Most investing can be considered, either: emotional, reactionary or noise-driven. Investors often hunger for an inside scoop on what the market will do based on an event, be it a real event or imagined. However one of the keys to investment success is, quite simply, to avoid the noise. The constant drumbeat of extraneous information and actions based upon this noise is considered behavioral. Evidence-based investing is essentially the opposite of behavioral investing.

Why use the evidence based approach?

There is now a growing movement among the financial advice profession and among investors to base decisions on what has been shown to work in a disciplined approach to asset management. So that where others would use forecasts, relationships or emotions to guide their decisions, practitioners of evidence based investing, or EBI as it is sometimes referrred to is substituted for facts, logic and reason. It’s about making decisions based on things that we know are factually true rather than guess work.

The origins of evidence based investing parallel evidence-based medicine. This method  essentially accepted research to optimize the decision-making thought process for the best outcome for the patient.  Sticking to the medical thesis, why would a doctor recommend a different, more costly solution if the current path to wellness has been proven time and again?

What are the origins of evidenced based investing?

Beginning in the 1950’s, academic researchers began to apply scientific methods to the study of finance and markets. Over the course of the next several decades, from this enormous body of work, EBI was born, and today’s fortunate investors are able to benefit from this valuable research.

In the investing world, this translates to a goal of using current evidence to help maximize an individual’s investment returns while minimizing risk from market downturns. In more simplistic terms, evidence-based investing means that whatever you decide to do, make sure you have an evidence-based reason for doing it, and always be prepared to amend your plan when the evidence necessitates a change.

What is the factor – based model?

The adoption of factor investing is accelerating. One reason it is increasingly being embraced is that portfolio return expectations are evidence based. Although much of the evidence consists of repeated analysis of the very data sets used to derive an investment model in the first place,  the risk premiums earned from factor investing over very long periods (up to 117 years) and across many markets (up to 23) report on the long-term profitability of following strategies based on market capitalization, value versus growth, dividend yield, stock-return momentum, and low-volatility investing.

With factor-based investing, historically the data shows that if your holdings have a bias toward small-cap, toward cheaper valuations, and toward high quality over long periods of time, you’ll likely do better than the market, because history shows us that stocks with those characteristics, on average, statistically tend to outperform the benchmark.

Fama & French are renowned for devising the original Three-factor model. The Three Factor Model replaced Capital Asset Pricing Model (CAP-M) as the most widely accepted explanation of stock prices in the aggregate and investor returns. The model separates stock returns into three distinct risk factors:

(1) Market risk

(2) The outperformance of small versus big companies

(3) The outperformance of high book versus small book/market companies.

So the main factors driving expected returns are sensitivity to the market, sensitivity to size, and sensitivity to value stocks, as measured by the book-to-market ratio.

Utilizing this model and aiming for increased expected returns that do not rely on any magic performance by an active manager takes a long step forward in turning investment management from voodoo science into a real discipline.

Whether you favour the evidence based and factor based model or not, with any investment it is important to stay the course. Learn to recognize noise, and then learn to tune it out. This will almost always lead to better investment results.