The document summarizes the Fundamental Review of the Trading Book (FRTB), which establishes new capital requirements for market risk. It outlines the standardized approach and internal models approach, both of which involve calculating expected shortfall and stressed value-at-risk. Banks will need to store and process significantly more market data to meet the new requirements, which are estimated to increase median capital requirements by 22% and weighted average capital requirements by 40%. Technical challenges include automating extensive data gathering, pricing, and reporting to support the new risk measurement approaches and capital calculations.
Fundamental Review of the Trading Book (FRTB) – Data Challengesaccenture
In this Accenture Finance & Risk presentation we explore the challenges facing banks responding to the new Fundamental Review of the Trading Book (FRTB) rules and offer guidance on how to respond to these. http://bit.ly/2fojCKB
Fundamental Review of the Trading Book (FRTB) – Data Challengesaccenture
In this Accenture Finance & Risk presentation we explore the challenges facing banks responding to the new Fundamental Review of the Trading Book (FRTB) rules and offer guidance on how to respond to these. http://bit.ly/2fojCKB
Fundamental Review of the Trading Book - What is FRTB and why start now?Morten Weis
Presentation on new minimum standard for market risk capital, known as Fundamental Review of the Trading Book "FRTB", issued by the Basel Committee January 2016. Given by Dr. Morten Weis, independent risk management expert, at a workshop arranged by KPMG Denmark 9 June 2016 in Copenhagen, Denmark. Focus is on general introduction to the new capital standard, with emphasis on the standard method as it is used by most banks in Denmark. Advice is shared on why to start FRTB preparations now, despite rules expected in force first from 2019.
The presentation is in pdf format, but might not display correctly unless downloaded.
Given the recent financial crisis and the extended impact on global credit market and liquidity, it is imperative that financial institutions strengthen their market risk management capabilities to effectively meet compelling business objectives and challenges which include portfolio pricing and portfolio exposure management
Counterparty Credit Risk and CVA under Basel IIIHäner Consulting
Financial institutions which apply for an IMM waiver under Basel III need to fullfill a broad set of requirements. We present the quantitative, organizational and operational implications and provide some hand-on guidance how to fulfill the regulatory requirements.
Throughout this presentation, you’ll learn:
General risks faced by banking institutions on the financial markets.
How the main banking regulatory bodies’ actions are framing the banking industry (FRTB, TLAC, etc.).
About the application of Value-at-Risk (VaR) and Expected Shortfall (ES) as portfolio risk measures.
Complementary techniques to VaR and ES: Sensitivity Analysis (Greeks), Stress-testing.
Link between VaR & ES and regulatory capital.
This presentation is the one stop point to learn about Basel Norms in the Banking
This is the most comprehensive presentation on Risk Management in Banks and Basel Norms. It presents in details the evolution of Basel Norms right form Pre Basel area till implementation of Basel III in 2019 along with factors and reason for shifting of Basel I to II and finally to III.
Links to Video's in the presentation
Risk Management in Banks
https://www.youtube.com/watch?v=fZ5_V4RW5pE
Tier 1 Capital
http://www.investopedia.com/terms/t/tier1capital.asp
Tier 2 Capital
http://www.investopedia.com/terms/t/tier2capital.asp
Basel I
http://www.investopedia.com/terms/b/basel_i.asp
Capital Adequacy Ratio
http://www.investopedia.com/terms/c/capitaladequacyratio.asp
Basel II
http://www.investopedia.com/video/play/what-basel-ii/?header_alt=c
Basel III
http://www.investopedia.com/terms/b/basell-iii.asp
RBI Governor - Raghuram G Rajan on the importance if Basel III regulations
https://youtu.be/EN27ZRe_28A
The talk I gave at WBS 2020 Quant Finance Conference, Spring Edition, on "re-imagining" XVA so as to integrate it naturally into the front office workflow.
The key idea is to represent all FMTMs in spectral form via inline regression (even those FMTMs that are originally generated analytically within forward MC), and to treat this step as completion of "extended model" calibration. The regression coefficients can then be treated as derived market data, somewhat similar to non-parametric local volatility.
Viewed this way, extended model (MC) is generating not only true background factors, but also FMTMs, which can be trivially reconstructed when and where needed, together with the rest of the background factors. Collateral dynamics specification can then be interpreted as XVA "payoff", possibly scripted.
