Omam stockholm mar12_print

For professional clients only

Old Mutual Global Equity Absolute Return Fund

Ian Heslop, Fund Manager

GEAR 2011 highlights

• Returned +12.6% in 2011 (I class USD)

• Annualised volatility since launch 4.7% compared to 18.3% for MSCI World*

• Ranked #1 in sector during 2011*

• A-rated in the new Citywire Alternative UCITS ratings** (end of December 2011)

• Winner of the best relative value equity fund in UCITS Hedge Awards 2012

2 | Old Mutual Global Equity Absolute Return Fund

Source: *OMAM. **Rating attained at end of December 2011.

Old Mutual’s quantitative strategies team

• Managing quantitative long-only, regional and global funds, UCITS III absolute return and hedge funds

• Expertise in investment research, portfolio construction and systems development

• Academic advisory board

• Access to external researchers through virtual laboratory

Investment team principals

Ian joined the team in May 2004 and has over 13

Head of Quantitative Research / Fund ManagerDr Amadeo Alentorn CFA

Amadeo joined the team in January 2005. He has

Head of Quantitative Modelling Systems / Fund ManagerMike Servent

Mike joined the team in November 2004 with over 11

Head of Quantitative Strategies / Fund ManagerDr Ian Heslop

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 (Oxford) and a PhD in Medicinal Chemistry (Edinburgh)

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 Robotics (Plymouth), a MSc in Computer Science and PhD in Computational Finance (Essex).

Mike joined the team in November 2004 with over 11 years of quantitative systems development experience, including Barra 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.


Strong performance with low volatilityLow correlation to equity and bond markets

S.I

% return Correlation vs

1m 3m 6m 1y 2y

01/07/09 to

31/01/12

MSCI World Index

JP Morgan Global

Bond Index

Old Mutual 0 5% 0 4% 1 2% 10 7% 11 9% 13 7% 0 1 0 1Old Mutual Global Equity Absolute Return Fund

-0.5% -0.4% 1.2% 10.7% 11.9% 13.7% -0.1 -0.1

Morningstar GIF sector average* 0.9% -4.5% -7.8% -7.6% -4.3% -0.7% 0.7 0.3

Source: OMAM/Morningstar, bid to bid, net income reinvested, US dollar terms. Periods to 31/01/2012. *Morningstar GIF sector average: GIF OS Alternative – Market Neutral - Equity Correlation data since launch 01/07/09 to 31/01/2012.


The uses of market neutralityMore efficient portfolio

10

11

Global equities

Global equities +10% Global Equity Market Neutral

8

9

UR

N (%

)

Global equities

7

8

ALI

SED

RET

U

5

6

AN

NU

A

Analysis based on 5,000 random simulated portfolio allocations to regional equity indices.

14 15 16 18 19 204

ANNUALISED RISK (%)

17

g q y


Source: Performance based on net total returns to MSCI regional indices, and returns to the HFRX Equity Market Neutral index, from 31/1/99 to 28/2/11.

Old Mutual Global Equity Absolute Return Fund

• The fund aims to deliver

Objective

The fund aims to deliver absolute returns that have a low correlation with equity and bond markets through a

Global, diversified equity portfolio

Market neutrality –pure alpha

bond markets, through a market neutral portfolio of global equity stocks

ReturnReturnvolatility target

of 6%

Low correlation to global stock markets

| Old Mutual Global Equity Absolute Return Fund6

GEAR: low correlation to equities and bonds60-day correlation since fund launch

80%

100% Fund v equity correlation

Fund v bond correlation

20%

40%

60%

-20%

0%

-80%

-60%

-40%

-100%

Sep-09 Dec-09 Mar-10 Jun-10 Sep-10 Dec-10 Mar-11 Jun-11 Sep-11 Dec-11

Source: Bloomberg. Old Mutual Global Equity Absolute Return Fund versus MSCI World Index and JP Morgan Global Aggregate Bond Index. Fund launched July 2009


