Building a Fund from $30 bn to $324 bn While Keeping the Alpha - - PowerPoint PPT Presentation

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Norges Bank Investment Management

“Exploring Capacity Issues:”

Building a Fund from $30 bn to $324 bn While Keeping the Alpha Capability

The Q-Group Spring 2007 Seminar, Georgia, 28 March

Knut N. Kjaer, CEO Norges Bank Investment Management

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Agenda

• Background and Facts
• Transition in Two Dimensions:

Strategic: From Oil to International Securities Financial: From Cash to Equities

• The Alpha Challenge
• Results
• Discussion

The Advantage of Size Capacity Constraints

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Background and Facts

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Source: Fact sheet 2006

The Ranking of Oil Producers 2005

(mill b/d)

Production

2.51 2.64 2.97 3.03 3.63 3.76 3.91 7.27 9.44 9.47 Kuwait Venezuela Norway Canada China Mexico Iran USA Russia Saudi Arabia

Net export

1.38 1.66 2.09 2.09 2.12 2.18 2.34 2.74 6.64 7.38 Libya Mexico UEA Nigeria Venezuela Kuwait Iran Norway Russia Saudi Arabia

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The Norwegian Oil Fund and NBIM

• Norway is the world’s 3rd largest exporter of oil
• Since the late 1990’s the bulk of oil revenue has been

saved to the Oil Fund for future generations

• NBIM was established in 1998 and manages the Oil

Fund and the bulk of the Central Bank’s currency reserves

• The Ministry of Finance owns the Fund and sets the

benchmark

• Asset under management in NBIM increased from

USD 30 bn at inception in 1998 to USD 324 bn at year end 2006

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Projected Growth of the Government Pension Fund - Global

Source: National Budget 2007, October 2006

50 100 150 200 250 300 350 400 450 500 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

• Bn. USD

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A Possible Scenario

Ownership in Equity Markets

0.00 % 0.20 % 0.40 % 0.60 % 0.80 % 1.00 % 1.20 % 1.40 % 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Percent of FTSE Market Cap Europe America Asia Total

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Norges Bank Investment Management (NBIM)

• NBIM was established in 1998 as a separate wing of

Norges Bank. NBIM is organised as a business unit. Offices in Oslo, London and New York

• Funds managed by NBIM as of 31 Dec 2006 (billion

USD):

The Pension Fund - Global 286 The Foreign Exchange Reserves 36 The Petroleum Insurance Fund 2 Total 324

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NBIM / Organisation Chart

Executive Director

Knut N. Kjær

Executive Director

Knut N. Kjær

Fixed Income

Investments Operations

Dag Løtveit Bjørn Egge

Fixed Income

Investments Operations

Dag Løtveit Bjørn Egge

Equity

Investments Operations

Yngve Slyngstad Stephen A. Hirsch

Equity

Investments Operations

Yngve Slyngstad Stephen A. Hirsch

Legal / Finance / HR

Marius N. Haug Bjørn Taraldsen Kristin S. Kleven

IT Infrastructure

Ilse Bache

Risk, Performance & Accounting

Ilse Bache

Corporate Governance

Henrik P. Syse

Offices in Oslo, London and New York Number of Employees as of 31.12.2006: 132

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Benchmark for the Pension Fund-Global

EQ - Asia / Pacific 6 % FI - Americas 21 % FI - Asia / Pacific 3 % EQ - Europe 20 % FI - Europe 36 % EQ - Americas / Africa 14 %

Strategic benchmark: 60 % Fixed Income 40 % Equities “Smart” rebalancing:

• Monthly inflows
• Asset class / region

with largest negative deviation from benchmark

Equity index: FTSE All World Index Large & Mid Cap

• Approx. 2 400 equities

Fixed income index: Lehman Brothers Global Aggregate Government / Agency / Corporate / Securitized

• Approx. 9 300 bonds

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Transition in Two Dimensions: Strategic: Oil to International Financial Securities Financial: Cash to Equities and Fixed Income Securities

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Petroleum Wealth - Autumn 2006

Petroleum in the ground: Net present value of the government’s future cash flows from oil activities. Estimated at NOK 3660 billion at constant 2007 values (Source: National Budget 2007) 100 200 300 400 500 600 Petroleum In Ground Oil fund Equities Bonds USD Bn

