Portfolio Performance Measurement & Attribution Analysis

Portfolio Performance Measurement & Attribution Analysis

Monday 01 Feb 2021

  • Duration: One Week
  • City: Madrid 
  • Fees: Classroom: 4300 GBP / Online: 1950 GBP

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Introduction:

The main goal of portfolio performance evaluation is to measure value creation provided by the portfolio management industry. In recent years, the demand for “reliable and admissible” performance measures has increased as an investment in mutual and exchange-traded funds has exploded in popularity among small investors across the globe. This Course produces a census of the main measures of portfolio performance that have been proposed in the literature. We discuss their limits and provide a classification based on their properties and objectives.

Performance evaluation is an essential tool for understanding the quality of the investment process. Practitioners must take care, however, to understand how performance results are generated. They need a good understanding of the performance methods used, the data inputs, and the limitations of those methods.

By the end of the course you will be able to:

  • Calculate portfolio returns using a number of techniques
  • Select appropriate benchmarks for portfolios
  • Understand active and passive portfolio management strategies
  • Conduct comprehensive performance attribution for portfolios of all asset classes
  • explain the following components of portfolio evaluation and their interrelationships: performance measurement, performance attribution, and performance appraisal;
  • describe attributes of an effective attribution process;
  • distinguish between return attribution and risk attribution and between macro and micro return attribution;
  • describe returns-based, holdings-based, and transactions-based performance attribution, including advantages and disadvantages of each;
  • interpret the sources of portfolio returns using a specified attribution approach;
  • interpret the output from fixed-income attribution analyses;
  • describe limitations of appraisal measures and related metrics;
  • Evaluate the skill of an investment manager.

Who should attend?

Portfolio managers and support personnel, wealth managers, investors, private bankers and financial advisors. Prerequisite knowledge:

  • Intermediate MS Excel skills
  • Basic probability and statistics
  • Familiarity with fixed income instruments and concepts
  • Familiarity with equity valuation concepts

Course Outlines:

Day 1

Introduction

  • Why measure portfolio performance?
  • The measurement process
  • A brief history of asset returns
  • Review of quantitative tools

The Mathematics of Portfolio Returns

  • Arithmetic vs. geometric rates of return
  • Value (money) weighted rates of return
  • ICAA, simple and modified Dietz methods
  • Time weighted rates of return
  • Hybrid methodologies
  • Linked modified Dietz and linked IRR
  • Portfolio component returns

Day 2

Benchmarking

  • Desirable properties for benchmarks
  • Index calculation methodologies
  • Price weighted indices
  • Market capitalization indices
  • Equally weighted indices
  • Benchmark selection
  • Benchmark statistics

Day 3

Adjusting for Risk

  • Return distributions
  • Market price of risk
  • Risk measures (Drawdown, VaR, CVaR, etc.)
  • Risk-adjusted returns
  • Selecting a risk measure
  • Risk-adjusted performance measures for equity and fixed income
  • Risk-adjusted performance measures for hedge funds

Day 4

Performance Attribution: Foundations

  • Active vs. passive portfolio management
  • Attribution standards
  • Arithmetic attribution techniques
  • Geometric attribution techniques
  • Multi-currency attribution
  • Risk-adjusted attribution

Fixed Income Attribution

  • Duration attribution
  • Yield curve analysis and decomposition
  • Yield curve attribution

Day 5

Performance Measurement and Attribution for Derivatives

  • Futures
  • Swaps
  • Options, warrants and convertible bonds
  • Market neutral attribution: 130/30 funds
  • Multi-period Attribution
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