violation of BSM 4. Subordinate Debt: In distress (low firm value), volatility of financial firm will increase, value of subordinate debt will increase while value of senior debt will decline. This is because subordinate debt behaves like equity when the firm has low value and behaves like senior debt when the firm is not in financial distress 5. Interest rate Dynamics: Increases in interest rate will decrease the value of debt. To hedge debt, we need to account for the interactions between changing interest rate and firm value. 6. Difficulties with Merton Model: a. Firms capital structure is more complex than assumed b. Merton model does not allow for jumps in the firm value (Defaults are surprises) c. PD using Merton Model: PD = N ( ln(f) ln(v) μ(t t)+0.5σ2 (T t) ) and σ T t LGD = F PD Ve μ(t t) N ( ln(f) ln(v) μ(t t) 0.5σ2 (T t) ) where σ T t i. F is face value of zero coupon bond, ii. V is value of firm, iii. T is maturity date of bond, iv. σ is volatility of firm value, v. μ is expected return on value of firm

9 7. Credit Risk Portfolio Models: Model Name Credit Risk+ Credit Metrics Moody s KMV Credit Portfolio View Explanation Measures credit risk using common risk factors. There are only two outcomes: Default or no-default. The PD is dependent on the credit ratings and sensitivity to each risk factor. All risk factors have a mean value of +1. The risk factors are assumed to follow a gamma distribution. If the value of risk factor increases, the probability of default increases It is used to calculate credit VaR of large portfolios. Calculate PV of all debt flows using forward rates obtained from the spot rate curve for each rating category. Multiply the probability of rating change with the mean value obtained. IN cumulative probability, look at significance level and the value is VaR It calculates EDF(Expected Default Frequency) for each obligor. It solves for firm value and volatility. The primary advantage is that it uses current equity values It models the rating transition matrix using macroeconomic cycle data. Macroeconomic factors are considered the prime moving factors in default rates. 8. Credit Derivatives: a. Credit Default Put: It pays on maturity on the default of the debt. b. Credit Default Swap: The purchaser of CDS seeks credit protection. The purchaser will make fixed payments to the seller of CDS for the life of the swap or until a credit event occurs c. Total Rate of Return Swaps (TORR): The exchange of total return on a bond for a floating rate (e.g.libor) plus a specified spread. The total return also includes both capital gains and cash flows (e.g. Coupons) over the life of the swap d. Vulnerable Options: An option holder receives the option payment only if the seller of the option is able to make the payments. The correlation between the value of the firm and the underlying asset value is important for valuation of the vulnerable options.

10 SPREAD RISK AND DEFAULT INTENSITY Reading: Spread Risk and Default Intensity Models (Chapter 7, Allan Malz, Financial Risk Management: Models, History, and Institutions (Hoboken, NJ: John Wiley & Sons, 2011)) 1. Credit Spreads: Difference in yields between the security and a reference security of the same maturity a. Yield Spread: YTM Risky Bond YTM of govt. Bond b. i-spread: YTM Risky Bond Linearly interpolated YTM of govt. bond c. z-spread(zero coupon): spread that must be added to the Libor spot curve to arrive at the market price d. asset-swap spread: spread on the floating leg of an asset swap on a bond e. credit default swap spread: is the market premium of a CDS on similar bonds of the same issuer f. Option adjusted spread: version of the z-spread that takes account of options embedded in the bonds 2. Spread 01: Change in the bond price from a 1 basis point change in the z spread 3. Hazard Rate: The hazard rate, also called the default intensity, denoted λ, is the parameter driving default a. Cumulative probability of default is given as 1 e λt and that of survival is e λt b. As t grows large, default probability converges to 1 and survival probability to 0 4. Risk neutral hazard rates: λ t Z t 1 RR 5. Advantages of Using CDS for Hazard Rate: Primary advantage is that CDS rates are observable. CDS has large liquid contracts for longer maturities. 6. Spread Risk: Change in the value of securities from changing spreads. Entire CDS curve is shocked p and down by 0.5 basis points to compute the CDS mark to market value. Spread risk can also be measured by the historical or forward looking standard deviation of credit spreads.

