New Challenges in Measuring Risk and Managing Credit Portfolios. Charles Stewart and Jing Zhang IACPM Spring Meeting; 12 May 2011

Transcription

1 New Challenges in Measuring Risk and Managing Credit Portfolios Charles Stewart and Jing Zhang

2 Contents» Putting A Sense of Mission Back Into Portfolio Management» Liquidity Risk and CPM: An Overview» Liquidity Risk and CPM: Analytical Issues and Solutions» Summary 2

3 Putting A Sense of Mission Back Into Portfolio Management

4 Recap Half a century of ignored mistakes: real estate, telecoms, home mortgages, etc.» banks plan for asset expansion irrespective of price or boom / bubble = excessive lending under loosened underwriting standards, with much lower margins 4

5 Recap Half a century of ignored mistakes: real estate, telecoms, home mortgages, etc.» banks plan for asset expansion irrespective of price or boom / bubble = excessive lending under loosened underwriting standards, with much lower margins More than one-in-eight risk managers believe that they are ignored by their employer, they have insufficient influence to manage risk properly at their organisation, and it is the organisation that is at fault. The Times, February 23rd

6 Recap Half a century of ignored mistakes: real estate, telecoms, home mortgages, etc.» banks plan for asset expansion irrespective of price or boom / bubble = excessive lending under loosened underwriting standards, with much lower margins More than one-in-eight risk managers believe that they are ignored by their employer, they have insufficient influence to manage risk properly at their organisation, and it is the organisation that is at fault. The Times, February 23rd risk management by financial institutions [has] been unacceptably poor, and a major improvement of risk management by private institutions is of the essence. Jean-Claude Trichet, President, ECB Interview with WSJ,27 th January

7 Inevitable Consequences» Regulatory tsunami» Stakeholder challenges and backlashes» Revisiting an appropriate Risk Infrastructure; linking shared risk ownership and measurement, with proportional reward Strategy (Setting, Execution, Monitoring) People (Inclination, Behavior, Communication) Authority (Ownership, Weight, Influence)» Evidence of increasing investment in risk management (not just undercapitalised / overleveraged banks) 7

8 Better-Informed and More Timely Decision Making» Do you know what bets you / your people are making?» Can you afford the consequences if those bets are incorrect?» Do boundaries reflect strategy, risk appetite, product markets, and clients?» Are current exposures within established limits and boundaries?» Is the risk / reward ratio appropriate?» Can you isolate the unusual, unintended, unacceptable risks?» Do the right people discuss, monitor, and manage the risks? 8

9 The Real Challenge: ERM Compute Capital Consolidate Risks Financial Income Non-Financial Income Product Processing costs Sales & Marketing costs Overhead costs Revenues & Costs Measure Profitability Generate Reports for Management Compute Margins / Allocate Costs Perform simulations & stress-testing scenarios Credit Risk Market Risk Operational Risk Liquidity Risk Capital Risk Adjusted Performance Measurement Ex-post RAROC Scenario Analysis & Simulations Ex-ante RAROC Risk Appetite & Capital Allocation Originated Exposures New Business Origination Real-time analysis (scoring, pricing, settling, hedging ) Limits Risk Monitoring vs. Defined Limits Limits Policies Measure new exposures Risk & and Performance in real-time Monitor Exposure Concentration on key business dimensions Allocate capital to businesses

10 Memories are Short Despite the severity of the crisis, we are already seeing signs that its lessons are beginning to fade. * *Stefan Walter, Secretary General, BCBS at the Financial Stability Institute, Basel 6 th April 2011 The costs of banking crises are extremely high but, unfortunately, the frequency has been as well. Since 1985, there have been over 30 banking crises in Basel Committee-member countries.* Roughly, this corresponds to a 5% probability of a Basel Committee-member country facing a crisis in any given year a one in 20 chance Many countries have been affected by the global fallout. Those who cannot remember the past are condemned to repeat it George Santayana 10

