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For investment professionals only in the UK. Citywire Switzerland 2012 – 19-21 September 2012
Old MutualGlobal Equity Absolute Return FundIan Heslop, Head of Quantitative Strategiesp, g
Old Mutual Asset Managers (UK) Limited, 2 Lambeth Hill, London EC4P 4WR. 020 7332 7500. omam.co.uk
Old Mutual Global Equity Absolute Return Fund
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Old Mutual Global Equity Absolute Return Fund
Sector GIF Offshore Alternative – Market Neutral – Equity
Ai Ab l t t th t h l l ti ith it d b d k tAim Absolute returns that have a low correlation with equity and bond markets
Manager Ian Heslop, Amadeo Alentorn and Mike Servent
Recognition
Record Strong performance with low correlation to equity and bond marketsRecord Strong performance with low correlation to equity and bond markets
Terms 1.5% AMC for A (retail) share class. 0.75% for I (institutional) share class
Ian Heslop is Citywire A rated and Citywire A Alternative UCITS rated for his risk-adjusted performance for the period 31/07/2009 to 31/07/2012
Old Mutual Global Equity Absolute Return Fund1 |
Old Mutual’s quantitative strategies team
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Old Mutual s quantitative strategies teamInvestment team principals
Dr Ian Heslop
Head of Quantitative Strategies/ Fund Manager
Dr Amadeo Alentorn CFA
Head of Quantitative Research/Fund Manager
Mike Servent
Head of Quantitative Modelling Systems/Fund Manager
Ian joined the team in May 2004 and has over 13 years’ investment experience (9 years quantitative investment experience), including OMAM and BGI Ian holds a BA in Chemistry
Amadeo joined the team in January 2005. He has extensive experience of quantitative research and software development, including Bank of England Amadeo holds a BEng in
Mike joined the team in November 2004 with over 11 years of quantitative systems development experience, including BarraInternational and COR Risk Systems Mike OMAM and BGI. Ian holds a BA in Chemistry
(Oxford) and a PhD in Medicinal Chemistry (Edinburgh)
Bank of England. Amadeo holds a BEng in Robotics (Plymouth), a MSc in Computer Science and PhD in Computational Finance (Essex).
International and COR Risk Systems. Mike developed optimisation, backtesting and modelling software used by OMAM while at COR. He holds a BA in Physics from Oxford.
Managing quantitative long-only, regional and global funds, absolute return and hedge fundsExpertise in investment research, portfolio construction and systems developmentAcademic advisory boardAccess to external researchers through virtual laboratory
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Old Mutual Global Equity Absolute Return Fund
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Old Mutual Global Equity Absolute Return Fund
The fund aims to deliver absolute returns that ha e a lo co elation ith eq it and bond
Objective
Global, diversified equity portfolio
Targeting absolute returns over rolling
have a low correlation with equity and bond markets, through a market neutral portfolio of global equity stocks
equity portfolio 12 month periods
Return volatility target of 6%
Low correlation to global stock markets
Market neutrality –pure alpha
Liquid, transparent UCITS fund with daily dealingpure alpha fund with daily dealing
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Strong performance with low volatility
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Strong performance with low volatility
% return Correlation vs
Si MSCI JP M
Low correlation to equity and bond markets
1m 3m 6m 1y p.a. 2y p.a.
Since inception**
p.a.
MSCI World Index
JP Morgan Global Bond
Index
Old Mutual Global Equity Absolute Return Fund A (retail) share class GBP
0.9 1.5 3.2 2.1 10.4 5.1 (0.1) (0.3)A (retail) share class GBP
Morningstar GIF sector average* 0.5 -1.2 -4.6 -7.5 -6.1 -0.1 0.5 (0.4)
Dynamic investment approach delivering strong performance
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Source: OMAM/Morningstar, bid to bid, net income reinvested. Sterling terms. Periods to 31/08/12 *Morningstar GIF sector average: GIF OS Alternative – Market Neutral – EquityCorrelation data since launch 01/07/09 to 31/08/12** Inception date: 01/07/09
The uses of market neutrality
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The uses of market neutralityMore efficient portfolio
10
11
Global eq ities
Global equities +10% Global Equity Market Neutral
8
9
etur
n (%
)
Global equities
6
7
Ann
ualis
ed re
Analysis based on 5,000 d i l t d tf li
4
5
random simulated portfolio allocations to regional equity indices.
