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Fundamental Review of the Trading Book
OVERVIEW & IMPLEMENTATION NOTES
FEBRUARY 2016
Contents
1. Introduction
2. Standardised Approach
Sensitivities-based capital charge
3. Internal Models Approach
Approved desk capital charge
Scope and scale
4. Capital Impact
5. Technical Requirements
6. Implementation Notes
Introduction
May 2012
Consultation started :
Fundamental Review of the Trading Book (FRTB)
January 2016
Final standards published :
Minimum Capital Requirements for Market Risk
Implementation timetable
1 January 2019
Deadline for national supervisors to implement
under domestic legislation.
31 December 2019
Deadline for regulatory reporting by banks using
the revised market risk framework.
Key Points
 A clearer, more objective boundary between the trading book and
banking book to reduce incentives for regulatory arbitrage.
 A revised risk measurement approach and calibration to better
capture tail risk, liquidity risk and periods of significant financial stress.
 A revised standardised approach to provide a simple but sufficiently
risk-sensitive alternative to internal models.
 A revised internal models-based approach with more rigorous model
approval and better capitalisation of material risk factors.
 More complex internal models approach requires up to 30x more
data storage and processing capacity than existing Basel capital
calculations.
Standardised Approach (SA)
Must be calculated by all banks and reported monthly (and as requested by the supervisor).
SA Capital Charge (CC) = Sensitivities-based CC + Default Risk Charge + Residual Risk Add-On
Residual Risk Add-On (RRAO)
Includes any risk that would otherwise
not be capitalised under the proposed
SA, such as behavioural risk or exotic
underlying risk.
Simple sum of gross notional amount of
instruments bearing residual risks,
multiplied by a risk weight of:
• 1.0% for instruments with an exotic
underlying.
• 0.1% for instruments bearing other
residual risks.
Default Risk Charge (DRC)
Banking book-based treatment of
default risk, adjusted to take into
account more hedging effects.
Based on Jump to Default (JTD)
calculation.
Sensitivities-based Capital Charge
(Details on next slide)
SA: Sensitivities-based Capital Charge
to risk factors, eg: Assign to risk buckets and aggregate using prescribed:within broad risk classes.
Issuer credit spread curve
Calculate net sensitivities
General Interest Rate
FX
Credit Spread
Commodity
Equity
for instruments
with optionality
Currency (EUR, USD…)
Credit quality (IG, HY…)
Sector (Sovereigns, RMBS…)
Category (Energy, Livestock…)
Currency pair (USD/CNY,
EUR/GBP…)
Market cap (Large, Small)
Economy (Emerging, Advanced)
Sector (Telco, Financials…)
correlations
• between risk factors within a bucket.
• across buckets within a risk class.
For each risk class, take the worst
case of low, medium and high
correlation scenarios.
Tenors on currency
risk-free yield curvedelta
Equity option underlying at
different maturitiesvega
• delta
• vega
• curvature
Issuer credit
spread curvecurvature
risk weights
• applied to net sensitivities.
• reflect relative risk of buckets and risk
factors, eg tenors on a yield curve.
Internal Models Approach (IMA)
IMA capital charge (CC) = Approved Desk CC + Default Risk Charge + Unapproved Desk CC
Standardised Approach CCModellable Risk CC + Non-Modellable Risk CC
Approved Desk CC
(Details on next slide)
Default Risk Charge
• Default simulation with 2 types of
systematic risk factors.
• Weekly calculation: 99.9% VaR based on
constant positions over 1 year time horizon.
Standardised Approach may
also act as a floor or surcharge
to the IMA capital charge.
Stressed Capital Add-On
(SES)
Global Expected Shortfall
(ES)
All securitised products are ineligible for inclusion in the internal models-based capital
charge and must be capitalised using the standardised approach.
Computed on a daily basis firm-wide and at trading desk level.
Firm-wide requirements on models, stress testing and risk management processes.
