Strategic Asset Allocation - COMESA Monetary Institute (CMI)

Central Bank of Egypt
Strategic Asset Allocation
March-14
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Central Bank of Egypt
Index
I.
What is Strategic Asset Allocation?
1. Definition of SAA
2. Process of Setting the Investment Policy
II.
SAA Process
1. Objectives & Investment Horizon
2. Risk Tolerance
3. Identify Eligible Asset Classes
4. Determine Market Assumptions
5. Portfolio Construction
6. Optimal currency composition
III. Validation of SAA
IV. Implementation of SAA
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Central Bank of Egypt
Index
V.
Details on SAA Techniques
1. SAA Approaches
2. Historical Analysis
3. Shortfalls of Historical Analysis
4. From Historical to Forward-Looking Approach
5. The Nelson-Siegel Yield Curve Model
6. SAA Model
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I- What is Strategic Asset
Allocation?
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1. Definition of SAA
“The process by which an institution determines the
appropriate neutral asset allocation at any point in time
to achieve its long-term investment objectives”
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2. Process of Setting the Investment Policy
1. Articulate Objectives and Investment Horizon
2. Specify Risk Tolerance and Constraints
3. Identify Eligible Asset Classes
4. Determine Capital market assumptions (e.g. expected
returns) on a forward-looking basis
5. Decide on neutral asset allocation and Implement the
SAA
* Source: World Bank
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II- SAA Process
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1. Objectives & Investment Horizon
Objective:
• Capital Preservation
• Achieve a minimum required rate of return
• Match assets and liabilities
• Minimize volatility of returns.
The investment horizon is the time over which the
portfolio is used and over which returns and risks should be
managed and measured.
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1. Objectives & Investment Horizon
Based on historical USD Government bond returns 1953-2006
Source: World Bank
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2. Risk Tolerance
• Risk tolerance is defining how much the institution
tolerates in terms of risk, which needs to be translated into a
risk measure such as;
- shortfall probability
- probability of not achieving a certain target return
- worst case outcome at a certain confidence level.
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2. Risk Tolerance
Commonly risk measures:
• Duration
• Volatility of total returns
• Downside risk measures
1. Shortfall probabilities
 Probability of negative return
 Probability of underperforming a hurdle rate / benchmark
2. Minimum return at given confidence level
 Value at risk
3. Expected Shortfall
 Expected Loss
 Conditional Value at Risk
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3. Identify Eligible Asset Classes
• Selection of eligible asset classes is an important step in the
asset allocation process.
• Section should not be based on the riskiness of stand alone
asset class.
• Asset classes could include; cash, Government bonds,
Agencies, TIPS, Corporates, ABS, MBS.
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4. Determine Market Assumptions
Expected returns for each asset class
• Historical
• Factor models
• Autoregressive models
Volatilities and correlations
• Historical
• Autoregressive models such as GARCH models
• Regime switching model
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5. Portfolio Construction
Most Common : Mean variance optimization
Assumption: returns are normally distributed.
• Inputs:
 Expected return of each asset class
 Standard deviation of each asset class
 Correlation of returns between asset classes
• Output:
 The efficient frontier, i.e. the set of portfolios
with the highest expected return for a given level of risk.
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5. Portfolio Construction
• Efficient frontier: set of portfolios which have the lowest
possible variance for a given target expected return.
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III. Validation of the SAA
• Back-testing of SAA:
 Robustness checks: compare ex-ante risk limit with expost risk of the portfolio
• Sensitivity analysis of key parameters
 Impact analysis: How much do the portfolio weights
change when expected return assumptions or
risk assumptions are changed.
 Marginal analysis: how much does the risk of the
portfolio change for a small change in the weight of
one of the assets
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IV. Implementation of SAA
• SAA optimal allocation is implemented through selection
of benchmarks (neutral point)
• Decide on Rebalancing rules.
• Active or passive management.
• Risk budget for active management.
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Details on SAA
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1. SAA Approaches
• Historical Approach
• Forward-Looking Approach
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• Carry historical Analysis on historical returns for different
durations.
• Calculate different risk measures for different duration
benchmarks in order to reflect the bank objective and risk
tolerance over a certain time horizon.
40%
Minimum
30%
Maximum
Average
20%
10%
6.3%
5.9%
6.5%
6.4%
7.1%
6.8%
6.7%
7.4%
7.3%
0%
-10%
Source: World Bank
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4
3
2
1.5
1
0.75
0.5
-20%
0.25
Central Bank of Egypt
2. Historical Analysis
Duration
20
• The shortfalls of Pure Historical Analysis:
ML UST 1-3 12-Month Return
25.00%
20.00%
15.00%
10.00%
5.00%
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Jan-04
Jan-03
Jan-02
Jan-01
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-95
Jan-94
Jan-93
Jan-92
Jan-91
Jan-90
Jan-89
Jan-88
Jan-87
Jan-86
Jan-85
0.00%
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3. Shortfalls of Historical Analysis
21
• Capital preserving portfolio indeed? See February and
March, 2005
ML UST 1-3 12-Month Return
18.00%
16.00%
14.00%
12.00%
10.00%
8.00%
6.00%
4.00%
2.00%
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Jan-05
Jan-04
Jan-03
Jan-02
Jan-01
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-95
Jan-94
Jan-93
Jan-92
Jan-91
Jan-90
Jan-89
Jan-88
-2.00%
Jan-87
0.00%
Jan-86
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3. Shortfalls of Historical Analysis
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Jan-05
Jan-04
Jan-03
Jan-02
Jan-01
Jan-00
Jan-99
Jan-98
Jan-97
Jan-96
Jan-95
Jan-94
Jan-93
Jan-92
Jan-91
Jan-90
Jan-89
Jan-88
Jan-87
Jan-86
Jan-85
Jan-84
Jan-83
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3. Shortfalls of Historical Analysis
• What happened to 2 yrs yield?
USGG2YR Index
14
12
10
8
6
4
2
0
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3. Shortfalls of Historical Analysis
• Historical Analysis Approach assumes “Constant
duration though not constant risk”
– If our portfolio has an average duration of 2 years with
a current yield of 1.5%, and yields go up by 1%, we
will achieve a –ve return
– However, if the current yield is 5%, and yields go up
by even 3%, we will not achieve a –ve return
• Hence, for the same duration, as yield decreases , the
probability of negative returns increases (and vice versa)
so:
Prob of –ve return is a function of current yield level,
volatilities and market environment.
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3. Shortfalls of Historical Analysis
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4. From Historical to Forward Looking Approach
• First step towards forward-looking analysis: Scenario
Analysis by estimating different yield curve scenarios