11 PORTFOLIO CREDIT RISK Reading: Portfolio Credit Risk (Chapter 8, Allan Malz, Financial Risk Management: Models, History, and Institutions (Hoboken, NJ: John Wiley & Sons, 2011)) 1. Default Correlation: the likelihood of having multiple defaults in a portfolio of debt issued by several obligors. a. ρ 12 = π 12 π 1 π 2 π 1 (1 π 1 ) π 2 (1 π 2 ) 2. Credit VaR: Defined as the quantile of the credit loss less the expected loss a. If default correlation in a portfolio of credits is equal to 1, then the portfolio behaves as if it consisted of just one credit. No credit diversification is achieved b. If default correlation is equal to 0, then the number of defaults in the portfolio is a binomially distributed random variable c. Credit VaR is higher for higher probability of default but decreases as credit portfolio becomes more granular, that is, contains more independent credits, each of which is a smaller fraction of the portfolio 3. Single Factor Model (Conditional Default Model): Used to examine impact of varying default correlation based on a credit position. Each firm i, has a default correlation βi with market return m. The firms asset return is 2 2 defined as: a i = β i m + 1 β i ε i where mean is β i m and standard deviation is 1 β i 4. Credit VaR with Single Factor Model (Unconditional Distribution): x(m) = Φ [ k βm 2] where m is realized market return, β 2 is default correlation and Φ means standard normal value. The probability of reaching the default threshold is the same as the probability that market return is m or lower i.e. Φ(m). 5. Credit VaR using Copula: Define the copula function, simulate default times, obtain market values and profit and loss data for each scenario, compute portfolio distribution statistics 1 β

12 STRUCTURED CREDIT RISK Reading: Portfolio Credit Risk (Chapter 9, Allan Malz, Financial Risk Management: Models, History, and Institutions (Hoboken, NJ: John Wiley & Sons, 2011)) 1. Definitions: a. Securitization: Pooling of credit sensitive assets and creation of new securities b. Capital Structure: Refers to the priority assigned to the tranches of a securitized asset c. Credit Enhancements: can be external or internal i. External: Credit protection is through swaps or insurance. ii. Internal: Over-collaterlization or excess spread provide credit protection d. Waterfall Structure: Outlines rules that govern distribution of cash flows to different tranches e. Default 01: PD is shocked by 10 bps and tranches are revalued using simulations 2. Three-tiered Securitization Structure: a. Has three tranches (Equity, Mezzanine and Senior) b. Equity tranche has the lowest priority 3. Simulation of Credit losses a. Estimate parameters like Default rate, pair-wise correlations and generate simulation b. Compute losses for each simulation run 4. Effects on Tranche Values a. Senior Tranche i. As PD or Correlations increase, value of Senior tranche declines b. Equity Tranche i. As Correlation increases, value of equity tranche increases ii. As PD increases, value of Equity tranche decreases c. Mezzanine Tranche i. When PD and correlations are low, it resembles a Senior tranche ii. When PD and correlation are high, it resembles a equity tranche

13 DEFINING COUNTERPARTY CREDIT RISK Reading: Defining Counterparty Credit Risk (Chapter 3, Jon Gregory, Counterparty Credit Risk and Credit Value adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012). 1. Definitions: a. Counterparty Credit Risk: Counterparty is unable or unwilling to fulfill contractual obligations b. Repos: Short term lending agreements usually secured by collateral. c. Credit Exposure: Loss that is conditional on counterparty defaulting 2. Methods to manage counterparty risk: a. Cross Product netting: Netting agreement allows counter parties to net cross-product payments b. Close-out: Immediate closing of all contracts with a counter party c. Collateralization: Collateral to support net exposure between counter parties d. Walk-away: Allows party to cancel all transactions if a counterparty defaults e. Central Counterparties: Routing transactions through exchanges

