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Tactical Asset Allocation session 5. Andrei Simonov. Agenda. What is tactical asset allocation? Mean-variance perspective on TAA and SAA Predictability January dummy Business cycle variables Explaining risk premia: US, World, Sweden. Currency risk premia - PowerPoint PPT Presentation
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04/21/23Tactical Asset Allocation1
Tactical Asset Allocation Tactical Asset Allocation sessionsession 5 5
Andrei Simonov
04/21/23Tactical Asset Allocation2
AgendaAgenda
What is tactical asset allocation? Mean-variance perspective on TAA and SAA Predictability
– January dummy
– Business cycle variables
– Explaining risk premia: US, World, Sweden.
– Currency risk premia
– Caveats: data snooping, statistical issues.
04/21/23Tactical Asset Allocation3
What is TAA?What is TAA? Exists since early-to-mid- 80-ies. By now $100-200 bln are under management by TAA
managers A TAA managers’s investment objective is to obtain
better-than-expected return with (possibly) lower-than-benchmark volatility by forecasting the returns of two or more asset classes and varying asset class exposure in systematic manner (Phillips, Rogers & Capaldi, 1996)
Can TAA funds be interpreted as stand-alone asset class?
04/21/23Tactical Asset Allocation4
Conditioning Information and Portfolio Conditioning Information and Portfolio AnalysisAnalysis
Er
Vol
Add conditioninginformation and weightschange through time. Frontier shifts.
04/21/23Tactical Asset Allocation5
Optimal portfolio for risk-averse investorOptimal portfolio for risk-averse investor
1V1
RV11R
V
1V1
1Vw
1V11V1
RV1
1RVw
1w
1VwR
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V1w
1wVwwRw
1
11
portfoliomin var
1
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11
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1
1
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Global
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TTT
NNN
NTT
TTT
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wwHere
E
04/21/23Tactical Asset Allocation6
Equilibrium and TAAEquilibrium and TAALet us assume that there exists long-term
expected returns vector e. However, due to predictability of asset returns, eE(R)
0)(
0)(
)(0
11
11
11
1
11
1
11
portfoliomin var
1
1*
nn
jj
nnTT
tTacticalBe
T
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etStrategicB
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Global
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erEerE
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11
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04/21/23Tactical Asset Allocation7
How to do it?How to do it?
We need a model that explains the connection between today’s variables and tomorrow returns.
Candidates: economic business cycle variables and Jan. Effect.
04/21/23Tactical Asset Allocation8
Example: Incredible January EffectExample: Incredible January Effect
Excess returns associated with small firms w.r.t. Large-cap stocks
Ritter: Tax effect. Is it so?Incredibly Shrinking January Effect
(William J. Bernstein ).
04/21/23Tactical Asset Allocation9
Example: dividend yieldExample: dividend yield
Fama-French (1988). 1927-1986 Holding period
Coeff. t(coeff) R2
M 0.21 1.40 0.00 Q 1.07 2.10 0.01
1 2.47 1.27 0.01 2 7.38 2.04 0.09 3 9.94 2.21 0.13 4 12.86 2.43 0.19
• May not be sustained out of sample
04/21/23Tactical Asset Allocation10
Risk and return over the business cycleRisk and return over the business cycle mtmtmttm RrRE var, ????
G-7 output output level
potential line
end. recess beg. expan end. expan beg. recess Average returns
15.23% 10.36% 6.96% 2.86%
Return volatility
12.59% 10.63% 16.85% 26.98%
US Term Structure 1970-1995US Term Structure 1970-1995
Andrei Simonov - debt and money markets11
04/21/23Andrei Simonov - debt and money markets12
Evaluation of 2001 and 2008 Evaluation of 2001 and 2008 RecessionsRecessions
In July 2000, the Yield Curve inverted forecasting recession to begin in June 2001.
Official NBER Peak is March 2001 (Yield Curve within one quarter accurate).
In March 2001, the Yield Curve returned to normal forecasting the end of the recession in November 2001.
On July 17, 2003 the NBER announced the official end of the recession was November 2001.
In August 2006 , the Yield Curve inverted forecasting recession to begin in July 2007.
Official NBER Peak is December 2007 (Yield Curve within two quarters accurate).
In May 2007, the Yield Curve returned to normal forecasting the end of the recession in January 2008.
On September 20, 2010 the NBER announced the official end of the recession was June 2009.
