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© Philip Symes, 2006
CALYPSO ENTERPRISE RISK SYSTEM Dr Philip Symes
Introduction Calypso's Enterprise Risk Service (ERS) is part of their Front-to-Back software system.
© Philip Symes, 2006
Calypso ERS provides the Middle Office risk function. – Risk control and risk management solution. The system is designed to manage: – market risk; – credit risk; – limits. The back testing functionality included in the system meets the requirements from Basel2 IRB approach. Operational risk is on the roadmap to be integrated.
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Contents Brief overview of the Calypso suite of products. Brief overview of functionality of Calypso ERS. Technical overview of Calypso ERS (how it works).
© Philip Symes, 2006
Integrating ERS with other Front Office solutions (Calypso and other systems). Scenario methodology: – Application of methodologies in Calypso ERS; – Historical simulations (detailed); – Stress testing. Watchpoints for risk implementation.
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© Philip Symes, 2006
Calypso ERS Areas Calypso ERS is Calypso's new Middle Office risk management solution. Market risk areas: – Risk factor sensitivities; – Historical Value at Risk simulation; – Stress testing; – Back testing. Limits: – Market risk; – Counterparty credit risk. Credit Risk: – Counterparty credit exposure.
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The Calypso Product Suite Calypso is a cross asset Front-to-Back Office banking software system.
Calypso is designed to work “out of the box” and is configurable for specific environments.
© Philip Symes, 2006
Calypso's system architecture makes it highly configurable and extendable: – Pricing libraries can be added in Java and C++; – External databases can be referenced; – This makes it appropriate for dynamic environments. Calypso interacts with other Front and Back Office systems through information feeds.
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The Calypso Product Suite (cont.)
© Philip Symes, 2006
Summary of Calypso “solutions”:
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Front-to-Back Integration Calypso ERS integrates with Calypso’s front-to-back software system. This gives considerable advantages when integrating risk systems for compliance and cost.
© Philip Symes, 2006
Cost savings arise from: – – – – –
IT department specialising in fewer systems; Lower licence and support costs; Less infrastructure; Lower setup costs; A simplified systems that reduces operational risk.
The system also requires less training for users who only have to learn one system.
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Calypso ERS Architecture
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Calypso ERS separates the user interfaces and back end processes.
The user interface is the ERS Web Browser: – Thin-client presentation layer; – Web services – DHTML, XML, etc.
© Philip Symes, 2006
The back end works using ERS engines: – –
A distributed computing GRID; Service-oriented architecture.
The ERS engines: – Manage portfolio risk analysis; – Use existing FO pricing libraries to create P&L vectors.
Calypso ERS Architecture (cont.)
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Browser DHTML XML / AJAX
Web Server SOAP
Web Services (Apache Tomcat)
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JDBC
Ad-hoc Requests
Risk Risk Engines ERS Engines Engines
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Java RMI TCP/IP or Multicast
JDBC
Data Server
Java RMI
JDBC
ERS Results
Database
Event Server
Calypso ERS Architecture (cont.)
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The Calypso ERS Results service acts as a warehouse of official risk numbers: – ERS can run on Sybase and Oracle databases; – Can even run on a different database to Calypso.
© Philip Symes, 2006
The service can work with numbers from within Calypso or from an external database. Historical scenarios are accessed directly from the database – Better performance than using the Data Server The results can be exported to different formats – E.g. MS Excel for spreadsheet analysis.
Calypso ERS Architecture (cont.)
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© Philip Symes, 2006
Runs off a batch job overnight – This takes about 5 hours to perform simulations for 100,000 trades; – System does not run in real-time. ERS can run in distributed computing or GRID environment – Using Calypso Dispatcher (DC) or Data Synapse (GRID). P&L vectors are used as the main building blocks of risk analysis – This is because VAR is not a coherent risk measure (see RiskMetrics presentation); – In particular, VAR is not subadditive.
Calypso & ERS Integration
© Philip Symes, 2006
Calypso ERS uses the same pricing environment as Calypso – This means that the same pricing libraries are used – Therefore ERS does not need a separate pricing methodology ERS could be accessed from the Calypso GUI – This would require development work – The API allows ERS extensions The bucket hedge function is available – More work on this is on the “roadmap” – But ERS is not a FO system
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Simulation Methodology
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ERS deals is mainly a historical simulation VAR engine. Portfolios are repriced based on the simulated results – This revaluation is done by creating a new pricing environment (PE).
