1. Market Risk – Internal Model Approach
K.G.Bhandari
IndusInd Bank Ltd.
March 15, 2010
Indian Banks’ Association
4th Annual summit 2010

2. Basel Accord
Capital requirement were simplistic and rigid – but did not reflect underlying economic risks of banks / FIs
Now, capital requirements are more risk sensitive - reflects economic risk assumed
These new standards are generally based on Value-at-Risk (VaR) methods
VaR is a measure of loss at given confidence level and directly translates into measure of buffer capital
Basel-I Accord sets Minimum Capital requirements to guard against Credit Risk
To control expanding Trading activities, Capital Charge for market risk was included later

3. Standardised Method – Capital Charge for Market Risk
Based on pre-specified, standarised, ‘building – block approach’
Market risk is computed for portfolios exposed to interest rate risk, exchange risk, equity risk and commodity risk
Takes into account Notional amount and market parameters
Main drawback – ignores diversification across market risks – within each category and across different categories
Highly conservative – Adds up capital charge for each category
Assumes that Worst Loss will hit all portfolios at the same time
Does not reward prudent diversification

4. Internal Model Approach
IMA recognises –
Risk Management models in use – far more advanced than rigid rules
Banks can use their own VaR models as basis for capital requirement for Market Risk
VaR is a robust Risk Measurement and Management Practice

5. IMA - Qualitative Criteria
Independent Risk Control Unit responsible for design and implementation of Bank’s risk management systems
Regular Back-Testing
Initial and on-going Validation of Internal Model
Bank’s Internal Risk Measurement Model must be integrated into Management decisions
Risk measurement system should be used in conjunction with Trading and Exposure Limits.
Stress Testing
Risk measurement systems should be well documented
Independent review of risk measurement systems by internal audit
Board and senior management should be actively involved

6. IMA - Quantitative criteria
Quantitative Parameters :
VaR computation be based on following inputs :
Horizon of 10 Trading days
99% confidence level
Observation period – at least 1 year historical data
Correlations : recognise correlation within Categories as well as across categories (FI and Fx, etc)
Market Risk charge : General Market Risk charge shall be – Higher of previous day’s VaR or Avg VaR over last 60 business days X Multiplier factor K (absolute floor of 3)

7. Market Risk Charge Market Risk charge on any day ‘t’
SRC – Specific Risk Charge

8. Back testing Possible cause and remedies of the "Yellow" zone
Basic Integrity of the model
Deficient model accuracy
Intra day trading
Bad luck

9. Internal Model Approach - Benefits
Internal VaR system is more precise
VaR account for correlations
Market risk charge under IMA likely to be lower
With improvements in risk measurement techniques, IMA will enable capital charge to be more precise
Market Risk charge needs to be computed and monitored daily
Each day VaR is compared with the subsequent Trading profit or loss
Back Testing will help to refine the framework

10. Market Risk – Advanced Risk Measurement Techniques enables Bank to effectively control the amount of market risk it assumes and allocate capital for the same
‘Know’ your risks
Control Measures
Allocate Capital
Measurement Techniques
Marking to Market
Duration, Convexity
Price Value of a Basis Point
VaR - Forex (Spot & Forward)
Stress Testing
Scenario Analysis
Duration Limits
VaR Limits
Stop Loss Limits
Counterparty Exposure Limits
Country Exposure Limits
Standardized Model
Internal Model
Time
Sophistication
Mark to Market
Duration
Value at Risk
Stress Testing
Use of Statistical
analysis to
determine
maximum losses
Use of ‘What if’
scenarios to
determine losses
in extreme
events
Cashflow
measure the
sensitivity of
fixed income
instruments
Revaluation of
the portfolio to
measure notional
P/L
Use of statistical

11. Market Risk Amendment Paradigm becomes explicit  Frequency of loss
Expected
loss 
Stress
loss 
Unexpected loss
Amount of loss

12. 1 4 2 3 Supporting Factors for Risk Management
Involve of the board of directors and high level management 4 2
Effective Risk Management
Set up risk management system
Formulate risk management policies and procedures
Establish a unit to operate risk management 3

13. Limitations to Risk Management
Involve of the board of directors and high level management
Not enough cooperation
Low qualification
Lack of independence to make a decision
Not transparence
Formulate risk management policy and procedures
Policies/ procedures not match with risks
Underdevelopment Infrastructure
Rigid to implement
Communication failure
Establish a unit to operate risk management
Lack of adequate structure
Staff has less experience
Lack of independence
Set up risk management system
No follow up and control system
Not enough risk assessment/ management instruments
Database and IT system

14. Internal Model Approach
Supervisory objectives
better risk management
continual upgrading and encouragement of innovation in risk management methodology and
improved risk sensitivity and measures.