14 NETTING, COMPRESSION, RESETS AND TERMINATION Reading: (Chapter 4, Jon Gregory, Counterparty Credit Risk and Credit Value adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012). 1. Definitions: a. ISDA Agreement: International Swaps and Derivative Association (ISDA)Master agreement standardizes OTC agreements to reduce legal certainties and mitigate credit risk b. Acceleration Clause: Allows acceleration of future payments on some credit events c. Reset agreement: readjusts parameters that are heavily in the money by resetting the trade to be at the money d. Trade Compression: Reduction in net exposure by removing portfolio redundancies among trade with multiple counterparties 2. Netting and Close out: a. Netting refers to combining cash flows from different contracts with the same counterparty into a single net amount b. Close out netting: netting of contract values in the event of counterparties default

15 COLLATERAL Reading: (Chapter 5, Jon Gregory, Counterparty Credit Risk and Credit Value adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012). 1. Definitions: a. Collateral: An asset supporting a risk in legally enforceable way b. Valuation Agent: Calculate exposure, credit support amounts, delivery or return of collateral c. Credit Support Annex: Incorporated into ISDA agreement allows parties to mitigate credit risk through posting of collateral d. Threshold: Level of exposure below which collateral will not be called e. Rehypothecation: refers to posting of collateral to other counterparties 2. Types of Collateral Used: Cash, Government Securities. Can also include MBS, Corporate Bonds, and Commercial Paper

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17 CENTRAL COUNTERPARTIES Reading: Central Counterparties (Chapter 7, Jon Gregory, Counterparty Credit Risk and Credit Value Adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012)) 1. Objective of CCP: To reduce counterparty risks and provide a safety net for systemic risks 2. Functions of CCP: a. CCP positions itself between two parties of a transaction, this is called novation b. Requires initial as well as variation margins c. Maintains a fund called default fund or reserve fund 3. Weakness of CCP: a. OTC derivatives are illiquid, long-dated and complex compared to exchange traded derivatives and hence are a challenge b. CCP s clearing OTC products will become systemically important themselves creating a moral hazard during times of distress c. CCP s introduce more costs d. Mutualisation means all members are treated in the same way. Most credit-worthy members may see less advantage of their stronger credit quality. 4. Loss Waterfall Model: Example: Current Annual profits

18 CREDIT EXPOSURE Reading: Credit Exposure (Chapter 8, Jon Gregory, Counterparty Credit Risk and Credit Value Adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012)) 1. Definitions: a. Expected Exposure(EE): Amount that is expected to be lost in case of positive MtM b. Potential Future Exposure(PFE): Estimate of MtM value at some point in the future or the worst exposure at a given time interval in the future for a given confidence level c. Expected Positive Exposure(EPE): It is the average EE through time d. Effective EE: Non-decreasing EE. Used to capture risk for roll-over transactions e. Effective EPE: Average of Effective EE f. Re-margin Period: Period from which a collateral call takes place to when the collateral is actually delivered 2. Calculating EE and PFE 2 a. EE: 0.4 σ E T M years 2 b. PFE: k σ E T M 2 where σ E is volatility of collateralized exposure and T M is re-margin frequency in where k is a constant depending on the confidence level (e.g. for 99% k=2.33) 2 c. Volatility if there are non-cash collateral: σ σ 2 2 2σ 1 σ 2 ρ where σ 1 and σ 2 are volatilities of underlying and collateral 3. Disadvantages of PFE: a. It assumes a strongly collateralized position b. It fails to account for collateral volatility c. Liquidity and liquidation risks are not considered d. Wrong way risk is not considered

