Can fund managers
asset allocate?
Andrew Clare,
Dirk Nitzsche
&
Meadhbh Sherman
Centre for Asset Management Research,
Cass Business School, London.
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Overview
• What we are assessing are TAA skills
• Previous, related work
• Data & methodologies
• Sub-set of results
• Summary
• All the results are preliminary; final version of paper should be available
in September; also in process of updating the results
Copyright: Andrew Clare, 2012
Page 1
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Some previous work in this area
• Sharpe (1988, 1992) asserted that:
• a fund’s asset allocation decisions account for almost all of its fund’s
performance
• Brinson, Hood and Beebower (1986) examine the performance of 91 US
pension funds using data from 1974 to 1983 they found that:
• the policy mix explained 93.6 percent of the average fund’s return variation
over time (as measured by the R2)
• Brinson, Singer and Beebower (1991) quarterly returns data on 82 US
pension funds spanning the period 1977 to 1987
• active investment decisions did little to improve portfolio performance
because any abnormal performance was insignificant
Copyright: Andrew Clare, 2012
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Some previous work in this area
• Using UK pension fund data, Blake, Lehmann & Timmerman (1999)
• the majority of return is derived from the strategic asset allocation decision
• Using data on large Canadian and US pension funds Andonov et al
(2011) find:
• that changes in asset allocation, market timing and security selection
generate positive abnormal returns of 17, 27 and 45 basis points per year
respectively
• Using a small sample of US managers Weigel (1991) finds that
• the vast majority (over 75%) of managers exhibit positive, significant market
timing ability
• managers that are good at market timing are paying for this skill in the form
of negative returns to non-market-timing strategies
Copyright: Andrew Clare, 2012
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Data
• We collected monthly, net of fee returns data on multi-asset class retail
funds managed in Canada, the UK and the USA
• Data sample is January 2000 to December 2010 – 714 funds
• We also collected data on monthly proportions of multi asset class funds
invested in: Cash, Govt bonds, Corporate bonds & Equities
• Data sample is January 2006 to December 2010 – 355 funds
• We use the two data sets as the basis for two approaches to the problem
Copyright: Andrew Clare, 2012
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The multi-asset class funds
All categories
Conservative
Allocation
Moderate Allocation
Aggressive
Allocation
Equity
50.17
30.98
58.57
68.08
Bond
34.99
48.61
29.88
17.23
Cash
9.54
12.35
7.74
6.04
Other
3.78
6.33
2.51
4.67
No. of funds
349
116
196
37
All categories
Cautious Managed
Balanced Managed
Active Managed
Equity
63.76
45.24
68.74
80.97
Bond
17.17
33.20
12.99
2.31
Cash
10.15
12.78
9.80
7.23
Other
8.58
8.34
8.25
9.26
No. of funds
134
48
49
37
All categories
48.48
36.97
10.53
1.26
231
Fixed Income
Balanced
26.01
50.76
14.62
1.66
73
US
UK
Canada
Equity
Bond
Cash
Other
No. of funds
Copyright: Andrew Clare, 2012
Neutral Balanced
53.26
34.23
10.06
1.06
95
Equity Balanced
64.1
23.67
7.08
1.05
58
Tactical
Balanced
64.05
26.45
8.53
0.73
5
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Methodology
• We apply variants of two methodologies to determine whether fund
managers can ‘time’ their asset allocation decisions
• We effectively test for tactical rather than strategic timing abilities
• Methodology 1:
• This is based on the “conditional beta” approach which imputes timing
ability using fund returns (Ferson and Schadt (1996)):
• We use several variants of this approach on the longer data set
Copyright: Andrew Clare, 2012
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Methodology 1
• If θ2 is positive it implies successful timing of equity market
• If θ3 is positive it implies successful timing of corp bond market
• If θ4 is positive it implies successful timing of govt bond market
• If θ5 is positive it implies successful timing of cash
Copyright: Andrew Clare, 2012
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Results – US and UK
Timing coefficients
1
2
3
4
US All
US- Conservative Allocation
US- Moderate Allocation
US- Aggressive Allocation
% Neg
%
Sig
Pos
% Sig
Neg
% Pos
% Neg
%
Sig
Pos
% Sig
Neg
% Pos
% Neg
%
Sig
Pos
% Sig
Neg
% Pos
3
Timing
Coeff
Equity
1.43
6.30
25.50
74.50
0.00
13.51
18.92
81.08
0.86
6.90
18.10
81.90
2.04
4.59
31.12
68.88
4
Corp
4.58
0.86
78.51
21.49
13.51
2.70
75.68
24.32
1.72
0.00
81.90
18.10
4.59
1.02
77.04
22.96
5
Govt
0.86
10.60
24.07
75.93
2.70
10.81
35.14
64.86
0.00
7.76
22.41
77.59
1.02
12.24
22.96
77.04
6
Cash
7.74
47.85
21.49
78.51
8.11
37.84
24.32
75.68
7.76
51.72
18.10
81.90
7.65
47.45
22.96
77.04
% Sig
Pos
% Sig
Neg
% Pos
UK-All
UK- Cautious Managed
UK- Balanced Managed
% Neg
UK- Active Managed
% Sig
Pos
% Sig
Neg
% Pos
% Neg
% Sig
Pos
% Sig
Neg
% Pos
% Neg
% Sig
Pos
% Sig
Neg
% Pos
% Neg
% Sig
Pos
% Sig
Neg
% Pos
% Neg
0
7.46
13.43
86.57
0.00
12.50
16.67
83.33
0.00
4.08
8.16
91.84
0.00
5.41
16.22
83.78
9
Equity
10
Corp
5.22
1.49
55.97
44.03
4.17
0.00
58.33
41.67
6.12
2.04
53.06
46.94
5.41
2.70
56.76
43.24
11
Govt
0
14.18
11.19
88.81
0.00
14.58
27.08
72.92
0.00
18.37
0.00
100.00
0.00
8.11
5.41
94.59
12
Cash
1.49
13.43
32.09
67.91
0.00
29.17
2.08
97.92
2.04
8.16
44.90
55.10
2.70
0.00
54.05
45.95
•
Corporate bond timing more prevalent than equity market timing
•
UK Cautious Managed, can’t seem to time cash!
