For internal use only Private Wealth Management Deutsche Bank Asset Allocation Why Dynamic Asset Allocation is winning the race? Arnaud de Servigny
Asset Allocation
Feb 24, 2016
Asset Allocation. Why Dynamic Asset Allocation is winning the race? Arnaud de Servigny. A review of the current Asset Allocation paradigm . Modern Portfolio Theory R.I.P.!. - PowerPoint PPT Presentation
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For internal use only
Private Wealth ManagementDeutsche Bank
For internal use only
Asset AllocationWhy Dynamic Asset Allocation is winning the race?
Arnaud de Servigny
For internal use only
Private Wealth ManagementDeutsche Bank
A review of the current Asset Allocation paradigm.
Modern Portfolio Theory R.I.P.!
For internal use only
Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
On The Efficient Frontier, there is a high degree of certainty and therefore a high degree of concentration!
3
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
The efficient frontier usually relies on a limited number of support assets
4
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
There is very little year on year stability of the Efficient Frontier
5
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Out-of-sample, the efficient frontier usually drifts to much more modest & sub-optimal performance
6
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Over the past 20 years there has been a trend of growing out-of-sample under performance of the MPT
7
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
The Market portfolio (CAPM) & the MPT portfolios are equally not doing well
8
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Why doesn’t it work? There is no variance stability of main asset classes!
1 The critical values for the 90%, 95% and 99% level tests are respectively below 1.22, 1.36 and 1.63, for an rejection (21”0 of no break.
9
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
A test to see if we face a fat tail problem or a regime switching problem?
10
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
« Through the cycle » correlation and covariance do not exist!
11
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Private Wealth ManagementDeutsche Bank
Let us try to look at the world differently!
For internal use only
Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Regime Switching models in a nutshell
13
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Out-of-sample performance of a 3 asset Regime Switching model
14
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Time
Regime 1Recession
Regime 2Growth
An “all weather” mean-variance optimisation fails to capture regime changes and therefore fat tails & the dynamics of fat tails
“Through the Cycle “ Average
Fat tailed “through the cycle” distribution
15
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Time
Regime 1Recession
Regime 2Growth
EWMA Estimation of monthly mean / covariance matrix
An Unknown complex multi-regime environment can be approximated by a regularly re-estimated Mean-Variance framework updated with latest information (EWMA estimation)
Monthly mean variance process
Uni
t of ti
me
delta
( t)
Uni
t of ti
me
delta
( t)
Uni
t of ti
me
delta
( t)
Uni
t of ti
me
delta
( t)
Uni
t of ti
me
delta
( t)
Uni
t of ti
me
delta
( t)
16
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012 17
A Case Study
A full out-of-sample Analysis
In one case 4 asset classes (CashTB, IG Bond, HY Bond, US Equity ), in the other 9 (CashTB, Gov Bond, IG Bond, HY Bond, Dev Equity, EM Equity, Commodities, Real Estate, Hedge Funds)
The targeted volatility level in the portfolio is 8%
4 methodologies:Equally weightedMean-Variance reestimated every year based on a 10-year sliding windowMean-Variance reestimated every year using a memory decay estimation method (EWMA)Mean-Variance reestimated every month using a memory decay estimation technique (EWMA)
For internal use only
Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Who better copes with the 8% target vol out-of-sample?
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%
35.0%Risk Control (9 assets)
Mean Variance EWMA yearly Eq Wgt EWMA monthlyVo
latil
ity (T
arge
t vs
Actu
al)
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110.0%
5.0%
10.0%
15.0%
20.0%
25.0%
30.0%Risk Control (4 assets)Mean Variance EWMA yearly Eq Wgt
Vola
tility
(Tar
get v
s Ac
tual
)
18
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
What is the true level of asset diversification in each approach?
2001 2002 2003 2004 2005 2006 2007 2008 2009 20100.9
1.1
1.3
1.5
1.7
1.9
2.1
Diversification (4 assets)Mean VarianceEWMA yearly Eq WgtEWMA monthly
Conc
entra
tion
inde
x
2001 2002 2003 2004 2005 2006 2007 2008 2009 20100.9
1.1
1.3
1.5
1.7
1.9
2.1
Diversification (9 assets) Mean VarianceEWMA yearly Eq WgtEWMA monthly
Conc
entra
tion
inde
x
19
For internal use only
Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
Tail Risk
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
-20%-18%-16%-14%-12%-10%-8%-6%-4%-2%0%
Max Monthly drawdown(9 assets)
Mean Variance EWMA yearly Eq Wgt EWMA monthly
Mon
thly
retu
rn
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
-20%
-15%
-10%
-5%
0%
Max Monthly drawdown (4 assets)
Mean Variance EWMA yearly Eq Wgt EWMA monthly
Mon
thly
Ret
urn
20
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012 21
The Return Dynamics
2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
-40%
-30%
-20%
-10%
0%
10%
20%
30%9 asset portfolio performance
Mean Variance Equal Weight
EWMA yearly (L=0.85) EWMA monthly
Out
of S
ampl
e an
nual
retu
rn
Mean Variance EWMA yearly Eq Wgt EWMA monthly EWMA monthly0.00
0.20
0.40
0.60
0.80
1.00
10yr sharpe (9 assets)
For internal use only
Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
A clearer picture!!!
Mean Variance EWMA yearly Eq Wgt EWMA monthly EWMA monthly0.00
0.20
0.40
0.60
0.80
1.00
1.20
10yr sharpe (4 assets)
Mean Variance EWMA yearly Eq Wgt EWMA monthly EWMA monthly0.000.100.200.300.400.500.600.700.800.901.00
10yr sharpe (9 assets)
22
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Private Wealth ManagementDeutsche Bank Arnaud de Servigny
CFA – 4th July 2012
What is the degree of stability in the portfolios?
Mean Variance EWMA yearly Eq Wgt EWMA monthly0.0%
50.0%
100.0%
150.0%
200.0%
250.0%
300.0%
350.0%
Asset rotation (9 assets)
Aver
age
rota
tion
Mean Variance EWMA yearly Eq Wgt EWMA monthly0.0%
50.0%
100.0%
150.0%
200.0%
250.0%
300.0%
Asset rotation (4 assets)
Aver
age
rota
tion
23
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24Data as of 20.06.2012
Market Prices: Long-term results
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