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PENSION FUND
INVESTMENT AND
REGULATION
- A MACRO-STUDY
Yu-Wei Hu
Brunel University, West London, UK
Presentation in UNSW, Sydney, on 4-5th July 2005
Pension Fund Assets Growth
PFA growth has been dramatic over past
decades, and there are signs that such trend will
continue (Davis and Hu 2004)
 See OHP for data details (Hu 2005a, 2005b)
 As of 2003, total PFA US$ 15tr within 19
OECD countries; on average, 40% of GDP
 As of 2003, total PFA US$ 390bn within 36
EMEs; on average, 12% of GDP

P.F. Investment Strategies (Davis 2001)
1. DB - Sponsors are obliged to guarantee
retirement benefits, i.e. bearing the
investment risk
Asset and Liability Management (ALM)
approach (Inkmann and Blake 2004; Blake
1997)
2. DC - Risk transferred to employees
Mean-Variance (M-V) approach, i.e.
portfolio optimisation (Markowitz 1991)
Mean-Variance Approach


MAX ( R p )
subject to  p 2  
(1)
MIN ( p 2 )
subject to R p  
(2)
Equation 1 is the case where return maximised for
a given level of risk
Equation 2 is the case where risk minimised for a
given level of return (used in this paper)
Research Objectives
1. The central question in this paper is whether
restrictions on PF’s foreign investment are
justified
 2. In addition, what is PF’s optimal portfolio
composition, based on the data we have
Background:
Despite the benefit of global investment in terms
of risk diversification (Davis 2001, Solnik 1998),
pension funds investment restriction is still
common in many countries, e.g. limits of PFs
investment on foreign assets in 19 of 28 OECD
countries (Yermo 2003)
Risk-Change (RC) Ratio

Measures the extent to which the optimal PF
portfolio suffers from higher risk if there is a shift
from PPR to QAR (Davis 2001) in terms of
foreign investment
 i , m   i , m
 100


 i ,m
m
M
RCi 
n
 : SD under QAR;  * : SD under PPR
m : start mean; M : end
n : number of
mean
int ervals; i :
country index
Sharpe Ratio

Measures the magnitude of the reward-torisk

Definition: Return/Risk; Risk: standard
deviation
Data Description




Returns on 9 classes of assets, i.e. MP, BL, MO,
CB, GB, EQ, PR, FEQ, FB (Davis 2001, 2002)
Observation period: 1966-2004
38 countries: 22 OECD+16EMEs
Data sources: Global Financial Data, Datastream,
etc.
See OHP For Empirical Results 1
Optimal PFs Portfolio
Composition, Under The M-V
Framework
Considered 3 real return levels, i.e. 3%, 5%
and 7%
 9 asset classes (OECD PFs); 8 asset classes
without MO (EME PFs)
 Over 1966-2004
 Methodology: mean-variance approach, i.e.
minimise risk for a given return

See OHP For Empirical Results 2
Main Findings
Higher PF portfolio returns required, higher
proportion allocated to equities, (OECD and
EMEs ) consistent with financial theories
 Under all scenarios, foreign assets do not
account for an important share of OECD
PFs, i.e. around 5-10%. Explain the “home
bias” puzzle?
 Our results give evidence of the
diversification benefits from investing in
property (Booth 2002)

Findings Summary





After a shift from PPR to QAR, on average, risk
increases by 41% for EMEs PF, while by 4% for
OECD PF.
After a shift from PPR to QAR, on average, Sharpe
ratio drops by 20% for EMEs PF, while by 3% for
OECD PF.
As regards optimal portfolio part, there is evidence
that higher return required, more allocated to equities
In addition, foreign assets in OECD PF’s optimal
portfolio always do not account for a large share
(Home bias)
Meanwhile, the importance of investing in alternative
assets, e.g. property is found.
Policy Implications
From the financial perspective, foreign
investment restriction on PFs is not justified
 Investment restrictions on alternative assets,
e.g. property, (maybe hedge funds?) need to
be eased

Cautions
The M-V approach may be only, or most
relevant to DC plans
 Preconditions needed for EMEs to take
advantage of these diversification benefits,
e.g. sound banking systems, relatively
experienced regulators (Davis 2005; Blake
2003; Mitchell 1998; Vittas 2000)

THANK YOU FOR YOUR
ATTENTION!
^_^