Liquidity Risk is normally a crucial issue in a banking crisis, however, during the 2007-2010 period, Liquidity has not been as difficult for us as we may have thought. There are many reasons for this, but number one is the fact that today’s community bankers simply have a better understanding of the various techniques for raising both retail deposits and wholesale funds. What does make this crisis a bit different is the relative pricing efficiencies in the wholesale or non-core funding arena these days and our session will focus on how bankers can avoid those difficult examiner discussions about the use of FHLB Advances and Brokered Deposits. It’s all about process and we will provide guidance on what needs to be in your ALCO Policy as it relates to wholesale funding. We will also explore the April 2010 Liquidity and Funds Management Guidance to ensure your bank is up to speed on those requirements. Finally, we will provide specific guidance on both Ratio Analysis and creating your Contingency Funding Plan and will review a sample CFP.
This presentation provides a highlight of the key issues in the management of Market Risk. It touches briefly some of the elements of the Basel 2 Accord with respect to Market Risk
The Fundamental Review of the Trading Book (FRTB) is a major challenge for the banking sector. This new Accenture Finance & Risk Services presentation explores the key implications of the new requirements and highlights key differences with previously published standards. Access this link for more information on FRTB: http://bit.ly/1NnY1RN
Fundamental Review of the Trading Book - What is FRTB and why start now?Morten Weis
Presentation on new minimum standard for market risk capital, known as Fundamental Review of the Trading Book "FRTB", issued by the Basel Committee January 2016. Given by Dr. Morten Weis, independent risk management expert, at a workshop arranged by KPMG Denmark 9 June 2016 in Copenhagen, Denmark. Focus is on general introduction to the new capital standard, with emphasis on the standard method as it is used by most banks in Denmark. Advice is shared on why to start FRTB preparations now, despite rules expected in force first from 2019.
The presentation is in pdf format, but might not display correctly unless downloaded.
Given the recent financial crisis and the extended impact on global credit market and liquidity, it is imperative that financial institutions strengthen their market risk management capabilities to effectively meet compelling business objectives and challenges which include portfolio pricing and portfolio exposure management
Counterparty Credit Risk and CVA under Basel IIIHäner Consulting
Financial institutions which apply for an IMM waiver under Basel III need to fullfill a broad set of requirements. We present the quantitative, organizational and operational implications and provide some hand-on guidance how to fulfill the regulatory requirements.
Throughout this presentation, you’ll learn:
General risks faced by banking institutions on the financial markets.
How the main banking regulatory bodies’ actions are framing the banking industry (FRTB, TLAC, etc.).
About the application of Value-at-Risk (VaR) and Expected Shortfall (ES) as portfolio risk measures.
Complementary techniques to VaR and ES: Sensitivity Analysis (Greeks), Stress-testing.
Link between VaR & ES and regulatory capital.
This presentation is the one stop point to learn about Basel Norms in the Banking
This is the most comprehensive presentation on Risk Management in Banks and Basel Norms. It presents in details the evolution of Basel Norms right form Pre Basel area till implementation of Basel III in 2019 along with factors and reason for shifting of Basel I to II and finally to III.
Links to Video's in the presentation
Risk Management in Banks
https://www.youtube.com/watch?v=fZ5_V4RW5pE
Tier 1 Capital
http://www.investopedia.com/terms/t/tier1capital.asp
Tier 2 Capital
http://www.investopedia.com/terms/t/tier2capital.asp
Basel I
http://www.investopedia.com/terms/b/basel_i.asp
Capital Adequacy Ratio
http://www.investopedia.com/terms/c/capitaladequacyratio.asp
Basel II
http://www.investopedia.com/video/play/what-basel-ii/?header_alt=c
Basel III
http://www.investopedia.com/terms/b/basell-iii.asp
RBI Governor - Raghuram G Rajan on the importance if Basel III regulations
https://youtu.be/EN27ZRe_28A
The talk I gave at WBS 2020 Quant Finance Conference, Spring Edition, on "re-imagining" XVA so as to integrate it naturally into the front office workflow.
The key idea is to represent all FMTMs in spectral form via inline regression (even those FMTMs that are originally generated analytically within forward MC), and to treat this step as completion of "extended model" calibration. The regression coefficients can then be treated as derived market data, somewhat similar to non-parametric local volatility.