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Petroleum Wealth - Value at Risk

Value at Risk is defined as one standard deviation in this context. The actual values will fluctuate outside the bands in one out of three years 20 40 60 80 100 120 140 160 180 200 Petroleum In Ground Oil fund Equities Bonds USD Bn

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Real Global Market Returns 1900 – 2005

0.10 1.00 10.00 100.00 1000.00 1 8 9 9 1 9 6 1 9 1 3 1 9 2 1 9 2 7 1 9 3 4 1 9 4 1 1 9 4 8 1 9 5 5 1 9 6 2 1 9 6 9 1 9 7 6 1 9 8 3 1 9 9 1 9 9 7 2 4 Equities Bonds Money market Oil

Source: Dimson, Marsh & Staunton, Triumph of the Optimists, 2002, with updates 376 6 3 2

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Portfolios of Oil and Equities

0.00 % 1.00 % 2.00 % 3.00 % 4.00 % 5.00 % 6.00 % 7.00 % 0.00 % 5.00 % 10.00 % 15.00 % 20.00 % 25.00 % 30.00 % 35.00 %

Standard deviation Real Return

100% equities 100% oil

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Portfolios of Equities, Oil and Bonds

0.00 % 1.00 % 2.00 % 3.00 % 4.00 % 5.00 % 6.00 % 7.00 % 0.00 % 5.00 % 10.00 % 15.00 % 20.00 % 25.00 % 30.00 % 35.00 %

Standard deviation Real Return

100% equities 100% oil 100% bonds

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Strategy: Transition From Petroleum

• The Oil Fund’s key function is to diversify the

Petroleum Wealth into a broad portfolio of international securities

• The transition takes down the expected risk

significantly and increases the expected return

• The Fund makes the income stream from the

non-renewable resources permanent

• The intention is to spend only the (expected) real

return at the annual public budgets, thus preserving the capital of the fund for all future generations

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Implementation:Transition From Cash

5 10 15 20 25 30 35 40 45 50 1998 1999 2000 2001 2002 2003 2004 2005 2006 Inflow in USD (bill) 10 20 30 40 50 60 70 Inflow in % of MV Inflow LHS Inflow as % of MV at the beg. of year RHS

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Trading Efficiency

• Given the expected large inflows and expected large size,

NBIM knew early on that efficient trading was critical to success

• If trading was not efficient, NBIM would easily spend any

alpha generated and more

• System advances over the last 9 years along with

management willing to focus on trading has enabled NBIM to build the infrastructure and gain the expertise to compete in a competitive part of the marketplace

• Data is the key to improving trading efficiency. Tracking

all data components of the trading cycle is extremely difficult but more than pays for the effort

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Total Equity Trade Volume 98 - 06

• 5

10 15 20 25 Sep98 Dec98 Mar99 Jun99 Sep99 Dec99 Mar00 Jun00 Sep00 Dec00 Mar01 Jun01 Sep01 Dec01 Mar02 Jun02 Sep02 Dec02 Mar03 Jun03 Sep03 Dec03 Mar04 Jun04 Sep04 Dec04 Mar05 Jun05 Sep05 Dec05 Mar06 Jun06 Sep06 Dec06 Billions USD Singlestock (phys) Program Futures Equity Swaps FX

Equity trading volume tripled from the end of 2004 to the summer of 2006 and is expected to increase for the foreseeable future

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How is Volume Distributed (%)

0 % 20 % 40 % 60 % 80 % 100 % Jan04 Mar04 May04 Jul04 Sep04 Nov04 Jan05 Mar05 May05 Jul05 Sep05 Nov05 Jan06 Mar06 Mai06 Jul06 Sep06 Nov06 Electronic Agency Natural Capital

Natural flows and capital are the sweet spots for broker interaction. This is an area of focus for us. Tracking costs told us that agency is not optimal relative to other alternatives.

