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IBM Algorithmics Modeling for Algo Scenario Engine

Modeling for Algo Scenario Engine™ is an advanced scenario generation application. It is an important part of integrated market and credit risk solutions. The scenarios created in ASE are based on historical time series data of observable market rates and prices. The scenarios generated by ASE are used for simulation and stress testing of portfolios. This course builds upon the Introduction to ASE.

Upon successful completion of the course, the participant will be able to:

  • Describe the Describe the databases within ASE and the role of each within AlgoOne
  • Identify elements in batch processing affecting scenario generation
  • Demonstrate the creation of a single-step MonteCarlo scenario set
  • Demonstrate the creation of a multi-step MonteCarlo scenario set
  • Construct conditional scenarios
  • Build Risk Neutral scenarios
  • Assemble Standard Shift Scenarios
  • Use the command line interface to ASE to facilitate data export
  • Transfer data between ASE and RW
  • Use Algorithmics documentation to navigate ASE models and options

Profil uczestnika

This advanced course is aimed at finance individuals, including risk managers, trading analysts, investment managers, and financial analysts.

Agenda

Day 1:

  • Review of ASE GUI and environment
  • Discuss Input data requirements for scenario generation in ASE
  • Review of ASE into its components
    • Blocks/ Models/ Estimations/ Transformations/Scenario Generator
  • Bring all the components together in Scenario Sets
  • Create single and multi-step Monte Carlo Scenarios through deeper analytics
  • Construct conditional scenarios
  • Build Risk Neutral scenarios
  • Assemble Standard Shift Scenarios
  • Transfer data between ASE and RiskWatch

Wymagane przygotowanie uczestników

Basic knowledge of UNIX is required.

You should have completed:

  • IBM Algorithmics Introduction to Algo Scenario Engine

Zagadnienia

INFORMACJA CENOWA:
od - zł netto za jedną osobę

CZAS TRWANIA (dni): 1

KOD SZKOLENIA: G0202G

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