© Philip Symes, 2006
Trades are revalued using this PE to get a P&L vector of changes in the trade's net present value – Each vector element is the P&L for one day in the simulation period.
VAR is calculated from these P&L vectors – They are stored for trades and portfolios.
Simulation Methodology
© Philip Symes, 2006
The risk factors used are the same as the underlying market data factors used for pricing: – Interest rates – Credit spreads – Equity prices – Foreign exchange rates – Volatility These are not correlated – the portfolios are just revalued based on RF changes from feeds They are then fed into a set of historical simulation vectors.
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Simulation Methodology
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Extreme returns are modelled in the same way as other returns if they occur in the historical period. No time-based scaling is done at the moment, but functionality for this will be added.
© Philip Symes, 2006
With exponential weighting added to the volatility, for example, the decay factor λ moves away from 0:
Simulation Methodology
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© Philip Symes, 2006
The implied return on the risk factors is used to change the yield curve with an: – Absolute change (i.e. ±x bps) – Relative (fractional) change – Weighted percentage change The Calypso pricing model is then used to price the product off the new change in underlying factors – A warning is given if there is not enough historical data for the period required No drift is modelled in these scenarios – 1-day or 10-day VAR is the main result – Drift is not sensible below ~3 month horizon
Simulation Methodology (cont.)
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Time Series DB
Mkt Data EOD
Scenarios
© Philip Symes, 2006
Generate Scenarios
Trades from GUI
Trades Feed
Scenarios Market Data Trades
ERS Engines
Calypso DS/DB
Scenarios
PnL Vectors
VaR
Results XML
VaR
Total Total
Scenarios
Org. Org.
VaR
Org.
Group Group Group Group Group VaR
Excel
External System
PnL Vectors
© Calypso
Desk
Aggregate
Desk
Desk Desk
Desk
Desk
VaR
Desk
PnL1 PnL1 PnL1 PnL1 PnL1 PnL1 PnL1 P&L PnL11 PnL1 PnL1 PnL1 PnL1 PnL1 PnL1 PnL1 PnL1 PnL1 PnL1 PnL2 PnL2 PnL2 PnL2 PnL2 PnL2 PnL2 P&L PnL22 PnL2 PnL2 PnL2 PnL2 PnL2 PnL2 PnL2 PnL2 PnL2 PnL2 PnL3 PnL3 PnL3 PnL3 PnL3 PnL3 PnL3 P&L PnL33 PnL3 PnL3 PnL3 PnL3 PnL3 PnL3 PnL3 PnL3 PnL3 PnL3 .
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PnLn PnLn PnLn PnLn PnLn PnLn PnLn P&L PnLnn PnLn PnLn PnLn PnLn PnLn PnLn PnLn PnLn PnLn PnLn
Portfolio Hierarchy Leaf Nodes
PnL Vectors
Historical Simulation
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Calypso ERS takes historical data from an external price history database – Input can be fractional, relative or absolute.
© Philip Symes, 2006
From these prices, the shifts in risk factors are calculated. The period for collecting the historical data can be specified: 1 year, 4 years, etc. Forecast horizons are configurable: 1 day, 10 day, etc. The historical data set can be updated at customisable periods: daily, monthly, etc.
Credit Risk Simulation
© Philip Symes, 2006
Credit risk is done through credit exposures: – The Mark-to-Market Plus Add-on method is used; – This is a standard technique (Basel I). Marking to market is done using the Calypso pricing libraries applicable to each product: – This gives the current value of the credit exposure; – Can use the same pricing environment as the Front Office; – This means that no approximations or price mismatches come from the risk system.
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Credit Risk Simulation
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© Philip Symes, 2006
An add-on is made for potential future exposure market – I.e., the add-on accounts for the volatility of the product; – It accounts for the risk that exposure may increase over time. This add-on is time and product dependent typically varies between: – 0-2% for IR products; – 1-8% for FX products; – 5-10% for equities.