Recent recessions in retrospectRecent recessions in retrospectBusiness cycle Yield curve
NBER Peak
NBER Trough
Legth of Cycle
Inversion Lead Normal Lead Length of Inversion
Dec-69 Nov 70 11 Oct-68 14 Feb-70 9 16
Nov-73 Mar-75 16 Jun-73 5 Jan-75 2 19
Jan-80 Jul-80 6 Nov-78 14 May-80 2 18
Jul-81 Nov-82 16 Oct-80 9 Oct-81 13 12
Jul-90 Mar-91 8 May-89 14 Feb-90 13 9
Averages 11 11 7 15
Mar-01 Nov-01 8 Jul-00 8 Mar-01 8 8
Dec-07 June-09 18 Aug-06 16 May-07 12 9
Andrei Simonov - debt and money markets13
04/21/23Tactical Asset Allocation14
04/21/23Tactical Asset Allocation15
04/21/23Tactical Asset Allocation16
Date10 Year Treasury Yield
3 Month Treasury Yield (Bond Equivalent Basis) Spread Rec_prob
14-Apr 2.71 0.03 2.68 5.38%
14-May 4.19%
14-Jun 2.52%
14-Jul 1.61%
14-Aug 1.25%
14-Sep 1.07%
14-Oct 1.54%
14-Nov 1.35%
14-Dec 1.01%
15-Jan 1.02%
15-Feb 1.33%
15-Mar 1.31%
15-Apr 1.29%
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
1/4 1/16 1/28 2/9 2/21 3/5 3/17 3/29 4/10 4/22 5/4
June 2011 Meeting OutcomesImplied probability
0.0% - 0.25%
0.50%
0.75%
Producer Price index (Apr); Retail Sales (Apr); Business Inventories (Mar); Bernanke Speech
June 2012 meeting outcome
18
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
3/1 3/8 3/15 3/22 3/29 4/5 4/12 4/19 4/26 5/3 5/10
August 2011 Meeting OutcomesImplied probability
0.0% - 0.25%
0.50%
0.75%
Producer Price index (Apr); Retail Sales (Apr); Business Inventories (Mar); Bernanke Speech
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
4/1 4/6 4/11 4/16 4/21 4/26 5/1 5/6 5/11
September 2011 Meeting OutcomesImplied
probability
0.0% - 0.25%
0.50%
0.75%
Producer Price index (Apr); Retail Sales (Apr); Business Inventories (Mar); Bernanke Speech
Duke Duke survey: survey: Pessimistic /Pessimistic /Optimistic Optimistic CFOsCFOs
04/21/23Tactical Asset Allocation21
04/21/23Tactical Asset Allocation22
Annual Real Economic Growth After Annual Real Economic Growth After Yield Curve InversionsYield Curve Inversions
0.00%0.50%1.00%1.50%2.00%2.50%3.00%3.50%4.00%4.50%
Up to one year afterinversions
Other quarters
04/21/23Tactical Asset Allocation23
Stock Returns and U.S. Yield CurveStock Returns and U.S. Yield Curve
-0.5
0
0.5
1
1.5
2
2.5
3
AU AT BECA DK FR DE
HK IT JP NLNO SG ES SE CH
UK USW
O
Inversion Normal
Average Monthly Returns in %
Data throughNovember 2000
04/21/23Tactical Asset Allocation24
Average Monthly Stock Returns After Average Monthly Stock Returns After Yield Curve InversionsYield Curve Inversions
0.00
0.20
0.40
0.60
0.80
1.00
1.20
1.40
After first month ofinversion
Normal
Equally weighted
Value weighted
Based on 19 countries.
