A new research group, formed by Momentum Investments, North-West University and the University of Pretoria, say that a significant investment performance gap exists between South African individual investors measured against a well-diversified portfolio.<\/p>\n
As part of the study, investment decisions of approximately 17,600 individual investors were followed over the last decade.<\/p>\n
Initial results point towards the existence of a significant negative ‘behavioural gap’ between investment returns of individual investors, compared to returns on a well-diversified investment portfolio.<\/p>\n
The researchers found that during a period of market turmoil, such as the 2008-2009 crisis, 1 in 2 individual investors underperform by 1.1% per year. During ‘normal’ market conditions, 1 in 4 investors underperforms by 1% per annum.<\/p>\n
“Over a 20-year time horizon, such underperformance could lead to a cumulative underperformance gap of between 22% and 24%,” the researchers said.<\/p>\n
“The results confirms research by Barclays Wealth in the United Kingdom that revealed a gap that would cost investors 21% of their retirement fund over a 20-year horizon.”<\/p>\n
Other notable statistics include:<\/p>\n
Over the past 10 years, there was a marked increase in individuals that opt towards making their own investment decisions. The research group set out to gain a better understanding of the factors that influence such investment decisions by individuals.<\/p>\n
“It is well known that individual investors often tend to overreact to short term market movements. A phenomenon referred to as \u201cherding\u201d, where individuals react in a similar way to short term market information, could lead to overreaction and painful losses,” the researchers said.<\/p>\n
“Information that spreads at immensely high speed \u2013 even though it may not be true \u2013 could nudge numerous investors into making significant decisions about where their money is placed.”<\/p>\n
Next steps for the research group include a deeper understanding investor behaviour through advanced statistical and machine learning techniques \u2013 this will enable the creation of an \u201cearly warning\u201d tool whereby investors could be alerted in a timely fashion about potential market conditions and the potential impact of their investment decisions.<\/p>\n