Presentation on theme: "Technical Specialist - Market and Counterparty Credit Risk Policy"— Presentation transcript:
1 Technical Specialist - Market and Counterparty Credit Risk Policy The Market risk framework and the Fundamental Review of the Trading BookMichele MarzanoTechnical Specialist - Market and Counterparty Credit Risk PolicyBank of EnglandThe views expressed in this presentation are my own and do not necessarily reflect the views of the Bank of England.
2 Section 1: overview of the current market Risk Framework What is market RiskCurrent Market Risk FrameworkResponse the crisis: Basel 2.5Section 2: overview of the Fundamental Review of the trading book.Background: the problems with the current frameworkNew trading book boundaryNew internal modelsNew standardised approachRecap
3 RisksTypes of RiskMarket Risk is the risk that the value of your position will change due to changes in market risk factors.Credit/Issuer risk is the risk of loss due to:borrower default on any type of debt by failing to make payments which it is obligated to doapplies to bonds, loans, off-balance sheet exposuresCounterparty risk is the risk that the counterparty to a transaction (e.g. derivatives) could default before the final settlement of the transaction's cash flows.Credit risk assessment:Assessing “creditworthiness”Ratings systems: Rating agenciesBank’s own models
4 Risks – cont’d Types of Risk Liquidity risk can be: Market liquidity is the risk that a firm cannot sell an asset (bonds, loans, shares, derivatives, currency) because nobody wants to buy it at its assumed value, within the time requiredFunding liquidity is the risk that liabilities cannot be met when they fall dueOperational risk is the risk of loss resulting from inadequate or failed internal processes, people and systems or from external events.SecurityReconciliationOperations MIOperational risk assessment:No generally agreed metricsData gathering (i.e. classifying events according to type and severity)Reduction achieved by controls over movement of data, manual operations and adequate reporting
5 Market Risk The five standard market risk factors include: Equity risk = risk that stock prices will change.Interest rate risk = risk that interest rates will change.Currency risk = risk that foreign exchange rates will change.Commodity risk = risk that commodity prices (i.e. grains, metals, etc.) will change.Credit spread risk = risk that bond rates will change relative to interest rates.Market risk measurement:Nominal positionMarket valueSensitivityStress and scenario testingValue at Risk
6 Market Risk – cont’dA single risk-factor is the smallest unit for which risk is calculated.Risk-types are defined as the collection of all risk-factors (single risk-factors or term-structures) across different currencies, indices.Interest rate risk measuresCash-flows and time value of moneyYield to maturity, duration and convexityPV01, PVBP, DV01, BPVCredit risk measuresPar CDS spread, z-spread, YtM spreadCredit Duration and CS01 or CR01Option risk measuresDeltaGammaVegaRhoTheta
7 Value at RiskValue at Risk is an aggregated risk measure used to estimate the risk of a trading portfolio.VaR expresses many different types of risk as a “common currency”.VaR models predict the worst case loss expected over the holding period within the probability set out by the confidence interval.Specifically, the loss one would expect to exceed over a specific holding period to a certain level of confidence:1 day 99% VaR of £1m tells you that you would expect to lose £1m or more on one day in every hundred or 2-3 times a year.Typically firms use 1 day 95% or 1 day 99%.We make firms use a 10 day holding period one-tailed for their PRR calculation.The firm can use the square root of time method.Fat tail.
8 VaR Methodology Main methods of calculating VaR: Historical simulation Most frequently used by firmsRe-run the market moves that occurred on each of previous N daysCalculate p&l on today’s positions for each day’s movementsVaR is 5th (say) worst outcomeVariance-CovariancePopular with some smaller firms with linear risk portfoliosEstimate NxN variance-covariance matrix (N underlying market variables)Assume market variables are distributed multivariately normallyAssume p&l responds linearly to market variablesMonte CarloUse is growing, but very IT intensive for complex productsWork out covariance matrix and assume normality (or any other distribution)Generate several sets of random correlated market movements from assumed distributionCalculate p&l for each set of movements
9 VaR Methodology Historical Simulation Simple concept Run portfolio over last N days (e.g. N=500) to calculate distribution of losses that would have occurred on the actual portfolioAssume the past resembles the future
10 VaR - HistSim Historical Simulation Advantages Avoids making statistical assumptionsCaptures outliers or tail eventsActual correlations and volatilitiesGives a “worst case” scenario (built in stress test)Handles non-linear instruments, but dependent on implementation (in practice simplifications/approximations very common)Easy to understandDisadvantagesHuge amount of market data requiredMay not respond rapidly to changes in volatilityComputationally intensiveStatistical assumptions are implicit and can give false comfort (e.g. assumption of constant vol, constant correlation)No explanation of relationship between risk factors“Ghost” effectsCredit default data
11 VaR – Montecarlo Sim Monte Carlo simulation MarketdataMonte Carlo simulationLike HS, simulation approachLike VCV, uses multivariate (or lognormal) model of underlying market movesSeries of market moves randomly generated (“draws”)P&l effects then calculated in similar way to HSSimulate market movementsBased on historical dataGives richer simulation of “possible outcomes”Apply to current portfolioAssume the past resembles the futureEstimate variance-covariance matrix.Use matrix and random number generator to generate random market moves.Use simulated market moves to calculate random p&l effects on present portfolio.Portfolio dataUse simulated distribution of portfolio values to compute VaR.