Viewed this way, extended model (MC) is generating not only true background factors, but also FMTMs, which can be trivially reconstructed when and where needed, together with the rest of the background factors. Collateral dynamics specification can then be interpreted as XVA "payoff", possibly scripted.
Liquidity Risk is normally a crucial issue in a banking crisis, however, during the 2007-2010 period, Liquidity has not been as difficult for us as we may have thought. There are many reasons for this, but number one is the fact that today’s community bankers simply have a better understanding of the various techniques for raising both retail deposits and wholesale funds. What does make this crisis a bit different is the relative pricing efficiencies in the wholesale or non-core funding arena these days and our session will focus on how bankers can avoid those difficult examiner discussions about the use of FHLB Advances and Brokered Deposits. It’s all about process and we will provide guidance on what needs to be in your ALCO Policy as it relates to wholesale funding. We will also explore the April 2010 Liquidity and Funds Management Guidance to ensure your bank is up to speed on those requirements. Finally, we will provide specific guidance on both Ratio Analysis and creating your Contingency Funding Plan and will review a sample CFP.
This presentation provides a highlight of the key issues in the management of Market Risk. It touches briefly some of the elements of the Basel 2 Accord with respect to Market Risk
The Fundamental Review of the Trading Book (FRTB) is a major challenge for the banking sector. This new Accenture Finance & Risk Services presentation explores the key implications of the new requirements and highlights key differences with previously published standards. Access this link for more information on FRTB: http://bit.ly/1NnY1RN
Outlook and market survey on the fresh Standards for Minimum capital requirements for market risk (FRTB), published January 14th, 2016.
FRTB will deeply impact banks on IT, process, human and organizational aspects.
CH&Co can assist banks navigate through these fundamental changes
SlideshareData management implications of the Fundamental Review of the Tradi...Leigh Hill
Fundamental Review of the Trading Book (FRTB) is two years away. Significant data management changes and challenges presented by the regulation call for an early start on implementation. The webinar will discuss the challenges of FRTB and provide practical guidance on how best to achieve efficient and effective compliance.
Join the webinar to find out about:
- The requirements of FRTB
- Data management challenges
- Best practice approaches
- Benefits of compliance
- Expert implementation guidance
Considerations for an Effective Internal Model Method Implementationaccenture
In this Accenture Finance & Risk presentation we discuss an approach banks can use to develop, manage, and monitor a robust and effective Internal Model Method program. Learn more about the Accenture Finance & Risk Practice: bit.ly/2j2JD6X
Solving the FRTB Challenge: Why You Should Consider an Aggregation SolutionFIS
Many banks face multiple challenges around market risk, with outdated infrastructure, fragmented systems, and inflexible reporting tools. And now FRTB raises the stakes. The Fundamental Review of the Trading Book is the biggest change in market risk rules that we’ve seen in a generation.
The answer to the FRTB challenge is a centralized aggregation solution that allows you to source required prices from one or more front-office and risk engines, perform bank-wide FRTB calculations using those inputs, and combine the results with intermediate data and expose inputs via reporting and analysis tools.
View our slideshow to learn more about aggregation challenges and why you should consider an external solution.
TradeTech Europe 2011 is the largest and most senior meeting place for the electronic trading community. It gathers over 2,000 buy side traders, brokers, trading venues, regulators, industry experts, economists and fund managers. It is created by the industry advisory board and is highly valued by all participants. TradeTech is designed to give you true value and help you grow in your job, ensuring top results and great performance for every member of your team.
everis Marcus Evans FRTB Conference 23Feb17Jonathan Philp
everis was Gold Sponsor of the Marcus Evans Conference ‘4th Edition: Impact of the Fundamental Review of the Trading Book’ at Canary Wharf, London on 23-24th February 2017.
This was a timely opportunity to catch up with banks and solution partners as we move into the implementation phase of Fundamental Review of the Trading Book (FRTB) programmes. We heard views and case studies across a range of topics including market risk methodology, operating model definition and data and systems architecture design.
Our presentation at the conference focused on the architectural challenges posed by FRTB.
everis was Gold Sponsor of the Marcus Evans Conference ‘4th Edition: Impact of the Fundamental Review of the Trading Book’ at Canary Wharf, London on 23-24th February 2017.