14 15 16 18 19 204
Annualised risk (%)17
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Source: Performance based on net total returns to MSCI regional indices, and returns to the HFRX Equity Market Neutral index, from 31/01/99 to 28/02/11
Investment process - overview
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Investment process overview
Stock selection t t i
Portfolio t ti
Final tf li
Capital allocation t t t istrategies construction portfolioto strategies
Portfolio
Large opportunity set - 3,500 global stocks
Research
Rigorous implementation of clear, intuitive investment insights
Forecasts
Diversified alpha sourcesOptimal capital allocation across
Efficient, constrained, risk controlled portfolio constructionTransparent performance attribution to alpha sources
Historical strategy analysis spanning multiple economic cycles
p palpha strategies based on expected payoffsIn-built risk control and downside risk mitigation attribution to alpha sourcesdownside risk mitigation
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Investment process – details
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Investment process details
Dynamic valuation Market Dynamics Sustainable Growth Analyst Sentiment Company Management
Attractive valuationsBalance sheet quality
Strong medium and short-term trends; Industries
with macro support
Strong growth characteristics; Expectations
likely to be fulfilled
Analyst upgrades; Market under-
reaction
Good investment decisions; Efficient use
of capital
Dynamic valuation Market Dynamics Sustainable Growth Analyst Sentiment Company Management
Allocation to strategies
Strategy weightings vary based on investor sentiment, risk and macro conditions
Portfolio construction
Structured process, risk management, return diversification, portfolio controls and market impact
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Dynamic valuation – cyclicality of value returns
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Dynamic valuation cyclicality of value returns
Example: North America
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Source: OMAM. Data to 30/11/2011
Capital allocation: sentiment/uncertainty spectrum
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Capital allocation: sentiment/uncertainty spectrum
A market proxy to assess the macro environment in real time
Identify current positioning on sentiment/uncertainty C fid t
Risk environment
spectrum
Analyse expectations of the five strategies, given the current position
Tilt t t i hti di l
Confident
Market Tilt strategy weightings accordingly
OptimisticPessimistic
Market sentiment
Uncertain
Proprietary analysis to assess the market environment
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Capital allocation over time
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Capital allocation over time
Strategies are employed to differing degrees, depending on the environment
Portfolio allocations by strategy (%)
f day
s Dynamic ValuationDynamic Valuation
Market Dynamics and Dynamic Valuation tend to have higher allocations
0 5 10 15 20 25 30 35 40 45 50
# of
Market DynamicsMarket Dynamics
0 5 10 15 20 25 30 35 40 45 50
Sustainable GrowthSustainable Growth
0 5 10 15 20 25 30 35 40 45 50
Analyst SentimentAnalyst Sentiment
0 5 10 15 20 25 30 35 40 45 50
0 5 10 15 20 25 30 35 40 45 50
Company ManagementCompany Management
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Source: OMAM. Data from January 1994 to January 2012Positions correct at the end of January 2012
0 5 10 15 20 25 30 35 40 45 50
Performance attribution by strategy
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Performance attribution by strategy
5%
6%
2%
3%
4%
0%
1%
2%
-2%
-1%
August 2012 YTD 2011August 2012 YTD 2011
Dynamic Valuation Market Dynamics Sustainable Growth Analyst Sentiment Compant Management
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Source: OMAM. Data to 31/08/12
Key drivers of performance since launch
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Key drivers of performance since launch
Positive returns from all five strategiesPositive returns from all five strategies
20.6%
3.8%
8.3%
2.0% 1.2%
5.3%
Dynamic valuation Market dynamics Sustainable growth Analyst sentiment Company management Total
No one sector dominates
8.5%
y y g y p y g
2.9% 3.0%
3.7%
2.6%
3 8%4.6%
3 7%
0.6%0.0%
-0.1%
0.5%0.6%
0.4%
-0.4%
1.0%
-0.3%
0.4%
1.3%
0.5%
1.8% 1.5%
-0.2%
0.7%
3.8% 3.7%
Asia Pacific Europe Japan North America
0.4% 0.3%
Con
sum
erD
iscr
etio
nary
Con
sum
erS
tapl
es
Ener
gy
Fina
ncia
ls
Hea
lth C
are
Indu
stria
ls IT
Mat
eria
ls
Tele
com
s
Util
ities
Sector allocation Stock selection
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Source: OMAM as at 31/08/2012
Asia Pacific Europe Japan North AmericaSector allocation Stock selection
5 key reasons to invest
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5 key reasons to invest
Aims to beat cash in all market conditions
Typically lower volatility versus long-only equity funds
Flexible, dynamic investment process
Diversified, global equity portfolio
Market neutral fund
A highly diversified global equity absolute return fund
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Investment details
