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http://www.sundaytimes.lk/110220/BusinessTimes/bt34.html
You’d probably guess it isn’t too hard to categorize slime mold, the somewhat yucky green stuff you get in damp places. But you’d be wrong. As it turns out, slime mold has some strange behaviour – so strange, in fact, that it stumped scientists for centuries.
When food is abundant, slime mold cells operate as independent single-celled units. They move around, eat bacteria, and divide to reproduce. When food is in short supply, however, the slime-mold cells converge and form a cluster of tens of thousands of cells. The cells literally stop acting as individuals and start acting like a collective. That’s why slime mold is so hard to categorize: it is an “it” or a “they” depending on the circumstance.
Investment approaches based solely on attributes, without considering the circumstances, also don’t make much sense. Sometimes a stock that looks expensive is cheap, and what looks cheap is expensive. It’s context dependent.
Yet the investment industry is full of attribute-based analysis and expects professional investors to stick with such absurd criteria. Growth style investors try and beat the market by filling their portfolios with companies that are rapidly increasing sales and earnings, without too much concern about valuation. Value style investors load up on cheap stocks with a decent yield and consider corporate growth.
Most money managers actually believe their attribute-based investment style-combined with their skill, will generate market-beating results. These various investment approaches are grounded in theory: a belief that investor actions will lead to satisfactory outcomes.
The word “theory,” however, makes most investors and corporate managers leery because they associate theory with theoretical which implies impractical. But if you define theory as a contingent explanation of cause and effect, it is eminently practical. A sound theory helps predict how actions or events lead to specific outcomes across a broad range of circumstances.
The main message is that much of the investment theory is unsound because it’s based on poor categorization. The same is true for much of the management theory. More specifically, investors generally dwell on attribute-based categorizations (like low multiples) versus circumstances based categorizations. A shift from attribute- to circumstance-based thinking can be of great help to investors and managers. Take a lesson from slime-mold.
In a thought provoking paper, Clayton Christensen, Paul Carlile and David Sundahl break the process of theory building into three neat parts. The first task is to describe what you want to understand in words and numbers. In this stage, the goal is to carefully observe, describe, and measure a phenomenon to be sure that subsequent researchers can agree on the subject. Stock market performance is a good example of a phenomenon that requires good theory. Today we take for granted the descriptive phase of the market. The first major quantitative performance study of any stock market was undertaken only as recently as 1964 by Lawrence Fisher for US equities.
The second part of theory building requires classification of the phenomena into categories based on similarities. This step is intended to simplify and organise, so that it differences between phenomena can be classified. The investing world is full of categories, including value vs. growth, large vs. small capitalization, cyclical vs. non-cyclical etc. These categories are deeply ingrained in the investment world and many firms have built their businesses on their validity.
Finally, it’s important to build a theory that explains the behaviour of the phenomena. A robust theory based on sound categorization explains case and effect, why the cause and effect works, and most critically under what circumstances the cause and effect operates. Importantly, a theory must be falsifiable.
The investment world is filled with theories about investment returns. Proponents of the efficient-market theory argue that no strategy exists to generate superior risk-adjusted investment returns. Active money managers (and most brokers) pursue myriad strategies based on the theory that their approach will lead to excess returns.
Proper categorization is critical for good theory. Theories evolve from attribute-based categories to circumstance-based categories as they improve - theories that the rest of circumstance-based categories tell practitioners what to do in different situations. In contrast, attribute-based categories prescribe action based on the traits of the phenomena.
This is important for investors who often rely on attribute-based categories. One example is low-price-earnings-multiple investing, often a central plank in value investing. An investor would have fared poorly for the last 125 years (based on US data) using this thesis to time in (when PE’s are low) and out (when PE’s are high) of the market. This doesn’t mean that low PE’s are bad but does mean that buying the market when the PE is low is not a valid theory for generating superior long-term returns.