Credit Risk Simulation
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© Philip Symes, 2006
The MTM plus add-on method is fast and conservative in its risk assumptions: – But it is considered outdated by many banks; – Potential Future Exposure (PFE) is the proposed new method. An improved credit risk handling system will be ready within the next few months – Development focus shifting towards credit risk This new system will handle collateral through Calypso’s collateral management system This will be Basel 2 compliant
Back Testing
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Basel2 requires that banks back test their VAR models. Calypso ERS meets this by showing: – The actual P&L; – The no-action (hypothetical) P&L.
© Philip Symes, 2006
The VAR and P&L results are stored every day for each portfolio. The back test analysis is performed automatically at the specified period. The analysis checks for the number of times the actual P&L exceeds the VAR – Classification is in Basel2 colours: red, yellow or green.
Stress Tests Stress testing scenarios are needed to complement simulations – See RiskMetrics presentation for more details.
© Philip Symes, 2006
These are setup in Calypso using the Scenario Editor – Shocks to the portfolio, e.g. IR steepeners, are built into the Workspace of the main Calypso system. The Calypso scenarios analyses are used in ERS – Less drilldown functionality is provided in ERS than Calypso Portfolios can then be revalued based on these scenarios and the results can be summarised.
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Stress Tests
© Philip Symes, 2006
A custom stress test in Calypso’s Scenario Editor:
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Limits
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© Philip Symes, 2006
A new Calypso Limit Engine limits the risk of a portfolio – Other Calypso systems will be migrating to this; – Single engine will manage all limits in Calypso. Limits can be placed on Market Risk factors: – Risk factor sensitivity; – VAR limits; – Stress limits.
Limits
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© Philip Symes, 2006
Limits are placed on Credit Risk factors: – Exposure limits per counterparty; – Legal entity hierarchies are applied to counterparties; – Availability of assets (liquidity). Limits can be configured: – Limits can be set at at different periods ●
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realtime, intra-day or end of day;
Limit exceptions are programmable in the Calypso workflow.
Simulation Reports
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© Philip Symes, 2006
ERS has access to the Calypso Risk Reporting Tool via the Calypso GUI. Results are summarised using VAR: – Different confidence levels can be selected, e.g. 99%; – VAR histograms are drawn; – Descriptive statistics are presented in the reports; – Risk and return measures, e.g. RAROC, are not included. Risk amounts can be attributed to different factors – Risk can be shown due to FX, IR, etc. Drill-down functionality shows risk by different criteria:
Advantages of ERS
© Philip Symes, 2006
ERS has several advantages over larger systems: Speed – Fast system with little overhead that can run off existing architecture Integration with existing Calypso FO and BO systems Small infrastructure and resource overheads. This makes the system suitable for banks with short term positions with hedge fund clients – Also suitable for larger hedge funds where infrastructure exists.
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Watchpoints
© Philip Symes, 2006
Certain key parts of the project must be monitored – See the POC Kit for more details. The next few slides deal with points in 3 key areas of project implementation from philipsymes.com’s experience: – Project level watchpoints; – Business level watchpoints; – Data watchpoints.
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Project Watchpoints The scope of the project: – Must have detailed requirements documented; – Need to be aware of “scope creep”.
© Philip Symes, 2006
Production release cycle: – Analyse testing requirements (POC); – Ensure the release is controlled (implementation). All elements of the project should be properly documented. Acceptance (success) criteria for the project must be pre-defined.
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Business Watchpoints
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© Philip Symes, 2006
Business needs to understand the risk measures being presented: – This includes VAR, stress tests and expected shortfall; – Stakeholder involvement is essential. Systems integration: – Software systems must be compatible; – Use banking and industry standards where possible.
Data Watchpoints
© Philip Symes, 2006
Data requirements are always underestimated: – In house data sources preferable; – Need to analyse gaps in required data. Data and systems must be integrated: – Calypso ERS uses FO pricing libraries; – Need the ability to drill-down on data provided; – Shared asset control across business units.
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Summary
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ERS is Calypso's new risk service offering.
© Philip Symes, 2006
It is designed to integrate with existing Calypso systems and other Front Office systems and pricing libraries. ERS includes support for: – Historical simulation; – Basel 2; – Stress testing. Results are summarised as reports: – Risk numbers are handled through P&L vectors; – VAR measures are calculated from these; – These meet regulatory requirements, e.g. Basel2.