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Investment details
Launch date: July 2009
Minimum investment: €, $, £ 1,000 A (retail) share class. €, $, £ 100,000 I (institutional) share class
Annual management charge: € $ £: 1 5% for A (retail) share class 0 75% for I (institutional) share classAnnual management charge: €, $, £: 1.5% for A (retail) share class. 0.75% for I (institutional) share class
Performance fee: 20% of outperformance above a hurdle rate (central bank base rate – semi annually)
High water mark: Yes
Dealing frequency: DailyDealing frequency: Daily
Dealing cut off time/valuation point: 12 noon Irish time
Share classes: US dollars/euro/sterling (euro/sterling share classes are hedged against the US dollar base currency)
Structure: Ireland-domiciled UCITS fund S uc u e e a d do c ed UC S u d
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Appendix
Optimise risk and return profile
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Optimise risk and return profileInvestment parameters
Gross leverage reset to 200% each time we trade
Net leverage reset to 0% at each trading day
Regional allocations Constraints
33% North America (30-35% constrained)
33% Pan Europe (30-35% constrained)
17% Asia ex Japan (15-20% constrained)
Net countries constrained at +/- 1%
Net regions constrained at +/- 0.3%
Net sectors constrained at +/- 10%
17% Japan (15-20% constrained) Net industries constrained at +/- 10%
Stocks constrained at +/- 1.5%
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Stock example: Sulzer
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Stock example: Sulzer
Sulzer is a Swiss firm manufacturing pumping solutions and industrial equipment.
Dynamic valuation turned positive in 2010 as earnings expectations were not fully incorporated into its price
Sulzer % stock performance
expectations were not fully incorporated into its price.
Market Dynamics was positive as manufacturing benefited from the global economic recovery.
Sustainable Growth improved as the stock’s historic growth h t i ti l k d t i bl i t th f tcharacteristics looked sustainable into the future.
Analyst Sentiment was broadly positive over the period as market under-reacted to analyst forecasts
Company Management was positive but moving towards Sulzer % stock characteristics
neutral due to recent acquisitions.
Overall, there was wide support for opening a long position in April 2010, and after profiting from a strong rally, this position was closed as the company was then fairly priced.
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Source: OMAM
Systematic Investments team
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Systematic Investments team
Paul Simpson, Head of Alternatives
Systematic Investments
Quantitative StrategiesStatistical Arbitrage Managed Futures
Key product(s) Key product(s) Key product(s)Global Statistical Arbitrage Global, regional and single country equity
long-onlyGlobal and regional equity market neutralRegional equity 130/30
Managed futures absolute return
PrincipalsIan HeslopAmadeo AlentomMike Servent
Portfolio construction Modelling and systems Research
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Biographies
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Biographies
Ian Heslop joined the Quantitative Strategies team in 2004 from OMAM’s Global Equities team, where he was a fund manager specialising in the global technology and
Dr Ian HeslopHead of Quantitative Strategies/Fund Manager
Amadeo Alentorn joined OMAM in 2005 as an intern, while studying a PhD in Computational Finance at the University of Essex before becoming a full time
Dr Amadeo AlentornHead of Quantitative Research/Fund Manager
Mike Servent joined OMAM in November 2004 from
Mike ServentHead of Quantitative Modelling Systems/Fund Manager
a fund manager specialising in the global technology and biotechnology sectors. He joined the Old Mutual group from Barclays Global Investors, where he was a UK quantitative fund manager. Ian has a BA in Chemistry from Oxford University and completed a PhD in Medicinal Chemistry at Edinburgh University.
University of Essex, before becoming a full-time quantitative analyst in 2006. During his PhD he developed a new option pricing model using extreme value theory and collaborated with the Bank of England in several research projects, developing models for systemic risk of banking networks and liquidity of payment systems Prior to this he worked as a software
jBarra International where he was a Senior Consultant specialising in the implementation of multi asset-class risk systems. Prior to this he spent five years with COR Risk Solutions, which developed the optimisation, backtestingand modelling software currently used by the Quantitative Strategies Team at OMAM. At COR he worked as
Lawrence Clark
payment systems. Prior to this he worked as a software developer. Amadeo holds a BEng in Robotics from the University of Plymouth and an MSc in Computer Science from the University of Essex. He is a CFA charterholder.
Dr Yuangao Liu
Commercial Development Manager as well as undertaking research projects with various clients. Mike has an MA in Physics from Oxford University.
