Assessing the Long Term Return of Australian Superannuation Funds

Transcription

1 Assessing the Long Term Return of Australian Superannuation Funds Dr. Banita Bissoondoyal-Bheenick Prof. Robert Brooks Mr. Warren McKeown Assoc. Prof. Xibin Zhang ASI Conference 6 th Sept 2017

2 Agenda Introduction Objective of Research Contribution Key Research Questions Data and Modelling Framework Results Conclusion 2

3 Introduction Being one of the countries with highest investment, Australian Superfunds tend to be more active in the asset allocation decision They are well known to have very low investment portfolios around conservative assets. In Australian superfunds held equity at round 40-50% -similar to the United states Australia superfunds investment in equity is one of the highest - more than 50% of their assets in equities directly or indirectly 3

4 Objective/Aim of Research Given the high level of returns reported as well as the large losses reported by the superfund industry in Australia, the focus on this study is to provide a comprehensive analysis of the returns of the superfund industry. The aim of the project is to assess the risk-return trade-off in the long term for the Australian superannuation funds. Hence, we assess what mix is more appropriate for superannuation fund members and what differences may be observed among the various portfolios over a sustained period of market volatility? 4

5 Contribution Modern portfolio theory in finance suggests a risk-averse investor can construct portfolios to optimize or maximize expected return based on a given level of market risk. Our first contribution: While most of the analysis has been undertaken in the US market, the key contribution of our study is to assess whether the high risk and high return theory holds for Australian Our second key contribution: The second key contribution will be to the time diversification literature that is assessing the relationship between investment risk and the investor s time horizon. 5

6 Key Research Questions Our analysis addresses the following key issues: Is the performance of a multisector aggressive category better than a multisector moderate option over the longer term? If multisector aggressive outperform in the long term: how long is long term? What is the impact of a financial crisis on the return behaviour? 6

7 Data and Modelling Framework The empirical analysis is primarily based on the Morningstar Direct database. The sample period is 27 years from January 1990 to December The choice of the data period captures a few key dates: 1992: Superannuation Guarantee was introduced, periods of high volatility including the South East Asian crisis in 1997 to 1998, the GFC from mid-2007 to 2009, and Chinese stock market volatility from August 2015 to February 2016, 7

8 Data and Modelling Framework We obtain the monthly price index of the superannuation funds for the period 1990 to December We also obtain the historical monthly asset allocation of the funds for our sample period. The historical monthly asset allocation is available for the various asset classes which include, cash, domestic and international fixed interest, domestic and international shares, domestic and international listed property as well as unlisted property. Our initial sample consists of 1213 super funds in Australia. 8

9 Data and Modelling Framework While there are various classifications that can be used to provide investment options, we classify the funds in four broad categories and follow the definition provided by Canstar. We consider the Multi-Sector Aggressive, Multi-Sector Growth, Multi-Sector Balanced, and Multi-Sector Moderate categories 9

10 Data and Modelling Framework We clean the data and keep only those super funds that belong to the following four categories. Consequently, we have 862 super funds which include 116 funds from "Moderate" category, 87 funds from "Balanced" category, 184 funds from "Growth" category and 475 funds from "Aggressive". The high number of funds in the multi-sector aggressive category for the sample period shows the active asset allocation of Australian superannuation funds. 10

11 Results- Return Analysis Summary statistics of monthly raw return of super funds for the whole sample period from January 1990 to December 2016 across the four categories Moderate Balanced Growth Aggressive % % % % Maximum % % % % Minimum % % % % Count

12 Results- Return Analysis Estimated average annual returns for four categories for the whole sample period. 12

13 Results- Return Analysis Cumulative average annual returns for four categories for the whole sample period. 13

14 Results- Return Analysis Over both the 5 year and 10 year rolling window, on average, the multi-sector growth and multi-sector aggressive funds return outperform the returns of a multi-sector balanced and multi-sector moderate fund. The periods where the aggressive and growth funds have lower returns is mainly due to the GFC effect. Over the five year rolling window, the period 2005 to 2009 and over the 10 year rolling window, over the years 2000 to 2009, the returns are lower for the aggressive fund. Our results are consistent with the current market outlook, see for example returns published by Chantwest in April

15 Analysis of Return Behaviour over time Following the initial return analysis, we focus on whether the returns display mean reversion. A reversion involves the return will be back to the original state, that is as the return moves away from its normal value in the short term, it is expected that it will eventually return to its normal range over the longer term. The mean reversion is used in statistics to understand trading strategies. This strategy is based on the premise that at some point the market will revert to its normal pattern. The risk however is that the return to a normal trend is not guaranteed and hence we end up with a mean aversion. 15

16 Analysis of Return Behaviour over time The % of super funds exhibiting mean reverting and mean averting during whole sample period. Moderate Balanced Growth Aggressive Reverting Averting Reverting Averting Reverting Averting Reverting Averting VR(k) <1 >1 <1 >1 <1 >1 <1 >1 1 year year year year year Long horizon 6 year year year year year year year year year year

17 Analysis of Return Behaviour over time The % super funds exhibiting significant mean reverting and mean averting at 5% during whole sample period based on Bootstrap p- values. Reverting Moderate Balanced Growth Aggressive Averting Reverting Averting Reverting Averting Reverting Averting VR(k) <1 >1 <1 >1 <1 >1 <1 >1 1 year year year year year Long horizon 6 year year year year year year year year year year

18 Analysis of Return Behaviour over time The table showing the statistical significance shows that for super funds in the "Aggressive" category, more than 60 super funds exhibit significant mean reversion in returns at long horizons. Further, for the multi-sector growth fund and multisector aggressive, we have up to 100% mean reversion over the longer term. Hence, our key conclusion is that over the short term we have mean aversion and over the longer term we have mean reversion across all four categories of the funds. 18

19 Results Crisis Analysis We consider three financial crisis periods: 1997 Asian crisis period from May Dec 1998; 2002 Dot.com burst period from Jan 2000-Dec 2002; 2007 sub-prime crisis period from July 2007-March 2009 We equally analyse the post crisis period (mainly short term- 6 months post crisis) 19

20 Results Crisis Analysis Note we have results for the other crises, but we are presenting only the results of the 2007 crisis, that is the GFC Crisis Moderate Balanced Growth Aggressive Reverting Averting Reverting Averting Reverting Averting Reverting Averting VR(k) <1 >1 <1 >1 <1 >1 <1 >1 2 months months months months months

21 Results Crisis Analysis Post GFC 2007 crisis Return Behaviour Post Crisis 2007 Moderate Balanced Growth Aggressive Reverting Averting Reverting Averting Reverting Averting Reverting Averting VR(k) <1 >1 <1 >1 <1 >1 <1 >1 2 months months months months months

22 Results Crisis Analysis During the 2007 crisis, 66.67% of the funds are mean averting and only 33.33% is mean reverting based on variance ratios with 6-month holding period in the Multisector- Aggressive option. During the post 2007 crisis period we have mostly a mean averting pattern. The key difference of the crisis period as compared to the previous results is the mean averting pattern, however this is mainly over a shorter window. 22

23 Conclusion Our key findings can be summarized as: (1) on average, the risk-return trade off seems to hold in the Australia context over the longer term, that is, the return of aggressive and growth funds are better over the longer term; (2) the returns are mean averting in the short term and from a period of 5 years and above the returns seem to be mean reverting over the longer term horizons and hence, mean reversion or mean aversion is a function of the investment horizon and (3) post GFC, the returns indicate to be mean averting rather than mean reverting, but mainly over the short term. 23

24 Thank you very much. 24