Managing Alpha, Beta and the Funded Ratio:
Implementing Effective Portfolios after an ALM
Analysis
By Dr. Arun Muralidhar
Author: Innovations in Pension Fund Management
with assistance from
Sanjay Muralidhar and Rahul Rauniyar of Mcube Investment Technologies, LLC
Agenda
1)
A quick review of the pension fund balance sheet
a.
2)
3)
4)
Actuarial Liabilities – converting into a measurable Liability Benchmark
Implementing an Effective Portfolio and Impact on Funded Position
a.
Static SAA versus Liabilities – would have reduced Surplus
b.
Hiring External Managers
c.
Adding an Active Currency Program to Manage Currency Risk
d.
Simple Rebalancing Decisions
Managing Alpha and Beta to Improve Funded Position
a.
Beta Management: How Asset Allocation/Style Decisions can increase
Surplus and Lower Risk of Shortfall (and even improve some risk aspects)
b.
Alpha Management: Manage Your Managers for Better Performance
Summary: Intelligent Management of Alpha and Beta can Lower Funded Ratio
Risk
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Roadmap: From Static to Dynamic Portfolios
Set Static
Strategic
Asset
Allocation
Using ALM
Hire
Managers
on a Static
Basis (incl.
Currency)
Consider
Simple
Rebalancing
Strategies
Dynamic
“Beta”
Management
Dynamic
“Alpha”
Management
 Traditional approach – Alpha from external managers
 New approach – Add alpha from “informed decisions”
 Transparency and governance are critical
 Must monitor impact on Surplus and risk
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1. The Pension Fund Balance Sheet
Current
Assets
+
Future
Contributions
=
=
PENSION
OBLIGATIONS
(LIABILITIES)
+
Future
Returns
Funded ratio = assets/liabilities
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Pension Cash Flows (Euros)
1. Creating Liability Benchmarks: Cash Flows
12000000
10000000
8000000
6000000
4000000
2000000
0
1
6
11 16 21 26 31 36 41 46 51 56 61 66 71 76
Time (Years)
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1. Creating Liability Benchmarks: Using Swaps

Liabilities modeled as a portfolio of swaps (where pension fund can lock in
cash flows) or zero coupon bonds