15. Internal Model Framework

16. Impact & Benefits Best practice risk and capital management
In particular:
Risk management - processes and controls
Capital management - eligible capital and quality of capital
Improved market perception: enhanced reputation for risk management
Precise capital requirements and return on capital
Enhanced management information to support more optimal management decisions
Reduced costs: Operational efficiencies from better risk management

17. Internal model and its purpose
What is an internal model?
“A risk management system developed by the Bank to analyse the overall risk position, to quantify risks and to determine the economic capital required to meet those risks”
What is the purpose of an internal model?
To fully integrate processes of risk and capital management within the Bank

18. Expected Benefits Improved risk sensitivity
Better alignment of regulatory capital requirements with economic capital
Encouragement of innovation in risk management methodology leading to higher competitiveness through better risk management and hence lower costs of capital
More effective pillar 2 discussion and familiarity of the supervisor with more detailed exposure data
Cost efficiencies through re-use of risk modeling infrastructure for discussion with supervisors, rating agencies, analysts and shareholders.

19. Particular issues for banks
The regulatory requirements are not yet come
There is a shortage of skills and expertise
There are data limitations
Low base in terms of use of models and risk management; in effect, attempting to “jump a generation”
The operating environment is undergoing fundamental change
However, none of these difficulties are insurmountable if one learns from others
Most difficult IRB qualifying criterion to meet is not in relation to the models themselves but in relation to the use them - a major challenge
It needs to be recognised that a robust risk management framework is an essential prerequisite. Successful implementation, such as the use of models, can only be achieved if they integrate into a sound framework of systems and controls; in the case of certain banks, there may be some gap vis-à-vis international best practice

20. Specification of Market Risk Factors
For interest rates, there must be a set of risk factors corresponding to interest rates in each currency in which the bank has interest-rate-sensitive on- or off-balance sheet positions
The risk measurement system should model the yield curve using one of a number of generally accepted approaches
The risk measurement system must incorporate separate risk factors to capture spread risk
For exchange rates (which may include gold), the risk measurement system should incorporate risk factors corresponding to the individual foreign currencies in which the bank’s positions are denominated
For equity prices, there should be risk factors corresponding to each of the equity markets in which the bank holds significant positions
For commodity prices, there should be risk factors corresponding to each of the commodity markets in which the bank holds significant positions

21. Quantitative Standards
“Value-at-risk” must be computed on a daily basis
In calculating the value-at-risk, a 99th percentile, one-tailed confidence interval is to be used
“Holding period” will be ten trading days
“Effective” historical observation period must be at least one year
Banks should update their data sets no less frequently than once every three months and should also reassess them whenever market prices are subject to material changes
No particular type of model is prescribed – should captures all the material risks run by the bank
Banks will have discretion to recognise empirical correlations within broad risk categories
Banks’ models must accurately capture the unique risks associated with options within each of the broad risk categories
Each bank must meet, on a daily basis, a capital requirement expressed as the higher of
its previous day’s value-at-risk number measured according to the parameters specified in this section and
an average of the daily value-at-risk measures on each of the preceding sixty business days, multiplied by a multiplication factor
multiplication factor will be set by supervisory authorities on the basis of their assessment of the quality of the bank’s risk management system, subject to an absolute minimum of 3.
Banks using models will also be subject to a capital charge to cover specific risk (as defined under the standardised approach for market risk) of interest rate related instruments and equity securities

22. Stress Testing
Stress testing to identify events or influences that could greatly impact banks is a key component of a bank’s assessment of its capital position
Stress scenarios need to cover a range of factors that can create extraordinary losses or gains in trading portfolios, or make the control of risk in those portfolios very difficult
Stress tests should be both of a quantitative and qualitative nature, incorporating both market risk and liquidity aspects of market disturbances
Banks should combine the use of supervisory stress scenarios with stress tests developed by banks themselves to reflect their specific risk characteristics
Stress tests results should be reviewed periodically by senior management and should be reflected in the policies and limits set by management and the board of directors

23. External Validation
Validation of models’ accuracy by external auditors and/or supervisory authorities should at a minimum include
verifying the internal validation processes
formulae used in the calculation process as well as for the pricing of options and other complex instruments are validated by a qualified unit - independent from the trading area
Structure of internal models is adequate with respect to the bank’s activities and geographical coverage
results of the banks’ back-testing of its internal measurement system
data flows and processes associated with the risk measurement system are transparent and accessible

24. The Standardized Method
Risk classification is arbitrary.
Ignores diversification : leads to high capital requirements because risk charges are systematically added up across difference sources of risk
Captures Risk for positions as on the day and not for the period.