19 DEFAULT PROBABILITY, CREDIT SPREADS Reading: Default Probability, Credit Spreads, and Credit Derivatives (Chapter 10, Jon Gregory, Counterparty Credit Risk and Credit Value Adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012)) 1. Definitions: a. Cumulative Default Probability: Represents the likelihood of counterparty default from current time to a future date b. Marginal Default Probability: Likelihood of counterparty default between two future points in time c. Risk neutral default probability: Calculated from market information. They represent parameter value from observed market price d. Real world default probability: Calculated from historical data 2. Estimation approaches: a. Historical data approach: Use historical default data to forecast future default probabilities b. Equity based: Merton model, KMV are examples. It allows for dynamic approach to calculation i. Merton Model: Equity value is call option with strike price as debt level. All debt is considered as a single coupon payable at maturity. ii. KMV: Relaxes certain assumptions in the Merton model 3. Index Tranches: a. They create a capital structure for credit index whereby the loss is divided into mutually exclusive ranges. The losses are absorbed sequentially by equity, mezzanine, senior and super-senior tranches

20 CREDIT VALUE ADJUSTMENT Reading: Credit Value Adjustment (Chapter 12, Jon Gregory, Counterparty Credit Risk and Credit Value Adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012)) 1. Definitions: a. Credit Value: It is the price of counterparty credit risk. A positive CVA increases the costs of the m counterparty. It is calculated as CVA = LGD i=0 d(t i ) EE(t i ) PD(t i 1, t i ) i. d(t i ) are discount factors for future losses b. Incremental CVA: it is the change in CVA that a new trade will create c. Marginal CVA: Breaks down netted trades into trade level contributions to the sum total of CVA 2. CVA as running spread a. To calculate a running spread, the following formula is used Spread = EPE Credit Spread b. This is the amount a trader adds or subtracts from a trade leg as CVA 3. Impact of changes of Credit Spread/ Recovery rates on CVA a. CVA increases with increase in Credit Spread b. Increase in Recovery rate will reduce the CVA

21 WRONG WAY RISK Reading: Wrong Way Risk (Chapter 15, Jon Gregory, Counterparty Credit Risk and Credit Value Adjustment: A Continuing Challenge for Global Financial Markets, 2nd Edition (West Sussex, UK: John Wiley & Sons, 2012)) 1. Definitions: a. Wrong way Risk: Outcome of an association, dependence or linkage between exposure and counterparty creditworthiness that generates an increase in counterparty risk.

22 CREDIT SCORING Reading: Credit Scoring and Retail Credit Risk Management (Chapter 9, Michel Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition (New York: McGraw-Hill, 2014)) 1. Definitions: a. Retail Banking: Large number of small value loans where incremental exposure of any single loan is small b. Dark Side of Retail Credit: During economic troubles, there are sudden upward movements in default rates and unexpected falls in collateral values c. Characteristics: Information items/ Questions in credit applications d. Attributes: Answers to the characteristics given 2. Credit Scoring Models: a. Credit Bureau Scores: Known as FICO scores ( ). They are provided by an agency like Fair Isaac Corporation/ Equifax b. Pooled Models: Models built by outside vendors by collecting data from various sources. More expensive than generic scores like FICO c. Custom Models: Models are developed in-house by collecting the data on internal customers. Most expensive but are tailored and can offer the best risk adjusted pricing d. Key Variables: DTI (Debt to Income), LTV (Loan to Value), PMT (Payment type like ARM s) 3. Model/ Scorecard Performance AR = Actual Defaults AP = Model predicted defaults

23 CREDIT TRANSFER MARKETS Reading: The Credit Transfer Markets-and Their Implications (Chapter 12, Michel Crouhy, Dan Galai and Robert Mark, The Essentials of Risk Management, 2nd Edition (New York: McGraw-Hill, 2014)) 1. Flaws in subprime securitization a. OTD (Originate to Distribute) model reduced the incentives for the bank to monitor the creditworthiness of the borrower. Banks held many MBS in place of transferring risk. b. Growth in CDS markets made credit risk easier to trade enhancing the perceived liquidity of credit instruments c. Low risk premiums and rising asset prices contributed to low default rates reinforcing perception of low levels of risk 2. Techniques for Credit Risk Mitigation: Bond Insurance, Guarantees, Collateral, Early Termination(After a credit event), Reassignment(Transfer to 3 rd party after a credit event), Netting, Mark to Market, Loan Syndication, Credit Default Swaps(CDS) 3. Credit Derivatives: Credit Default Swaps (CDS) Total Return Swap (TRS) Credit Linked Note (CLN)

