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Research Affiliates and Dynamic Multifactor Strategies: Time to Time?
Evans, Richard B.; Pachauri, Abhinav Case F-1988 / Published August 11, 2021 / 23 pages.
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Product Overview

This case explores the dynamic allocation approach to investing, an approach that would time the market based on factors’ relative valuations. Research Affiliates created a RAFI Dynamic Multifactor US index that dynamically allocated five factor strategies: value, quality, momentum, size, and low volatility. In this course, students will utilize various information presented in the case to discuss why Research Affiliates decided to launch the strategy, how Research Affiliates times it, and what has been its performance relative to the Russell 1000 Index and other competitors. Students will also assess the strategy’s performance and some of the limitations of its dynamic strategy.


Learning Objectives

•To introduce smart-beta strategies and their construction •To compare value and momentum strategies over time and the potential benefits of diversifying across factor strategies •To explore the possibility of factor timing in a multifactor product and the design of that product •To contrast the performance of different dynamic factor timing implementation using the actual performance, risk, and factor exposure data

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  • Overview

    This case explores the dynamic allocation approach to investing, an approach that would time the market based on factors’ relative valuations. Research Affiliates created a RAFI Dynamic Multifactor US index that dynamically allocated five factor strategies: value, quality, momentum, size, and low volatility. In this course, students will utilize various information presented in the case to discuss why Research Affiliates decided to launch the strategy, how Research Affiliates times it, and what has been its performance relative to the Russell 1000 Index and other competitors. Students will also assess the strategy’s performance and some of the limitations of its dynamic strategy.

  • Learning Objectives

    Learning Objectives

    •To introduce smart-beta strategies and their construction •To compare value and momentum strategies over time and the potential benefits of diversifying across factor strategies •To explore the possibility of factor timing in a multifactor product and the design of that product •To contrast the performance of different dynamic factor timing implementation using the actual performance, risk, and factor exposure data