Equity volatility is volatile!Efficient risk management in the fund

35%

40% GEAR 60 Day Annualised Volatility

MSCI WORLD 60 Day Annualised V l tilit

25%

30%

Volatility

15%

20%

25%

10%

15%

0%

5%

Sep-09 Dec-09 Mar-10 Jun-10 Sep-10 Dec-10 Mar-11 Jun-11 Sep-11 Dec-11

Source: Bloomberg


Sep 09 Dec 09 Mar 10 Jun 10 Sep 10 Dec 10 Mar 11 Jun 11 Sep 11 Dec 11

Investment process – overview

Final portfolio

Portfolio construction

Capital allocation to strategies

Stock selection strategies

Research

• Rigorous implementation of clear intuitive Portfolio

L t it t 3 500 l b l t k• Rigorous implementation of clear, intuitive investment insights

• Historical strategy analysis spanning multiple economic cycles

• Large opportunity set - 3,500 global stocks

• Efficient, constrained, risk controlled portfolio construction

economic cycles

Forecasts

• Diversified alpha sources

O ti l it l ll ti l h

• Transparent performance attribution to alpha sources

• Optimal capital allocation across alpha strategies based on expected payoffs

• In-built risk control and downside risk mitigation


mitigation

Investment process – details

Dynamic valuation Portfolioconstruction

s

Dynamic valuation• Attractive valuations • Balance sheet quality

M k t d i Risk management• Downside risk control• Risk budget

Return diversificationM lti l t t i s

trat

egie

s Market dynamics• Strong medium & short-term trends• Industries with macro support

Sustainable growth


Final portfolio

• Multiple strategies• Broad opportunity set

Structured process• Rigorous• Dispassionatek

sele

ctio

n Sustainable growth• Strong growth characteristics• Expectations likely to be fulfilled

Analyst sentiment

in response to investor sentiment, risk environment and macroeconomics

spass o a e

Portfolio controls• Sector/industry• Liquidity management

Market impact

Sto

ck Analyst sentiment• Analyst upgrades• Market under-reaction

Company management Market impact• Trading costs• Turnover

Company management• Good investment decisions• Efficient use of capital


Dynamic valuation – cyclicality of value returnsExample: North America

101 Book to PriceOMAM Valuation factor

OMAM Quality factor

urns

umul

ativ

e re

tuC

u

Jul81 Jul83 Jul85 Jul87 Jul89 Jul91 Jul93 Jul95 Jul97 Jul99 Jul01 Jul03 Jul05 Jul07 Jul09 Jul11

100

Source: OMAM.

Jul81 Jul83 Jul85 Jul87 Jul89 Jul91 Jul93 Jul95 Jul97 Jul99 Jul01 Jul03 Jul05 Jul07 Jul09 Jul11


Market neutral: more than portfolio construction

0.8

1.0 Dynamic valuation

valuationValuation

n

0.6

Cor

rela

tio

0.2

0.4

-0 2

-

-0.4

-0.2

1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Source: OMAM. Proprietary strategies versus MSCI World Index.


Capital allocation based on market environmentDynamically allocating to strategies that are expected to outperform

• A market proxy to assess the macro environment in real time

Risk Environment

environment in real time

• Identify current positioning on sentiment/uncertainty spectrum

Confident

M k t sentiment/uncertainty spectrum

• Analyse expectations of the five strategies, given the current position

OptimisticPessimistic

Market Sentiment

g , g p

• Tilt strategy weightings accordingly

U t iUncertain

Proprietary analysis to assess the market environmentProprietary analysis to assess the market environment



Capital allocation based on market environmentCurrent allocations Portfolio allocations by strategy

0 5 10 15 20 25 30 35 40 45 50

Market Dynamics

% of

# of

day

s

• Overweighting market dynamics and company

A l t S ti t

Dynamic Valuation

0 5 10 15 20 25 30 35 40 45 50

% of portfoliomanagement

• Underweighting analyst sentiment

0 5 10 15 20 25 30 35 40 45 50

Analyst Sentiment

C

sentiment

• Other strategies in line with their historic weights

0 5 10 15 20 25 30 35 40 45 50

Company Management

Sustainable Growth

0 5 10 15 20 25 30 35 40 45 50

Sustainable Growth


Source: OMAM. Data from January 1994 to January 2012

Positions correct at the end of January 2012

Key drivers of performance in 2011Positive returns from all five strategies

• Correctly rotated into high quality stocks early on the year

• Captured profitable trends within equity marketsCap u ed p o ab e e ds equ y a e s