11 Liquidity Risk in CPM: An Overview

12 Regulatory Emphasis on Liquidity Risk Management» Basel: the maintenance of a sufficient cushion of high quality liquid assets to meet contingent liquidity needs.» Fed: a cushion of liquid assets, and a formal, well-developed contingency funding plan (CFP) as primary tools for measuring and managing liquidity risk.» CEBS: The introduction of a liquidity premium is being proposed to eliminate the mismatch between assets and liabilities, especially in times of crisis. 12

13 Liquidity Risk in the Context of Credit Portfolio Management Liquidity risk:» Market liquidity» Funding liquidity While the mandate of CPM is usually for credit risk, effective CPM improves liquidity for banks:» Bank s overall liquidity can be affected by the asset quality of its loan book» Bank s overall liquidity strategy should include the identification of those loans or loan portfolio segments that may be easily converted to cash Funding liquidity and CPM: Significant challenges in funding loan assets with matched liabilities as the results of the uncertainties in:» Variable usage of credit lines» Extension and rollover of existing facilities» Pre-payment of facilities» Default 13

14 Liquidity Risk and CPM: Key Analytical Issues 1. The impact of market liquidity/ill-liquidity on valuation, risk calculation, and funding 2. The uncertainty in the future portfolio size and the characterization of the resulting distribution 3. An economic/analytical framework to asses the contingent liquidity risk as a result of the uncertainty of future portfolio size and funding uncertainty 14

15 Liquidity Risk and CPM: Analytic Issues and Solutions

16 Incorporating Liquidity into Pricing and Valuation Suppose firm XYZ has a 5-year CDS traded (or quoted) at 259 bps:» What is the proportion of 259 bps that is due to the credit component (i.e., expected loss)?» How much of the 259 bps is due to the no-credit component, such as liquidity (illiquidity)?» What factors drive the liquidity? Why do these questions matter?» For pricing and hedging decisions» For economic capital and VAR calculation» For understanding the bank s funding cost that is influenced by liquidity 16

17 Liquidity Risk Framework: CAPM with Liquidity If asset return is determined by a price movement and a transaction cost (r-c), an equilibrium of CAPM style can be described as* Investors requires a premium if an asset has:» Higher illiquidity» Higher return correlation with the market» Illiquidity co-moves with market illiquidity» Is less liquid in down market» Lower return when market has liquidity problem *Acharya and Pederson (2005) 17

18 Our Approach to Understanding Liquidity in CDS First, we explicitly model the credit component in valuation:» A Fair Value Spreads (FVS) Framework that incorporates: EDF, LGD, and risk premium Second, we extract the market liquidity factor from the difference between CDS and FVS. Third, we estimate various betas/correlations related to liquidity: ll 1., : correlation between idiosyncratic liquidity and market liquidity lr 2. :, : correlation between idiosyncratic liquidity and market return rl, 3. : correlation between firm s return and market liquidity factor 18

19 Explaining CDS Spread with Liquidity Effects We run regressions with increasing number of variables to explain the cross-sectional drivers for CDS relative to FVS. CDS it log 0t 1 t r, R 2 t l, L FVS it c 3 t l, R 4 t r, L 5t i it R-squares from the Regression With beta(l,r) only With beta(l,l) only Include all Betas 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% In cross-section, non-credit components of CDS spreads are correlated with size, illiquidity levels, and liquidity risk A lender probably should charge a higher rate if the borrower is small A lender probably should charge a higher rate if the cost of selling the loan is high A lender probably should charge a higher rate if the cost of selling the loan is higher when the market liquidity is dried up

20 Understanding the Distribution of Future Portfolio Size Uncertainties in future portfolio size as the result of:» Variable usage of credit lines» Extension and rollover of existing facilities» Pre-payment of facilities» Default» Change in business strategy The analytical goal is to construct the distribution of future portfolio size that accounts for the above uncertainties and the portfolio-effect:» The distribution gives expected (average) and unexpected value» It accounts for the correlation effects» It facilitates stress testing A particular challenge is in characterizing the dynamic usage of credit lines 20

