AcadiaSoft offers an ISDA SIMM™ static or dynamic Backtesting & Benchmarking Service that includes both back-testing of SIMM™ over a historical period and benchmarking SIMM™ against four industry-standard risk methodologies to assist in monitoring the effectiveness of SIMM™ as a margin model.
We know that complying with the latest regulations can be burdensome. It requires your fi rm to have access to experienced resources, investment in IT systems, a complete set of historical market data and a thorough understanding of the requirements in a timely and repeatable process. AcadiaSoft brings fi rms a unique and cost-effective Backtesting and Benchmarking service for Initial Margin calculations that can be put in place ahead of regulatory approval or as a substitute for costly internal processes. In line with industry best-practice, clients are able to choose either static or dynamic backtesting for their statistical output.
IM Backtesting & Benchmarking inputs and outputs
Key Features:
- Transparency: standard, open process enables fi rms to fully understand and monitor SIMM™ performance
over a quarter as well as provide materials for regulatory review - Static backtesting: holds the portfolio information and SIMM constant, then calculates historical P&L’s by
applying a rolling 10-day risk factor market movements to the constant quarter-end portfolio - Dynamic backtesting: portfolio information and SIMM evolve day-over-day, and actual P&Ls are calculated
based on realized risk factor market movements over the 10-days following each portfolio date - Data security: clients upload portfolios in a secure, tested environment
- Standardized market data: all users share common market data provided by market-leading, independent sources
- Standard portfolios/risk factors: includes standard portfolios and risk factors for performance to be monitored through changing market conditions
- Intelligence: the service uses differing specifications to allow for a more thorough understanding of the model’s performance, including benchmarking of SIMM™ against multiple metrics:
- Full Revaluation Historical Simulation VaR – quantile of the empirical distribution generated by the full revaluation P&L vector
- Historical Simulation Taylor VaR – p-quantile of the empirical distribution generated by the sensitivity-based P&L vector.
- Non-normal Parametric VaR – Parametric VaR output for some benchmarks will use non – normal, “fat tailed” distributions such as Student T or General Pareto distributions
- DCO (CCP) monitoring – DCO (CCP) margin model specifications will be mirrored in the benchmarking VaR methods to ascertain what a CCP would calculate for an equivalent risk
- Ad-hoc backtests: the service provides for ad-hoc backtests to support clients’ use of SIMM™ through volatile or changing market conditions
- Full support through the upcoming Risk Free Rates (RFR) transition from LIBOR
- Monitor and support RFRs into the OIS Sub Curves of each respective currency
- Calculate and support current LIBOR based curves
- Monitor and apply the appropriate fallbacks to SOFR as prescribed by the industry and ISDA
- Seamless transition to when IBORs are discontinued
- Ability to source market data to value SOFR and all global risk free rates based product
Key Benefits:
- Lower cost through mutualization
- Reduced regulatory and operational risk by utilizing an industry standard process that achieves maximum automation
- Validation of internal processes – useful comparison tool
- Regulator ready, detailed quarterly report provided
- Voice of the industry – Our service was developed with the industry via extensive input from working groups.