The portfolio is designed to exhibit high correlation with the ASX200, yet with a distinct value bias – systematically adopting overweight positions in companies that are trading at lower than average valuation multiples, and underweight positions in those that are trading at above average multiples.
This systematic approach avoids the common cognitive biases that affect most investors, ultimately detracting from their performance. It also allows the strategy to be rigorously tested, enabling a far better understanding of its risk and return characteristics.
In our own testing of the strategy over the 20 years to December 2013, the portfolio outperformed the market by an average of almost 3% per annum, with risk adjusted returns more than 25% greater than the benchmark index.
Whilst the fundamental assumption underlying traditional financial market theory remains that markets are generally efficient, there are a number of anomalies that have been identified that show this is not always the case. Perhaps the most well documented and extensively researched of these is the ‘value effect’ – the observation that stocks with low market prices relative to their fundamental value (value stocks) tend to outperform stocks with high market prices relative to their fundamental value (growth stocks).
Numerous empirical studies have been undertaken examining the value effect – both attempting to confirm its existence, and more recently attempting to explain why it exists and has persisted for such a long period of time.
One of the first studies to prove the existence of the ‘value effect’ was conducted by Sanjoy Basu (1977), who found a significant negative relationship between Price to Earnings ratios and average returns for US stocks. Similar results have been obtained through examination of Price to Book multiples (Stattman 1980; Fama and French 1992), Price to Sales (Fisher 1984), and Dividend Yield (Fama and French, 1988; Siegel, 2005).
In recent years, research has increasingly shifted from proving the existence of the ‘value effect’, to explaining its remarkable persistence. Whilst many theories exist, in our view the most intuitively appealing explanation attributes the persistence of this anomaly to cognitive biases that can lead to over-reaction and under-reaction on the part of investors (De Bondt and Thaler, 1985; Barberis, Shleifer and Vishny, 1998). Cognitive biases such as representativeness (investors over-reacting to trends in data) and conservatism (investors reacting too slowly to new and surprising data points) lead to investors consistently mis-pricing securities, resulting in lower long-term returns.
By utilising an entirely systematic portfolio construction approach with a value bias, we are able to eliminate the potential to be influenced by these damaging cognitive biases, and instead ensure that our portfolio is positioned in such a way as to profit from the remarkably persistent ‘value effect’.
The objective of our own portfolio research was to identify an entirely systematic way to construct a diversified, blue-chip Australian equities portfolio, with a high degree of correlation with the ASX200 Index, yet with a distinct value bias – allowing us to profit from the well documented benefits of the ‘value effect’.
Focusing on the key valuation metrics most commonly examined in the academic literature (Price to Earnings, Price to Sales, Price to Book and Dividend Yield), we generated an adjustment factor that could be applied to market-capitalisation weightings, to systematically adopt over-weight positions in stocks that were trading at below average valuation multiples, and under-weight positions in stocks trading at above average multiples.
By examining stocks in relation to all four metrics, we reduced the likelihood of unintentional skews as a result of anomalous data points in any single factor. In order to minimise transaction costs and maximise tax-efficiency of the portfolio, the portfolio was set to be re-balanced on an annual basis.
The results of our testing correspond broadly with the conclusions of previous studies. The generated portfolio*1 outperformed the market by almost 3% per annum over the entire testing period (January 1994 – December 2013), and by a more modest, but still significant 1.8% per annum over the last 10 years to December 2013. Outperformance of the index was also relatively consistent, with positive outperformance recorded in 16 of 20 years tested.
The increased returns did come at the expense of slightly higher risk, with standard deviation of returns for the Bellmont Core Equity of 17.52%, compared with 16.95% for the index. This slight increase in risk was more than offset by the increased returns however, with risk-adjusted returns (Sharpe ratio) of 0.45 vs 0.36 for the index.
A summary of the performance statistics can be found below:
|Average Return (1994-2013)||Average Return (2004 – 2013)||Standard Deviation||Sharpe Ratio|
|Bellmont Core Equities Portfolio||13.58%||13.96%||17.52%||0.4547|
|ASX 200 Accumulation Index||10.59%||12.13%||16.95%||0.3616|
Stattman D. (1980). Book values and stock returns. The Chicago MBA: A Journal of Selected Papers, 4, 25-45.
Fisher, K. (1984). Super Stocks, Dow Jones-Irwin
Siegel, J. (2005). The Future for Investors, Crown Business
*1 All data quoted under the title “Our Research Results” are the result of back-testing and do not represent actual performance of any client account. The information is based, in part, on hypothetical assumptions made for modeling purposes that may not be realised in the actual management of portfolios. No representation or warranty is made as to the reasonableness of the assumptions made or that all assumptions used in achieving the returns have been stated or fully considered. Alternative modeling techniques or assumptions might produce significantly different results and prove to be more appropriate. Past hypothetical, back-test or simulated results are neither indicators nor guarantees of future returns. Unlike an actual performance record based on trading actual client portfolios, hypothetical, back-tested or simulated results are achieved by means of the retroactive application of a back-tested model itself designed with the benefit of hindsight. The back-tested performance includes hypothetical results that do not reflect the deduction of advisory fees, brokerage or other commissions, and any other expenses that a client would have paid.
|Portfolio Value||Total Fee|
|$50,000 – $499,999||1.30% *|
|$500,000 – $1,000,000||1.10% **|
|> $1,000,000||0.90% ***|
The above management fees are payable, monthly in arrears.
|Portfolio Value||Total Fee|
Bellmont Direct Accounts are available to investors who have over 1 million invested with Bellmont.
The minimum investment for a Bellmont Core Equity Portfolio is $50,000.
All figures quoted are exclusive of GST
Brokerage on Managed Account transactions will be charged at 0.10%
* Managed Account Fee Breakdown: Custody & Administration 0.40% Investment Management 0.90%
** Managed Account Fee Breakdown: Custody & Administration 0.40% Investment Management 0.70%
*** Managed Account Fee Breakdown: Custody & Administration 0.40% Investment Management 0.50%