Approvals at individual trading desk level based on:
• Assessment of model performance.
• Clear thresholds for breaches of backtesting and P&L attribution procedures.
Potentially 5×3×6=90 revaluations, although many combinations are not valid.
IMA: Approved Desk Capital Charge
Non-Modellable Risk
Stressed Capital Add-On (SES)
Capitalised with stress scenario that is at least
as prudent as ES 97.5% confidence threshold
over time of extreme stress.
Capital Charge (CC) is floored at a
multiple of the 60-day average CC
Multiplier for ES varies between 1.5 and 2
depending on backtesting performance.
Modellable Risk
Global Expected Shortfall (ES)
Base calculation
97.5% 10-day (overlapping) Expected Shortfall
Full revaluation
Adjust for liquidity
Combine total ES with partial ES values, scaled
up to each liquidity horizon
Calibrate to period of stress
Combine three ES values to produce stress
period with full set of risk factors
Disallow some diversification
Calculate equally-weighted average of total
and non-diversified (sum of partial) ES values
total ES value
with shocks to all risk factors
12 month period of greatest
stress, with a reduced set of risk
factors.
Current 12 month period, with a
reduced set of risk factors.
Current 12 month period, with
the full set of risk factors.
total ES value
with shocks to all risk classes
4 partial ES values
with shocks to subsets of risk factors with liquidity horizons of at least 20
days, 40 days etc.
5 partial ES values
with shocks to one of the
regulatory risk classes
IMA: Scope and Scale
FRTB framework Jan 2016 Revised Basel II framework Dec 2010
Positions 100,000
Including equity, commodity, FX, interest rate and credit instruments, and their derivatives.
Market risk measure Expected Shortfall (daily) Value at Risk (daily)
Stressed Value at Risk (weekly)
Risk factor combinations ~20 valid combinations of liquidity horizon and risk class
Only a fraction of these will apply to each individual position,
so there is scope to improve efficiency by eliminating
redundant valuations.
1
Only a total scenario (all factors shifted) is required.
Scenarios 250 ES 1 year time horizon.
3 sets of scenarios to calibrate to a period of stress
Two of the sets of scenarios use a reduced set of risk factors,
so will produce fewer than the 20 valid combinations listed
above. If there is 10 years of history for the full set of risk
factors, it may be possible to use a single set of scenarios,
effectively applying the full set of risk factors to the stress
period directly.
500 VaR 2 year time horizon.
500 Stressed VaR 1 year time horizon with antithetical scenarios.
Total scenario valuations 100,000 x 20 x 3 x 250 = 1,500,000,000 (daily)
Full revaluations
100,000 x 1 x 500 = 50,000,000 (daily)
100,000 x 1 x 500 = 50,000,000 (weekly)
Data volume (monthly)
Based on one result using 20 bytes
~600GB ~25GB
Comparison of computing resources against existing Basel II.5 regulation, based on example portfolio with 100,000 positions.
~30x more data & compute
Capital Impact
Final calibration produces lower overall capital requirement than earlier versions of the framework.
Overall market risk capital charge contributions:
72% non-securitisation exposures.
23% non-CTP securitisation exposures.
5% correlation trading portfolio (CTP)
securitisation exposures.
Compared to current framework, revised
framework shows an approximate:
22% increase in median total
market risk capital requirement.
40% increase in weighted
average capital requirement.
For the median bank,
standardised approach produces
a 40% higher total capital charge
compared to internal models.
At the 25th percentile, SA
produces a 10% lower
capital charge than IMA.
At the 75th percentile, SA
produces a 200% higher
capital charge than IMA.
Comparing the two approaches in the revised framework for non-securitisations:
Analysis based on end-June 2015 data in the BIS document
“Explanatory note on the revised minimum capital requirements for market risk”
Technical Requirements
Standardised Approach Internal Models Approach
DataGathering
Positions Drive all capital calculations.
Notionals and market values feed into other calculations, eg default risk and residual risk.