25. The Standardized Approach
Guidelines to compute
Interest rates risk
Exchange risk
Equity risk
Commodity risk
The bank's total risk is computed as the summation of the 4 categories
ignoring correlations
Provide a robust measure of interest rate risk taking into account
Systematic/Market risk
duration
basis risk across maturities
Specific/Idiosyncratic risk

26. The Standardized Approach - Market Interest Rate Risk
Market risk is defined via Maturity Bands

27. Specific Interest Risk Charge
The capital charge for specific risk is designed to protect against an adverse movement in the price of an individual security owing to factors related to the individual issuer
Capital Charge for Interest Rate Risk
Where,
= Capital Charge for Total Interest rate Risk
= Capital Charge for General Interest rate Risk
= Capital Charge for Specific Interest rate Risk

28. The Internal Model Approach (IMA)
Rely on Internal Risk Management of the Bank
for the first time Regulation recognized that bank had developed trustable risk management systems
if this approach lead to lower Capital Charge, Banks have incentives to develop sophisticated and more accurate models
However, need to be approved by Regulation
sound and sufficient details on the VAR and diversification models at qualitative and quantitative levels

29. The Internal Model Approach (IMA) - Qualitative Requirements
Independent Risk Control Unit
The bank must a risk control that is independent of trading and reports to senior management, to minimize conflicts of interests
Back testing
Involvement
senior
sufficient resources
Use of limits
Stress Testing
Compliance (to a documented set of policies)
Independent Review

30. The Internal Model Approach (IMA) - Qualitative Requirements
Requirement on risk factors :
at least 6 factors for yield curve risk + separate risk factors to model spread risk
for equity, the model should at least consist of beta mapping on an index, a more detailed approach could consist in adding industry factors, as well as individual risk factor modeling
for active trading in commodity, the model should account for for movements in the spot plus convenient yields
bank should also capture the non linear price characteristics of options (gamma, vega , ...)
Correlation within broad risk categories are recognized explicitly

31. The Internal Model Approach (IMA) - VAR
Market Risk Charge = VAR
Shall be computed every day
for a10 days horizon
Bank can use a daily VAR and scale it using the square root time rule
with a 99% confidence level
with an observation period based on at least one year moving window of historical data
shall be set at the higher of the previous day's VAR, or the average over the 60 business days,
times a multiplicative factor k
determined by regulator (in the range of 3 to 4) to prevent model misspecifications
a plus factor is added (depending on the performance of the model)

32. Stress Testing
Stress Testing can be described as a process to identify and manage situations that could cause extraordinary losses
Tools
Scenarios Analysis
Stressing Models
Policy Response

33. Stress Testing - Scenarios Analysis
Evaluating the portfolios
under various states of the world
evaluating the impact
changing evaluation models
volatilities and correlations
Scenarios requiring no simulations
analyzing large past losses
Scenarios requiring simulations
running simulations of the current portfolio subject to large historical shocks
e.g crash, etc ...
Bank specific scenario
driven by the current position of the bank rather than historical simulation
Much more subjective than VAR
Can help to identify undetected weakness in the bank's portfolio

34. Back testing
Statistical testing that consist of checking whether actual trading losses are in line with the VAR forecasts
The Basle back testing framework consists in recording daily exception of the 99% VAR over the last year
Even though capital requirements are based on 10 days VAR, back testing uses a daily interval, which entails more observations
On average, one would expect 1% of 250 or 2.5 instances of exceptions over the last year
Too many exceptions indicate that
either the model is understating VAR
the Bank is unlucky
How to decide ?
Statistical inference

35. Basel Market Risk Charges
The Market Risk Charge
Quantitative parameters
Market risk charge
Plus factor
Stress Testing
A process to identify and manage situations that could cause extraordinary losses
Scenarios requiring no simulation
Scenarios requiring a simulation
Bank-Specific scenarios

36. Basel Market Risk Charges
Back testing
A statistical testing framework that consists of checking whether actual trading losses are in line with VAR forecasts
Exceptions
The Penalty Zones
Basic integrity of the model
Deficient model accuracy
Intraday trading
Bad luck

37. Internal Model Approach - VaR
Qualitative Requirements :
To use IMA, banks need to satisfy Qualitative Requirements
Robust risk measurement systems in place – must be integrated into Management Decisions
Conduct Stress Tests regularly
Independent Risk Monitoring Framework