EncartaLabs

IBM Algorithmics Introduction to Algo Risk Application

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.

COURSE AGENDA

IBM Algorithmics Introduction to Algo Risk Application
(Duration : 1 Day)

1

Introduction to ARA and Navigation

2

Understanding how to set up the General Preferences

3

Understanding how ARA develops its analytics

  • Various Aggregation Methods
  • How they are seen in the Results Viewer
  • Absolute vs Relative Risk
  • Concentration Profiles
  • Analyzing the risk through different Trading Strategies
  • Create and Manage Limits
4

Understand how ARA generates Reports

5

Various Aggregation Methods

6

How they are seen in the Results Viewer

7

Absolute vs Relative Risk

8

Concentration Profiles

9

Analyzing the risk through different Trading Strategies

10

Create and Manage Limits

IBM Algorithmics Advanced Risk Management with Algo Risk Application
(Duration : 1 Day)

1

Review of ARA and Navigation

2

What-if architecture and Enabled functionality

3

Drill-Through architecture and process flow

4

What-if deal functionality, architecture and process flow

5

What-if scenarios

6

Critical scenario characteristic, architecture and workflow

7

Enhanced features including Multiple-Context, Policy analysis and attribution,

8

Rule based Reporting, VaR Graphing and Scheduler

IBM Algorithmics Integrating Algo Risk Application
(Duration : 2 Days)

1

Market Risk Dataflow & Regulatory Capital Data flow

2

ARA GUI Functional Overview and Navigation

3

Installing ARA

4

Configuration files, flavours and directory structures

5

Authentication, Users and Administration

6

Internationalization

7

Configuring ARA for AlgoDataGrid

8

Adding new contexts (MtF) and data file links

9

Batch and iaracli commands

10

Configuring ara.properties

11

Upgrading ARA

12

Troubleshooting ARA

13

Changing Config files, Batch and Upgrades

IBM Algorithmics Portfolio Optimization with Algo Risk Application
(Duration : 1 Day)

1

Overview of Optimization in ARA

2

Steps to Opimization in ARA

3

Creating an Optimization Problem in ARA

  • Objective Function
  • Trade List and Limits Table
  • Global Constraints
4

Objective Function

5

Trade List and Limits Table

6

Global Constraints

7

Optimization Problem Processing and Results

8

Optimization Problem Management

9

Use of Trade Restrictions in Optimization

IBM Algorithmics Portfolio Replication in Algo Risk Application
(Duration : 2 Days)

1

Day 1

  • PortfoIio Replication Overview: Purpose, Applications, Process and Theory
  • Algo Portfolio Replication Components: RiskWatch and Algo Risk Application (ARA)
  • The Steps to Portfolio Replication
  • Replicating Universe Asset Types - Modeling in RiskWatch
  • Mark-to-Future Asset and Liability Cube Creation in RiskWatch
  • RiskWatch Workshop - Creating MtF Cubes in the Stress Room
  • Portfolio Optimization in ARA
  • Building Portfolio Replication Optimization Problems in ARA
  • Assessing Replication Quality: Goodness of Fit Metrics, Standard RP Reports, and Deficiencies
  • Improving Replications using Trading Restrictions
2

Day 2

  • Portfolio Replication Hands-On Workshop using ARA Optimization Module
  • Open Discussion and Wrap-Up

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 4,000 Modules on a variety of subjects
  • All courses are delivered by Industry Veterans
  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

View our other course offerings by visiting http://encartalabs.com/course-catalogue-all.php

Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.

Top