This was a timely opportunity to catch up with banks and solution partners as we move into the implementation phase of Fundamental Review of the Trading Book (FRTB) programmes. We heard views and case studies across a range of topics including market risk methodology, operating model definition and data and systems architecture design.
Our presentation at the conference focused on the architectural challenges posed by FRTB.
In our earlier blog, we discussed PD terminology and PD calibration approaches as applicable to the IFRS 9 framework. In this blog, we have discussed the methodologies for adjusting PDs for the ‘forward-looking’ macroeconomic scenarios and development of PD Term Structure.
As the race against time to comply with IFRS 9 guidelines begins, several software solutions are being bandied about as a quick fix solution for automating the entire impairment modelling process. While automating is definitely the way to go in initiatives such as these, the question remains as to whether the software architecture should be of a strategic integrated nature or one that is decoupled and modular. In Aptivaa, we believe the answer to this lies in the 4Rs question: Readiness, Reflectiveness, Redundancy and Regularity.
A key metric that summarizes the credit worthiness of a bank’s obligor is the Probability of Default (PD). Besides credit worthiness assessment and capital computation under IRB, PD is one of the key metrics required in the updated IFRS 9 accounting standards. At present, there are many PD related terminologies used in the banking industry, such as: PIT PD, TTC PD, 12-month PD and so on. Such a wide spectrum of terminologies has led to confusion among users, especially when it comes to IFRS 9, which lays special focus on PIT PD and lifetime PD. This blog intends to clarify these key terminologies.
As discussed in our previous blog, PIT PD describes an expectation of the future, starting from the current situation and integrating all relevant cyclical changes & all values of the obligor idiosyncratic effect with appropriate probabilities. A PIT PD mimics the observed default rates over a period of time. TTC PDs, in contrast, reflect circumstances anticipated over an extremely long period, and thus nullify the effects of credit cycle. Basing it on these definitions, the current article focuses on range of PD Calibration approaches for aligning internal rating model output with actual default rates.
Transition matrices and PD’s term structure - Anna CornagliaLászló Árvai
A transition matrix is a square matrix describing the probabilities of moving from one state to another in a dynamic system. In each row there are the probabilities of moving, from the state represented by that row, to the other states. Thus each row of a transition matrix adds to one.
Nick Wade Using A Structural Model For Enterprise Risk, Dst Conference 2011...yamanote
On why a multi-factor or structural model of risk might be a good idea at the enterprise level, rather than the more common VaR models based simply on historical returns
Interest rate risk management for banks under Basel II, presentation by Christine Brown, Department of Finance , The University of Melbourne, Shanghai, December 8-12, 2008
Evaluation of Capital Needs in Insurancekylemrotek
Presentation on capital adequacy analysis for property casualty insurance companies, as presented to Milliman\'s 2008 Casualty Consultants Forum in Denver
EAD Parameter : A stochastic way to model the Credit Conversion FactorGenest Benoit
This white paper aims at estimating credit risk by modelling the Credit Conversion Factor (CCF) parameter related to the Exposure-at-Default (EAD). It has been decided to perform the estimation thanks to stochastic processes instead of usual statistical methodologies (such as classification tree or GLM).
Our paper will focus on two types of model: the Ornstein Uhlenbeck (OU) model – part of ARMA model types – and the Geometric Brownian Movement (GBM) model. First, we will describe, then implement and calibrate each model to ensure relevance and robustness of our results. Then, we will focus on GBM model to model CCF.
This presentation is an overview Cost of Capital.
Dr. Soheli Ghose ( Ph.D (University of Calcutta), M.Phil, M.Com, M.B.A., NET (JRF), B. Ed).
Assistant Professor, Department of Commerce,St. Xavier's College, Kolkata.
Guest Faculty, M.B.A. Finance, University of Calcutta, Kolkata
This presentation by Gerhard Scheuenstuhl & Christian Schmitt, RiskLab, was made at the OECD-Risklab-APG Workshop on pension fund regulation and long-term investment held in Amsterdam on 7 April 2014. Discussions focused on: long-term pension investment strategies under risk-based regulation; riskiness and procyclicality in pension asset allocation; and, regulatory challenges for long-term illiquid assets.