All investors use theory, either wittingly or unwittingly. The lesson from the process of theory building is that sound theories reflect context. Too many investors cling to attribute-based approaches and wring their hands when the market doesn’t confirm to what they think it should do.
http://www.sundaytimes.lk/110220/BusinessTimes/bt34.html
You’d probably guess it isn’t too hard to categorize slime mold, the somewhat yucky green stuff you get in damp places. But you’d be wrong. As it turns out, slime mold has some strange behaviour – so strange, in fact, that it stumped scientists for centuries.
When food is abundant, slime mold cells operate as independent single-celled units. They move around, eat bacteria, and divide to reproduce. When food is in short supply, however, the slime-mold cells converge and form a cluster of tens of thousands of cells. The cells literally stop acting as individuals and start acting like a collective. That’s why slime mold is so hard to categorize: it is an “it” or a “they” depending on the circumstance.
Investment approaches based solely on attributes, without considering the circumstances, also don’t make much sense. Sometimes a stock that looks expensive is cheap, and what looks cheap is expensive. It’s context dependent.
Yet the investment industry is full of attribute-based analysis and expects professional investors to stick with such absurd criteria. Growth style investors try and beat the market by filling their portfolios with companies that are rapidly increasing sales and earnings, without too much concern about valuation. Value style investors load up on cheap stocks with a decent yield and consider corporate growth.
Most money managers actually believe their attribute-based investment style-combined with their skill, will generate market-beating results. These various investment approaches are grounded in theory: a belief that investor actions will lead to satisfactory outcomes.
The word “theory,” however, makes most investors and corporate managers leery because they associate theory with theoretical which implies impractical. But if you define theory as a contingent explanation of cause and effect, it is eminently practical. A sound theory helps predict how actions or events lead to specific outcomes across a broad range of circumstances.
The main message is that much of the investment theory is unsound because it’s based on poor categorization. The same is true for much of the management theory. More specifically, investors generally dwell on attribute-based categorizations (like low multiples) versus circumstances based categorizations. A shift from attribute- to circumstance-based thinking can be of great help to investors and managers. Take a lesson from slime-mold.
In a thought provoking paper, Clayton Christensen, Paul Carlile and David Sundahl break the process of theory building into three neat parts. The first task is to describe what you want to understand in words and numbers. In this stage, the goal is to carefully observe, describe, and measure a phenomenon to be sure that subsequent researchers can agree on the subject. Stock market performance is a good example of a phenomenon that requires good theory. Today we take for granted the descriptive phase of the market. The first major quantitative performance study of any stock market was undertaken only as recently as 1964 by Lawrence Fisher for US equities.
The second part of theory building requires classification of the phenomena into categories based on similarities. This step is intended to simplify and organise, so that it differences between phenomena can be classified. The investing world is full of categories, including value vs. growth, large vs. small capitalization, cyclical vs. non-cyclical etc. These categories are deeply ingrained in the investment world and many firms have built their businesses on their validity.
Finally, it’s important to build a theory that explains the behaviour of the phenomena. A robust theory based on sound categorization explains case and effect, why the cause and effect works, and most critically under what circumstances the cause and effect operates. Importantly, a theory must be falsifiable.
The investment world is filled with theories about investment returns. Proponents of the efficient-market theory argue that no strategy exists to generate superior risk-adjusted investment returns. Active money managers (and most brokers) pursue myriad strategies based on the theory that their approach will lead to excess returns.
Proper categorization is critical for good theory. Theories evolve from attribute-based categories to circumstance-based categories as they improve - theories that the rest of circumstance-based categories tell practitioners what to do in different situations. In contrast, attribute-based categories prescribe action based on the traits of the phenomena.
This is important for investors who often rely on attribute-based categories. One example is low-price-earnings-multiple investing, often a central plank in value investing. An investor would have fared poorly for the last 125 years (based on US data) using this thesis to time in (when PE’s are low) and out (when PE’s are high) of the market. This doesn’t mean that low PE’s are bad but does mean that buying the market when the PE is low is not a valid theory for generating superior long-term returns.
All investors use theory, either wittingly or unwittingly. The lesson from the process of theory building is that sound theories reflect context. Too many investors cling to attribute-based approaches and wring their hands when the market doesn’t confirm to what they think it should do.
