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THIERRY BECHU - CIO, Aequam Capital

THIERRY KUAGBENU - Responsable des Solutions d’Investissement, Aviva Investors France, CFA, FSA, FRM

GUILLAUME MONARCHA - Responsable de la Recherche Quantitative, Orion Financial Partner

Les objectifs du cours

We propose a deep dive into the factor investing universe, from its academic foundations to practical implementation. This course will consider two complementary perspectives, focusing on both:

  • the structuring side of smart beta, factor-based, and alternative risk premia strategies, through the presentation of their implementation process, from stock selection to portfolio construction and strategy management
  • a buy-side perspective, from performance attribution and strategy selection, to the management of multi-factor / multi-asset diversified portfolios.

The course is organized around four parts. First, we will introduce the academic foundations of factor investing, and present the typology of the current investment universe (smart beta, factor investing and alternative risk premia). The second part is dedicated to the presentation of long-only equity-based investment strategies (both smart beta and factor-based), and to the introduction of multi-factor investing. In the third one, we will review the alternative risk premia (ARP) universe across the various asset classes (equities, commodities, interest rates, FX), and we will address the issue of the management of ARP allocations. In the fourth part, we will consider the role of factor-based investment strategies (smart beta, factor investing and ARPs) within a diversified, multi-asset solution context.

Plan du course

Introduction (Guillaume Monarcha, 3h)

Part 1 (Thierry Béchu, 7h30)

  • 1.1. Beta
  • 1.2. Smart beta strategies
  • 1.3. Factor investing
  • 1.4. Multi-factor investing

Part 2 (Guillaume Monarcha, 9h)

  • 2.1. Alternative risk premia
  • 2.2. The management of ARP allocations

Part 3: Multi-asset solutions (Thierry Kuagbenu, 4h30)

  • 3.1. Introduction
  • 3.2. Theory
  • 3.3. Practical applications

Prerequisites: be familiar with basic quantitative tools (statistics, estimation of linear models, constrained linear optimization), and portfolio theory.




Exam and group project

Group project: will consist in the construction and backtesting of systematic investment strategies, risk premia allocations, replication and application of research papers...