21 Estimating Usage and Usage Given Default of Credit Lines Recently, we have undertaken a comprehensive empirical study to understand the usage pattern of credit lines and drivers. Two data sources: 1. Data (mostly middle market) from eight US institutions from Credit Research Database (CRD) consortium 2. Manually collected usage and usage given default data for some publically traded firms in US The dataset has information on commitment amount, drawn amount, maturity, interest rate, collateral, internal rating, default information, EDF Period: 2000Q3 2010Q2 Highlights of the findings:» Middle market UGD and LEQ are high. Average UGD is 76% (median 94%). Publicly listed firms have relatively lower UGD and LEQ. Usage reaches a high level two years before default. Non-defaulted firms have lower usage than defaulters.» Usage is positively related with default risk. We do find evidence that bank monitoring seems to restrict usage.» During the recent recession, usage went up slightly after Lehman s collapse, then came down. We do observe that commitment has been cut down more from

22 A Simulation Approach to Measuring Future Portfolio Size Asset Value 12% 8% Borrower 2 s Usage Borrower 2 s Credit Migration Borrower 1 4% 0% 20% 40% 60% 80% Borrower 2 Asset Value Portfolio Size Distribution 12% 8% Borrower 2 s Usage Borrower 2 s Credit Migration % % 20% 40% 60% 80% 0 35% 40% 45% 50% 55% 60% 65% 70% 22

23 Measuring Contingent Liquidity Risk in a Stylized Economic Setting Consider a simplified, two-period setting:» A bank extends backup lines of credit to a pool of homogeneous borrowers Borrowers future demand for liquidity (line utilization) is uncertain» The bank funds the credit lines using a combination of long-term funds (a liquidity buffer), and short-term debt, refinanced at each period Future funding costs are uncertain» The bank s funding cost and the borrowers line usage are correlated» Availability of short-term funds is limited in severe market conditions What amount of liquid assets should the bank hold in order to absorb potential losses due to adverse funding conditions? 23

24 Measuring Bank Cash Flows 24

25 Characterization of the Funding Within a structural model of default, the funding spread charged to the bank at the time of refinancing can be written as:» A systemic event may result in severe limitations with access to funding 1 1 Markets Functioning Shutdown» An institution-specific event may result in the bank s inability to raise funds Shutdown 1 1 Bank is Viable Net Cash Flow ( L) 0 t t 25

26 Bank Modeling the Joint Dynamics Bank Funding Spread Bank Credit Migration Asset Value 1bps 10bps 100bps 1000bps Market Risk Premium Borrower Asset Value Bank Gains/Losses 12% 8% Borrower Usage 12% 8% 12% Borrower Credit Migration 4% 8% 4% 0% 4% 20% 40% 60% 80% -12% -8% -4% 0% 4% 8% 0% 0% 20% 40% 60% 80% 20% 40% 60% 80% 26

27 Case Study: Liquidity Provisioning for a Portfolio of Homogeneous Borrowers Bank Characteristics Maturity of short-term debt: 1 year Cost of long-term debt: 1.2% 1 year default probability: 25 bps LGD: 50% RSQ: 35% Borrower Characteristics No. of Homogeneous Borrowers: 1,000 Maturity of credit line: 2 years Contractual Usage Fee: 2% 1 year default probability: 1% RSQ: 25% 29

28 Liquidity Buffer Under Different Assumptions 30

29 Contractual Fee = 200bps FTP = 233bps Incorporating Contingent Liquidity Costs in Funds Transfer Pricing Assumptions: Corr(Bank,Borrower) = 20%, w/ Market Shutdown Credit Spread 154bps Contingent Liquidity Spread 79bps Reference Rate 31

30 Funds Transfer Price 32 Extensions General approach to Funds Transfer Pricing: Commercial Margin Credit Spread Option Spread Funding Liquidity Spread Contingent Liquidity Spread Reference Rate The expected cost of funds required to support the exposure during its remaining life The cost of maintaining a sufficient cushion of high quality liquid assets to meet sudden or unexpected obligations 32