Lawrence Clark joined OMAM in November 2006, having spent the previous year as a postgraduate physicist at Oxford University conducting research into carbon nanomaterials for quantum information processing. Lawrence has an MPhys from Oxford University,
Quantitative Developer
Yuangao Liu joined OMAM in November 2007 from Jacobs UK, where he was a structural engineer specialising in building computer models to solve a variety of engineering problems. Previously he was a project research assistant at Tsinghua University, Beijing.
Quantitative Analyst
y y,specialising in financial market complexity and computer programming.
p j g y, j gYuangao has a PhD in Structural Engineering from Imperial College, London and a BEng in Civil Engineering from Tsinghua University, Beijing. He is a FRM charterholder.
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Biographies (Consultants)
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Biographies (Consultants)
Peter Pope has researched and published extensively in th f it l k t fi i l ti d
Dr Peter PopeProfessor of Accounting
Mark Salmon’s current research interests lie in financial t i b h i l fi d t f
Dr Mark SalmonProfessor of Finance
Dr Stephen SatchellReader in Financial Econometrics/Fellow of Trinity CollegeCass Business School, City University University of WarwickUniversity of Cambridge
the areas of capital markets, financial reporting and international equity valuation. Prior to his current role in OMAM’s Academic Advisory Board, he was Head of the V-Lab research program in the quantitative strategies team from 2006 to 2010. Before joining Cass in 2011, Peter Pope previously held academic positions at Lancaster University Management School Strathclyde
econometrics, behavioural finance and aspects of international macroeconomics. He is Professor of Finance at the University of Warwick and is Director of the university’s Financial Econometrics Research Centre and Finance Research Institute, as well as External Professor at the European University Institute in Florence. He currently also acts as a consultant to the Bank of
Stephen Satchell focuses on both empirical and theoretical aspects of econometrics, finance, risk measurement and utility theory. His very strong econometric techniques knowledge has proved invaluable for OMAM’s quantitative strategies team. Steve is a reader in financial econometrics at Cambridge, F ll f T i it C ll C b id d i iti Lancaster University Management School, Strathclyde
Business School and Liverpool University. He has also been visiting professor at the Stern School, New York University, and the University of California at Berkeley. He is a qualified accountant and was a member of the U.K. Accounting Standards Board Academic Panel.
He currently also acts as a consultant to the Bank of England and is a Research Fellow of the Centre for Economic Policy Research associated with the International Macro Programme. He has served as a consultant to a number of city institutions and was a member of a task force set up by the European Commission to consider exchange rate policy for the
a Fellow of Trinity College, Cambridge, and a visiting fellow at Birkbeck College, University of London. He holds two PhDs (Cambridge and London), an MSc (Sydney) and an MA (Cambridge). He has refereed widely in academic journals and has affiliations with professional bodies in finance. He has published widely in varied areas of finance including equity return and risk g p y
euro. Mark has a BA from Essex University and an MSc from the London School of Economics. He has published widely in academic journals, including Econometrica, The Annals of Statistics, Journal of Econometrics, the Economic Journal, the Journal of Economic Dynamics and Control, Journal of Empirical
in varied areas of finance, including equity return and risk models, style rotation, asset allocation, trading rules, volatility, option prices, exchange rates, and property markets.
Finance and the International Economic Review.
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Biographies (Consultants)
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Biographies (Consultants)
Mikhail Chernov’s research focuses on empirical asset i i bl d li ti f t i
Dr Mikhail ChernovAssociate Professor of Finance
Christopher Malloy’s main interests lie in the behavioural t f i i l fi Hi h t t
Dr Christopher MalloyAssistant Professor of Business Administration
Ian Marsh’s areas of expertise include exchange rate d lli d f ti dit i k d lli d
Dr Ian MarchProfessor of Finance
London Business School Harvard Business School, Finance Unit Cass Business School, City University
pricing problems and applications of econometric methods to finance. His main areas of interest are options, volatility, fixed income and credit and he makes a strong contribution to our growing expertise in non-equity asset classes. Mike is an Associate Professor of Finance at the London Business School. Formerly he was an Associate Professor of Finance at Columbia
aspects of empirical finance. His research concentrates on asset pricing, investments and portfolio choice and he helps to continue to advance our equity strategies. Chris is Assistant Professor of Business Administration in the Finance Unit of Harvard Business School. Prior to this he was Assistant Professor of Finance at the London Business School having previously been a Research and
modelling and forecasting, credit risk modelling and applied financial econometrics. He spent four years as a banker and economist prior to completing his PhD and has spent time as a researcher at the International Monetary Fund and the Bank of England’s Financial Stability area, as well as acting as a consultant to a range of financial institutions Ian has a BA from Sheffield was an Associate Professor of Finance at Columbia
Business School in New York. He holds BS and MS degrees from Moscow State University and a PhD in Finance from Pennsylvania State University. He has published in the Journal of Finance, the Journal of Econometrics and the Journal of Financial Economics.