Liability Benchmark
Weight

1 Year Swap
1%

2 Year Swap
4%

5 Year Swap
9%

10 Year Swap
21%

20 Year Swap
25%

30 Year Swap
40%
100%

Now Annual Growth in Surplus/Deficit = Asset Return – Liability Return

Assets and Liabilities can be marked-to-market daily!
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2. Invested Fund can be Modeled vs. Liabilities
PENSION LIABILITIES
INVESTED FUND
Currency
Overlay
10%
Equity
32%
Europe
GPR
Property
Surplus
Fixed Income
53%
Cash
0%
North
America
Emerging
Japan
Euro
Govt.
Global
Credit
Alternatives
5%
High
Yield
Real Estate
10%
EMG
Debt
Pacific
ex Japan
= External Managers
Liabilities, as modeled, had an annual return of approximately 8%
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2. Assumptions for Analysis
 Decision analysis performed for the period from January 2002
to December 2004 (period for which swaps data was available)
 Liabilities modeled as a portfolio of swaps
 Assumed initial funding ratio (FR) in January 2002 was 110%
 All analysis is based on one historical path and projected
forward
 Rebalancing/Asset Allocation/Style decisions assume no
transaction costs
 Client had a strategic currency hedge on international equities
= 100% hedge to base currency – many Japanese funds are
similar and this can be a major contributor to returns and risk
 Excess return computed using arithmetic excess return
calculation
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2a. Performance of Static SAA vs. Liabilities
Over this period, Static SAA underperformed liabilities – surplus would decline
Annualized
Growth in
Surplus *
-0.72%
Volatility of
Ann. Growth in
Surplus
6.64%
Probability
(FR < 105)
At end 2006
30%
Max Drawdown
of Surplus
-8.68%
Ann. Liability Return = 8.2%
(Benchmark)
Ann. Asset Return = 7.5%
(Portfolio)
* Asset return – Liability return
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•FR = Funded Ratio
9
Chart of Page 9
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Mcube
Investment Technologies, LLC
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2b. Impact of External Managers – Static Allocations
PENSION LIABILITIES
INVESTED FUND
Currency
Overlay
10%
Equity
32%
Europe
GPR
Property
Surplus
Fixed Income
53%
Cash
0%
North
America
Emerging
Japan
Euro
Govt.
Global
Credit
Alternatives
5%
High
Yield
Real Estate
10%
EMG
Debt
Pacific
ex Japan
= External Managers
Only look at external managers in mainstream asset classes
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2b. Managing Alpha – External Managers
 Many clients hire external managers to generate
alpha
 Static contribution of all managers is one source of
return
 Impact of all managers not always positive…..
 May pay high fees for negative impact…..
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2b. Performance of Static SAA+ Managers
Over this period, external managers underperformed – surplus declines more
Annualized
Growth in
Surplus *
-0.92%
Volatility of Prob (FR < 105) Max Drawdown
Ann. Growth in
of Surplus
At end 2006
Surplus
6.64%
33%
-8.76%
Ann. Liability Return = 8.2%
(Benchmark)
Ann. Asset Return = 7.3%
(Portfolio)
* Asset return – Liability return
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•FR = Funded Ratio
13
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2c. Impact of Adding Alpha – Currency Alpha
PENSION LIABILITIES
INVESTED FUND
Currency
Overlay
10%
Equity
32%
Europe
GPR
Property
Surplus
Fixed Income
53%
Cash
0%
North
America
Emerging
Japan
Euro
Govt.
Global
Credit
Alternatives
5%
High
Yield
Real Estate
10%
EMG
Debt
Pacific
ex Japan
= External Managers
Assume initially that only currency is managed actively
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2c. Explaining Currency Management
 Funds invest abroad for higher yield = inherit currency risk
 Passive hedge ratio = 100% hedged back to base currency
 Active currency management involves buying and selling
currencies (USD/JPY, USD/EUR, JPY/EUR etc.) for profit
 These strategies are typically uncorrelated to other strategies
 Currency strategies do not need funding and generate cash!
 Active currency management can lower Asset-Liability risk
(Chap 5: Innovations in Pension Fund Management)
 Can have a meaningful impact on pension fund
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2c. Currency: USD/JPY and EUR/JPY
USD has declined nearly 25% from 2001 high – full hedging added returns
EUR has gained appx. 40% from 2000 low – full hedging hurt returns
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2c. Why Currency Management is Useful
 Good programs have an information ratio close to 1
 Risk can scale easily: typical overlay = 2% alpha
 Contribution to total fund can be as much as 20 bps
 If successful – such strategies generate cash without
requiring funding
 Many US funds are using higher alpha strategies as a
way of generating cash to cover shortfall between
contributions and pension payments
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2c. Static SAA+ Managers + Currency Overlay
Active currency added 0.27% at fund level – surplus decline reduced; risk is lower
Annualized
Growth in
Surplus *
-0.64%
Volatility of Prob (FR < 105) Max Drawdown
Ann. Growth in
of Surplus
At end 2006
Surplus
6.59%
29%
-8.62%
Ann. Liability Return = 8.2%
(Benchmark)
Ann. Asset Return = 7.6%
(Portfolio)
* Asset return – Liability return
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•FR = Funded Ratio
19
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2d. Implementing a Rebalancing Policy
 Typical rebalancing is either calendar or range-based
 Example: +/- 5% range around benchmark weight for most
assets; 4% for Real Estate
 When range hit, go either to range or target or in-between
 Such a policy gives staff discretion = Tracking Error
 MOST IMPORTANT: Most policies are silent about what to do
inside the ranges (most funds do nothing!!)
 Board or staff are taking implicit bets on the market – must
make explicit decisions for good governance
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2d. Impact of Rebalancing
 Most rebalancing decisions have some element of
“active” decision making in them
 “Pure” passive is the Dutch model of only annual
rebalancing (Calendar-based rebalancing)
 However, portfolio can drift dramatically away from SAA
 Alternative Rebalancing options such as volatility based
rebalancing also have an active element
 Can the pension fund staff do better by making decisions
explicit?
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2d. Performance of Portfolio with Rebalancing
Annual rebalancing added 0.07% at fund level – surplus decline reduced
Annualized
Growth in
Surplus *
-0.57%
Volatility of Prob (FR < 105) Max Drawdown
Ann. Growth in
of Surplus
At end 2006
Surplus
6.72%
28%
-8.63%
Ann. Liability Return = 8.2%
(Benchmark)
Ann. Asset Return = 7.6%
(Portfolio)
* Asset return – Liability return
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•FR = Funded Ratio
23
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2. Summary Findings on Static Portfolios
 In this case, the SAA would have caused Surplus to fall
 Over this period, external managers also detracted returns
 Active currency management (as did the passive hedge) added
returns and lowered risk
 Rebalancing added some returns, but surplus is still declining
 Must use additional decisions that are under the control of
pension fund staff to improve overall portfolio and ALM
profile
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3. Intelligent Management of Assets
 Many clients look for low correlation among assets =
good diversification
 Low correlation also means asset class performance
will go through cycles – this aspect is often ignored
 Intelligent staff should not sit by as markets evolve –
similar principle applies to cyclicality of managers
 Analysis of SaR (Surplus at Risk) must include
“automatic, intelligent decisions” that go beyond
rebalancing
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3a. Intelligent Management of Assets
INVESTED FUND
Equity
32%
Europe
Europe vs. US
GPR
Property
Fixed Income
53%
Equity vs. FI
North
America
Emerging
Japan
Euro
Govt.
Global
Credit
HY vs. IG
Alternatives
5%
High
Yield
Real Estate
10%
EMG
Debt
Pacific
ex Japan

