Wednesday, December 17, 2014

WYSIATI and systematic trading



Nobel Prize winner Daniel Kahneman's core insight describing the faulty thinking of many decision-makers is found in odd acronym, WYSIATI. It stands for "What You See Is All There Is." Decision-makers want to jump to conclusions quickly, but there is a problem for many when they only see what is immediately available and not what may be lurking behind the scenes. WYSIATI thinking focuses on the obvious and not what could be most important. It is easier and faster to think this way. It is associated only with the "known knowns" and does to anticipate the "unknowns" or what is not immediately obvious.

WYSIATI represents the problem when we use our system 1 or fast thinking and not our deductive reasoning skills or system 2 slow thinking. Kahneman often refers to WYSIATI in the context of information. When decisions rely on the  information that immediately available as the complete set of information that is needed, investors are likely to make a faulty decision. When investors have to make quick decisions, they will likely believe that they have complete information. In those situations, investors will too often jump to conclusions. This would be the misuse of system 1 or fast type of thinking.

If the information is difficult to find or obtain, again it is more likely investors will assume that what is currently available is the complete set of information that is necessary for making a decision. Decision-makers like to feel in control and one of the easiest ways to ensure that control is to believe that you have complete information or situational awareness. It is the analyst's version of "out of sight, out of mind".  

We will too often only focus on the information that is staring us in the face. If there is a news announcement, we will assume that it is the reason for the market rising or falling regardless of what past evidence may suggest. Thinking of alternatives may be too difficult because it requires recall and analysis. The WYSIATI intuition is a nice way of wrapping up many of the behavioral bias that have been catalogued in finance. This includes behavioral problems such as the anchoring, availability, or recency bias. 

Systematic or rules-based trading can solve this decision problem, yet can also be subject to this processing trap. The nice feature of systematic models is that all relevant information can be used to find and develop the best decisions. An investor is not limited to what is immediately available. Historical as well as obscure or information readily available can be employed to find the best model for predicting market direction. This processing can be done slowly and at our leisure to find the right data and information relationships.

Of course, the benefits of  deliberate systematic analysis can be mitigated if you do not use all of the data available. The modeler who only looks at limited price data will be subject to a WYSIATI problem. The  model may not look outside of the immediate price information and consequently could be caught by surprise from a major  announcement.  Following the price action to the exclusion of all other information may not stop someone from hitting an impending brick wall. Using limited data will place greater emphasis on risk management as tool for limiting loses.

If WYSIATI is a serious problem, it calls for more exhaustive research to ensure you have seen all perspectives. Conducting comprehensive and  thorough analysis along with thinking outside of convention "wisdom" is the only solution to the ever-present WYSAITI problem. Thoughtful rules are a helpful first step.

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