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Can't travel? Don't want to travel? LFS LiveLFS Live brings the class to you!

  • Live interactive training from world renowned practitioners in the comfort of your own home
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Correlation and Related Dependency Concepts in Investment Management

Despite the very well-known facts that dependencies in financial markets are time-variable and can have a major impact on the overall risk of portfolios and balance sheets, information regarding advanced methodologies in dependency analysis is hard to find and often fragmentary.

In this intensive program, correlation and related dependency concepts take centre stage. After a systematic introduction to empirical and mathematical properties of the traditional correlation concept, more recent methodologies are presented and examined in detail. This will help practitioners to derive deeper insights into real-word dependency structures, and solve practical issues in working with scenario-based approaches and deriving forward-looking estimators.

Participants will solve exercises based on typical situations encountered in applied dependency analysis, allowing them to find new inspiration and to take home practical tools to further improve their practice.

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  • Date:
  • Venue:
  • Manhattan - New York
  • Fee:
  • US$1745 per day

This course is also available in London Time Zone and Singapore Time Zone

Who The Course is For

  • Buy-side and sell-side risk managers
  • Investment managers of traditional and alternative assets
  • All staff involved with quantitative analysis
  • Programmers and application developers

Learning Objectives

  • Understand the limitations of traditional linear correlation analysis
  • Gain familiarity with modern dependency concepts beyond correlation
  • Learn how to apply scenario analysis to correlation forecasting and stress-testing
  • Analyze the implications of dependency on portfolio risk
  • Gain a deeper understanding of the advantages, and disadvantages, of quantitative methods in investment decision making

Prior Knowledge

  • Basic understanding in statistics, especially linear regression
  • Familiarity with modern portfolio theory and portfolio risk analysis

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