Active Management of the Norwegian Government Pension Fund Global - - PowerPoint PPT Presentation

Active Management of the Norwegian Government Pension Fund – Global

Andrew Ang Ann F. Kaplan Professor of Business, Columbia Business School William N. Goetzmann Edwin J. Beinecke Professor of Finance and Management Studies, Yale School of Management Stephen M. Schaefer Professor of Finance, London Business School

Background to Study

• Crisis
• Question
• Approach
• Result

Norwegian Pension Fund ‐Global

The fund's quarterly return and accumulated annualized return 1/1/1998 – 3/1/2010.

Excess Return

Guidelines

• Allocation (60/40) is law
• Tracking error
• Benchmarks
• Social responsibility

Our Mandate

• Efficient market evidence
• Performance
• Recommendation

Efficient Markets

• Modern EMH recognizes real‐world frictions

– information, transactions costs, financing costs

• Tests show there are multiple factors driving returns

– Factors not completely understood – market portfolio is inefficient

• Violations occasionally found

– difficult to capture in scale – Particularly via delegated management structures – Never sure if you profit from risk or skill

• Little good empirical evidence on alternatives

– Hedge funds, VC etc.

Performance Analysis

• Has active management added value?
• Was active management important in crisis?
• What explains active component of returns?
• How did external managers perform?

Performance

• We define an active return of a fund to be the return relative

to the fund benchmark.

• We also analyze residual returns, ResRet, which are defined

as:

• where the fund beta, is estimated by a regression of the fund

return on a constant and its benchmark.

t t t

bmk ret Act − =

t t t

bmk ret resret β − =

Overall Fund Cumulated Active Returns

1998 2000 2002 2004 2006 2008 2010

• 1

1 2 3 4 5

1998 2000 2002 2004 2006 2008 2010

• 7
• 6
• 5
• 4
• 3
• 2
• 1

1 2 3

Cumulated Fixed Income Active Returns

Panel B 1998 2000 2002 2004 2006 2008 2010

• 1

1 2 3 4 5 6 7 8

Cumulated Equity Active Returns

Average Returns to Active Management

Total Fund Fixed Income Equity Full Sample Pre‐2008 Full Sample Pre‐2008 Full Sample Pre‐2008 Monthly

• avg. ret.

.02% .03% .00% .01% .05% .06%

P‐value

.56 .01 .98 .45 .08 .02

Variance Attribution of Fund Returns

Total Fund Fixed Income Equity Full Sample Pre‐2008 Full Sample Pre‐2008 Full Sample Pre‐2008 Benchmar k Return

99.1% 99.7% 97.1% 99.8% 99.7% 99.7%

Active Return

.09% .03% 2.9% .02% .03% .3%

Total Return

100% 100% 100% 100% 100% 100%

5 10 15 20 25 30 35 40 45 50

• 8
• 6
• 4
• 2

2 4

Fixed Income External Active Mean Returns and SEs

Panel B 50 100 150

• 6
• 4
• 2

2 4 6 8

Equity External Active Mean Returns and SEs

Active Returns Residual Returns Mean Skew Alpha Skew Fixed Income External Returns (wrt Mandate Benchmark) Mean

‐0.45 ‐0.89 ‐0.53 01.12

Median

‐0.06 ‐0.67 ‐0.07 ‐1.19

Cross sectional std

0.94 1.42 1.03 1.49

Equity External Returns (wrt Mandate Benchmark) Mean

0.09 0.00 0.05 0.03

Median

0.05 0.01 0.05 0.02

Cross sectional std

0.73 0.69 0.67 0.70

External Active Returns

Fixed Income Equity

Expense Ratios Across Funds Annual

Mean (EW) 0.87% 0.76% Median 0.04% 0.14% CS STD 5.08% 5.04%

Performance Fee Ratios Across Funds

Mean (EW) 0.17% 0.29% Median 0.01% 0.01% CS STD 0.64% 0.77%

Fees Aggregated Across All External Funds (VW)

Mean Exp 0.06% 0.17% Mean Perf 0.07% 0.17%

Fees and Expenses

What Explains Active Returns?

• Similar strategies/timing
• Style analysis
• Common factors

Factors

• TERM: Difference between long‐ and short‐maturity U.S. Treasury bond returns.
• CREDITAa: Difference between Aa and Treasury bond returns.
• CREDITBaa: Difference between Baa and Aa bond returns.
• CREDITHY: Difference between high yield and Baa bond returns
• FXCARRY: Captures the carry trade of investing in currencies with high interest

rates and shorting currencies with low interest rates.

