L11 Credit Risk PDF - Investment Risk Management 2024-2025

Credit Risk 6FNCE001C Investment Risk Management 2024-2025 Today … Financial risks: a helicopter view risk management process key risk classes The term structure of interest Credit risk the credit decision credit risk evaluation: quantitative vs. qualitative cre...

Credit Risk 6FNCE001C Investment Risk Management 2024-2025 Today … Financial risks: a helicopter view risk management process key risk classes The term structure of interest Credit risk the credit decision credit risk evaluation: quantitative vs. qualitative credit risk measurements methods for computing the default risk overview of PD models Financial risks: a helicopter view Financial risks: a helicopter view Main financial risks What are the steps of risk management process? Step 1: Identify the risks Step 2: Quantify and estimate the risk exposures or determine appropriate methods to transfer the risks Step 3: Determine the collective effects of the risk exposures or perform a cost- benefit analysis on risk transfer methods Step 4: Develop a risk mitigation strategy (i.e., avoid, transfer, mitigate, or assume risk) Step 5: Assess performance and amend risk mitigation strategy as needed Financial risks: a helicopter view Key risk classes Market Risk considers how changes in market prices and rates will result in investment losses. four subtypes: interest rate risk – the risk that an investment's value will change due to a change in the absolute level of interest rates, in the spread between two rates, in the shape of the yield curve, or in any other interest rate relationship equity price risk – general market risk and specific risk (unique factors of the entity) foreign exchange risk - monetary losses that arise because of unhedged or not fully hedged foreign currency positions commodity price risk - the price volatility of commodities (e.g., precious metals, base metals, agricultural products, energy) Financial risks: a helicopter view Key risk classes Credit Risk a loss suffered by a party whereby the counterparty fails to meet its financial obligations to the party under the contract. four subtypes of credit risk: default risk - non-payment of interest and/ or principal on a loan bankruptcy risk - the risk is that the liquidation value of the collateral is insufficient to recover the full loss on default. downgrade risk - decreased creditworthiness (based on recent financial performance) of a counterparty to a transaction settlement risk – at the settlement date the position that is losing may simply refuse to pay and fulfil its obligations Financial risks: a helicopter view Key risk classes Liquidity risk two subtypes: funding liquidity risk - when an entity is unable to pay down or refinance its debt, satisfy any cash obligations to counterparties, or fund any capital withdrawals. trading liquidity risk - when an entity is unable to buy or sell a security at the market price due to a temporary inability to find a counterparty to transact on the other side of the trade Operational Risk considers a wide range of "non-financial" problems such as inadequate computer systems (technology risk), insufficient internal controls, incompetent management, fraud (e.g., losses due to intentional falsification of information), human error (e.g., losses due to incorrect data entry or accidental deletion of a file), and natural disasters. Term structure of interest Term structure of interest (yield curve) The term structure of interest (also known as yield curve) refers to, not dynamic, but static relationship between the interest rates and the associated maturities of debt instruments. Term structure of interest (yield curve) There are several different reasons why interest rates on a debt security or loan may differ for different maturities. Liquidity preference theory provides a reason why, in theory, the yield curve is normally upward sloping, so that long-term financial assets offer a higher yield than short-term assets. Liquidity preference means that investors prefer having cash now to deferring the use of the cash by lending or investing it. Investors also prefer having cash sooner to having cash later. They therefore want compensation in the form of a