31 Benefits of this Economic Framework Provides guidance on:» the level of liquid assets a financial institution should hold in order to absorb potential losses due to adverse funding conditions» how a financial institution should account for the cost of holding liquidity reserves when originating loans or when calculating a transfer price It accounts for correlation between borrowers funding needs, bank s liquidity requirements, and the market price for risk: imperative in understanding liquidity risks Is flexible and allows for integration with credit and other risks 33

32 Summary

33 The Convergence of ALM and CPM The Senior Supervisors Group study on risk management practices during the financial crisis found that firms that fared better aligned treasury functions more closely with risk management processes. These firms had created internal pricing mechanisms that provided incentives for individual business lines to control activities that might have otherwise led to significant balance sheet growth or unexpected reductions in capital. In particular, these firms had charged business lines appropriately for building contingent liquidity exposures to reflect the cost of obtaining liquidity in a more difficult market environment. Senior Supervisors Group, Observations on Risk Management Practices During the Recent Market Turbulence, March 6, 2008, Page 3 35

34 36

35 Contacts Charles Stewart Senior Director Moody's Analytics One Canada Square Canary Wharf London E14 5FA Jing Zhang Managing Director Moody's Analytics 405 Howard Street Suite 300 San Francisco, California (0) direct +44 (0) mobile

36 Moody s Analytics provides strategic solutions for measuring and managing risk. We assemble best practices across credit, economics, and financial risk management, helping you compete in an evolving marketplace. In addition to distributing the credit ratings and proprietary research of Moody s Investors Service, we offer quantitative models and enterprise risk management software as well as training and professional services that are tuned to your business challenges. 38

37 moodysanalytics.com 2011 Moody s Analytics, Inc. and/or its licensors and affiliates (collectively, MOODY S ). All rights reserved. ALL INFORMATION CONTAINED HEREIN IS PROTECTED BY COPYRIGHT LAW AND NONE OF SUCH INFORMATION MAY BE COPIED OR OTHERWISE REPRODUCED, REPACKAGED, FURTHER TRANSMITTED, TRANSFERRED, DISSEMINATED, REDISTRIBUTED OR RESOLD, OR STORED FOR SUBSEQUENT USE FOR ANY SUCH PURPOSE, IN WHOLE OR IN PART, IN ANY FORM OR MANNER OR BY ANY MEANS WHATSOEVER, BY ANY PERSON WITHOUT MOODY S PRIOR WRITTEN CONSENT. All information contained herein is obtained by MOODY S from sources believed by it to be accurate and reliable. Because of the possibility of human or mechanical error as well as other factors, however, all information contained herein is provided AS IS without warranty of any kind. Under no circumstances shall MOODY S have any liability to any person or entity for (a) any loss or damage in whole or in part caused by, resulting from, or relating to, any error (negligent or otherwise) or other circumstance or contingency within or outside the control of MOODY S or any of its directors, officers, employees or agents in connection with the procurement, collection, compilation, analysis, interpretation, communication, publication or delivery of any such information, or (b) any direct, indirect, special, consequential, compensatory or incidental damages whatsoever (including without limitation, lost profits), even if MOODY S is advised in advance of the possibility of such damages, resulting from the use of or inability to use, any such information. The ratings, financial reporting analysis, projections, and other observations, if any, constituting part of the information contained herein are, and must be construed solely as, statements of opinion and not statements of fact or recommendations to purchase, sell or hold any securities. NO WARRANTY, EXPRESS OR IMPLIED, AS TO THE ACCURACY, TIMELINESS, COMPLETENESS, MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE OF ANY SUCH RATING OR OTHER OPINION OR INFORMATION IS GIVEN OR MADE BY MOODY S IN ANY FORM OR MANNER WHATSOEVER. Each rating or other opinion must be weighed solely as one factor in any investment decision made by or on behalf of any user of the information contained herein, and each such user must accordingly make its own study and evaluation of each security and of each issuer and guarantor of, and each provider of credit support for, each security that it may consider purchasing, holding, or selling. 39