Price END  Price BEG   Cash Received
Total Return 
Price BEG
• A Simple Approximation:
TR t  y t 1/12  MD  Δy t
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4. From Historical to Forward Looking Approach
• Limitation: Scenario Analysis is good as a start for
forward looking approach; however, it undermines the rolldown component.

TR 12yr  y 02yr /12  MD  y123 mth  y 02yr

TR 12yr  y 02yr /12  MD  y12yr  y 02yr
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

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5. The Nelson-Siegel Yield Curve Model
• Nelson and Siegel FORMULA
1et 
1et t 
2,t 
z(t)0,t 
1 1,t 
e .
 t 
 t

The Level
Factor.
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The Slope
Factor.
The Curvature
Factor.
28
5. The Nelson-Siegel Yield Curve Model
14%
12%
• An increase in β1 increases
short yields more than long
yields thereby changing the
slope of the yield curve.
Beta 0
USGG30YR Index
10%
8%
6%
4%
2%
8
Ja
n-0
5
Ja
n-0
2
Ja
n-0
9
Ja
n-9
6
Ja
n-9
3
Ja
n-9
0
Ja
n-9
7
Ja
n-8
4
n-8
Ja
n-8
1
0%
Ja
• The long-term factor β0
governs the yield curve level.
An increase in β0 increases all
yields equally, thereby changing
the level of the yield curve.
3.00%
30 yrs yield - 3M yield
2.00%
Beta 1
1.00%
0.00%
-1.00%
-2.00%
-3.00%
-4.00%
-5.00%
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De
c-0
7
De
c-0
4
De
c-0
1
De
c-9
8
De
c-9
5
De
c-9
2
De
c-8
9
De
c-8
6
12.000%
10.000%
8.000%
2* 2 yrs - (3M+30 yrs)
6.000%
Beta 2
4.000%
2.000%
0.000%
-2.000%
-4.000%
-6.000%
De
c-0
7
De
c-0
4
De
c-0
1
De
c-9
8
De
c-9
5
De
c-9
2
De
c-8
9
De
c-8
6
-8.000%
De
c-8
3
• An increase in β2 will have
little effect on very short or
very long yields but will
increase medium-term yields,
thereby increasing yield curve
curvature.
De
c-8
3
De
c-8
0
-6.00%
De
c-8
0
Central Bank of Egypt
16%
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Central Bank of Egypt
5. The Nelson-Siegel Yield Curve Model
• What if we estimated this model every week for an entire
year.
• It turns out that it is better to keep λ fixed across time. This
adds quite a bit of stability to the model.
• Each week would give us three different parameters. We
would get slightly different values each week for b1, b2, and
b3.
• We could then look to see how these parameters evolve
over time.
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Central Bank of Egypt
6. SAA Model
•
The weekly data over the past years has provided us with time series data for
the Nelson-Siegel model’s parameters.
•
Estimate parameters of vector autoregressive model “VAR(1)” based on
historical Nelson Siegel factors.
•
Define asset classes: return on these asset classes is a function of the
fundamental variables
•
Simulate VAR model over a certain horizon and calculate return of differ
ent asset classes.
•
Output: different yield paths over a certain investment horizon (1 year) where
government bonds with different maturities can be priced on the expected
curve.
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Central Bank of Egypt
Thank you
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