![]() Learning their strengths and weaknesses enables you to understand how they can complement one another. These detection techniques are important when you’re deciding whether to go with a signature or anomaly detection engine, but vendors have become aware of the benefits of each, and some are building both into their products. There are two primary threat detection techniques: signature-based detection and anomaly-based detection. Whether you need to monitor hosts or the networks connecting them to identify the latest threats, there are some great open source intrusion detection (IDS) tools available to you. ![]() Definition of benchmarks, based on indexes and contributions.Originally written by Joe Schreiber, r e-written and edited by Guest Blogger, r e-re edited and expanded by Rich Langston.Possible distribution of the software to additional machines.Parallel calculation and simulation, using available processor cores.Market data and historical series data, incl.Notification system: messages, sounds and e-mails.Support of standard transactions for all instrument types.Free attributes in portfolios, instruments and positions.Structured Monte Carlo simulation for market risk internal models.Neural network for clustering of time series and for defining multi-factor instruments.Flexible reporting - Crystal Reporter, Jasper reports, QlikView, etc.External data import via service API or importer module.Batch mode and management of calculation sequences, including time-controlled sequences.Multi-entity and multi-user mode, user rights over objects, using role definitions.Flexible configuration of the system functionality, through licensing of modules, models and features.Flexible configuration and setting of work environment and nomenclatures, such as currencies, cities, countries.Native service API clients – Java, JavaScript, etc.Flexible multi-window and multi-language GUI.Full historisation support of all entities.Support of large sets of databases: Oracle, MS SQL, DB2, My SQL and others.High portability due to Java programming languages and Java-based technology packages.Uses HTML / CSS / JavaScript only – no applets, flash and alike. Supported APIs – Messaging (JMS), REST, WS-SOAP.Some test cases include 100.000 positions Īccessing the system only via the respective API or GUI, which makes the integration easy: A typical simulation consists of around 1000 positions.Designed for integration with other applications, but can also operate alone.1 in section Swiss Solvency Test in Risk Engine. Advanced risk measurement methods, based on Monte Carlo simulation that are taking into account all details of the contracts.Their main goal is to represent positions with known behavior but unknown expected behavior, e.g. Data driven and predictive Models – engineering position relationships according to the marker, based on known market history.In contrast to the usual excel modelling in Excel, Risk Engine models can undergo risk analysis, stress testing and behaviour analysis that are available in the system User-defined by Rules - perfect for modelling and analysis of new contracts in funds, insurance companies, banks, credit institutions, etc.Its main goal is to represent positions with respect to regulatory requirements, e.g. Delta-Gamma Model - by definition or derived from internal models.Delta Model – by definition or derived from internal model.Its main goal is to represent positions as observed / defined on the tradable market Internal Model – discounted cash flow, rules, data driven or predictive (AI).Advanced stress testing on all types of factors in groups or per factor basis.Precise modelling of investments – cashflow generation, conventions, optionality, etc.Precise modelling of the market – prices, indices, yields, spreads, scenarios, statistics, yield and credit spread curve bootstrapping, normalisation and interpolation, etc.Risk Engine Future Developments & Extensions.Risk Framework Future Developments & Extensions.
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