Integration of Credit and Market Risk

Transcription

1 GARP Delhi Chapter meeting New Delhi July 27, 2012 Integration of Credit and Market Risk Dr. Dayanand Pandey Vice Dean, Jindal Global Business School Sonepat, NCR Delhi 7/27/2012 Dr Dayanand Pandey 1

2 Interaction of Market and Credit Risk Economic theory tells us that market and credit risks are intrinsically related to each other and, more importantly, they are not separable Jarrow and Turnbull(2000) 7/27/2012 Dr Dayanand Pandey 2

3 Interaction of Market and Credit Risk For many reasons, both historical and practical, market and credit risk have often been treated as if they are unrelated sources of risk: the risk types have been measured separately, managed separately, and economic capital against each risk type has been assessed separately. The development of credit risk transfer markets and the moves to mark-to-market accounting for portions of held-to-maturity banking book positions, however, have blurred distinctions between them and raise questions regarding approaches that treat the two types of risks separately. Market participants have argued that there are significant diversification benefits to be reaped from the integrated measurement and management of market and credit risks. 7/27/2012 Dr Dayanand Pandey 3

4 Interaction of Market and Credit Risk Robert Jarrow and S. Turnbull are amongst the first to explicitly model market and Credit risk together, using a reduced- form factor approach. Experience during the financial crisis illustrates that the integrated measurement and management of different forms of risk remains a challenge for industry practitioners, researchers and financial supervisors alike. The recent research highlights in particular the errors that can occur in the aggregation of the two types of risk and the strong relationships between them that suggest caution in the use of pragmatic distinctions between them. 7/27/2012 Dr Dayanand Pandey 4

5 Interaction of Market and Credit Risk Senior Supervisors Group (2008) conclude that banks that are more severely affected by the crisis tend to have difficulties integrating certain market and credit risks across business lines, whereas firms that are less affected practice a more comprehensive approach to risk management. This points to the need for better enterprise risk management, i.e., the integrated measurement and management of all relevant risks irrespective of where they may lie in the organization. 7/27/2012 Dr Dayanand Pandey 5

6 Interaction of Market and Credit Risk Some important questions on the interaction of both the risk: Can one usefully define and distinguish the two forms of risk? What relationships exist between them? Are present risk management and aggregation approaches precise in measuring and managing their combined risk? How should risk aggregation within the economic capital framework recognize the links between the two risk categories? How should regulation and supervision account for these relationships? What role does market liquidity play in the interaction of them? 7/27/2012 Dr Dayanand Pandey 6

7 Credit and Market Risk Credit risk includes not only direct losses from cash flows that cannot be received due to issuer s default, but also indirect losses when the asset value plunges because the possibility of the counterpart s default rises in the future. Credit Risk results from the combination of financial and macroeconomic risk factors with idiosyncratic and firm specific risk factors. Banking book vs. Trading book. Credit, fundamentally, is a risk of something happening that has never happened before. Modeling challenges of market and credit risk are different in terms of frequency, history of data and statistical distributions. 7/27/2012 Dr Dayanand Pandey 7

8 Approaches in Credit Risk Modeling The most accepted Merton model of credit risk assumes interest rate risk non existent and the traditional fixed income duration/convexity model assumes credit risk non existent. Assumptions in Merton s model: Interest rates are constant Perfectly competitive markets The assets of the company are perfectly liquid In Structural models, the likelihood of a firms default is linked to firm specific structural variables, namely the market value of a firms asset and its total debt. The key input parameters are the volatility of the asset value and a measure of firms leverage. 7/27/2012 Dr Dayanand Pandey 8

9 Credit Spreads, PD and Economic Growth Tang and Yan(2007) have shown in their paper that credit spreads decrease with the GDP growth rate and increase with the volatility of growth rate. Credit spreads are counter-cyclical. This result is also related to the observed negative correlation between interest rate and credit spreads. Ceteris paribus, an increase in the economic growth will increase the firm level growth and hence decrease the PD and Credit spread. Credit spreads also widen,when investors are more risk averse. Tang and Yan used CDS data for credit spread and KMV EDF for PD. During economic expansions, firms with high cash flow betas have lower credit spreads, ceteris paribus than firms with low cash flow betas. This relation reverses during economic recessions. 7/27/2012 Dr Dayanand Pandey 9

10 IMCR Working group on Interactions Interaction of Market and Credit Risk (IMCR) group suggests market and credit risk sometimes interacts in a non-linear fashion- in other words, losses from default can depend on movements in market prices, while changes in prices can depend on whether there is a default or rating migration. In this case, the combined risk sometimes be higher than the sum of market and credit risk. ICMR paper argues that diversification benefits as they are normally measured assume that the world is fairly linear. With non- linear interactions of market and credit risk, straight aggregation is not sufficient. There is a compounding effect and the effect may be greater than the sum of the parts. The only way to address to solve the puzzle is to look the risk holistically: it may be that the risks are reinforcing; it may be there are diversification benefits. Can t be sure. 7/27/2012 Dr Dayanand Pandey 10