• Identified companies with superior management teams

5%6%7%

Dynamic ValuationM k D i

1%2%3%4% Market Dynamics

Sustainable GrowthAnalyst SentimentCompany Management

0%1% Company Management

Source: OMAM


Key drivers of performance in 2011 – no one sector dominates

2.5%

3.0% Sector Allocation

Stock Selection

1 0%

1.5%

2.0%

0.0%

0.5%

1.0%

-0.5%

0.0%

Source: OMAM


Key drivers of performance in 2011 – no one region dominates

6 0%

5.0%

6.0%

4.0%

3.0%

1.0%

2.0%

0.0%

Asia Pacific ex Japan Europe Japan North America

Source: OMAM


Asia Pacific ex Japan Europe Japan North America

Strengths of our approach

• Experienced team of quantitative investment experts• Experienced team of quantitative investment experts

– Investment principals have worked together for over 7 years

– Supplemented by an Academic Advisory Board and external team of researchers

• Five robustly-designed stock selection strategies, providing exposure to

proprietary drivers of investment return

– Value and growth strategies adjusted for quality

– Measures to capture quality of company management

• Proprietary, dynamic capital allocation tools, allocating to strategies at g gthe appropriate point in the cycle

• Risk management embedded in very step of the process


g y p p

Biographies

Dr Amadeo AlentornHead of Quantitative Research / Fund Manager

Amadeo Alentorn joined OMAM in 2005 as an intern, while studying a PhD in Computational Finance at the University

Mike ServentHead of Quantitative Modelling Systems / Fund Manager

Mike Servent joined OMAM in November 2004 from Barra International where he was a Senior Consultant

Dr Ian HeslopHead of Quantitative Strategies / Fund Manager

Ian Heslop joined the Quantitative Strategies team in 2004 from OMAM’s Global Equities team, where he was a fund

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 developer in the IT industry and in

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, backtesting and modelling software currently used by the Quantitative Strategies Team at OMAM. At COR he worked as Commercial Development Manager as well as undertaking research projects with various clients Mike has an MA in

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.

worked as a software developer in the IT industry and in the manufacturing industry. 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.

research projects with various clients. Mike has an MA in Physics from Oxford University.

Lawrence ClarkQuantitative Developer

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

Dr Yuangao LiuQuantitative Analyst

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 nanomaterials for quantum information processing.

Lawrence has an MPhys from Oxford University, specialising in financial market complexity and computer programming.

of engineering problems. Previously he was a project research assistant at Tsinghua University, Beijing. Yuangao 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.


Biographies (Consultants)

Dr Mark Salmon Professor of FinanceUniversity of Warwick

Mark Salmon’s current research interests lie in financial t i b h i l fi d t f

Dr Stephen SatchellReader in Financial Econometrics / Fellow of Trinity College University of Cambridge

Stephen Satchell focuses on both empirical and theoretical t f t i fi i k t d

Dr Peter Pope Professor of AccountingCass Business School, City University

Peter Pope has researched and published extensively in h f i l k fi i l i d 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 England

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, 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

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 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 euro. Mark has a BA from Essex

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 models, style rotation, asset allocation, trading rules, volatility, option prices, exchange rates, and property markets.

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.

p yUniversity 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 Finance and the International

p , g , p p y

Economic Review.


Biographies (Consultants)

Dr Ian MarchProfessor of FinanceCass Business School, City University

Ian Marsh’s areas of expertise include exchange rate d lli d f ti dit i k d lli d 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 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 International Money and Finance & Explorations in Economic History.


Important informationFor professional clients only, and not to be distributed to or relied upon by retail clients. Past performance is not a guide to future performance.

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 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

h ld t l t thi d t f it t t Th i i t h ld t th i f ti i thi d t 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 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 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.

The performance data shown do not take account of the commission and costs incurred on the issue and redemption of shares 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 and Old Mutual Fund Managers 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


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Omam stockholm mar12_print

Economy & Finance

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