The IBM Algorithmics Introduction to Algo Risk Application training course will provide Delegates with an overview of ARA, with hands-on experience in its functionality.
The IBM Algorithmics Advanced Risk Management with Algo Risk Application training course will, provide the opportunity to become familiar with the newest features and gain broader experience with the overall application.
The IBM Algorithmics Integrating Algo Risk Application training course introduces Delegates to Algo Risk Application, the components and related services, architecture, and troubleshooting techniques in order to be able to manage the product on a day to day basis.
The IBM Algorithmics Portfolio Optimization with Algo Risk Application training course provides specialized hands-on training in the use and application of the software's portfolio optimization functionality.
The IBM Algorithmics Portfolio Replication in Algo Risk Application training course provides a practical overview of portfolio replication for insurance, with hands-on training in the construction of replicating portfolios.
By attending IBM Algorithmics Introduction to Algo Risk Application workshop, Delegates will learn:
- "Slice and dice" portfolios in ARA by means of aggregation
- Build risk management reports for selected portfolios
- Generate Monte Carlo and Historical VaR reports, with parametric method comparisons
- Perform portfolio scenario analysis, including stress testing
- Undertake "what-if" analysis of portfolios
- Define user-preferences
- Build virtual portfolios and benchmarks as a basis for tracking and related forms of relative risk analysis
- Manage your portfolios, benchmarks, and reports
By attending IBM Algorithmics Advanced Risk Management with Algo Risk Application workshop, Delegates will learn to:
- Navigate the IBM Algo Risk Application to produce desired reports
- Articulate the underlying what-if architecture and workflows, describing how they support critical features and processes
- Perform a Drill-Through using a sample data set to view instrument attributes and underlyings, investigate scenario sets and visualize component risk factors
- Perform on demand analysis of individual risk factors in a portfolio context
- Add assets (previously simulated) to an existing sample portfolio using what-if methods
- Add new assets (not previously simulated) to an existing sample portfolio using what-if deal features
- Demonstrate the creation new scenarios for a sample market event against a sample portfolio using what-if scenarios
- Refine a scenario set to isolate specific trigger times or instruments to solve a sample business problem using what-if scenarios
- Describe the "Critical Scenarios" feature and its benefits
- Use Critical Scenarios to create new scenarios using combinations of existing scenarios, apply various criteria to the selection and combination of scenarios
- Compare VaR measures across two dates using multi-context enhancements
- Explore a sample portfolio's risk profile using attribution
- Describe new graphical representations of VaR
- Use the scheduler to automatically create and save reports on a regular basis
- Utilize the Rule Based Reporting functionality
By attending IBM Algorithmics Integrating Algo Risk Application workshop, Delegates will learn:
- Understanding Configuration files
- Starting and stopping services
- Troubleshooting services
- Log files, directory structures and best practices
- Linking cubes and data files
- Market configuration specifics, Basel Management Reporting configuration specifics
- Authentication modes, ASEC authentication (Basel)
By attending IBM Algorithmics Portfolio Optimization with Algo Risk Application workshop, Delegates will learn:
- How to create and manage portfolio optimization problems in ARA
- How to define and build objective functions
- How to set and populate the universe of tradeable instruments
- Setting limits and trading cost assumptions on individual securities
- Global constraints applied at the whole portfolio and/or group level
- Multi-Objective optimization, and the use of use of normalization and scaling
- The use of trade budgets and penalties in portfolio optimization
By attending IBM Algorithmics Portfolio Replication in Algo Risk Application workshop, Delegates will:
- Discuss the various concepts of portfolio replication, including theory, processes, and applications
- Understand how RiskWatch and ARA are employed as key Algo components in portfolio replication construction
- Describe the primary steps in portfolio replication
- Select specific replicating asset types
- Describe the Mark-to-Future cube generation process, and build MtF Cubes in RiskWatch for both the assets and liabilities based on the impact of a pre-defined economic scenario set on a variety of risk factors
- Create a replicating portfolio from a given asset universe, using ARA's optimization module
- Use trade restrictions and penalties to improve the quality of replicating portfolios
- Assess the quality of replicating portfolios, including in-depth post-optimization goodness-of-fit analysis in ARA
A basic knowledge of risk management principles such as Value-at-Risk, scenario analysis, and derivatives is presumed.
Knowledge of windows, Unix and Linux at the command prompt, familiar with systems support and infrastructure
Basic understanding of the concept and applications of portfolio optimization
For IBM Algorithmics Introduction to Algo Risk Application: ARA end-users, particularly risk managers/analysts, portfolio managers and traders, investment analysts, and other financial professionals.
For IBM Algorithmics Integrating Algo Risk Application: technical support personnel, operators and Integration Engineers who need a good understanding of ARA.
For IBM Algorithmics Advanced Risk Management with Algo Risk Application: market risk manager or portfolio manager.
For IBM Algorithmics Portfolio Optimization with Algo Risk Application: ARA end-user, particularly risk managers/analysts, portfolio managers, traders, and other investment professionals.
For IBM Algorithmics Portfolio Replication in Algo Risk Application: insurance industry end-user, particularly risk managers, risk analysts, and actuaries.