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Electronic Trading Volumes 2004 - 2006

• 1

2 3 4 5 6 J a n 4 M a r 4 M a y 4 J u l 4 S e p 4 N

• v

4 J a n 5 M a r 5 M a y 5 J u l 5 S e p 5 N

• v

5 J a n 6 M a r 6 M a y 6 J u l 6 S e p 6 N

• v

6

Billions

• 10 %

0 % 10 % 20 % 30 % 40 % 50 % 60 % 70 % Value Percent

Being nimble is important in the fast changing trading environment. We see electronic trading as an important tool required to improve efficiency and lower total trading costs.

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Volume By Instrument 2006

• 5

10 15 20 25 30 35 40 45 Physical Swap

• Elec. Phys
• Elec. Swap

Billions

Swaps have there place in an investment strategy, but are expensive to trade given constraints in execution. Tracking costs enabled us to see the costs confirming what the traders were telling us.

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Cutting the Trading Cost

Total Single Stock Trading Cost

5 10 15 20 25 30 35 40 45 2003 2004 2005 2006

Basis points Tax&Charges Commission Shortfall

Diligent management enabled a significant decrease in trading costs despite strong growth in volume and average ticket size

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Trading - Conclusions

• Actively managing and monitoring all trading costs is

important

• Lowering commissions is only a small start
• The ability to influence the trading mix has changed

dramatically over the last 5 years giving the buyside the tools to actively manage total trading costs

• The key to lowering trading costs is Data and access to
• Data. Good Data is important not only for improving

trading costs but should also be extended to improving portfolio management decisions

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The α Challenge

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Challenges in Alpha Management

• Create excess return against the benchmark
• targeting 0.25% over rolling 3 year horizons
• with costs less than 0.1% ex performance fees
• and annual inflow at USD 20 – 50 bn / year

Excess Return, Basis Points

20 40 60 80 100 120 140 1998 1999 2000 2001 2002 2003 2004 2005 2006

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Management strategy Tactical allocation Factor-based strategies Fundamental strategies Relative value Analytical ability + + ++ +++ Number of independent positions

• +++

++ Implementation costs +++ + ++ + Experience

• ++

+++ Expenses Low Moderate High High Expected information ratio Low Moderate High High

Move to More Scalable Alpha-Strategies May Imply Lower Information Ratio

• NBIM prefers relative value and fundamental

strategies

• Our IR is now 1.22 However, we may be forced to

move to more factor based strategies

http://www.norges-bank.no/english/petroleum_fund/articles/2004/highest_excess_return/

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The Principles behind Our Active Management

• Very high respect for the market. Applying financial
• theory. Humility and discipline
• Active management only where there may be

some less market efficiency and where we find/develop managers with unique expertise

• Specialization. More than 100 sub-portfolios
• Extensive delegation. No committee structure
• Incentives linked to performance

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"Financial Market Theory for Cautious Investors"*

"The possibility of achieving an above average return lies in being able to identify cases of incomplete market equilibrium. To be able to detect what is abnormal, it is necessary to know what is normal."* * Jan Mossin, Markedseffisiens (Market efficiency), TANO, 1986

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Textbook Approach to Active Portfolio Management

• Active management is a process. Active

management begins with raw information, refines into forecasts, and then optimally and efficiently constructs portfolios balancing those forecasts of return against risk

• Active management is forecasting, and a key to

active management performance is superior information

• Active managers should forecast as often as possible

(the fundamental law)

• Mathematics cannot overcome ignorance/lack of

information

R.C. Grinold & R.N. Kahn, Active Portfolio Management, 1994, 1999

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”The Fundamental Law of Active Management”

• Information Ratio = Return / Risk

Information Coefficient (IC) = corr[α, θ] α = expected (ex ante) return θ = actual (ex post) return corr[α, θ] = correlation between α and θ BReadth (BR) = number of independent positions

• The Challenge: Improve IC (hit ratio)
• and/or increase breadth by taking many independent

positions and trade often

BR IC IR ⋅ =

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Neccessary Conditions for Creating Alpa

• Talented people
• Motivated and challenged in a

rational, efficient and supportive structure

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Rational and Supportive Structure

• Clear investment philosophy
• Various investment strategies
• Specialization
• Large number of independent positions
• Good access to information
• Alpha separated from Beta
• Low costs in trading and transitions

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Specialization and Independence

• Specialization, focus

Very clearly defined mandates. Specialist expertise to provide the competitive edge needed in a near efficient market

