Intellectual self-discipline
One of the most important ways we manage biases is simply to be aware of them when we make investment decisions. We will ask ourselves ‘am I being influenced by anything other than fundamental, rational reasons? Does the evidence support my view?'
Playing devil’s advocate
One way to ensure that decisions are being made without bias is to follow the ‘devil’s advocate’ approach. Once we have reached a conclusion, we will try to build a counter-argument as best as we can. This can be difficult, but it is important to be as thorough as possible and to compare the opposing arguments before making a final decision.
We look at the whole picture
When creating or reviewing our investment strategies we look at a number of different areas as part of our macroeconomic overview. We set out a number of specific factors and measures in advance to monitor at a top level. This prevents us from cherry-picking those data that support our views (therefore resisting confirmation bias), while also allowing us to dig deeper and gain a better insight into specific economic factors.
We focus on the fundamentals
Our starting point when investing is to look at fundamentals (such as company earnings or specific elements of the economic backdrop) and how the market is pricing these. This keeps our investment strategy on the correct, long-term path while also looking out for mispriced risks and opportunities. When there are sharp moves in markets, the first question we usually ask ourselves is ‘has anything happened to change our fundamental assumptions?’ which helps us resist emotional biases such as loss aversion.
We work as a team
We have an Asset Allocation Committee that works together on any changes to our asset models, rather than relying on an individual’s views. We believe it is important to maintain a culture that promotes friendly challenges to views and encourages robust discussions around all investment decisions.
We use statistical techniques
When looking at data, we use statistical techniques to ensure that relationships are statistically significant. A line of best fit may look like it has a trend, but we need to crunch the numbers to be sure.
The human brain is predisposed to find patterns – that’s why people often see shapes and faces in clouds. It’s very good at pattern recognition, but problems arise when there are a lot of noisy data and the brain tries to find patterns. Statistical techniques help us to resist seeking out patterns in what is effectively just noise.