Trader’s calendar Trader’s calendar (from yahoo)(from yahoo)
04/21/23Tactical Asset Allocation25
Last Week Next Week
DateTime (ET)
Statistic For Actual Briefing Forecast Market Expects Prior Revised From
May 27 8:30 AMDurable Orders Apr 0.8% -2.0% -1.3% 3.6% 2.9%
May 27 8:30 AMDurable Goods -ex transportation Apr 0.1% -0.4% -0.2% 2.9% 2.4%
May 27 9:00 AMCase-Shiller 20-city Index Mar 12.4% 12.0% 11.8% 12.9% -
May 27 9:00 AMFHFA Housing Price Index Mar 0.7% NA NA 0.6% -
May 27 10:00 AMConsumer Confidence May 83.0 81.5 82.7 81.7 82.3
May 28 7:00 AMMBA Mortgage Index 05/24 -1.2% NA NA 0.9% -
May 29 8:30 AMInitial Claims 05/24 300K 325K 318K 327K 326K
May 29 8:30 AMContinuing Claims 05/17 2631K 2650K 2650K 2648K 2653K
May 29 8:30 AMGDP - Second Estimate Q1 -1.0% -0.5% -0.5% 0.1% -
May 29 8:30 AMGDP Deflator - Second Estimate Q1 1.3% 1.3% 1.3% 1.3% -
May 29 10:00 AMPending Home Sales Apr 0.4% 1.0% 1.0% 3.4% -
May 29 10:30 AMNatural Gas Inventories 05/24 114 bcf NA NA 106 bcf -
May 29 11:00 AMCrude Inventories 05/24 1.657M NA NA -7.226M -
May 30 8:30 AMPersonal Income Apr - 0.3% 0.3% 0.5% -
May 30 8:30 AMPersonal Spending Apr - 0.1% 0.2% 0.9% -
May 30 8:30 AMPCE Prices - Core Apr - 0.2% 0.2% 0.2% -
May 30 9:45 AMChicago PMI May - 60.0 60.3 63.0 -
May 30 9:55 AMMichigan Sentiment - Final May - 81.0 81.4 81.8 -
04/21/23Tactical Asset Allocation26
What variables matter?What variables matter?
Methodology: 1. Exploratory: regressing
returns at t on informational variables at t-1
2. ”Correct one”: first finding economic risk premia (a la APT) and then regressing it on informational variables at t-1
04/21/23Tactical Asset Allocation27
Do informational variables have Do informational variables have predictive ability?predictive ability? Info variables:
– January dummy
– Past excess return on Equally weighted CRSP index
– Spread between 1 and 3 mo T-bills
– Dividend yield
– Spread between Baa and Aaa corporate bonds
– 1-mo T-bill rate
04/21/23Tactical Asset Allocation28
Here how it looks like...
04/21/23Tactical Asset Allocation29
Performance & Business CyclePerformance & Business Cycle
-30
-20
-10
0
10
20
30
Expansion geometric mean Recession geometric mean
Average Annual Returns During U.S. Business Cycle Phases
Data through June 2002
04/21/23Tactical Asset Allocation30
Performance & Business Cycle (2)Performance & Business Cycle (2)
0
10
20
30
40
50
60
Australi
a
Austria
Belg
ium
Canad
a
Den
mar
k
Finlan
d
France
Ger
man
y
Hong K
ong
Irelan
d It
aly
Japan
Nether
lands
New
Zea
land
Norway
Portugal
Spain
Swed
en
Switzer
land
UK USW
orld
World
ex-U
S
EAFE
Expansion std.dev. Recession std.dev.
Average Annual Volatility During U.S. Business Cycle Phases
Data through June 2002
04/21/23Tactical Asset Allocation31
Performance & Business Cycle (3)Performance & Business Cycle (3)
-0.2
0
0.2
0.4
0.6
0.8
1
Australi
a
Austria
Belg
ium
Canad
a
Den
mar
k
Finlan
d
France
Ger
man
y
Hong K
ong
Irelan
d It
aly
Japan
Nether
lands
New
Zea
land
Norway
Portugal
Spain
Swed
en
Switzer
land
UK USW
orld
World
ex-U
S
EAFE
Expansion correlation with US Recession correlation with US
Correlations During U.S. Business Cycle Phases
Data through June 2002
04/21/23Tactical Asset Allocation32
3. Performance & Business Cycle (4)3. Performance & Business Cycle (4)
0
5
10
15
20
25
30
35
40
45
Australi
a
Austria
Belg
ium
Canad
a
Den
mar
k
Finlan
d
France
Ger
man
y
Hong K
ong
Irelan
d It
aly
Japan
Nether
lands
New
Zea
land
Norway
Portugal
Spain
Swed
en
Switzer
land
UK US
World
World
ex-U
S
EAFE
Expansion covariance with US Recession covariance with US
Covariances During U.S. Business Cycle Phases
Data through June 2002
04/21/23Tactical Asset Allocation33
How important are global factors?How important are global factors? Based on Ferson-Harvey RFS95 Question here is: what is more important, local or global
factors for predictability of asset returns. Global Informational variables: : ”old friends”: 1 mo t-bill, div.
Yield on MSCI World index, spread between 10yr and 3 mo T-bills, Eurodollar/US treasury spread, lagged market return, January dummy.
Local informational variables: Country x div. Yield, 30-day t-bill rate, term spread, lagged MSCI country x market return.
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04/21/23Tactical Asset Allocation34
So, what So, what matters?matters?