• Independence, low correlation

Different types of investment strategies in various units; a large number of individual investments. No committee decisions; no predefined processes

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0 % 1 % 1 % 1 % 1 % 0 % 1 % 1 % 2 % 3 % 1 % 2 % 2 % 0 % 0 % 1 % 1 % 1 % 1 % 3 % 2 % 1 % 1 % 1 % 2 % 1 % 1 % 1 % 1 % 0 % 1 % 1 % 2 % 1 % 1 % 2 % 1 % 0 % 0 % 1 % 1 % 1 % 0 % 1 % 1 % 1 % 1 % 0 % 1 % 1 % 1 % 1 % 1 % 1 % 0 % 0 % 0 % 1 % 0 % 1 % 2 % 1 % 1 % 0 % 1 % 0 % 1 % 2 % 2 % 2 % 2 % 0 % 1 % 0 % 1 % 1 % 1 % 2 % 0 % 2 % 0 % 0 % 1 % 0 % 2 % 1 % 1 % 0 % 2 % 1 % 2 % 1 % 0 % 1 % 1 % 2 % 1 % 1 % 1 % 2 %

21 % 14 % 43 % 22 % Oslo cre Oslo gov NY cre NY gov

Example: Risk Allocation Fixed Income

18 % 49 % 1 % 0 % 12 % 14 % 6 %

• Ext. mgrs

RV GV QP EI Cred AO

F.I. RV Pos.

Correlation matrics, profit units

Average 0.02

EI cred b cred a rv gv qp ao ext a EI 1 cred b

• 0.754115

1 cred a 0.152501 -0.208785 1 rv 0.723803 -0.822739 0.296542 1 gv 0.180472 0.44208 0.209786 0.2730606 1 qp 0.457215 -0.328319 0.136915 0.0839749 0.092456 1 ao 0.387236 -0.560345 0.674421 0.6618643 0.036886 -0.063968 1 ext a

• 0.271266
• 0.38964

0.323637 -0.0025061 -0.612593 -0.359838 0.125951 1

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Talented People

• NBIM learning from external and internal

management: Alpha creation is mostly about the property of the people. Only special talents create alpha.

• The key issues is then: How to recruit, develop,

motivate and retain talents

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Empowerment and Ownership

• Individual investment mandates and considerable freedom to

develop own investment style, methodology and tools

• Individual incentive structure
• clearly defined and measured
• ‘managing own money’
• Ownership in all other processes
• operations included in the business units
• division of responsibilities, defined work task
• Independence in team structure
• optimal size for flexibility and communication
• accountability and visibility without ‘atomization’
• blending competition and support
• avoiding ‘group think’

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Performance

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Average Annual Net Real Return Since 31/12 1996

• Average annual net

real return (adjusted for management costs and inflation) is 4.58 %

• Annual real return on

the benchmark is 4.12 %

0.0 % 1.0 % 2.0 % 3.0 % 4.0 % 5.0 % 6.0 % 7.0 % 8.0 % 9.0 % 10.0 % 1999 2000 2001 2002 2003 2004 2005 2006

Net Real Return on Actual Portfolio Net Real Return on Benchmark

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Excess Return Last Three Years

• 0.2 %
• 0.1 %

0.0 % 0.1 % 0.2 % 0.3 % 0.4 % 0.5 % 0.6 % 0.7 % 0.8 % J a n

• 4

M a r

• 4

M a y

• 4

J u l

• 4

S e p

• 4

N

• v
• 4

J a n

• 5

M a r

• 5

M a y

• 5

J u l

• 5

S e p

• 5

N

• v
• 5

J a n

• 6

M a r

• 6

M a y

• 6

J u l

• 6

S e p

• 6

N

• v
• 6
• 0.2 %
• 0.1 %

0.0 % 0.1 % 0.2 % 0.3 % 0.4 % 0.5 % 0.6 % 0.7 % 0.8 % Monthly excess return Three years rolling excess return

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Annualised Contributions to Gross Excess

• Return. 2004-2006. Percentage Points

External management Internal management Total Excess return in each asset class Equity management 0.18 0.20 0.38 0.95 Fixed income management 0.04 0.16 0.20 0.32 Total 0.22 0.36 0.58

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Information Ratios 2004 – 2006

The IR is a measure of risk-adjusted return and is an indicator of skills in investment management. It is calculated as the ratio of excess return to the actual relative market risk to which the portfolio has been exposed. The IR indicates how much excess return is achieved for each unit of risk.