12 General vs Specific Harder to get a SR recognition: SR models have generally performed worse in volatile conditionsMost excessive backtesting exceptions issues relate to SR models.The market risk and specific risk VaR can be aggregated assuming zero correlation (independent validation):General (GR)Specific (SR)Equity(indices)(name specific)Interest Rate(rates)(credit)FX(all FX risk)Commodities(all commodity risk)
13 Approval Process - cont’d The Board & senior management must be involvedMarket Risk management should be independent of the trading unit and report directly to senior managementVaR model validationIndependent from development team and documentedPrudent Valuation of positionsValuation adjustments for illiquidity, concentrated positions, model risks, operational risks, administration risk, close out risk need to be consideredIT systemsSystem development and change controlInternal audit / Annual independent reviewAccuracy, completeness, consistency
14 Risks not in VaR (RNIV)Systematically identify and measure risks not captured or not captured adequately by the VaR model and hold a self-determined quantity of capital against material exposures.These risks can be significant P&L drivers, and hence require capitalisation: during and after the 2007/8 crisis VaR models performed badly (many backtesting exceptions).VaR type RNIVs = P&L Impact (Percentile Move)Stressed RNIVs = P&L Impact (Stress Scenario Move)Risks not in pricing models:Libor tenor basisRisks not in VaR Engine:Skew, Convexity, Vol of Vol, Cross gamma, Mean reversion, SeasonalityInadequate data (liquidity, lack of history):Correlation, Dividend, ProxyBeyond 99%-tile or 10-day liquidity horizon:FX depeg/repeg risk, Gap risk.
15 BacktestingCompare 1-day VaR forecast with actual p&l outcomes to try to assess model accuracyFor one-tailed 99%, on average, 2.5 exceptions every 250 days.If the number of exceptions is high, VaR model could be not good enough and the firm will be subject to capital charge penalty (plus factor).Perform overall and at sub-portfolio levelGeneral and Specific risks portfolioAnalyse reasons for exceptionsThree months of back testing data is needed before model recognition is granted.Inaccurate Model – VaR too smallInaccurate Model – VaR too large
16 Basel 2.5 New capital component for Market risk Stressed VaR (SVaR) All firms with CAD 2 (VaR)-modelLess procyclicalSelection of 12 months period during which inputs (relevant market risk factors) experience significant stressRelevance to the firm’s portfolioReview requirement: changes in positioning in trading portfolios need to trigger a review of stressed period selectionIncremental Risk Charge (IRC)All firms with specific interest rate risk (~credit spread volatility) in VaR modelDefault and migration risksComprehensive Risk Measure (CRM)Firms with correlation trading portfolios (CDOs and basket credit derivatives), alternative to standard rules.
17 Basel 2.5MARKET RISKINTEREST RATE RISK EQUITY RISK FX RISK COMMODITY RISKStandardisedGeneral market riskSpecific riskStandardised charges for sec and Re-sec.Internal modelsGeneral Market riskVaRStressed VaRSpecific RiskIDRCIRCCRM
18 FRTB - BackgroundThe financial crisis exposed weaknesses in the market risk framework (which hadn’t materially changed since the market risk amendment in 1996).In 2009 the Basel Committee introduced a set of revisions to the current market risk framework to address the most material issues – Basel 2.5. The fundamental review of the trading book was initiated to deal with all of the identified weaknesses in a coherent manner.The first CP for the fundamental review of the trading book was published in May 2012.A second CP with detailed draft Accord text was published in October 2013, taking into account comments received on CP1.
19 BackgroundThe new market risk framework aims to address the weaknesses of the pre-crisis framework:The permeable / subjective nature of the trading book boundary.A range of problems with the internal model approach:Poor capture of varying liquidity of traded positions;Pro-cyclical calibration that did not focus on stressed losses;Lack of capture of tail-risk;No capture of default and migration risk.Lack of risk sensitivity of the standardised approach, meaning a lack of credible threat of removal of model permission.
20 New trading book boundary Current boundary is largely based on trading intent – difficult to evidence / police in practice.New boundary maintains a link with trading intent, but aims to be less susceptible to arbitrage by providing more guidance and more information for supervisors:Presumptive lists of instruments that are in the trading book (e.g. positions designated as held for trading for accounting purposes, instruments resulting from market making activities);Limit on switching instruments after initial designation;Explicit supervisory authority to re-designate positions;Reporting requirements to support supervision.
22 New internal models (2)More granular approval process – approval at desk level with P&L attribution and backtesting requirements.Expected shortfall rather than VaR, calibrated to stressed conditions and with varying liquidity horizons.Criteria to determine which risk factors at each trading desk are modellable or non-modellable – separate approach to capitalise each type.Separate default risk model to capture default risk in the trading book (with greater specification on calibration).All securitisations excluded from the internal model approach.
23 ES (modellable risks) + IDR + Non-modellable risks New internal models (3)Total capital requirement for eligible desks =ES (modellable risks) + IDR + Non-modellable risks
24 New standardised approach New standardised approach aims to achieve a balance of risk sensitivity and simplicity.Within each risk class capital requirements calculated based on sensitivities with prescribed risk factor shocks and correlations across risk factors.No diversification across risk classes (equity risk, commodity risk, foreign exchange (FX), general interest rate risk (GIRR), credit spread risk (CSR), default risk).Non-delta risk of options capitalised under the scenario matrix approach.Aim is to have an approach that is a credible fall-back to internal models.
25 Recap The new framework is designed to address the following: The permeable / subjective nature of the trading book boundary.A range of problems with the internal model approach:Poor capture of varying liquidity of traded positions;Pro-cyclical calibration that did not focus on stressed losses;Lack of capture of tail-risk;No capture of default and migration risk.Lack of risk sensitivity of the standardised approach, meaning a lack of credible threat of removal of model permission.