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PRMIA - Being smarter than your beta
This presentation is intended for investment professionals
A case for neither passive indexing nor traditional active
portfolio construction
Emmanuel Matte CFA, FSA,FICA
Senior Vice-President, Investment Solutions
514-499-2538, [email protected]
April 2013
Back to basics…
2
Typical current process:
• Selecting asset classes (i.e. which «beta» to invest in)
• Allocation (strategic mix) to these asset classes
• Active management
Tactical allocation
Security selection
Portfolio construction Asset Allocation
(Beta)
Active management
(alpha)
Sources of return
Some Observations
3
Current process can hide some risks:
• Modeling risks
The ultimate benchmark of a pension plan is the liabilities
True investors’ objectives (i.e. absolute return, pension liabilities) often not reflected in the
decision model (relatives return vs benchmark)
• The selection of asset classes based on benchmark that are sub-optimal; thus the
resulting strategic portfolio will also be sub-optimal
• Some assets classes serve to hedge a liability (i.e. bonds within a pension portfolio)
and not as a return seeking asset nor to «diversified» returns volatility
• Tactical considerations often considered in setting the strategic or selecting the
market investment policy (i.e. level of rates)
“Insanity is doing the same thing, over and over again, but expecting different
results.” - Albert Einstein
To keep things simple…
Equities
Alternatives
Bonds
4
• Bonds: Traditional indices (i.e. DEX, DEX Long) hide significant embedded
uncompensated risks when not aligned with the desired liability structure
• Equities: Market Cap based indices forced investors into risky exposure and significant
«alpha» is in fact «beta management»
• Alternatives: Typical indices are almost always not representative of the actual investment
made
5
The fact that an opinion has been widely held is no evidence whatever that
it is not utterly absurd.
- Bertrand Russell
Conclusion: Market indices may be simple to use but are not meeting investors’ objectives
A customized bonds portfolio
7
Typical expected cash flow
2013
2014
2019
2024
2029
2034
2039
2044
2049
2054
2059
2104
2113
2114
Ca
sh
Flo
w
Your fixed income (FI) is not like any other asset class
You start with a debt, not cash (it is like being “short” a portfolio of bonds)
Key Messages:
• FI act as an offsetting position to your
liabilities
• Mismatches between FI and liabilities
are typically uncompensated risks
• If FI is highly correlated with liabilities,
then it should not be seen as an asset
class providing diversification but as a
hedging strategy
Do you have the right bond benchmark?
8 Universe bonds are not aligned with most client liabilities
Typical Pension Plan Liability vs DEX Universe Bond Index
Maturity
Cas
h F
low
Liabilities DEX Universe Bond Index
Typical Pension Plan Liability vs DEX Long Term Bond Index
Maturity
Cas
h F
low
Liabilities DEX Long Term Bond Index
Hidden Risks of Actuarial Valuations
9
Not worth your while?
10
Return
Seeking Assets
Liability
Hedging Assets
SLI Customized
BenchmarkDEX Universe DEX LTB
Combination of
DEX Indices*
0% 100% 0.2% 15.3% 5.5% 5.5%
10% 90% 1.7% 15.7% 6.7% 6.7%
20% 80% 3.3% 16.2% 8.2% 8.1%
30% 70% 5.0% 16.8% 9.8% 9.7%
40% 60% 6.9% 17.4% 11.4% 11.3%
50% 50% 8.9% 18.1% 13.1% 13.1%
60% 40% 11.1% 18.8% 14.9% 14.8%
70% 30% 13.5% 19.5% 16.7% 16.6%
80% 20% 16.1% 20.3% 18.4% 18.4%
90% 10% 19.0% 21.2% 20.2% 20.2%
100% 0% 22.2% 22.0% 22.0% 22.0%
Asset Mix Liability Hedging Assets Benchmark
* Combination of DEX indices that matches pension plan total durationSource: PC-Bond and Standard Life Invetsments
Moving Away from Market Cap Weighted Benchmarks for Equities
The risk of market-cap based benchmark
12
• Concentration risks (sector, region, securities)
• Momentum driven strategy (weights driven by herd mentality)
• Implicit risk positions uncontrolled over time
• Counterintuitive strategy (« Buy high, sell low »)
31%
46%
23%
Commodities
& Energy
Financials
Other
TSX
• “Macro themes” often dominate added value and/or risk profile
• Portfolio construction skill or “beta management”; example :
Value vs Growth
Long term commodities views
« Low Vol »
High dividends
Etc…
Is it true portfolio construction?
13
0
5
10
15
20
25
30
35
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
S&P 500 Sector Weights (%)
Information Technology Financials
Health Care Consumer Discretionary
Consumer Staples Energy
Industrials Utilities
Materials Telecommunication Services
Source: Bloomberg.
What if we were ignoring published indices?
• Concept : When you prepare dinner, do you make use of everything that you
have in your pantry? Are you weighing them equally?