11 Regulatory Capital and Risk Measurement Regulatory capital for Credit risk at the moment is calculated for each loan separately. Regulatory capital for market risk does not take into account counterparty default. But for some positions in the trading book (OTC derivatives etc), Regulatory capital takes into account counterparty risk. Breuer, Jandacka, Rheinberger and Summer(2008) argue that in many situations a split into credit and market portfolio is not possible because positions in the portfolio will simultaneously depend on market and credit risk factors. Paul Kupiec (2007) and others have shown that the piecemeal approaches for measuring market and credit risk can lead to underor overestimates of capital relative to the capital allocation estimated using an integrated model. 7/27/2012 Dr Dayanand Pandey 11

12 Summary of Regulatory Capital ICAAP Summary Credit Risk 000 Pillar I Min Regulatory Capital AED 000 Pillar II Capital AED 000 Market Risk 000 Operational Risk 000 Total Pillar I 000 Pillar 2 Credit Concentration Risk 000 Pillar 2 Interest Rate Risk in Banking Book 000 Pillar 2 Other 000 Total Pillar Capital derived from Stress Testing 0 Required Capital as per ICAAP 0 Current Capital 000 Surplus / (additional required) 0

13 Economic Capital and Risk Aggregation The calculation of bank wide aggregated risk figures(economic capital) is an essential aspect of Modern risk management. Risk aggregation refers to a process to estimate the amount of Economic Capital that a firm believes is necessary to absorb potential losses associated with each of the individual risks. The significant issue is about the manner in which risks are aggregated. Ideally an integrated risk modeling approach would be preferable to account for material interactions between market and credit risk. Market conditions can affect the firm characteristics on default probability and credit spread, because economically sensitive firms should benefit more in economic expansions and suffer more in economic recessions. 7/27/2012 Dr Dayanand Pandey 13

14 Economic Capital EC is defined as sufficient surplus to meet potential negative cash flows and reductions in value of assets or increases in value of liabilities at a given level of risk tolerance, over a specified time horizon. EC is defined as the excess of the market value of the assets over the fair value of liabilities required to ensure that obligations can be satisfied at a given level of risk tolerance, over a specified time horizon. EC is defined as sufficient surplus to maintain solvency at a given level of risk tolerance, over a specified time horizon.

15 Economic Capital- Calculation 7/27/

16 Integration of Market and Credit Risk No unified economic capital model exists which integrates both market and credit risks in a consistent fashion. Systematic macroeconomic risk drivers impact on both the risks simultaneously. Rosenberg and Schuermann (2006) show that the additive (top down) approach overestimates risk by more than 40%. A typical alternative, assuming joint normality of risks, underestimates risk by a similar amount. Diversification is often divided into two components: Intra-risk and inter-risk. In a large portfolio of credits, idiosyncratic risk is fully diversified and the only source of portfolio loss uncertainty is the default rate that is driven by the common latent Gaussian factor. 7/27/2012 Dr Dayanand Pandey 16

17 Integration of Market and Credit Risk Alessandri & Drehmann (2009) show that simple capital exceeds integrated capital under a broad range of circumstances. A relatively large portion of credit risk is idiosyncratic, and thus independent of the macroeconomic environment in a normal environment, and the correlation between systematic credit risk factors and interest rates is itself not perfect. If assets in the banks portfolio are repriced frequently, increases in credit risk can be partly passed on to borrowers. Credit risk of a portfolio has a large systemic component in a stressed macroeconomic environment and coupled with stressed liquidity scenarios, it becomes mainly driven by systematic factors(which direct/indirect fall on most of the firms). 7/27/2012 Dr Dayanand Pandey 17

18 Integration of market and Credit Risk The chance to sell and buy credit risk, instead of holding loans until maturity, placed banks under increased pressure to know the Present value of their assets well before maturity. This posed a great challenge to risk modeling as present value depends on in a complex way on market factors. This was also accompanied by a strong and robust technological progress in modeling. The increased opportunity to encash the strong diversification benefits on Capital added the real value. 7/27/2012 Dr Dayanand Pandey 18

19 Credit and Market risk Interactions Despite the complexity of these relationships, many banks have historically taken a Top down approach to measuring Enterprise wide Risk measuring each risk type separately and adding them together. Many banks have in past argued the Top down approach leads to conservative estimates of risk because it assumes perfect correlation between credit and market risk. So long as market and credit risk are not perfectly correlated, the diversification effects would be ignored, leading to overestimation of risk. 7/27/2012 Dr Dayanand Pandey 19

20 Top Down vs. Bottom-up Approach In the Top down approach, the individual risk marginal distributions are derived separately and then aggregated through a variance covariance or copula approach; while in the Bottom up (Base level) approach, a full modeling of common risk drivers and of their interactions are taken into account. In general the Top down approach fails to capture the interdependencies between both the risks. However, the difficulty is to choose the correct copula function, especially given the limited access to adequate data. Top down approach of integrating market and credit risk could be subject to error due to the compounding effect as well. Some banks are using Mark-to- Future(MtF) architecture of some vendors to handle credit risk in trading portfolios. 7/27/2012 Dr Dayanand Pandey 20