Business School, having previously been a Research and Teaching Assistant at the University of Chicago's Graduate School of Business and a Research Assistant at the Washington DC Board of Governors of the Federal Reserve System. He has a BA in Economics from Yale University and a PhD in Finance and an MBA from the University of Chicago. He has published in the Journal
of financial institutions. Ian has a BA from Sheffield University, an MSc from Birkbeck College, University of London and a PhD from Strathclyde University, all in economics. He has published in many journals including the Journal of Finance, Journal of Monetary Economics, Review of Economics & Statistics, Journal of International Money and Finance & Explorations in Economic History.y g p
of Finance.y p y
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Important information
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Important information
FOR INVESTMENT PROFESSIONALS ONLY. THIS DOCUMENT IS NOT SUITABLE FOR RETAIL CLIENTS.
This information is being communicated only to persons who have professional experience in matters relating to investments falling within Article 19(1) of the Financial S i d M k t A t 2000 (Fi i l P ti ) O d 2001 d d (th O d ) d t t h it th i b l f l t i t it t Services and Markets Act 2000 (Financial Promotion) Order 2001, as amended (the Order) and to persons to whom it may otherwise be lawful to communicate it to (all such persons being referred to as relevant persons). Other persons should not rely or act upon this document or any of its contents. The recipient should not use the information in this document in any way which would constitute 'market abuse'. This document does not constitute or form part of, and should not be construed as, any offer for sale or subscription of, or solicitation of any offer to buy or subscribe for, any securities nor should it or any part of it form the basis of, or be relied on in connection with, any contract or commitment whatsoever. No representation or warranty, express or implied, is or will be made by OMAM, its advisors or any other person as to the accuracy, completeness or fairness of the information or warranty, express or implied, is or will be made by OMAM, its advisors or any other person as to the accuracy, completeness or fairness of the information or opinions contained in this document and any reliance you place on them will be at your sole risk.The Company: Old Mutual Dublin Funds plc, 1 North Wall Quay, Dublin 1, Ireland. The Company is an Irish law umbrella UCITS authorised by the Central Bank of Ireland. The fund cited above is authorised for distribution in the UK, Italy, Spain, France, Sweden and Switzerland. Representative in Switzerland is First Independent Fund Services Ltd., Klausstrasse 33, 8008 Zurich, Switzerland. Paying agent in Switzerland is NPB New Private Bank Ltd, Limmatquai 1, P.O. Box, 8022 Zurich, Switzerland. French centralising agent is Société Générale, Tour Granite 75886 Paris cedex 18 (Contact: M. Huguesde VERGNES – Tel : 33 1 42 14 25 88). Please read the simplified prospectus of the Company before investing. The prospectus and simplified prospectus, articles of association and annual and semi-annual reports of the Company may be obtained free of charge from the Swiss Representative or the French centralising agent. Old Mutual Global Equity Absolute Return Fund is a subfund of Old Mutual Dublin Funds (the “Company”). The Company has been registered with the Spanish Securities Market Commission (Comisión Nacional del Mercado de Valores) under no. 894 of its registries, pursuant to Spanish laws and regulations. We recommend that you seek advice from your financial adviser before making an investment decision. A complete list of Spanish distributors is available at the CNMV website. Before investing in the Shares please read the Prospectus which is available on www omam co uk and at the local distributors appointed in Italy Past performance is not a investing in the Shares, please read the Prospectus which is available on www.omam.co.uk and at the local distributors appointed in Italy. Past performance is not a guide to future performance. Performances are net of taxes.The performance data shown do not take account of the commission and costs incurred on the issue and redemption of shares. Issued by Old Mutual Asset Managers (OMAM), the trading name of Old Mutual Asset Managers (UK) Limited. Old Mutual Asset Managers (UK) Limited, 2 Lambeth Hill, London EC4P 4WR, England. Registered in England No. 2949554. Authorised and regulated in the UK by the Financial Services Authority. Telephone calls may be recorded for security purposes and to improve our customer service. 09/12/U6708
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