Instrument risk factor sensitivities Used for sensitivities-based method. Determine applicable liquidity horizons.
Instrument metadata
(eg sector, credit quality, currency)
• Used for bucketing to determine risk weights and correlations.
• Used to determine risk weighting in DRC.
• Used to identify instruments with residual risks for RRAO.
• Used for proxying risk factors, eg to a sector index.
• Useful for reporting.
Actual & hypothetical P&L
 Used for backtesting to support model approval.
Historical market data
 • Time series for ES and VaR (for backtesting).
• Historical stress scenarios.
• Correlations, PDs and LGDs for default risk charge.
Pricing analytics Risk factor sensitivities (PV01, CS01 etc). • Pricing stress and ES/VaR scenarios.
• Scalability/flexibility to handle multiple revaluations
with subsets of risk factors.
Other analytics Calculation of sensitivities-based capital charge, DRC and RRAO. • Aggregation of ES values.
• Default simulation for default risk charge.
Reporting Enhanced reporting requirements at desk level, including daily/intraday limit reports (exposures, breaches and follow-up
action).
Monthly reporting of SA capital charge. Weekly P&L reports and internal/regulatory risk measure
reports (VaR/ES, backtesting).
Implementation Notes
 Be proactive, not reactive - requirements will change, new regulations will be added.
eg FRTB-CVA for counterparty credit risk
 Look at enterprise-wide risk.
Siloed solutions no longer work
 Design to reuse infrastructure for Standardised and Internal Models approaches.
 Aim for consistent interfaces to disparate systems.
Front Office position feeds
Pricing analytics
Historical market data
 Use a single pricing engine across front office and risk management to avoid extra model validation.
 Automate data gathering and cleaning.
Improve data quality
Free up risk managers from manual work
 Improve reporting to help Risk Management.
Trace sources of risk from capital charge back to positions and market data
Drill down to desk level and to individual positions, across all business lines
www.percentile.co.uk
info@percentile.co.uk
@pcentile
Percentile provides software for integrated and holistic
risk management in capital markets,
to deliver faster regulatory compliance and reduce
operational risk while lowering costs.
2016

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FRTB Overview & Implementation Notes

  • 1. Fundamental Review of the Trading Book OVERVIEW & IMPLEMENTATION NOTES FEBRUARY 2016
  • 2. Contents 1. Introduction 2. Standardised Approach Sensitivities-based capital charge 3. Internal Models Approach Approved desk capital charge Scope and scale 4. Capital Impact 5. Technical Requirements 6. Implementation Notes
  • 3. Introduction May 2012 Consultation started : Fundamental Review of the Trading Book (FRTB) January 2016 Final standards published : Minimum Capital Requirements for Market Risk Implementation timetable 1 January 2019 Deadline for national supervisors to implement under domestic legislation. 31 December 2019 Deadline for regulatory reporting by banks using the revised market risk framework. Key Points  A clearer, more objective boundary between the trading book and banking book to reduce incentives for regulatory arbitrage.  A revised risk measurement approach and calibration to better capture tail risk, liquidity risk and periods of significant financial stress.  A revised standardised approach to provide a simple but sufficiently risk-sensitive alternative to internal models.  A revised internal models-based approach with more rigorous model approval and better capitalisation of material risk factors.  More complex internal models approach requires up to 30x more data storage and processing capacity than existing Basel capital calculations.