External management Internal management Total Equity management 0.48 1.44 1.08 Fixed income management 1.69 2.58 2.77 Total 0.61 2.55 1.60

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Quarterly Excess Return Since 1998

Average annual excess return since 1998: 0.48 percentage points Cumulative excess return NOK 28,9 bill. Information ratio 1.22

• 0.4 %
• 0.2 %

0.0 % 0.2 % 0.4 % 0.6 % 0.8 % 1.0 % Q 1 9 8 Q 3 9 8 Q 1 9 9 Q 3 9 9 Q 1 Q 3 Q 1 1 Q 3 1 Q 1 2 Q 3 2 Q 1 3 Q 3 3 Q 1 4 Q 3 4 Q 1 5 Q 3 5 Q 1 6 Q 3 6

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Excess Return and Contribution to Total Risk From Active Management

Excess return and return on the benchmark portfolio

Benchmark Excess return

Risk contribution due to active management

Risk due to active management Benchmark risk

• Active management has increased the return with no

increased risk

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NBIM Critical Success Factors

• Time is spent on professional challenges – not marketing
• Empowerment of individuals (mandates and resources)
• Delegated power matters more than placement in org

charts

• No committee governance with unclear responsibilities
• Meritocracy – rewards and positions are based on

performance

• Ability to change leadership and structure when

performance or new challenges requires it

• Incentive level and structure is competitive and fosters the

targeted risk-taking and behavior

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Discussion

The Advantage of Size Capacity Constraints

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The Advantage of Size

• Economies of scale in beta management and

transition Easy to scale from a system and -competence base with fixed costs. Can afford large investments in systems Low commissions. Our flow has value Low trading costs gives more opportunity for applying quant strategies

• Size and organizational skills gives power to demand

and build new products with service providers, like: Custodians, prime brokers, prime custody, back-

• ffice
• Size advantage in securities lending
• 24/7 systems and organization

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The Advantage of Size (2)

• Access to company information; scale advantage in

some research, easier access to the global talent pool

• Some lower fees in external management
• Top credit rating; balance sheet advantages
• Some studies indicates a positive relation between

alpha and size (next two slides)

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Large funds did better than small funds.

Net Value Added versus Size (log10) 1991-2005 All Funds Log (Size) Coefficient 0.28% "t" statistic 4.3

"T" statistic values in excess of the absolute values of 2.0, 1.6 and 1.3 are significant at the 95%, 90% and 80% confidence levels, respectively.

Net Value Added vs. % Private Equity, % US Small Cap Stock, Total Cost (bps) and Size (log10) 1991-2005 All Funds Coefficient

"t" statistic

Private Equity 4.933% 2.8 US Small Cap Stock 2.700% 3.1 Total Cost

• 0.004%
• 1.4

Log (Size) 0.155% 1.9

• On average, the Net Value Added was

higher by 28 bps for a $1 billion fund compared with a $100 million fund.

• Size predicted Net Value Added since

larger funds have lower costs and have higher weightings in specialised, high performing asset classes. The belief is supported by the fact that the size factor was reduced significantly when the following factors were added: Total Cost, US Small Cap Stock, and Private Equity.

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Big is Better?

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Capacity Constraints

• Market impact. (Trading costs may eat to much of the

alpha return. But as explained, we try to build trading into an advantage)

• May have constraints in external active management
• Lack of scalability in some of the internal alpha strategies.

May be difficult to keep the return targets?

• May a fat and complacent organization follow with

increased size?

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Discussion

• Yes, it is possible to become to big, but we are still not

there

• When there is one owner of the assets; by splitting in

different portfolios, there is a risk for ending up with costly index management (overlap that average out active positions)

• Better way of splitting up: Keep the beta and transition

machines, set up different & focused alpha satellites

• Avoiding being fat & complacent: Line structure with real

delegation, results having effect on compensation and position for everybody, outsourcing of all activities that are not in the core business, individual measurement