Translating academic theory into evidence-based investing

When it comes to investing, there’s loads of guidance at your fingertips. The newspapers publish regular fund manager views and online platforms all have ‘selected’ stocks which they recommend to secure strong returns. They’ve done all the hard leg work; all you need to do is choose from among the ‘likely’ winners they’ve filtered out. It seems too good to be true; and it is.

The trouble starts when investors go back to look at the chosen funds; they can be dogged by the thought that the results are never quite as good as they expected; even with ‘good market performance’.  Still, investment is a long-term game; there is no point in bailing out early unless you have chosen a real dud fund, right? Some even wonder whether experiencing the highs and lows is the only way to get to grips with how to invest… Most don’t even think of the question, which is worse.

It is a little-known fact that scientists and researchers at universities globally have been looking into this conundrum for over 65 years. Starting back in 1952, one researcher discovered that combining stocks of different characteristics in a portfolio would lead to an overall better return, with fewer of the ‘ups and downs’ along the way; portfolio construction became important.  Building on this in the early 1960s, other researchers independently concluded that the best ‘risk-reward trade off’ was to hold the entire stock market in proportion, balancing this by cash or debt to lower or increase the risk; not putting all your eggs into one basket.  Yet another one could discern the ‘efficiency of markets’: prices adjust rapidly, albeit not perfectly, to new information, so that the market price is fair and reliable.  

Over the next 20 years, the advent of computing power offered researchers a greater understanding of share price movements in a new model. Whilst holding the market was an efficient thing to do, being exposed to the market, however, was not a ‘single risk’ question.  Numerous studies pointed to anomalies in the model before academic research, validated by ‘peer review’, concluded that these anomalies, enhanced the model.  They were actually dimensions of ‘risk and reward’ which could be used reliably to enhance portfolio performance.  They can be summarised into four: smaller companies, value companies, profitable companies and share price momentum.  By exposing a portfolio progressively to these factors, a better investment experience is obtained.  In this way, advances in investing were validated by empirical research, not from idle theorising.  

So far so good, but how does this help you to meet your investment goals?

Evidence-led investment is the best solution and is how professional advisers construct portfolios, for individual and institutional clients. This approach respects the advances offered by 65 years of academic research.  When combined with a low-cost approach to investment, it contributes to effective portfolios which can be backed by independent, third party data to show that you’re still on the right track every step of the way. 

When you add it all up, it’s common-sense investing, really!