case study: asset allocation at the texas teacher...
TRANSCRIPT
Topic Five:
Case Study: Asset Allocation at the Texas Teacher Retirement System
Case Study: Asset Allocation at Texas Teacher Retirement System
Background: The Teacher Retirement System of Texas (TRS) is a public defined-benefit pension fund dedicated to delivering retirement benefits and related services for more than 1,300,000 public education employees and their annuitants in the state of Texas. It currently has approximately USD 135 billion of assets under management.
Investment Problem: The Board of Trustees at TRS faces a typical “asset-liability” management problem in that they must invest so as to simultaneously satisfy the income needs of current retirees and beneficiaries as well as provide sufficient asset growth to provide for future funding needs. The system is currently underfunded relative to actuarial liabilities, largely due to the fact that contributions from the state legislature have not kept pace with needs.
Portfolio Optimization Application (Spring 2003): Mean-variance optimization approach across multiple asset classes, including U.S. equity, non-U.S. equity, fixed-income, private equity, hedge funds, and real estate. (Summer 2009 & 2014): Mean-VaR optimization within economic “asset silos”
Miscellaneous Issues: - AON Hewitt Associates in the main economic consultant to the TRS Board - TRS is required by state law to revisit strategic allocation process every 3-5 years
5 - 1
Summary of Current Situation: June 2014
5 - 2
Overview of Allocation Update Process
Several factors impact the ability of TRS to provide benefits to participants: Contributions to trust (employee and State) Level of benefits Return on invested assets
Significant capital market declines of 2008 have negatively impacted pension
funding levels
While asset allocation can be changed to influence the expected return going forward, investment decisions alone cannot close the unfunded liability Some change in contribution level or benefits may be necessary to improve funded
status Investment policy decisions must be integrated with the overall funding policy for the
System.
An asset allocation that is prudent and consistent with an aggressive pursuit of the equity risk premium (i.e. a relatively high allocation to return-driven assets, such as the current 79%) creates the best opportunities to control both long term total cost and shortfall risk. Marginal tweaks to the current target asset allocation may result in improvements in
the risk/return tradeoff without significant change to the absolute level of risk in the portfolio
5 - 3
Funding Framework #1: Fixed 6.4% Employee Rate; 10% Employer Max; 79% Non-Fixed Allocation
FY 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024Funded ratio percentile values:
5% 91% 70% 60% 54% 48% 46% 42% 39% 36% 33% 32% 30% 29% 28% 26% 26%25% 91% 73% 68% 65% 61% 56% 54% 53% 51% 51% 50% 50% 49% 49% 47% 46%50% 91% 75% 74% 72% 66% 62% 62% 62% 63% 63% 64% 65% 65% 65% 67% 67%75% 91% 78% 80% 76% 71% 69% 71% 73% 76% 78% 79% 80% 83% 85% 88% 91%95% 91% 81% 82% 80% 78% 79% 85% 92% 98% 105% 112% 119% 127% 130% 136% 142%
Total cost rate distribution:20%+ 0% 0% 0%
16.4% to 20% 85% 68% 60%13% to 16.4% 14% 19% 15%10% to 13% 0% 14% 25%
Less than 10% 0% 0% 0%
Projected Range of Funded Ratio
80%
112%
142%
72%64% 67%
54%
32%26%
91%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
110%
120%
130%
140%
150%
160%
170%
2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Dark shaded area indicates the 50% probability zone, and light shaded area indicates the 90% probability zone.
Median / trend line
No real upward trend at the median
Shortfall risk expanding
Contributions at the 16.4% max well over ½ of the time
5 - 4
Funding Framework #1: Distribution of Funded Ratio After 15 Years
Below 60% 60% to 80% 80% to 100% 100% to 115% Over 115%
41% 22% 15% 8% 14%
0%
5%
10%
15%
20%
25%
30%
35%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 110% 120% 130% 140% 150% 160% 170% 180% 190% 200%
Final Funded Ratio
Cos
t Afte
r 15
Yrs.
