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PENSION FUND INVESTMENT AND REGULATION - A MACRO-STUDY

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.

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PENSION FUND INVESTMENT AND REGULATION - A MACRO-STUDY

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  1. 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

  2. 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

  3. 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)

  4. 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)

  5. 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)

  6. 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

  7. Sharpe Ratio • Measures the magnitude of the reward-to-risk • Definition: Return/Risk; Risk: standard deviation

  8. 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.

  9. See OHP For Empirical Results 1

  10. 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

  11. See OHP For Empirical Results 2

  12. 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)

  13. 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.

  14. 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

  15. 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)

  16. THANK YOU FOR YOUR ATTENTION! ^_^

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