”Global only” model is already good enough
Adding local factors increases explanatory power of the model
04/21/23Tactical Asset Allocation35
Changes in Changes in vs changes in risk premium vs changes in risk premium
Only 2-4% of variation is due to beta’s.
)()'(
)()'('
EZEVarE
EZEVarEZEVar
04/21/23Tactical Asset Allocation36
What about currency risk premium?What about currency risk premium?
Currency specificiy: zero-sum gameDumas-Solnik: currency risk premia
exists. It is time-varying and predictable
04/21/23Tactical Asset Allocation37
Caveats:Caveats:
Data snooping– Foster, Smith and Whaley (98): by choosing to
max R2 via choice of instruments one can get significance when there is none.
– Not clear how to use as list of instruments already exists...
In-sample vs. Out-of-sample validation
04/21/23Tactical Asset Allocation38
Caveats(2)Caveats(2)
Statistical biases: autocorrelation, heteroscedastisity (via Monte-Carlo simulations).
Non-normality, excess skewness and kurtosis
04/21/23Tactical Asset Allocation39
How to deal with statistical issues?How to deal with statistical issues?
Bootstrap methodology:– Form empirical distribution of returns – Generate time series of returns (length T).– Perform the regression of interest– See how many times there exists significance
on level .
04/21/23Tactical Asset Allocation40
U.S. Risk PremiumU.S. Risk Premium
Survey BackgroundSurvey Background
Graham/Harvey: Survey CFOs every quarter Q2 2000 through Q4 2008 (52 quarters) Current survey attracts about 500 respondents
Why CFOs? – We know from previous surveys and interviews that the
CFOs use the risk premium for their capital budgeting
– Hence, they have thought hard about risk premium
– Should not be biased the way that analyst forecasts might be
04/21/23Tactical Asset Allocation41
04/21/23Tactical Asset Allocation42
04/21/23Tactical Asset Allocation43
Duke CFO magazine Global Business Outlook survey - U.S. - First Quarter, 201014. On February 12, 2010 the annual yield on 10-yr treasury bonds was 3.7%. Please complete the following:
Mean SD 95% CIMedianMinimumMaximum TotalOver the next 10 years, I expect the average annual S&P500 return will be: There is a 1-in-10 chance it will beless than: 1.30 8.13 0.61 - 1.99 2 -50 75 535Over the next 10 years, I expect the average annual S&P500 return will be: Expected return: 7.62 9.66 6.81 - 8.43 6 -20 100 544Over the next 10 years, I expect the average annual S&P500 return will be: There is a 1-in-10 chance it will begreater than: 11.76 11.43 0.79 - 12.72 10 -10 100 537Over the next year, I expect the average annual S&P 500return will be: There is a 1-in-10 chance it will be lessthan: -3.31 11.64 -4.30 - -2.33 0 -50 75 535Over the next year, I expect the average annual S&P 500return will be: Expected return: 5.62 8.44 4.91 - 6.33 5 -25 100 544Over the next year, I expect the average annual S&P 500return will be: There is a 1-in-10 chance it will begreater than: 11.39 8.81 10.65 - 12.14 10 -10 95 534
04/21/23Tactical Asset Allocation44
U.S. Risk PremiumU.S. Risk Premium
Momentum in Expectations for 1-year Momentum in Expectations for 1-year PremiumPremium
04/21/23Tactical Asset Allocation45
U.S. Risk PremiumU.S. Risk Premium
Extreme Returns Cause DisagreementExtreme Returns Cause DisagreementA. Disagreement over the one-year premium and past returns
y = -0.0614x + 3.9079R2 = 0.1684
y = 0.0194x2 + 0.0247x + 3.3696
R2 = 0.5892
0
1
2
3
4
5
6
-15 -10 -5 0 5 10
Past one-month excess S&P 500 return
Dis
agre
emen
t ove
r th
e on
e-ye
ar p
rem
ium
04/21/23Tactical Asset Allocation46
U.S. Risk PremiumU.S. Risk Premium
Positive Relation Between Disagreement Positive Relation Between Disagreement and Expected 10-year Returnsand Expected 10-year Returns
B. Ten-year premium and disagreement
y = 0.9777x + 1.5936R2 = 0.3165
0
1
2
3
4
5
6
7
8
1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9
Disagreement of ten-year premium forecasts
Mea
n te
n-ye
ar p
rem
ium
04/21/23Tactical Asset Allocation47
Conclusion:Conclusion:
TAA can be an important tool in asset allocation methodology.
It is based on time variation of real economic risk premia.
Selection of predictors is important.We are still in ”top-down” paradigm.Devil is in the details= implementation
matters.