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
Introduction to mean-variance optimization
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