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Can fund managers asset allocate? Andrew Clare, Dirk Nitzsche & Meadhbh Sherman Centre for Asset Management Research, Cass Business School, London.
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 1 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
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 2 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 R 2 ) 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
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 3 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
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 4 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
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 5 The multi-asset class funds USAll categories Conservative AllocationModerate Allocation Aggressive Allocation Equity50.1730.9858.5768.08 Bond34.9948.6129.8817.23 Cash9.5412.357.746.04 Other3.786.332.514.67 No. of funds34911619637 UKAll categoriesCautious ManagedBalanced ManagedActive Managed Equity63.7645.2468.7480.97 Bond17.1733.2012.992.31 Cash10.1512.789.807.23 Other8.588.348.259.26 No. of funds134484937 CanadaAll categories Fixed Income BalancedNeutral BalancedEquity Balanced Tactical Balanced Equity48.4826.0153.2664.164.05 Bond36.9750.7634.2323.6726.45 Cash10.5314.6210.067.088.53 Other1.261.661.061.050.73 No. of funds2317395585
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 6 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
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 7 Methodology 1 If θ 2 is positive it implies successful timing of equity market If θ 3 is positive it implies successful timing of corp bond market If θ 4 is positive it implies successful timing of govt bond market If θ 5 is positive it implies successful timing of cash
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 8 Results – US and UK 1 234 US All US- Conservative AllocationUS- Moderate AllocationUS- Aggressive Allocation Timing Coeff % Sig Pos % Sig Neg% Pos % Neg % Sig Pos % Sig Neg% Pos % Neg % Sig Pos % Sig Neg% Pos % Neg % Sig Pos % Sig Neg% Pos % Neg 3 Equity 1.436.3025.5074.500.0013.5118.9281.080.866.9018.1081.902.044.5931.1268.88 4 Corp 4.580.8678.5121.4913.512.7075.6824.321.720.0081.9018.104.591.0277.0422.96 5 Govt 0.8610.6024.0775.932.7010.8135.1464.860.007.7622.4177.591.0212.2422.9677.04 6 Cash 7.7447.8521.4978.518.1137.8424.3275.687.7651.7218.1081.907.6547.4522.9677.04 UK-All UK- Cautious ManagedUK- Balanced ManagedUK- 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 9 Equity 07.4613.4386.570.0012.5016.6783.330.004.088.1691.840.005.4116.2283.78 10 Corp 5.221.4955.9744.034.170.0058.3341.676.122.0453.0646.945.412.7056.7643.24 11 Govt 014.1811.1988.810.0014.5827.0872.920.0018.370.00100.000.008.115.4194.59 12 Cash 1.4913.4332.0967.910.0029.172.0897.922.048.1644.9055.102.700.0054.0545.95 Timing coefficients Corporate bond timing more prevalent than equity market timing UK Cautious Managed, can’t seem to time cash!
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 9 Results – Canada Canada-All Canada- Fixed Income Balanced Canada- Neutral Balanced Canada- Equity Balanced Canada- Tactical Balanced % Sig Pos % Sig Neg % Pos % Neg % Sig Pos % Sig Neg % Pos % Neg % Sig Pos % Sig Neg % Pos % Neg % Sig Pos % Sig Neg % Pos % Neg % Sig Pos % Sig Neg % Pos % Neg 15Equity 0.4312.1226.4173.591.3721.928.2291.780.0010.5330.5369.470.003.4543.1056.900.00 20.0080.00 16Cor Bond 3.46 43.2956.710.006.8516.4483.565.261.0552.6347.375.173.4560.3439.660.00 60.0040.00 17Gov Bond 2.60.8755.8444.162.741.3775.3424.662.111.0549.4750.533.450.0043.1056.900.00 40.0060.00 18Cash 4.339.9642.8657.141.376.8534.2565.756.329.4748.4251.585.1715.5244.8355.170.00 40.0060.00 Timing coefficients 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.
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 10 Results – summary Arguably Canadian managers are the better tactical asset allocators US (%)UK (%)CAN (%) % with All 4 classes Pos0.290.001.30 % with 3 out of 4 Pos7.454.489.96 % with 2 out of 4 Pos35.2423.1346.75 % with 1 out of 4 Pos55.5952.9938.96 % with none Pos1.4319.402.16 % with All 4 classes Sig + Pos0.00 % with 3 out of 4 Sig + Pos0.00 % with 2 out of 4 Sig + Pos0.570.000.87 % with 1 out of 4 Sig + Pos13.476.729.09 % with none Sig + Pos85.9693.2889.18
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 11 Methodology 2 This approach is much simpler and much more direct, than the returns- based 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 %AC j,t = α + β j R j,t+1 ) + ε j,t
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 12 Timing the equity market
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 13 Timing credit
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 14 Timing the govt bond market
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 15 Timing cash
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 16 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
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Click to edit Master title style Copyright: Andrew Clare, 2012 Page 17 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!
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