  • 4. Standardised Approach (SA) Must be calculated by all banks and reported monthly (and as requested by the supervisor). SA Capital Charge (CC) = Sensitivities-based CC + Default Risk Charge + Residual Risk Add-On Residual Risk Add-On (RRAO) Includes any risk that would otherwise not be capitalised under the proposed SA, such as behavioural risk or exotic underlying risk. Simple sum of gross notional amount of instruments bearing residual risks, multiplied by a risk weight of: • 1.0% for instruments with an exotic underlying. • 0.1% for instruments bearing other residual risks. Default Risk Charge (DRC) Banking book-based treatment of default risk, adjusted to take into account more hedging effects. Based on Jump to Default (JTD) calculation. Sensitivities-based Capital Charge (Details on next slide)
  • 5. SA: Sensitivities-based Capital Charge to risk factors, eg: Assign to risk buckets and aggregate using prescribed:within broad risk classes. Issuer credit spread curve Calculate net sensitivities General Interest Rate FX Credit Spread Commodity Equity for instruments with optionality Currency (EUR, USD…) Credit quality (IG, HY…) Sector (Sovereigns, RMBS…) Category (Energy, Livestock…) Currency pair (USD/CNY, EUR/GBP…) Market cap (Large, Small) Economy (Emerging, Advanced) Sector (Telco, Financials…) correlations • between risk factors within a bucket. • across buckets within a risk class. For each risk class, take the worst case of low, medium and high correlation scenarios. Tenors on currency risk-free yield curvedelta Equity option underlying at different maturitiesvega • delta • vega • curvature Issuer credit spread curvecurvature risk weights • applied to net sensitivities. • reflect relative risk of buckets and risk factors, eg tenors on a yield curve.
  • 6. Internal Models Approach (IMA) IMA capital charge (CC) = Approved Desk CC + Default Risk Charge + Unapproved Desk CC Standardised Approach CCModellable Risk CC + Non-Modellable Risk CC Approved Desk CC (Details on next slide) Default Risk Charge • Default simulation with 2 types of systematic risk factors. • Weekly calculation: 99.9% VaR based on constant positions over 1 year time horizon. Standardised Approach may also act as a floor or surcharge to the IMA capital charge. Stressed Capital Add-On (SES) Global Expected Shortfall (ES) All securitised products are ineligible for inclusion in the internal models-based capital charge and must be capitalised using the standardised approach. Computed on a daily basis firm-wide and at trading desk level. Firm-wide requirements on models, stress testing and risk management processes. Approvals at individual trading desk level based on: • Assessment of model performance. • Clear thresholds for breaches of backtesting and P&L attribution procedures.
  • 7. Potentially 5×3×6=90 revaluations, although many combinations are not valid. IMA: Approved Desk Capital Charge Non-Modellable Risk Stressed Capital Add-On (SES) Capitalised with stress scenario that is at least as prudent as ES 97.5% confidence threshold over time of extreme stress. Capital Charge (CC) is floored at a multiple of the 60-day average CC Multiplier for ES varies between 1.5 and 2 depending on backtesting performance. Modellable Risk Global Expected Shortfall (ES) Base calculation 97.5% 10-day (overlapping) Expected Shortfall Full revaluation Adjust for liquidity Combine total ES with partial ES values, scaled up to each liquidity horizon Calibrate to period of stress Combine three ES values to produce stress period with full set of risk factors Disallow some diversification Calculate equally-weighted average of total and non-diversified (sum of partial) ES values total ES value with shocks to all risk factors 12 month period of greatest stress, with a reduced set of risk factors. Current 12 month period, with a reduced set of risk factors. Current 12 month period, with the full set of risk factors. total ES value with shocks to all risk classes 4 partial ES values with shocks to subsets of risk factors with liquidity horizons of at least 20 days, 40 days etc. 5 partial ES values with shocks to one of the regulatory risk classes
