This advanced course is aimed at finance individuals that are risk managers, trading analysts, investment managers and financial analysts. Also, non-finance individuals will benefit from this course as it gives perspective.
IBM Algorithmics Exposure Modeling in RiskWatch
The Credit Risk Analytics solution comprises of one main component: RiskWatch V4.5.3 (RW) RiskWatch is a comprehensive software application which provides a complete set of methodologies to measure, monitor, simulate and restructure risk.
cena szkolenia netto
- Setting up Transition Matrices and PD curves
- Building the pieces to define Credit Exposures at the trade level
- Includes Legal Entity definitions/ Credit Processes/ Output variable definition
- Defining and analyzing Credit Exposures at the Portfolio Level
- Setting up and Grouping of Netting Nodes
- Viewing and analyzing the Netting Hierarchy
- Building Credit Mitigation Portfolios
- Defining Collateral agreements - Credit Support Annex
- Defining, viewing and analyzing Credit Reports
- Slicing and dicing by Aggregation
- Simulating the portfolio
- Creating deeper analytic results like Potential Exposure, Total Exposure and Expected Loss
Wymagane przygotowanie uczestników
You should taken the course, "IBM Algorithmics Foundations of RiskWatch", where all the basics would be covered. Thus it is assumed that users already have familiarity with the system and can navigate fairly easily. Foundations of RiskWatch
A basic familiarity with derivative finance and risk management principles is assumed. For example, knowledge of a "plain vanilla" swap is useful.
- Understand the concepts behind Credit Exposures, Netting Agreements, and Collateral from a trading book perspective.
- Get a broad sense of the modules and how they interrelate to calculate the exposures
- Learn the various stages of defining the credit exposure variables
- Build relevant risk management reports on the portfolio