(% o
f pay
)
Severe shortfall risk after 15 years, with 41% chance of funded ratio below 60%
5 - 5
Revised Strategic Asset Allocation Process
Traditional Approach New TRS Approach
Survey
•Expected Returns, Volatilities, and Correlations
Construct •Robust Correlation Matrix
Optimize •Efficient Frontier Analysis using VaR
Analyze •Non-normality
Forecast • Future Economic Conditions
Hedge • Insurance
Determine
•Market Expectations for Return and Risk
Derive •Efficient Frontier
Identify
•Optimal Asset Mix on Efficient Frontier
5 - 6
Strategic Asset Allocation 2012 Assumptions – TRS and Aon Hewitt
o TRS Higher: • EM Equity • Credit • REITS and
value-added real estate.
o TRS Lower: • Treasury • TIPS • Private Equity
Ennis Knupp Correlation Matrix TRS Average Correlation Matrix
Glo
bal E
quity
Stab
le V
alue
Real
Ret
urn
Glo
bal E
quity
Stab
le V
alue
Real
Ret
urn
Global Equity 1.00 0.13 0.59 Global Equity 1.00 0.17 0.39Stable Value 0.13 1.00 0.33 Stable Value 0.17 1.00 0.48Real Return 0.59 0.33 1.00 Real Return 0.39 0.48 1.00
10 Year ForecastAsset Class Mean Return Std Deviation Sharpe
TRS EK TRS EK TRS EKUS Large Cap 8.0% 7.5% 16.3% 15.9% 0.32 0.43US Small Cap 9.3% 7.7% 20.4% 18.7% 0.32 0.38EAFE Unhedged 8.3% 7.4% 18.4% 19.0% 0.30 0.36Emerging Markets 8.8% 7.3% 25.0% 27.3% 0.24 0.25Private Equity 10.0% 10.4% 28.5% 30.3% 0.25 0.32Cash 2.7% 0.6% 0.5% 0.0% 0.00 0.00US Aggregate 4.4% 4.7% 6.5% 6.6% 0.26 0.62US Treasurys -- Intermediate 3.0% 4.3% 6.3% 5.1% 0.04 0.72US Treasurys -- Long 3.7% 4.6% 9.5% 12.1% 0.10 0.33US Investment Grade Credit 5.1% 5.0% 7.8% 8.6% 0.30 0.52US High Yield 6.9% 6.2% 11.1% 11.6% 0.37 0.48WGBI ex US Unhedged 3.3% 3.9% 8.9% 12.5% 0.06 0.26Emerging Market Debt 9.3% 6.4% 14.7% 14.7% 0.44 0.40Bank Loans 5.4% 4.9% 6.6% 6.6% 0.39 0.65Hedge Funds - Non-Directional 6.5% 5.5% 7.7% 7.2% 0.49 0.67Hedge Funds - Directional 8.3% 7.5% 10.3% 13.5% 0.54 0.51Real Assets 5.3% 7.3% 8.5% 16.0% 0.30 0.42REITS 8.0% 6.5% 20.0% 19.0% 0.26 0.31Direct Real Estate 6.6% 6.4% 8.8% 11.6% 0.44 0.50Value Added Real Estate 7.3% 6.7% 13.0% 26.4% 0.35 0.23US TIPS 4.0% 4.2% 5.9% 5.8% 0.20 0.63Global Inflation Linked Bonds 3.6% 4.4% 6.8% 6.5% 0.12 0.59Gold -1.0% n/a 20.0% n/a -0.19 n/aCommodities 4.9% 4.3% 21.3% 16.1% 0.10 0.23
5 - 7
Optimization Based on Highest Probability of Achieving Target Return
o Optimization
routine solves for the asset allocation that has the highest probability of achieving target
o Tested results using bearish, base case and bullish forecasts
Portfolio Distribution (14% Stdev)
0.00%
0.50%
1.00%
1.50%
2.00%
2.50%
3.00%
3.50%
4.00%
4.50%
-32.
5%
-29.
7%
-26.
9%
-24.
1%
-21.
3%
-18.
5%
-15.
7%
-12.
9%
-10.