• LIQUIDITY: Reflects periods of high and low liquidity. [on‐run off‐run 10 yr USG]
• VALGRTH: Difference in returns between “value” stocks and “growth” stocks.
• SMLG: Difference in returns between small and large stocks.
• MOM: Captures the momentum effect of going long U.S. stocks with past high

returns and short socks with past low returns.

• VOL: Captures differences between implied and realized volatility. Selling (delta‐

hedged) out‐of‐the money put options or covered calls.

We thank Kenneth French, Sergi Gorovyy, Antti Ilmanen, and Min Wei for providing data.

Fixed Income Factors

Panel B

1998 2000 2002 2004 2006 2008 2010

• 80
• 60
• 40
• 20

20 40 60 80 TERM CREDITAa CREDITBaa CREDITHY FXCARRY

Panel B 1998 2000 2002 2004 2006 2008 2010 10 20 30 40 50 60 70

Liquidity On-the-Run/Off-the-Run

Equity Factors

1998 2000 2002 2004 2006 2008 2010

• 40
• 20

20 40 60 80 100 120 140 VALGRTH SMLG MOM VOL

Partial Correlations

Fixed Income Equity Partial Corr P‐value Partial Corr P‐value TERM ‐0.21 0.01 CREDITAa 0.35 0.00 CREDITBaa ‐0.33 0.00 CREDITHY ‐0.01 0.92 FXCARRY ‐0.04 0.64 LIQUIDTY 0.35 0.00 VALGRTH ‐0.56 0.00 SMLG 0.41 0.00 MOM 0.02 0.80 VOL 0.28 0.00

Overall Fund Active Returns

1998 2000 2002 2004 2006 2008 2010

• 2
• 1.5
• 1
• 0.5

0.5 1 Fitted Whole Sample R

R2

= 0.65 Fitted pre-2008 R = 0.47 Actual

R2

Active Returns

• Are a small percentage of actual return

variance

– Function of controls on tracking error

• Active management mostly explained by

factor exposures

– Even when pre 2008 model is used – “Up to” factor estimation gives same results

• Paying alpha prices for factor returns?

– Cost of management is low

Factors as First Order

• The Fund has had large exposure to systematic risks

– We believe this exposure is entirely appropriate – These factors earn risk premiums over the long run

• Active management added only marginally to the performance of

the fund. – Did not detract from returns – May be beneficial for other aims

• We recommended the Fund move to a more top‐down,

intentional approach to choosing factor exposure – Factor exposure drives performance, active management does not – Factor exposure consistent with current asset allocation policy

Recommendation: Factor‐Based Investing

• Base investment philosophy on compensation for

taking systematic risk.

– Alpha is difficult to capture in large scale – Alpha risk is often factor risk in disguise – Factor risk premiums are long‐horizon investments

• Express through exposure to factor risk

– Fund already capturing premiums to multiple factor exposures – Factor exposures should be in the Fund’s benchmark – Measure and build your own factors; avoid availability bias – Use the factors to evaluate alternative asset classes

29

Candidate Factors

• Term risk
• Credit risk
• Equity risk premium
• Value‐growth risk
• Small‐large risk
• Momentum risk
• Volatility risk

All these factor portfolios could eventually be created and maintained by NBIM

30

Factor Allocation

• Placing factors into the benchmark consists of three

steps:

– Risk‐return analysis on each factor – Determining how much factor exposure to bear – Combining the factor exposures with the capstone market portfolio to yield an overall benchmark portfolio

• Set long‐run targets, like the 60%‐40% equity‐bond

target

– Important to rebalance factor exposures just as currently done for asset exposures – Automatic rebalancing essential to avoid arbitrary and time‐inconsistent actions

31

Recommendation: Expectations Management

• Categorize assets by horizon

– Cash – Short‐term (Fixed Income) – Long‐term (Equity Risk Premium, Real Estate)

• Horizon buckets set appropriate expectations

– Appropriate performance review – Appropriate future liquidity planning

32

Benefits

• Better understanding of risk‐return trade‐offs
• Weighing the addition of new factors or asset

classes to the portfolio

• Allowing the investor to determine which

factors should have large or small exposure

• Better benchmarking for active management
• More robust portfolios

33

Overall Summary

• Summary of empirical studies of active management

and the Efficient Market Hypothesis [EMH]

– There is no compelling evidence to recommend “pure” indexing but finding managers with excess risk‐adjusted returns is difficult

• Evaluation of NBIM’s historical track record

– The active risk of the Fund is overall small, has a positive mean, and has large exposure to systematic factors

• Recommendation of how the Fund’s advantages can

be exploited

– Allow the asset owner to decide how much factor risk is appropriate by bringing factors into the Fund’s benchmark and creating horizon categories for assets

34