higher return for being unable to use their cash now. The required return increases with the length of time for which the cash is unavailable Expectations theory states that interest rates reflect expectations of future changes in interest rates. If interest rates are expected to rise in the future, the yield curve will slope upwards. When interest rates are expected to fall, short-term rates may be higher than long-term rates, and the yield curve downward sloping. Thus, the shape of the yield curve gives an indication about how interest rates are expected to move in the future. The market segmentation theory of interest rates suggests that the slope of the yield curve will reflect conditions in different segments of the market. This theory holds that the major investors are confined to a particular segment of the market and will not switch segment even if the forecast of likely future interest rates changes. Government policy on interest rates may be significant too. A government policy of keeping interest rates relatively high may have the effect of forcing short-term interest rates higher than long-term rates. Credit risk: a broader view Credit risk: a broader view Credit risk - probability that a borrower will not pay back a loan in accordance with the terms of the credit agreement. Two key participants: Borrower, obligor, counterparty, issuer - the party receiving credit. Lender, creditor, and obligee - the party granting credit The risk can result from: - default on a financial obligation - an increased probability of default on a financial obligation - a more severe loss than expected due to a greater than expected exposure at the time of a default - a more severe loss than expected due to a lower than expected recovery at the time of a default - default on payment for goods or services already rendered (i.e., settlement risk) Credit risk: a broader view Credit risk evaluation willingness to pay vs. capacity to pay Qualitative techniques are used to evaluate the borrower’s willingness to repay e.g. face-to-face meetings, information gathering, “name lending“, etc. limitations: subjectivity Quantitative techniques are used to evaluate the borrower's ability to repay e.g. financial statements analysis limitations: - historical nature of the data - difficulties to make accurate projections Credit risk: a broader view Credit risk evaluation Probability of default (PD) The likelihood that a borrower will default. - however, a borrower may briefly default and then quickly correct the situation by making a payment, paying interest charges or penalties for missed payments. Loss given default (LGD) LGD represents the likely percentage loss if the borrower defaults. - both PD and LGD are expressed as percentages. Exposure at default (EAD) The loss exposure may be stated as a dollar amount. EAD can also be stated as a % of the nominal amount of the loan or the maximum amount available on a credit line. Expected loss (EL) Expected loss for a given time horizon is calculated as the product of the PD, LGD, and EAD (i.e., PD x LGD x EAD). Time horizon (tenor) the longer the tenor, the greater the risk to the lender Credit risk: a broader view Methods for computing the default risk Expert system - based on the so called 5 C’s of credit quality Character – reputation, repayment history Capital – equity contribution, leverage. Capacity – earnings, cash flows, volatility of earnings. Collateral – seniority, market value & volatility of market value of collateral. Cycle – economic conditions - limitations: inconsistency and subjectivity Credit scoring models - pioneered by Beaver (1966) and Altman(1968). They assign a numerical value to a firm, which indicates whether a firm is likely to default or not. Mainly used for small and private firms. - limitations: the assumption of linearity, data limitations (balance sheet data), not well grounded in economic theory. Credit risk: a broader view Methods for computing the default risk E.g. linear discriminant analysis - Altman's Z score Altman Z-score uses profitability, leverage, liquidity, solvency and activity to predict whether a company has a high degree of probability of being insolvent. Z-score = 1.2A + 1.4B + 3.3C + 0.6D + 1.0E Where: A = working capital / total assets B = retained earnings / total assets C = earnings before interest and tax / total assets D = market value of equity / total liabilities E = sales / total assets A score below 1.8 means the company is probably headed for bankruptcy, scores above 3 are not likely to go bankrupt Credit risk: a broader view Methods for computing the default risk Rating system - a credit rating is an alphanumeric grade assigned by credit rating agencies that summarizes the creditworthiness of a particular security or entity. - big three: Standard and Poor's (S&P), Moody's, and Fitch Ratings (Fitch) - AAA securities are considered virtually free of default risk, while a D rating signifies default. - rating migration (changes in ratings). Probability estimates are summarized in transition matrices, which show the estimated likelihood of a rating change for a company within a specified time period (usually one year). Credit risk: a broader view Methods for computing the default risk Option-theoretic structural approach (value-based models) Merton model: (Black-Scholes-Merton option pricing theory) - firm’s debt consists of a single zero-coupon bond issue that matures at time M at face value FM. At the maturity of the debt, if the value of the firm‘s assets is less than the value of the debt, then the firm must default. - Payoffs are the same as the payoffs for a call option, with the firm value (VM) as the underlying asset and principal amount as the exercise price payment to stockholders = max(VM - FM, 0) If FM> VM, payment to debt holders = FM - max(FM – VM, 0) Credit risk: a broader view Methods for computing the default risk Assumptions (Merton model): there is only one issue of equity and debt, and the debt is in the form of a zero-coupon bond that matures at a given date. default can only occur at the maturity date. the value of the firm is observable and follows a lognormal diffusion process (geometric Brownian motion). the risk-free interest rate is constant through time. there is no negotiation between equity and bondholders. there is no need to adjust for liquidity limitations: assumptions are unrealistic Credit risk: a broader view Methods for computing the default risk - the Merton model for PD (probability of default) is (assuming μ – the expected return on the firm value): ln 𝐹 − ln 𝑉 − 𝜇 𝑇 − 𝑡 + 0.5𝜎 2 𝑇 − 𝑡 𝑃𝐷 = 𝑁 𝜎 𝑇−𝑡 where 𝑁  cumulative normal distribution 𝐹 face value of the zero-coupon bond 𝑉 value of the firm 𝑇 maturity date on bond 𝜎 volatility of firm value Credit risk: a broader view Methods for computing the default risk ln 𝐹 − ln 𝑉 − 𝜇 𝑇 − 𝑡 + 0.5𝜎 2 𝑇 − 𝑡 𝑃𝐷 = 𝑁 𝜎 𝑇−𝑡 The above formula is the same as 𝑁(−𝑑2 ), which is found using BSM: 𝐶 = 𝑆 × 𝑁 𝑑1 − 𝐾 × 𝑒 −𝑟𝑇 × 𝑁 𝑑2 𝑃 = 𝐾 × 𝑒 −𝑟𝑇 𝑁 −𝑑2 − 𝑆 × 𝑁(−𝑑1 ) 𝑆 𝜎2 ln 𝐾 + 𝜇 + 2 𝑇−𝑡 𝑑1 = 𝜎 𝑇−𝑡 𝑑2 = 𝑑1 − 𝜎 𝑇 − 𝑡 Credit risk: a broader view Methods for computing the default risk The KMV model address some of the Merton model’s shortcomings (all the debt matures at the same time and the value of the firm follows a lognormal diffusion process). assumes: there are only two debt issues: the first matures before the chosen horizon, and the other matures after that horizon calculates a default point/default threshold: when the ratio of long-term liabilities to short-term liabilities is less than 1.5 𝑠ℎ𝑜𝑟𝑡 𝑡𝑒𝑟𝑚 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 + 0.5 × 𝑙𝑜𝑛𝑔 𝑡𝑒𝑟𝑚 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 when this ratio is greater than 1.5 0.3 × 𝑠ℎ𝑜𝑟𝑡 𝑡𝑒𝑟𝑚 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑠ℎ𝑜𝑟𝑡 𝑡𝑒𝑟𝑚 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 + 0.7 − × 𝑙𝑜𝑛𝑔 𝑡𝑒𝑟𝑚 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 𝑙𝑜𝑛𝑔 𝑡𝑒𝑟𝑚 𝑙𝑖𝑎𝑏𝑖𝑙𝑖𝑡𝑖𝑒𝑠 Credit risk: a broader view Methods for computing the default risk calculates probability of default based on the distance to default (DD) 𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑎𝑠𝑠𝑒𝑡 𝑣𝑎𝑙𝑢𝑒 − 𝑑𝑒𝑓𝑎𝑢𝑙𝑡 𝑡ℎ𝑟𝑒𝑠ℎ𝑜𝑙𝑑 𝐷𝐷 = 𝜎𝑒𝑥𝑝𝑒𝑐𝑡𝑒𝑑 𝑎𝑠𝑠𝑒𝑡 𝑣𝑎𝑙𝑢𝑒 if asset prices are lognormally distributed, the DD is 𝜎𝑉2 log 𝑉 − log 𝑑𝑒𝑓𝑎𝑢𝑙𝑡 𝑡ℎ𝑟𝑒𝑠ℎ𝑜𝑙𝑑 + 𝐸 𝑅𝑂𝐴 − 2 × 𝑚𝑎𝑡𝑢𝑟𝑖𝑡𝑦 𝐷𝐷 = 𝜎𝑉 × 𝑚𝑎𝑡𝑢𝑟𝑖𝑡𝑦 Credit risk: a broader view Methods for computing the default risk once DD is computed, the expected default frequency (PD) can be found