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
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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
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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
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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.
•
Act = ret − bmk
t
t
t
• We also analyze residual returns, ResRet, which are defined as:
resrett = rett − βbmkt
•
• where the fund beta, is estimated by a regression of the fund return on a constant and its benchmark. Overall Fund Cumulated Active Returns
5
4
3
2
1
0
-1
1998
2000
2002
2004
2006
2008
2010
Cumulated Fixed Income Active Returns
3
2
1
0
-1
-2
-3
-4
-5
-6
-7
1998
2000
2002
2004
2006
2008
2010
Cumulated Equity Active Returns
8
7
6
5
4
Panel B
3
2
1
0
-1
1998
2000
2002
2004
2006
2008
2010
Average Returns to Active Management
Total Fund
Monthly avg. ret.
P‐value
Full Sample
Fixed Income
Pre‐2008
Full Sample
.02%
.03%
.56
.01
Equity
Pre‐2008
Full Sample
Pre‐2008
.00%
.01%
.05%
.06%
.98
.45
.08
.02
Variance Attribution of Fund Returns
Total Fund
Full Sample
Benchmar
k Return
Pre‐2008
Fixed Income
Full Sample
Pre‐2008
Equity
Full Sample
Pre‐2008
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%
Fixed Income External Active Mean Returns and SEs
4
2
0
-2
-4
-6
-8
0
5
10
15
20
25
30
35
40
45
50
Equity External Active Mean Returns and SEs
8
6
4
2
Panel B
0
-2
-4
-6
0
50
100
150
External Active Returns
Active Returns
Mean
Residual Returns
Skew
Alpha
Skew
Fixed Income External Returns (wrt Mandate Benchmark)
Mean
Median
Cross sectional std
‐0.45
‐0.06
‐0.89
‐0.67
‐0.53
‐0.07
01.12
‐1.19
0.94
1.42
1.03
1.49
Equity External Returns (wrt Mandate Benchmark)
Mean
Median
0.09
0.05
0.00
0.01
0.05
0.05
0.03
0.02
0.73
0.69
0.67
0.70
Cross sectional std
Fees and Expenses
Fixed Income
Equity
Expense Ratios Across Funds Annual
Mean (EW)
Median
CS STD
0.87%
0.04%
5.08%
0.76%
0.14%
5.04%
0.17%
0.01%
0.64%
0.29%
0.01%
0.77%
Performance Fee Ratios Across Funds
Mean (EW)
Median
CS STD
Fees Aggregated Across All External Funds (VW)
Mean Exp Mean Perf
0.06%
0.07%
0.17%
0.17%
What Explains Active Returns?
• Similar strategies/timing
• Style analysis
• Common factors
Factors
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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
80
TERM
60
CREDITAa
CREDITBaa
CREDITHY
40
FXCARRY
20
0
-20
-40
Panel B
-60
-80
1998
2000
2002
2004
2006
2008
2010
Liquidity On-the-Run/Off-the-Run
70
Panel B
60
50
40
30
20
10
0
1998
2000
2002
2004
2006
2008
2010
Equity Factors
140
VALGRTH
120
SMLG
MOM
100
VOL
80
60
40
20
0
-20
-40
1998
2000
2002
2004
2006
2008
2010
Partial Correlations
Fixed Income
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
Equity
Partial
Corr
P‐value
VALGRTH
‐0.56
0.00
SMLG
0.41
0.00
MOM
0.02
0.80
VOL
0.28
0.00
Overall Fund Active Returns
1
0.5
0
-0.5
-1
-1.5
Fitted Whole Sample R
R2
= 0.65
Fitted pre-2008 R
R2
= 0.47
Actual
-2
1998
2000
2002
2004
2006
2008
2010
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
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Candidate Factors
Term risk
Credit risk
Equity risk premium
Value‐growth risk
Small‐large risk
Momentum risk
Volatility risk
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All these factor portfolios could eventually be created and maintained by NBIM
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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
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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
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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
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