Effective Portfolio Optimization Techniques

1 Day Workshop
(Workshop is not being offered at this time)

Qualifies for Continuing Education Credits:

• NASBA CPE - 9.6
• CFA CE - 8
• ACCA CPD

Introduction

This one-day workshop is designed for practitioners with the overall goal being to provide a clear, definitive understanding of the mean-variance framework and the issues with its application. The workshop explores in depth the extensions to the basic model (i.e., Resampling and Black-Litterman), and examines some of the limiting assumptions of the MV framework, with particular emphasis on transaction costs, non-normal distributions and dynamic portfolio problems. The workshop uses a fairly extensive Excel application to examine the mean-variance framework which delegates can use following the workshop. This intensive and highly interactive workshop provides delegates with a solid foundation in applying the mean-variance framework and its extensions, and offers practical case studies, group activities, and interactive Excel exercises to reinforce both the various concepts and the relationship among these concepts.

Who Should Attend?

This is an intensive and highly interactive workshop, with practical case studies, exercises and group activities, as well as the latest practical and theoretical insights designed for intermediate to advanced level professionals, with particular interest for those working within the areas of asset allocation, investment management, quantitative analysis, and portfolio management. The workshop will also be beneficial to those working outside the area of investment management who wish to gain a better understanding of this area of portfolio management and the latest methods and approaches.

What will you get out of this Workshop?

• Gain understanding in evaluating a company’s performance and capital structure using both qualitative and quantitative frameworks and tools

• Understand Markowitz’s mean variance optimization; the general framework, interpretation, analysis of results, strengths and weaknesses

• Learn about the practical extensions of mean-variance optimization and how they address shortcomings

• Explore the latest research on related practical issues, such as transaction costs and rebalancing

• Discuss the latest techniques in using stochastic programming to generate dynamic asset allocation strategies

• Practical Excel implementations that delegates will be able to reference after the workshop

For this highly interactive workshop, all delegates are strongly recommended to attend the workshop with a laptop computer loaded with Microsoft Excel with Visual Basic and Excel Solver Add-ins. There will be several interactive group sessions to work on real-life cases.

Content

Overview of portfolio optimization

What is portfolio optimization

Asset allocation considerations and objectives

Overview of approaches to portfolio optimization

Data issues and considerations

Learning Outcome: Attendees will gain a detailed understanding of portfolio optimization technology, its role as an asset allocation tool, and the data issues associated with its implementation

• What is mean-variance optimization

• Defining the inputs to MV optimization

• Determining an investor’s risk aversion

• Solving a MV optimization problem

• Constructing the efficient frontier and analyzing the output of MV

• Key features and criticisms of MV optimization

• Learning Outcome: Attendees will gain a detailed understanding of Markowitz’s mean variance optimization; the general framework, interpretation, analysis of results, strengths and weaknesses

INTERACTIVE: Getting started with matrix arithmetic and optimization in Excel

• Review of Excel matrix arithmetic functions

• Review of the Excel Solver for optimization problems

• Learning Outcome: By demonstrating how to use Excel matrix arithmetic and optimization functions, delegates will gain an understanding the basic tools needed to implement and extend the MV optimization framework

INTERACTIVE: Mean-variance optimization in Excel + CASE STUDIES

• Delegates will be provided with Excel files with macros to perform MV optimization and analyze output

• Case studies will be considered to demonstrate features and extremes of MV optimization

• Learning Outcome: By working with an Excel implementation of the MV framework and stepping through several case studies, delegates will deepen their understanding of the methodology and have a tool to apply their knowledge after returning from the course

Adaptations and extensions to MV optimization

• Accounting for skewness and kurtosis of asset return distributions

• Michaud’s criticism of MV optimization and the resampled frontier

• Black-Litterman approach

• Dynamic rebalancing/accounting for transaction costs

• Learning Outcome: Attendees will learn about important, practical extensions of the mean-variance optimization and how they address shortcomings

INTERACTIVE: Extensions to MV optimization in Excel + CASE STUDIES

• Delegates will be provided with Excel files to perform MV extensions

• Case studies will be considered to demonstrate features of variations of MV optimization

• Case studies to compare asset allocations produced by different approaches

• Learning Outcome: By working with an Excel implementation of the MV framework and stepping through several case studies, candidates will deepen their understanding of resampling and the Black-Litterman approach and have a tool to apply their knowledge after returning from the course

Portfolio optimization beyond mean-variance

• Dynamic investment problems

• Transaction costs

• Accounting for skewness and kurtosis of asset return distributions

• Asset liability management problems

• Learning Outcome: Attendees will examine the latest techniques in using stochastic programming to address non-normal return distributions and transaction costs and to generate dynamic asset allocation strategies