For more information please visit http://www.oecd.org/daf/fin/private-pensions/OECD-APG-workshop-pension-fund-regulation-LTI.htm
This is the fifth presentation for the University of New England Graduate School of Business course GSB711 Managerial Finance, offered by Dr Subba Reddy Yarram. This presentation examines risk, return and the Capital Asset Pricing Model (CAPM).
This presentation will survey and discuss various quantitative considerations in liquidity risk for a financial institution. This includes the concept of liquidity-at-risk (LaR) as a determinant of buffers, as well as how one defines and quantifies such buffers. We will also examine issues such as limit-related input for liquidity policy and transfer pricing as an alternative concept. Two stylized models of liquidity risk are presented and analyzed.
Similar to FRTB Overview & Implementation Notes (20)
how to swap pi coins to foreign currency withdrawable.DOT TECH
As of my last update, Pi is still in the testing phase and is not tradable on any exchanges.
However, Pi Network has announced plans to launch its Testnet and Mainnet in the future, which may include listing Pi on exchanges.
The current method for selling pi coins involves exchanging them with a pi vendor who purchases pi coins for investment reasons.
If you want to sell your pi coins, reach out to a pi vendor and sell them to anyone looking to sell pi coins from any country around the globe.
Below is the contact information for my personal pi vendor.
Telegram: @Pi_vendor_247
where can I find a legit pi merchant onlineDOT TECH
Yes. This is very easy what you need is a recommendation from someone who has successfully traded pi coins before with a merchant.
Who is a pi merchant?
A pi merchant is someone who buys pi network coins and resell them to Investors looking forward to hold thousands of pi coins before the open mainnet.
I will leave the telegram contact of my personal pi merchant to trade with
@Pi_vendor_247
What price will pi network be listed on exchangesDOT TECH
The rate at which pi will be listed is practically unknown. But due to speculations surrounding it the predicted rate is tends to be from 30$ — 50$.
So if you are interested in selling your pi network coins at a high rate tho. Or you can't wait till the mainnet launch in 2026. You can easily trade your pi coins with a merchant.
A merchant is someone who buys pi coins from miners and resell them to Investors looking forward to hold massive quantities till mainnet launch.
I will leave the telegram contact of my personal pi vendor to trade with.
@Pi_vendor_247
Lecture slide titled Fraud Risk Mitigation, Webinar Lecture Delivered at the Society for West African Internal Audit Practitioners (SWAIAP) on Wednesday, November 8, 2023.
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
how to sell pi coins in South Korea profitably.DOT TECH
Yes. You can sell your pi network coins in South Korea or any other country, by finding a verified pi merchant
What is a verified pi merchant?
Since pi network is not launched yet on any exchange, the only way you can sell pi coins is by selling to a verified pi merchant, and this is because pi network is not launched yet on any exchange and no pre-sale or ico offerings Is done on pi.
Since there is no pre-sale, the only way exchanges can get pi is by buying from miners. So a pi merchant facilitates these transactions by acting as a bridge for both transactions.
How can i find a pi vendor/merchant?
Well for those who haven't traded with a pi merchant or who don't already have one. I will leave the telegram id of my personal pi merchant who i trade pi with.
Tele gram: @Pi_vendor_247
#pi #sell #nigeria #pinetwork #picoins #sellpi #Nigerian #tradepi #pinetworkcoins #sellmypi
how can I sell pi coins after successfully completing KYCDOT TECH
Pi coins is not launched yet in any exchange 💱 this means it's not swappable, the current pi displaying on coin market cap is the iou version of pi. And you can learn all about that on my previous post.
RIGHT NOW THE ONLY WAY you can sell pi coins is through verified pi merchants. A pi merchant is someone who buys pi coins and resell them to exchanges and crypto whales. Looking forward to hold massive quantities of pi coins before the mainnet launch.
This is because pi network is not doing any pre-sale or ico offerings, the only way to get my coins is from buying from miners. So a merchant facilitates the transactions between the miners and these exchanges holding pi.
I and my friends has sold more than 6000 pi coins successfully with this method. I will be happy to share the contact of my personal pi merchant. The one i trade with, if you have your own merchant you can trade with them. For those who are new.
Message: @Pi_vendor_247 on telegram.
I wouldn't advise you selling all percentage of the pi coins. Leave at least a before so its a win win during open mainnet. Have a nice day pioneers ♥️
#kyc #mainnet #picoins #pi #sellpi #piwallet
#pinetwork
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