Modeling fat tails properly is not an easy task. Our risk management software methodology capitalizes on continuous research of fat-tailed modeling for financial applications that began in 1987. Continually improving and evolving our platform, we have invested collectively more than 100 years of research and development. Special care is taken to research market issues in-depth and then implement those models that provide the most realistic explanation of the behavior.
This is our mission – addressing the needs of the new market paradigm and delivering unique risk analytics insight through a practical set of user-friendly risk management software modules that, despite the complexity of the modeling required, guides portfolio and risk managers to make better decisions.
Cognity risk management software is engineered at its core to consistently and robustly model the real world phenomena of financial assets including:
Cognity's patented fat-tailed risk analytics framework translates our intellectual property into analytics that are predictive and reliable across all asset classes and market regimes.
Cognity's risk analytics dashboard reporting approach allows you combine your standard "normal" risk measure along side those of our patented fat-tailed risk management software framework:
|Classical Risk Reporting Measures||Cognity Fat-tailed Reporting Framework|
|Value at Risk||Expected Tail Loss (ETL)|
|Expected Tail Return (ETR)|
|Incremental VaR||Incremental ETL|
|Marginal Contribution to Volatility Risk||Marginal Contribution to ETL Risk|
|Marginal Contribution to Volatility Return||Marginal Contribution to ETL Return|
|Percent Contribution to Volatility Risk||Percent Contribution to ETL Risk|
|Percent Contribution to Volatility Return||Percent Contribution to ETL Return|
|Implied Volatility Returns||Implied ETL Returns|
|Factor Marginal Contribution to Volatility Risk||Factor Marginal Contribution to ETL Risk|
|Factor Percent Contribution to Volatility Risk||Factor Percent Contribution to ETL Risk|
|Component Standard Deviation||Component ETL|
The Cognity real world framework is implemented with special emphasis on handling realistic and very large dimensions, accurate parameter estimation, speed and scalability. Cognity risk analytics are unsurpassed in commercial risk management software offerings,
Gregory Crawford talks with David Merrill, CEO of FinAnalytica, talks about the communication gap between portfolio managers and risk managers and how that's being filled.
This webinar reviews a practical bottom up approach for aggregating risk across multi-asset class portfolios.
Functionality maximizes portfolio performance by guiding the investment decision and allocation process Module accounts for individual asset performance, as well as the assets’ interaction within the portfolio
Accounting for fat tails of individual instruments is not the same as managing those tails at portfolio level. Svetlozar (Zari) Rachev and Georgi Mitov explore how advanced copulas might address the problem of fat tails, dependence models and portfolio risk.