24 INTRODUCTION TO SECURITIZATION Reading: An Introduction to Securitization (Moorad Choudhry, Structured Credit Products: Credit Derivatives & Synthetic Securitization, 2nd Edition (John Wiley & Sons, 2010)) 1. Definitions: a. Securitization refers to the process of creation of asset backed securities from loan assets b. First loss piece/ equity tranche: The most junior tranche because it is impacted by losses first. c. Credit Enhancement: Measures that improve the rating of the ABS (Asset Backed Securities) e.g. Over collateralization, Senior/ Junior tranches, excess spread 2. Structures of SPV used for securitization: a. Amortizing: pay principal and interest on a coupon basis throughout the life b. Revolving: During the revolving period, principal repayments are used to purchase new receivables c. Master: Allows multiple securitization to be issued form same SPV 3. Performance Analysis: a. DSCR (Debt Service Coverage Ratio): Net Operating Income/ Debt Payments. Needs to be more than 1 b. WAC (Weighted Average Coupon): Weighted coupon rate of the MBS pool c. WAM (Weighted Average Maturity): Term to maturity of the underlying pool of MBS in months d. WAL (Weighted Average Life): s = t. PF(s) where PF(s) = Pool factor and t = actual/365 e. CPR (Constant Payment Rate): CPR = 1 (1 SMM) 12 where SMM is Single Monthly Mortality f. Public Securities Association (PSA): Standard value of CPR of 0.2% per month up to 30 months i.e. 6%. This is called 100% PSA. It assumes mortgages prepay slower during the first 30 months g. Default Ratio: Total credit card receivables written-off/ total credit card receivables h. Delinquency Ratio: Credit card receivables for more than 90 days/ total credit card receivables. i. MPR (Monthly Payment Rate): Reflects proportion of principal and interest that is repaid in a period

25 SUBPRIME MORTGAGE CREDIT Reading: Adam Ashcraft and Til Schuermann, Understanding the Securitization of Subprime Mortgage Credit, Federal Reserve Bank of New York Staff Reports, No. 318 (March 2008) 1. Friction in Subprime Mortgage Securitization: a. Mortgagor vs. originator: Typical mortgagor is not financially sophisticated b. Originator vs. Arranger: The arranger(issuer) is at an information disadvantage compared to the originator c. Arranger vs. Third Parties: Arranger has more information than third parties d. Servicer vs. Mortgagor: Conflict arises for delinquent loans e. Servicer vs. Third Parties: Moral hazard as servicer has incentive to show higher recovery rates f. Asset Manager vs. Investor: Investors rely on asset managers g. Investor vs. Credit rating Agencies: rating agencies are compensated by arranger and not the end user.

26 EVOLUTION OF STRESS TESTING Reading: The Evolution of Stress Testing Counterparty Exposures (Chapter 4, Stress Testing: Approaches, Methods, and Applications, Edited by Akhtar Siddique and Iftekhar Hasan (London: Risk Books, 2013)) 1. Definitions: 2. CCR: a. Counterparty Credit Risk i. Current Exposure or replacement cost: Greater of zero or market value upon default ii. Peak exposure: Measures distribution of exposures at high percentile at a future date iii. Expected exposure: Measures mean distribution of exposures at a future date iv. Expected positive exposure: Weighted average of expected exposures over time b. Credit Value Adjustment (CVA): represents market value of CCR (Counterpart credit risk) a. CCR as credit risk: Exposes an institution to CVA b. CCR as market risk: Leaves institution exposed to decline in counterparty creditworthiness 3. Shortcoming of stress testing: a. CCR is not aggregated with loan portfolio or trading position stress b. Stress testing current exposure is not optimal. Need to stress expected exposure c. Using current exposures can lead to significant errors, especially for at-the-money exposures d. Linearization of delta sensitivities in models can lead to significant errors