This post is the second of two based on Shane Parrish's Knowledge Project interview with Philip Tetlock, co-principal investigator of The Good Judgement Project, author of 'Superforecasting: The Art and Science of Prediction', and a professor at the Wharton School.
All investment decisions are based on present expectations of the weighted average of the various futures that could unfold with time. That's a mouthful, but the essence of the issue is that in order to arrive at a future value for a company, we must make assumptions about multiple factors, each of which can materially alter the 'intrinsic' (expected) value of a business. So, investors deal in forecasts. In this post I will discuss briefly three ways in which the quality of our forecasts can be improved, and suggest applications for investment committees.
Guesstimating
A good place to begin forecasting is guesstimating. Making guesstimates allows us to identify gaps in our knowledge, clearing up the zone of ignorance. Making guesstimates also enables us to review our assumptions when evaluating the quality of a forecast.
A good place to begin forecasting is guesstimating. Making guesstimates allows us to identify gaps in our knowledge, clearing up the zone of ignorance. Making guesstimates also enables us to review our assumptions when evaluating the quality of a forecast.
Forecasting teams
Some investors swear by a committee-based approach to asset allocation. The idea is this will result in ideas being challenged and hypotheses being questioned, reducing the impact of biases and the potential for errors. There is some merit to this approach, but often organisational hierarchy and homogenous information limit its benefits. Forecasting teams can be made more effective if individuals' success rates are tracked, and a weighted average of forecasts, which gives more weight to individuals with stronger track records in the relevant industry, is used. Forecasting teams can be made even more effective if they have access to distinct pools of information because decisions made when different pools of data point in the same direction, are likely to be more accurate. In the investing world, this is very difficult to achieve, but could still be partially achieved by splitting sources (annual reports, sell-side reports, company management meetings, and data analytics) encouraging team members to research each company independently and arrive at a conclusion before a discussion.
Some investors swear by a committee-based approach to asset allocation. The idea is this will result in ideas being challenged and hypotheses being questioned, reducing the impact of biases and the potential for errors. There is some merit to this approach, but often organisational hierarchy and homogenous information limit its benefits. Forecasting teams can be made more effective if individuals' success rates are tracked, and a weighted average of forecasts, which gives more weight to individuals with stronger track records in the relevant industry, is used. Forecasting teams can be made even more effective if they have access to distinct pools of information because decisions made when different pools of data point in the same direction, are likely to be more accurate. In the investing world, this is very difficult to achieve, but could still be partially achieved by splitting sources (annual reports, sell-side reports, company management meetings, and data analytics) encouraging team members to research each company independently and arrive at a conclusion before a discussion.
History rarely repeats itself...
...but it does rhyme. Mark Twain's eloquent quotation is often used to emphasise the importance of using past data and patterns in investment decision making. Tetlock's work cautions against over-learning patterns in history. Perhaps we should pay equal attention to both parts of Twain's wise words, as we continue to rely on the only truly concrete information available to us.
...but it does rhyme. Mark Twain's eloquent quotation is often used to emphasise the importance of using past data and patterns in investment decision making. Tetlock's work cautions against over-learning patterns in history. Perhaps we should pay equal attention to both parts of Twain's wise words, as we continue to rely on the only truly concrete information available to us.
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