IBM Algorithmics Portfolio Replication in Algo Risk Application

This course provides a practical overview of portfolio replication for insurance, with hands-on training in the construction of replicating portfolios.

Czas trwania

2 dni

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Profil uczestnika

This advanced course is for the insurance industry end-user, particularly risk managers, risk analysts, and actuaries.


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

Day 2:

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

Wymagane przygotowanie uczestników

Prior training and/or experience in RiskWatch and ARA is strongly recommended.


  • 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
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