Skip to content
Contact us

Release 24.04 Portfolio Analytics & Reporting

divider enhancementRisk Measurement MSCI RiskMetrics interface

Data processing - volume optimization

With this feature you can reduce number of benchmark constituents sent from SimCorp Dimension to MSCI. If several indexes are based on the same Index Universe Definition, then the constituents of those indexes are sent only once. This is especially useful when you have the same hedged and not hedged benchmarks in the same risk measurement calculation. This functionality is now supported in the Risk Measurements with the Relative tree Reporting Structure type and can be enabled through the special configuration setting called “Blend over index universe definition”. 


This enhancement enables you to send less positions through MSCI interface, which consequently results in the cost reduction. 

Subscription based licensing

Risk Analysis Manager and add-ons 

Sales module dependency

Risk Reporting 
MSCI RiskMetrics – Adaptor

Risk Management – Internal risk enhancements

Risk Analysis Manager - View long names for Portfolio and Portfolio Free Code nodes 

In the Risk Analysis Manager, it is now possible to view long descriptive names in the Reporting Structure for the Portfolio Free Codes splits only or for the Portfolio split only. The long names of the Portfolio Free Codes provide better description of the free code than the short name (ID) which has limited amount of the digits. 

By selecting new options, such as: Show long names in the tree for the Portfolio Free Code nodes and Show long names in the tree for the Portfolio nodes, you can view long descriptive names for those nodes but other nodes viewed as the Short names/IDs. 


View long names in the Reporting Structure tree for Portfolio and Portfolio Free Code nodes. 


This enhancement provides more flexibility and convenience in viewing reporting trees in the Risk Analysis Manager. 

Monte Carlo Value at Risk scenario generation enhancements

  • The Monte Carlo Value at Risk SimCorp Dimension internal model has been enhanced to generate scenario values using Sobol sequence methodology. Sobol sequence is one of the Quasi-random low-discrepancy sequences which has wide application in Monte Carlo Value at Risk computation. It is proved to be well-suited for the high-dimensional spaces, in particular the risk modelling for the scenarios with the high number of the risk factors. 
    The distribution of the scenario values obtained using Sobol methodology has the quantiles close to the analytical quantiles, which consequently leads to more accurate Value-at-Risk values. Sobol scenario generation method can be used with both Normal and Student-T distribution. 
  • In addition to the new scenario generation method, the improvement to Student-T distribution has been introduced in the Internal Risk module. As of version 24.04, when using Student-T distribution configuration the scenarios are generated using multivariate T-distribution which is better for modelling of multivariate data allowing for more accurate modelling of dependencies between the risk factor returns. 
    This is one of the robust and reliable approaches to handle correlated variables widely used in finance and well suited for the Monte Carlo VaR scenario generation process. The application of new computation approach helps to avoid systematic overestimation and underestimation of the Value at Risk analytics. This is not a configurable change, thus new methodology is now applied to all supported scenario generation methods (Faure, Sobol, Generalized Faure, Random) generated using Student-T distribution. 


Configure new scenario generation method for the Monte Carlo Value at Risk (Risk Factor Scenarios/Options/Additional Settings/ “Sobol” scenario generation).

Subscription based licensing

Risk Analysis Manager 

Sales module dependency

Risk Reporting
Various Risk Modules

Investment Forecasting & Solvency – various enhancements

Accounting forecasting, particularly projecting future balance sheet reports over 3-5 and more years, is crucial in the financial realm as it allows businesses to anticipate and prepare for potential financial challenges, manage risks, and make informed strategic decisions. The inclusion of Credit Loss Allowance (CLA) in these forecasts is particularly vital as it helps mitigate the impact of credit risk by estimating potential losses from non-performing loans, ensuring financial stability and regulatory compliance.

As of version 24.04, when forecasting credit loss allowance (CLA) in the Strategy Manager, SimCorp Dimension can also calculate CLA balances based on the cash flow reduced by a Cash flow adjustment factor (i.e. “full” cash flow assumption). A factor for each term unit equals to Loss Given default multiplied by the Probability of Default . A term unit in this scenario is time left to maturity on calculation date. For example, if your term unit is one year, the cash flows that are due in one year from the calculation date are adjusted.

Considering the Cash flow adjustment factor in the CLA calculations helps to dissolve the CLA balances, if the expected loss is not going to be realized, in small steps. 


Improved Credit Loss Allowance (CLA) simulation – contrasting new and previous versions.

Furthermore, we've enhanced support for the local German legal requirement Branchen Simulations Model (BSM) to streamline reporting of the future cash flows. You can now simulate cash flows of external fund components including dividends, coupons, redemptions, and maturity payments. Some transactions, such as redemptions, can also affect the position.

Cash flows for external fund components are derived from description of securities during position calculation. Simulated transactions are generated solely for passive strategies, not for what-if scenarios.

Following position calculation execution in the Position Results applet, you can review simulated cash flows and their effects for securities marked as Constituent. Results are accessible in Payments QC/PC, Balance nominal/number fields, and related analytics fields, with transaction details available in the Transactions since inception sub-window. Additionally, you can extract these cash flows from the database table using the Data Extractor.


Simulations of cash flows for external fund components in the Position Results. For example, consider a fixed-income bond with a 2% coupon per year and redemption in 2025.

Finally, you can include accrued interest for shocked and unshocked values when you calculate SSD Solvency II analytics using the external price. This allows to treat SSD more accurately when you calculate Solvency II figures for them using external price methodology.

Subscription based licensing

Strategy Manager & various add-ons

Sales module dependency

Strategy Manager - Calculations
Strategy Manager - Market Data Stress Test
Strategy Manager - What-if and Horizon Analysis
Strategy Manager - Position Calculation API
Strategy Manager - Reinvestment component

Browse the Release Portal


Learn more

Front Office

Learn More

Portfolio Analytics & Reporting

Learn More


Learn More

Alternative Investments

Learn More

Data Management

Learn More


Learn More

  • Privacy policy
  • Cookie Policy
  • Terms of Use
  • Trademark guidelines
  • Copyright © 2024 SimCorp A/S