Modeled a few asset allocation decisions possible in portfolio structure

Built a few simple rules (see Appendix) that are intuitive and available from
academic literature

Similar decisions can be developed for all asset pairings

Can add more rules for additional diversification (more returns/better risk)
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3a. Portfolio with Dynamic “Beta” Decisions
Intelligent beta decisions added 0.96% at fund level – SURPLUS NOW INCREASES
Annualized
Growth in
Surplus *
0.29%
Volatility of Prob (FR < 105) Max Drawdown
Ann. Growth in
of Surplus
At end 2006
Surplus
7.00%
21%
-8.0%
Ann. Liability Return = 8.2%
(Benchmark)
Ann. Asset Return = 8.5%
(Portfolio)
* Asset return – Liability return
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•FR = Funded Ratio
28
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Chart of Page 23
29
3a. Asset Allocation Recommendations
Fixed Income
Equity
Real Estate
Alternatives
Period when
liability value
rose
Results achieved with relatively low turnover – impact of transaction costs should be low
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3a. Summary Findings from Beta Management
 Can take advantage of low correlation across assets to
do better than a static mix or simple rebalancing
 Intelligent “automatic” decisions can increase Surplus
and lower SaR (or the probability that the funded
ratio will be below some threshold in the future)
 Requires only moderate tilts at infrequent intervals to
add meaningful value
 Such decisions are within the scope of well-run
pension plans
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3b. Managing Alpha – External Managers
 Static manager “alpha” is one source of return
 Managers can have low correlation with others
 Manager performance goes through cycles – why
fund a manager who is starting to underperform?
 However, since portfolio is dynamic, clients can use
cash flows to make intelligent “alpha management”
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3b. External Managers – Dynamic Allocations
PENSION LIABILITIES
INVESTED FUND
Currency
Overlay
10%
Equity
32%
GPR
Property
Europe
Surplus
Fixed Income
53%
Cash
0%
North
America
Emerging
Euro
Govt.
Japan
Pacific
ex Japan
Loans vs.
Mortgages vs.
Govt
Global
Credit
Alternatives
5%
High
Yield
Real Estate
10%
EMG
Debt
= External Managers
Europe vs.
UK
Look at managers who are not highly correlated
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3b. Ideas for “Alpha” Management
 In deciding between UK and Euro ex-UK managers,
favor the manager covering the market with a higher
interest rate
Added 0.37% annualized over a static mix
 In Euro Government bonds, favor the manager with
the greatest return momentum over last 3 months
Added return over a static mix of 4 managers
 Again, can do more rules for better returns/risk
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3b. Impact of Dynamic Alpha Management
Intelligent alpha decisions added 0.05% – SURPLUS INCREASES MORE
Annualized
Growth in
Surplus *
0.34%
Volatility of Prob (FR < 105) Max Drawdown
Ann. Growth in
of Surplus
At end 2006
Surplus
6.96%
19%
-8.21%
Ann. Liability Return = 8.2%
(Benchmark)
Ann. Asset Return = 8.6%
(Portfolio)
* Asset return – Liability return
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•FR = Funded Ratio
35
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Chart of Page 29
36
Summarizing Impact of Alpha and Beta Management
Ann. Growth in
Surplus
Option
Volatility
of Surplus
Prob. Funded
Ratio < 105% at
year end 2006
Static SAA
-0.72%
6.64%
34%
+ Managers (incl.
FX)
-0.64%
6.59%
29%
+ Rebalancing
-0.57%
6.72%
28%
+ Dynamic Beta (b)
+0.29%
7.00%
21%
+ Dynamic a
+0.34%
6.96%
19%
Annualized Liability Return (Benchmark) = 8.2%
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4. Summary Conclusions
 Many clients focus only on SAA, Rebalancing and
Static Allocations to External Managers
 Currency management may be critical to add
uncorrelated alpha
 More importantly, using dynamism in portfolio can
lead to additional returns and lower Surplus-at-Risk
 Dynamism can be in both managing beta and alpha
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4. Practical Choices to Improve Manage ALM
 Be smart about portfolio structure – allow for a
passive allocation for each asset class. This will allow
for more intelligent rebalancing while minimizing
transactions costs
 Evaluate managers not on an individual basis, but
also how they impact the total fund
 Can leverage your external managers to help develop
intelligent rules for alpha and beta – Verizon Model
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Contact Information:
Dr. Arun Muralidhar
Phone: 1-646-591-6991
email: asmuralidhar@mcubeit.com
Website: www.mcubeit.com
Information on Mcube and AlphaEngineTM
 Company was formed to help investors make better
decisions on asset allocation and managers with a
quick and easy-to-use web-based product
 Flagship product is the AlphaEngineTM
 Product is being used by corporate and public
pension funds, hedge fund fund-of-funds and even
investment managers in US, Europe and Canada
 Meant to Ensure Governance and Generate Alpha
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Appendix
2c. Some Simple Rules Make Money in Currency
Tested rules include:

