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Risk and Performance Analytics

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on 13 February 2013

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Transcript of Risk and Performance Analytics

Methodology Questions? Basics and Fundamentals Financial and Statistical terms and concepts

Microsoft Access

Bloomberg Terminal

Microsoft Excel (VBA) Upload Generator Generate Excel files for the Fund Portfolios and Benchmarks

Daily upload to build history

Automated system

Flagging problems that needed to be solved manually Fund Analysis Typical Macquarie fund analysed.

Compared the statistics with the objectives in the Product Disclosure Statement (PDS)

Fund typically high risk

Holdings in 25-35 Australian Equities

Aims to outperform the S&P/ASX200 Accumulation Index over medium to long term (before fees) Skills and Techniques Understanding investment types and their performance

Risk and statistical analytics

IT and computing skills

Self-learning was essential in some of the tasks

Researching Fund Reporting System Generate a report template from the Bloomberg Terminal

Determine important characteristics for analysis

Use VBA to extract necessary data Fund Analysis Demonstrate usefulness

Fund research

Analyse the influential characteristics of funds

Compare these characteristics with fund objectives Overweights and Underweights Automatic calculations

Composition of the fund

Concentrated on small amount of holdings Results and Outcomes Zan Lee Risk and Performance Analytics Main aims of the project Generate upload files to import onto the Bloomberg Terminal

Create an automated system

Implement a flagging system

Create tailor made reports Overview Introduction Macquarie Funds Group - Investment Risk Team

Increase independence of the investment risk team

Quickly and easily analyse fund data Generating upload files were successful

System was as automated as possible

Flagging system useful in picking up errors

Produced meaningful reports, capabilities

Self-learning and development Thank You HR - Pip Ringland and Helen Giang

MIM Investment Risk Team - Keith, Joel, Dan, Calista and Priyanka

Special thanks to my buddy, Tom Agenda 1. Introduction
2. Overview
3. Main Aims of the Project
4. Methodology
5. Fund Analysis
6. Results and Outcomes
7. Skills and Techniques
8. Questions Tracking Error Largest contributor to tracking error Boart Longyear, 28.44%

3 out of the Top 5 Overweights are present in the Top 5 Contribution to Tracking error Scenarios Performance Attribution Risk Adjusted Return
Full transcript