PENSION FUND INVESTMENT AND REGULATION - A MACRO-STUDY

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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

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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

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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)

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Mean-Variance Approach

• 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)

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Research Objectives

• 1. The central question in this paper is
  whether
• restrictions on PFs foreign investment
  are
• justified
• 2. In addition, what is PFs 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)

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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

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Sharpe Ratio

• Measures the magnitude of the reward-to-risk
• Definition Return/Risk Risk standard deviation

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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 OECD16EMEs
• Data sources Global Financial Data, Datastream,
  etc.

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See OHP For Empirical Results 1
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Optimal PFs Portfolio Composition, Under The M-V
Framework

• Considered 3 real return levels, i.e. 3, 5 and
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• 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

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See OHP For Empirical Results 2
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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)

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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 PFs 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.

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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

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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)

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THANK YOU FOR YOUR ATTENTION! _