How the scientist invested and won
Three years ago, we posed the question, How would a scientist construct a portfolio?. The results are in and the investment performance is as the scientist predicted.
In 2013 the CSIRO-Monash Superannuation Research Cluster released a paper Is fundamental indexation able to time the market? Evidence from the Dow Jones Industrial Average, concluded that equal weighting is the “highest performing” structure for a portfolio, better than market capitalisation and better than fundamental indexation.
The paper tested United States data for the years 1962 to 2009. United States data is used because this is the largest reliable data set available. The results are that investing $1 in 1962 would grow to:
- $100.86 in an equally weighted portfolio;
- $87.28 in a fundamental indexation portfolio; and only
- $59.04 in a market capitalisation portfolio.
Sophisticated models developed by such finance luminaries as Nobel Prize winning economist Eugene Fama and Robert Merton were used to determine the source of this outperformance. The conclusion is that equally weighting a portfolio outperforms market capitalisation because of three factors:
- higher exposure to smaller stocks rather than to bigger stocks;
- higher exposure to so-called ‘value stocks’, meaning those stocks with a high book-to-market ratio; and
better market timing.
- What the paper means by market timing is that equal weighting extracts more return when markets are rising and loses less when markets are falling.
Intrigued by the results, the research cluster tested its finding further in a 2015 study, The Viability of Alternative Indexation when Including All Costs. The new paper assessed the viability of the same indexing methods as the previous study but took into account all transaction costs using different rebalancing frequencies, trade sizes and fund sizes. Different fund sizes were considered as execution shortfalls can result in performance issues. These are known as capacity constraints. For each of the three fund sizes – $500 million fund (small), $1 billion (medium) and $10 billion fund (large) – the equal weight strategy was the best performer in terms of geometric returns and Sharpe ratios.
The authors however did find that equal weight indexing was capacity constrained due to liquidity constraints. This criticism can be overcome with effective index design. The design of an equal weight index should apply liquidity and size filters so as to increase the capacity at which it can be traded.
Australia’s first and only Australian equity equal weight ETF, VanEck Vectors Australian Equal Weight ETF ( MVW) tracks the MVIS Australia Equal Weight Index. It includes only the largest and most traded ASX securities thereby avoiding capacity constraints.
MVW has recently had its third anniversary and consistent with the research it has outperformed the market capitalisation based S&P/ASX 200 Accumulation Index. It did so by an average of 3.86% p.a. over the three years to 31 March 2017 returning 11.39% p.a. compared to 7.53% p.a.
In the highly concentrated Australian equities market, equally weighting a portfolio has delivered investors significantly improved diversification and reduced stock and sector concentration.
MVW has proven equal weighting is well suited to the highly concentrated Australian equities market, with passive outperformance that cannot be ignored.