• Then, why not…
1) Pick the desired meal (investment/risk objectives)
2) Find the right ingredients (stock selection)
3) Follow the recipe (weight the securities to best meet the objectives)
Revisiting portfolio construction
14
Currently, the majority of investors are following a “recipe” proportional to the
offering in the grocery store
Smart Beta
15
• Heuristic-based weighting methodologies
Equally weighted (dollar)
Equally weighted (risk)
Fundamental (value, growth, multiples, profits, dividends, etc.)
Technique factors (low volatility, momentum, etc.)
Macro-economic, thematic based
RAFI index
Etc.
1Source: Financial Analysts Journal, A survey of Alternative Equity Index Strategies, September/October, 2011.
Smart Beta
16
• Optimization-based weighting methodologies
Maximize certain risk measures subject to constraints
Max. Sharpe ratio
Min. variance / Min-VaR
Max. diversification index
EDHEC-Risk Efficient Equity Indices
Etc.
1Source: Financial Analysts Journal, A survey of Alternative Equity Index Strategies, September/October, 2011.
Illustration
17
Just like with the asset allocation…
…building an efficient frontier with “N” securties
Risk
Retu
rn
Market Cap Index
But is this only schoolbook theory?
Smart Beta
18
• Smart Beta strategies suffer from two main issues:
1. Highly reliant on models and parameters
2. Ignore market knowledge
• Potential consequences/risks:
High turnover
High concentration in small caps/low liquidity stocks
Heavy sector or style bias
“Any investor who strays from a weighting scheme such as capitalisation
weighting, for which the assumptions that determine the construction are
largely open to criticism and not proven, will probably take a good risk, in the
sense that there is a strong probability of doing better in the long term.”
- Smart Beta 2.0, EDHEC-Risk Institute, March 2013.
Issue – Models and Parameters
19
• Some heuristics models may sound simpler, but are often good only a
specific time period
i.e.: Equally vs market-cap weighting
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
Rolling 48-month Sharpe Ratio
Market Weight Equal Weight
S&P 500
20
• Optimization-based weighting methodologies
Theory: Low volatility anomaly = “less risk is more return!”
Reality: High model risk
-0.40
-0.20
0.00
0.20
0.40
0.60
0.80
1.00
1 2 3 4 5
Sh
arp
e R
ati
o
Quintile
Sharpe Ratio by Volatility Quintiles
In Sample
Out Sample
S&P 500, (rolling 48 months data from 1999 to 2012)
Issue – Models and Parameters
21
• Minimum volatility optimization can lead to high concentration issue
Security Allocation Minimum Volatility
Security AllocationS&P500
Risk management or risk transfer ?
Issue – Models and Parameters
Smart Beta : From theory… to reality
22
• Problem # 1: highly reliant on models and parameters
Robustness: Model remains valid under different parameters and market conditions
Risk: Model and parameters are not representative of the future reality
In-sample results/choices may not be reproducible out-of-sample
Theory (ex-ante) Reality (ex-post)
Solutions
23
• Solution #1: Pick THE right model… and be right (or lucky)
Will require to change model frequently
• Solution #2: Combined models (static)
i.e.: Value + Growth; High Div + Low Vol, etc…
Risk of having offsetting models (« closet indexer ») ou that amplify the risk
• Solution #3: Multi-model approach with statistical credibility (“smart portfolio”)
Recognize that each models have a (changing) probability of being the right one and
building the most robust portfolio in any of the scenarios
Low Vol High Div. Equally
Weighted
Market Cap.
based Mean/Variance … …
Optimal Portfolio
(the most robust “beta”)
X% y% z% w% s% …%
Problems…
24
• Problem # 2: Ignore market knowledge (qualitative)
M & A, IPO, Profit warning, Company transformation, Liquidity, etc…
Solution…
25
• Solution: Apply active management (stock selection and top-down strategies)
on the optimal portfolio
Universe Portfolio Optimal
multi-models
(quantitatif)
Active
management
(top-down /
bottom-up)
Market
Index optimisation
Sources of return
Acticve
Management « Alpha » from active manager
(rechearch and/or skill)
« Beta »
« Alpha » from beta optimisation
(process, methodology)
“Opportunity is missed by most people because it is dressed in overalls and
looks like work” - Thomas Edison
Customize Approach for « Alternatives »
Indices for alternatives
27
• Indices are typically « non investable » (i.e. real estate)
• Indices are non representative of the actual product used (i.e. hedge funds)
• Modeling process for allocation :
Breakdown asset class (or even better the actual product) into risk factor and then
assess risks diversification
• Process for manager/product selection (and monitoring) :
Absolute return / outcome approcah (i.e. benchmark or peer agnostic)
cash+x% with vol of y% on z years
“There are risks and costs to a program of action, but they are far less than
the long-range risks and costs of comfortable in action."
- J.F. Kennedy
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