Yield Curve Slope (Allocate to currency having flatter yield curve)

Carry Rule (Allocate to currency with higher 1 month LIBOR rate)

20-65 Day Moving Average Crossover (Allocate to currency that is
trending or has momentum)
Will only test for USD/JPY – very conservative implementation
Either hedge (+10%) or short 10%
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2c. Performance of USD/JPY Rules and Strategy
 Rules Evaluated: (a) yield curve; (b) carry; (c) moving average
 Tested from Jan 1990 – April 2005 (15 years)
 USD/JPY Strategy = Equally weight Yield curve, Carry, and MA
 Diversification improves information ratio, skill, & drawdown
 Can either be scaled up for more currencies, risk and alpha
Strategy/
Rules
USD/JPY
Strategy
USD/JPY
Yield Curve
USD/JPY
Carry
USD/JPY
MA 20-65
Annualized
Annualized Std
Return
Deviation
Information Cumulative Confidence Success
Ratio
Return
in Skill
Ratio
Ratio Good Max
/Bad Risk
Drawdown
0.35%
0.76%
0.46
5.4%
96%
52.5%
1.0
-2.35%
0.34%
1.11%
0.31
5.38%
88%
52%
0.93
-3.82%
0.29%
1.11%
0.26
4.46%
84%
52%
0.90
-3.48%
0.39%
1.11%
0.36
6.19%
91.4%
52%
1.08
-2.16%
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TAA/Style: Improved Risk/Return
 Used 4 simple/intuitive rules - scope for fine tuning and
adding a broader set of rules
 Assumes that over/underweight allocation for Equity and
Fixed Income are allowed in a +/- 5% range relative to
benchmark allocation – moves are small and infrequent
 TAA/Style decisions would have generate significant
additional alpha of over Euros 160 million in 2004 (0.93%
annualized) with impressive information ratio and confidence
in skill over static benchmark allocation to asset classes – even
if a small fraction of this is consistent/sustainable, it is
meaningful after transactions costs
 Rule based TAA/Style decisions normally also lower risk
(tracking error and drawdown) relative to other approaches
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TAA/Style Decisions: 4 Simple Rules Used
 Rules manage allocations between Equity and Fixed
Income, North America vs Eurobloc, High Yield vs Credit
Rule
Equity vs. Fixed:
Halloween Effect
Equity vs Fixed:
Oil and Economy
US vs Eurobloc:
interbank rates
HY vs Credit:
Yield Curve
Description
Trade
Frequency
Stocks tend to underperform bonds between June and
Oct – paper by a Dutch academic (works in US also)
Monthly
High oil price causes equity market to fall. Tilt towards
bonds when prices are rising and vice versa
Monthly
Overweight market with stronger Currency (based on
carry indications). Here we use Euro vs $.
Monthly
When the yield curve is upward sloping (progrowth) then high yield bonds outperform
Monthly
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2c. Efficacy of TAA/Style Allocation: ’02 -’04
All Decisions: Aggregate
Excess
TAA Decision: Eq vs FI
(100%)
Halloween Effect
Oil Rule
Equity Decision: US vs
Europe (32%)
Fixed Income Decision: HY
vs Credit (53%)
Excess
Annualized
Return
Tracking
Error
Information
Ratio
0.93%
0.44%
2.12
-0.12%
99.5%
84.2%
0.54%
0.60%
0.48%
0.35%
0.35%
0.50%
1.55
1.74
0.96
-0.12%
-0.11%
-0.26%
96.9%
98.3%
87.0%
73.7%
73.7%
57.9%
0.52%
0.32%
1.6
-0.13%
97.7%
73.7%
0.41%
0.21%
1.96
-0.08%
99.2%
73.7%
Worst
Confidence in Success
Drawdown
skill
Ratio

Evaluation period from 2002 to December 2004

Alpha represents pure asset allocation return (no manager alpha included) – kept
within the rebalancing range

Ideally test rules over longer historical period for better indication of long term
value-added and risk profile
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