1%
-7.3
%
-4.5
%
-1.7
%
1.1%
3.9%
6.7%
9.5%
12.3
%
15.1
%
17.9
%
20.7
%
23.5
%
26.3
%
29.1
%
31.9
%
34.7
%
37.5
%
40.3
%
43.1
%
45.9
%
48.7
%
51.5
%
Prob
abili
ty D
ensit
y
Return
Target Return(8.0%)
Expected Return(9.5%)
Probablility of Achieving Target Return(54.27%)
5 - 8
Probability – VaR Efficient Frontier
o While the 9.65%
target portfolio has a slightly higher probability of success, the 8% target portfolio has lower tail risk
o The critical difference between the 8% and 9.65% target portfolio is a 10% allocation to credit versus equities (i.e. 50/30/20 vs. 60/20/20)
8.0% Base Case - Simulated
9.7% Base Case - Simulated
9.7% Target Portfolio8% Target Portfolio
Current Portfolio
0%
10%
20%
30%
40%
50%
60%
5.00% 10.00% 15.00% 20.00% 25.00% 30.00% 35.00%
Prob
abili
ty o
f Rea
chin
g Re
turn
Tar
get
VaR (99%) (Higher is riskier)
Moving from the ideal 8% portfolio to the ideal 9.65%portfolio increases the chances of meeting the 9.65% target by 0.9% (47.0% to 47.9%) and increases the VaR by 5.9% (from 20.9% to 26.8%). The biggest difference between the two portfolios is the ideal 9.65% portfolio has 10% overweight to equity and underweight to credit relative to the ideal 8% portfolio.
5 - 9
TRS Long-Term Investment Plans
o The new policy introduces credit into the allocation at the expense of Treasury exposure
o Overall Real Return exposure remains unchanged
Current Policy Pre 2007 PolicyGlobal EquityUS Large Cap 20% 36% 4%
US Small Cap 5% 11% 9%
EAFE Unhedged 15% 12% 8%
Emerging Markets 10% 1% 9%
Private Equity 10% 4% 16%
Total Global Equity 60% 64% 46%
Stable ValueCash 1% 1% 1%
US Aggregate 0% 28% 0%
US Treasurys -- Intermediate 0% 0% 0%
US Treasurys -- Long 15% 0% 0%
US Investment Grade Credit 0% 0% 0%
US High Yield 0% 2% 2%
WGBI ex US Unhedged 0% 0% 0%
Bank Loans 0% 0% 0%
Emerging Market Debt 0% 0% 32%
Hedge Funds 4% 2% 0%
Total Stable Value 20% 33% 35%
Real ReturnReal Assets 5% 0% 0%
REITS 0% 0% 9%
Direct Real Estate 5% 3% 1%
Value Added Real Estate 5% 0% 5%
US TIPS 0% 0% 0%
Global Inflation Linked Bonds 5% 0% 0%
Gold 0% 0% 0%
Commodities 0% 0% 3%
Total Real Return 20% 3% 18%
Total Fund 100% 100% 99%
Suggested Policy - 8% Target
5 - 10
TRS vs. Peer Strategic Allocations: June 2014
5 - 11
Asset Allocation Recommendations: June 2014
5 - 12
Texas Teachers: Tactical Asset Allocation Program
In 2007, TRS made a major commitment to increase its risk-adjusted returns (i.e., alpha) throughout its entire organizational structure - This involved (i) allocating more capital to non-traditional asset classes
(e.g., private equity, hedge funds), and (ii) using more external managers
In connection with these organizational changes, TRS also launched a systematic effort to produce alpha through tactical asset allocation strategies - A new Portfolio Strategy & Execution team was formed and the
TAA Team is located within that segment of the Investment Management Division
- The TAA Team operates as an “overlay” entity that has responsibility for roughly 50-100 basis points of the total TRS portfolio
5 - 13
5 - 14
5 - 15
5 - 16
5 - 17
5 - 18
5 - 19
5 - 20
5 - 21
5 - 22
5 - 23
5 - 24
TRS Strategic Partner Network (SPN)
In July 2008, TRS made its first major initiative to use public market, external management - Four firms were selected and given the mandate to manage
customized, risk-controlled portfolios across all of the asset classes in the TRS investable universe
- Each firm was funded with USD 1 billion
The objectives of the program were - Access managers with proven track record of producing alpha - Create useful proprietary research through focused SPN project
collaboration - Maximize the full breadth of services and talent offered by the
selected external managers
5 - 25
5 - 26
5 - 27
Modifying the TAA Model: Stocks vs. Bonds 3.0
5 - 28
5 - 29
5 - 30
5 - 31
5 - 32
5 - 33
5 - 34
5 - 35
TAA at TRS: Update
5 - 36
5 - 37
5 - 38
5 - 39
5 - 40
Hedge Fund Replication: Review and Expansion
5 - 41
5 - 42
5 - 43
5 - 44
5 - 45
5 - 46
5 - 47
5 - 48
5 - 49