21 Underestimation of Risk A clear illustration of how a large underestimation of risk can occur through top down aggregation is in Breuer(2008). Consider a bank lending in FX to domestic borrowers. These positions contain market risk(exchange rate risk)and Credit Risk(Default risk). When the domestic economy contracts, the PD of the borrower goes up. When the domestic currency depreciates, ceteris paribus the value of the loan in domestic currency goes up. The ability of a domestic borrower to repay a loan in FX depends in a non linear way on fluctuations in the exchange rate. A depreciation has a malign effect on the repayment probability of a unhedged borrower and so a compounding effect emerges. 7/27/2012 Dr Dayanand Pandey 21

22 Underestimation of Risk An analysis of a FX loan in Austria indicates that simply adding up of risks underestimates the actual level of risk by a factor of several times. For example, for B+ rated obligor, the integrated risk management approach leads to an overall risk that is 1.5 to 7.5 times larger than the risk derived from a compartmentalized approach in which each risk is measured separately and then added up. This bias becomes more pronounced for portfolios with lower ratings. There are other examples of such complexities like including adjustable rate loans(also sub prime mortgage loans), matching long and short positions in OTC derivatives. 7/27/2012 Dr Dayanand Pandey 22

23 Credit Risk, Market risk and Liquidity The crisis has shown the importance of market liquidity specially, changes in liquidity can alter the mix of market and credit risk in bank portfolios. A sharp drop in liquidity mean banks would be forced to lengthen the horizons of trading book positions. Market shocks that increase the perceived credit risk of an instrument can cause liquidity to dry up, triggering a downward spiral in prices and liquidity. A drying up of liquidity associated with an increase in the liquidity horizon from two weeks to six months would have the same effect on the VaR of a portfolio of A3 rated assets as a two notch downgrade of these instruments to Baa2. As a situation becomes less and less liquid, it becomes more difficult to exit a position as a result of rating downgrades or an increase in defaults,and the credit component of market risk goes up. 7/27/2012 Dr Dayanand Pandey 23

24 Problems in Aggregation The first major obstacle to integrate market and credit risk measurement and management is that the metrics typically used for each of them are not fully comparable, with market risk models capturing full distributions of returns and Credit risk models focusing on losses from default and neglecting gains. The second important obstacle is the different time horizons over which risks are quantified. Integrated Risk measurement and management make very significant demands on data and technological infrastructure. 7/27/2012 Dr Dayanand Pandey 24

25 Risk Integration and Technological progress Although the sources and nature of credit risks may be different from market risk but integration is possible- Axiom software lab. A good market risk engine has solved 70-80% of the Credit risk problem- IRIS. FRS Global s Risk Pro is designed to operate with financial contracts rather than transactions and across the whole bank. For market risk, the engine calculates book and fair market value at the date of analysis and over time. Fermat, Algorithmics and Kamakura have devised simulations approaches. They enable the institutions to run scenarios that incorporate market and credit risk factors simultaneously. Algo uses Mark to- Future, which simulates scenarios and dynamics of portfolio holdings over time. 7/27/2012 Dr Dayanand Pandey 25

26 Risk Integration and Technological progress Kamakura uses a method, developed by Prof. Robert Jarrow, which involves simulating market and Credit risk events across a given horizon to calculate Credit Adjusted VaR. Disparity of time horizons seems to favor a simulation approach to integrate risk. Despite the vendors toll claims, few institutions have implemented a unified system.. Organizational change has to lead the way to bring market and credit risk under one umbrella. 7/27/2012 Dr Dayanand Pandey 26

27 References Nick Sawyer(2009): The Shock of interaction Risk Magazine. Rosenberg and Schuermann( 2006): A general approach to integrated risk management with skewed, fat tailed risks. Iscoe, Kreinin and Rosen(1999): An integrated Market and Credit Risk portfolio model. Tang and Yan(2007): Market conditions, Default Risk and Credit Spreads. Breuer, Jandacka, Rheinberger and Summer(2008): Regulatory capital for market and credit risk interaction: is current regulation always conservative? BIS(2009): Findings on the Interactions of market and credit risk, WP 16. Clive Davidson(2002): Weaving an integrated solution, Risk Magazine. Editorial of Journal of Banking and Finance on Interaction of Market and Credit Risk, Jarrow and Turnbull(2000): The Intersection of Market and Credit Risk, Journal of Banking and Finance. An integrative Risk Evaluation model for market and credit risk: Shuji Tanaka &Yukio Muromachi. Credit Risk and Market Risk: Analyzing US Credit Spreads: Hayette Gatfaoui. An Economic Capital Model Integrating Credit and Interest Rae Risk in the Banking Book: Alessandri & Drehmann. Integrating Interest rate risk and Credit Risk in ALM: Jarrow and Deventer, Kamakura Corporation An integrated Structural model for Portfolio Market and Credit risk: Bundesbank/BIS conference /27/2012 Dr Dayanand Pandey 27

28 The End Thank you all for listening patiently. We welcome your valuable comments. 7/27/2012 Dr Dayanand Pandey 28