Copyright: Andrew Clare, 2012
Page 8
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Results – Canada
Timing coefficients
Canada-All
%
Sig
Pos
%
Sig
Neg
%
Pos
Canada- Fixed Income
Balanced
%
Neg
%
Sig
Pos
%
Sig
Neg
%
Pos
Canada- Equity
Balanced
Canada- Neutral
Balanced
%
Neg
%
Sig
Pos
%
Sig
Neg
%
Pos
%
Neg
%
Sig
Pos
%
Sig
Neg
%
Pos
Canada- Tactical
Balanced
%
Neg
%
Sig
Pos
%
Sig
Neg
%
Pos
%
Neg
15
Equity
0.43
12.12
26.41
73.59
1.37
21.92
8.22
91.78
0.00
10.53
30.53
69.47
0.00
3.45
43.10
56.90
0.00
0.00
20.00
80.00
16
Cor Bond
3.46
3.46
43.29
56.71
0.00
6.85
16.44
83.56
5.26
1.05
52.63
47.37
5.17
3.45
60.34
39.66
0.00
0.00
60.00
40.00
17
Gov Bond
2.6
0.87
55.84
44.16
2.74
1.37
75.34
24.66
2.11
1.05
49.47
50.53
3.45
0.00
43.10
56.90
0.00
0.00
40.00
60.00
18
Cash
4.33
9.96
42.86
57.14
1.37
6.85
34.25
65.75
6.32
9.47
48.42
51.58
5.17
15.52
44.83
55.17
0.00
0.00
40.00
60.00
•
Bond timing more prevalent than equity market timing for Canadian funds
•
However, overall proportion that are found to have significant timing ability in all three
markets is very low.
Copyright: Andrew Clare, 2012
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Results – summary
US (%)
UK (%)
CAN (%)
% with All 4 classes Pos
0.29
0.00
1.30
% with 3 out of 4 Pos
7.45
4.48
9.96
% with 2 out of 4 Pos
35.24
23.13
46.75
% with 1 out of 4 Pos
55.59
52.99
38.96
% with none Pos
1.43
19.40
2.16
% with All 4 classes Sig + Pos
0.00
0.00
0.00
% with 3 out of 4 Sig + Pos
0.00
0.00
0.00
% with 2 out of 4 Sig + Pos
0.57
0.00
0.87
% with 1 out of 4 Sig + Pos
13.47
6.72
9.09
% with none Sig + Pos
85.96
93.28
89.18
• Arguably Canadian managers are the better tactical asset allocators
Copyright: Andrew Clare, 2012
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Methodology 2
%ACj,t = α + βjRj,t+1) + εj,t
• This approach is much simpler and much more direct, than the returnsbased approach
• It asks whether weightings rise/fall in proportion to market returns
• A positive value for β indicates that it does
• Again, we use a number of variants of this approach
Copyright: Andrew Clare, 2012
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Timing the equity market
80.0
71.15
70.0
60.28
Proportion of fund managers
60.0
57.34
50.0
40.0
37.50
30.0
21.79
20.0
12.96
10.0
6.29
5.36
0.0
ALL
Copyright: Andrew Clare, 2012
US
UK
CAN
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Timing credit
60.0
49.36
Proportion of fund managers
50.0
40.0
36.06
28.57
30.0
24.48
20.0
10.0
5.36
4.51
7.05
1.4
0.0
ALL
Copyright: Andrew Clare, 2012
US
UK
CAN
Page 13
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Timing the govt bond market
70.0
66.43
60.0
Proportion of fund managers
52.68
50.0
46.43
42.31
40.0
30.0
20.0
16.07
10.0
5.63
6.29
1.28
0.0
ALL
Copyright: Andrew Clare, 2012
US
UK
CAN
Page 14
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Timing cash
70.0
61.54
60.0
55.94
Proportion of fund managers
55.49
50.0
40.0
37.50
34.62
34.27
30.0
29.58
20.0
10.0
3.57
0.0
ALL
Copyright: Andrew Clare, 2012
US
UK
CAN
Page 15
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DGF … the new balanced
• Most of the research says that strategic asset allocation gives the
biggest bang for one’s buck
• In this work we are really looking at TAA
• There have been a huge number of DGFs launched recently; there is
SAA embedded in these funds
• Some DGFs emphasise the TAA overlay as an added source of return
Copyright: Andrew Clare, 2012
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Summary
• These are just a small set of the preliminary results
• But the basic finding is that:
• Using returns-based data there is little evidence of TAA ability amongst
these managers
• Using asset class weights, there is much more evidence of TAA ability
• However, in both cases it is still very difficult to distinguish this skill from
luck
• But as we know, sometimes it’s better to be lucky than good!
Copyright: Andrew Clare, 2012
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