Minimising Risk Exposure. Maximising Asset Management & Compliance.

Business challenge: Capital markets are extremely volatile and never has it been more critical to effective asset management to have timely access to accurate and thorough market risk analysis and modelling. Proper VaR calculations and risk exposure measurement are inherent compliance demands of Basel II banking regulations and increasingly regulators are focussing on stress testing and accurate risk assessment and management processes to ensure the professional management of market risk in asset portfolios.

VaR: VaR’s are the definitive statistical measures of market risk exposure and through extensive modelling of differing VaR types against a range of validated base data sets; risk adjusted asset valuations and the probability of loss can be accurately determined to a given degree of confidence within a given temporal horizon.

Technology: Client technology universes are complex. Multiple different systems feed vast amounts of data to management systems at different times and this complexity and data volume is expanding exponentially driven by market speed and technological advances. As broad slow and expensive legacy technologies give way to ultra fast data platforms and enterprise tactical solutions; laborious 10 – 15 hour overnight batch processes delivering T-1 risk report data far too late for market opening T-0 are giving way to the immediacy of ultra fast Tier 1 next generation risk calculation engines able to perform the hundreds of millions of data calculations required on demand.

Business Solution: Siag’s paradigm advance in Market Risk Engine calculation speed and performance with Tier 1 portfolio data volumes means that a full range of VaR calculations may be modelled along with other statistical measures such as VaE, ESF and P&L Vectors; fully stress tested and back tested to full portfolio revaluation in typically only an hour. This technology leap delivers not only comprehensive asset risk adjusted valuations and reports, but also delivers the time necessary to analyse this critical risk data, fully aggregated and consolidated from portfolio to Group holding level, in order to enable you to remove risk loaded T-1 positions in T-0 pre-trading before further market volatility erodes institutional liquidity or increases investment losses.

Comprehensive Analyses: For VaR reports to be meaningful a comprehensive view of the probability of losses must be modelled and established considering a 2-4 year historical data series per asset, parametric intraday volatility assessments, and Monte Carlo modelling for many types of derivative instrument. Each risk metric and risk report indicates a different piece of the jigsaw in assessing the overall probability of losses within the required time horizon.

Pricers: Specific optimal pricing formulae files must be available in the Engine library and assigned to  given asset classes within the portfolio aggregation structure rather than less precise Taylor Polynomial Approximations. In Tier 1 portfolios the correct consolidation and aggregation structures must be defined and created to satisfy different legal, fiscal and regulatory requirements within the Group holding structure and limits established which reflect the risk appetite of the institution and can create automatic alerting when predefined risk limits are breached by position exposure.

Stress Testing: Stress test scenarios which reflect accurate historical market volatilities under given extreme events. Stressed VaR must be calculated which considers price volatilities over fixed periods of market turbulence. Backtesting and calibrations must be conducted to verify the accuracy of the models and results. Only when all these measurements and models have been correctly completed using accurate validated source data can a portfolio be correctly revalued to a risk adjusted valuation which reflects its true value rather than a simplistic measure such as Mark to Market. Where asset prices are set against the current intraday volatility level which may not in anyway reflect historic price evolution or probable forward values then these are no more than a snapshot of volatility at a specific point in time with no related reference data to validate this specific market value in the context of historical or future predicted performance.

Base Data: All base data used for these critical risk adjusted valuations and Value at Risk modelling must be accurate and validated in order for Market Risk Engines to correctly model reports which indicate to a very high degree of accuracy in the upper 90% range; the actual Value at Risk on any asset and aggregated across the entire portfolio to a given degree of confidence within a specific temporal horizon.

Competence: Siag Risk Management are experts in this art; daily advising globally leading Tier 1 clients over market risk and credit risk management topics and carrying out risk adjusted valuations on over a million different instruments of all asset classes.

Timely Accuracy: Siag’s latest generation of ultra fast Tier 1 Market Risk Engines set globally performance leading risk calculation capability times and perform risk modelled and adjusted asset and portfolio valuations considering the full range of risk methodology variants defined above. This attention to detail means that the reports from Siag Market Risk Engines are delivered not only on time when they are most needed, but are also fully comprehensive and dependably accurate to a high degree of confidence.      

Methodology: Valuation formulae or pricer files must adapt to new asset classes and regulatory or client driven changes in preferred valuation methodologies. Siag has built dynamic pricer management MDE capability into its onboard libraries allowing you to determine the precise valuation formula to be applied to each asset class within your portfolio aggregation structure. The Market Risk Engine will invoke the correct pricer for each asset risk adjusted valuation which is modelled according to the asset classification assigned within the dynamic library mapper. Changes to pricer classifications may be assigned via this interface.   

Input Data Quality: Market risk reporting output quality however sophisticated a risk engine may be is dependant on accurate base data in both historic data series and EOD validated pricing. Price Manager as an intelligent golden data validation and management application is the ideal source feed tool for all market data and risk files from 3rd party systems. Data quality fed to the Market Risk Engine determines the quality of the risk engine report outputs. Ultra Fast Operational Speed and Validated Data Quality are the keys to the Siag Tier 1 Market Risk System.
Asset Classes: All asset classes may be accurately revalued adjusted for risk in the Siag Market Risk Engine for which market pricing and historical series data is available.

Programming / Connectivity / Scalability: All Siag advanced applications are designed from the first project planning meeting to maximise fully user orientated ease of implementation and daily use. Programmed in C++ for performance and Tier 1 dataloads, Siag applications are multiplatform, SOA and supplied with an open API for full connectivity to feeds and 3rd party systems. Full Data Synapse Grid enablement delivers scalability and adapts to rising data processing needs so your Siag Market Risk System grows with your operational needs without suffering scale performance penalties.   

Globally Class Leading Risk Engines: Siag Market Risk Engines have attracted significant interest and press coverage from both the international media and the world’s leading asset management organisations owing to their ultra fast calculation power, accuracy and speed in working with Tier 1 portfolio data loads. The elimination of overnight batch processing present in most Tier 1 asset management institutions is not only a competitive edge in data reporting speed; it allows expensive overnight batch data processing to be cost reduced and valuable resources re-assigned to more productive tasks.

• Historical data series VaR
• Parametric (Variance and Covariance) VaR
• Monte Carlo VaR
• Stressed VaR
• VaR with what if scenarios
• Aggregated and un-aggregated Historical series and Monte Carlo VaR
• VaR as calculated at previous dates (Essential for audit)
• Real time individual or combined portfolio valuations providing mark to market
• Real time portfolio valuation with what if scenarios providing what if mark to market
• VaR calculated with predefined and user defined what if stress scenarios: Stress testing
• Portfolio back testing
• Sensitivity analysis
• P&L Tracking
• P&L vectors calculated
• Simulations based on historic data series
• Monte Carlo simulations
• Incremental VaR + VaE
• VaE at 95% and 99% percentile of P&L vectors

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Peter Lindmark

CEO, Asymptotix

Tel: +352 691 156 388

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