  • 8. IMA: Scope and Scale FRTB framework Jan 2016 Revised Basel II framework Dec 2010 Positions 100,000 Including equity, commodity, FX, interest rate and credit instruments, and their derivatives. Market risk measure Expected Shortfall (daily) Value at Risk (daily) Stressed Value at Risk (weekly) Risk factor combinations ~20 valid combinations of liquidity horizon and risk class Only a fraction of these will apply to each individual position, so there is scope to improve efficiency by eliminating redundant valuations. 1 Only a total scenario (all factors shifted) is required. Scenarios 250 ES 1 year time horizon. 3 sets of scenarios to calibrate to a period of stress Two of the sets of scenarios use a reduced set of risk factors, so will produce fewer than the 20 valid combinations listed above. If there is 10 years of history for the full set of risk factors, it may be possible to use a single set of scenarios, effectively applying the full set of risk factors to the stress period directly. 500 VaR 2 year time horizon. 500 Stressed VaR 1 year time horizon with antithetical scenarios. Total scenario valuations 100,000 x 20 x 3 x 250 = 1,500,000,000 (daily) Full revaluations 100,000 x 1 x 500 = 50,000,000 (daily) 100,000 x 1 x 500 = 50,000,000 (weekly) Data volume (monthly) Based on one result using 20 bytes ~600GB ~25GB Comparison of computing resources against existing Basel II.5 regulation, based on example portfolio with 100,000 positions. ~30x more data & compute
  • 9. Capital Impact Final calibration produces lower overall capital requirement than earlier versions of the framework. Overall market risk capital charge contributions: 72% non-securitisation exposures. 23% non-CTP securitisation exposures. 5% correlation trading portfolio (CTP) securitisation exposures. Compared to current framework, revised framework shows an approximate: 22% increase in median total market risk capital requirement. 40% increase in weighted average capital requirement. For the median bank, standardised approach produces a 40% higher total capital charge compared to internal models. At the 25th percentile, SA produces a 10% lower capital charge than IMA. At the 75th percentile, SA produces a 200% higher capital charge than IMA. Comparing the two approaches in the revised framework for non-securitisations: Analysis based on end-June 2015 data in the BIS document “Explanatory note on the revised minimum capital requirements for market risk”
  • 10. Technical Requirements Standardised Approach Internal Models Approach DataGathering Positions Drive all capital calculations. Notionals and market values feed into other calculations, eg default risk and residual risk. Instrument risk factor sensitivities Used for sensitivities-based method. Determine applicable liquidity horizons. Instrument metadata (eg sector, credit quality, currency) • Used for bucketing to determine risk weights and correlations. • Used to determine risk weighting in DRC. • Used to identify instruments with residual risks for RRAO. • Used for proxying risk factors, eg to a sector index. • Useful for reporting. Actual & hypothetical P&L  Used for backtesting to support model approval. Historical market data  • Time series for ES and VaR (for backtesting). • Historical stress scenarios. • Correlations, PDs and LGDs for default risk charge. Pricing analytics Risk factor sensitivities (PV01, CS01 etc). • Pricing stress and ES/VaR scenarios. • Scalability/flexibility to handle multiple revaluations with subsets of risk factors. Other analytics Calculation of sensitivities-based capital charge, DRC and RRAO. • Aggregation of ES values. • Default simulation for default risk charge. Reporting Enhanced reporting requirements at desk level, including daily/intraday limit reports (exposures, breaches and follow-up action). Monthly reporting of SA capital charge. Weekly P&L reports and internal/regulatory risk measure reports (VaR/ES, backtesting).
  • 11. Implementation Notes  Be proactive, not reactive - requirements will change, new regulations will be added. eg FRTB-CVA for counterparty credit risk  Look at enterprise-wide risk. Siloed solutions no longer work  Design to reuse infrastructure for Standardised and Internal Models approaches.  Aim for consistent interfaces to disparate systems. Front Office position feeds Pricing analytics Historical market data  Use a single pricing engine across front office and risk management to avoid extra model validation.  Automate data gathering and cleaning. Improve data quality Free up risk managers from manual work  Improve reporting to help Risk Management. Trace sources of risk from capital charge back to positions and market data Drill down to desk level and to individual positions, across all business lines
  • 12. www.percentile.co.uk info@percentile.co.uk @pcentile Percentile provides software for integrated and holistic risk management in capital markets, to deliver faster regulatory compliance and reduce operational risk while lowering costs. 2016