Disciplined and systematic decision-making is often not about learning more finance and economics, but increasing skills at making better decisions. It is not what data you know, but what to do with the data once you have it. It could be about regression or a complex model, but it is often as easy as getting the direction right or just getting out of the way from bad events.
One of the key decision skills is learning how to process information and experiences; however, there is a gap between our ability to process risks described to us versus risks that we have experienced. This seems odd but is a reality. If you are told about risks, you will give rare events a higher risk weighting than the actual odds. The very act of describing rare events will increase you belief that they will occur. Put differently, if someone is told the odds of an events and then have to sample or experience the same event, your perception of the event or outcome will be different. The description-experience gap is real and needs to be understand and addressed regardless of what information that is presented to us.
More formally, a description of risks is a set of a priori probabilities. The experience of risk is statistical probabilities because there is sampling. There is a continuum between these two. If you only sample and do nothing else, you are at one extreme. If you just describe a set of probabilities without sampling you are at the other extreme. Take the extremes in an experienced risk. If we sample a distribution and we do not experience a rare event, we will give the chance of a rare event occurring very little weight. It was not in the sample, so it will not or cannot occur. The other extreme is placing a probability on a rare event where we have limited or no evidence, only a description.
When compared under testing, the description-experienced gap always occurs. We will choose the riskier option when desirable option occurs with higher probability and choose the safer option if the desirable option occurs with lower probability. Experience makes us give lower weight to rare events than objective probabilities. Descriptions will cause us to overweight the rare events which is just the opposite of experienced decision-making.
We will overweight rare events described to us and we will overweight the mean or likely result if we sample or experience. We are over-sensitive to rare events that we are told may occur. This has played havoc with decision researchers and cause some food for thought on how you make actual decisions. If there is no descriptive evidence and we have to rely on our experience only, we will underweight rare events. If you mix and match you will get smoothing in between the two results.
So what doe this mean for disciplined decision-making an the systematic manager?
1. Look at long sample. Use as much data as possible to experience rare events.
2. Generate scenarios of rare events that may not have been sampled.
3. Acknowledge that there is a gap and adjust to potential rare events.
4. Always diversify so that the chance of a rare event will not knock you out of the game.
One of the key decision skills is learning how to process information and experiences; however, there is a gap between our ability to process risks described to us versus risks that we have experienced. This seems odd but is a reality. If you are told about risks, you will give rare events a higher risk weighting than the actual odds. The very act of describing rare events will increase you belief that they will occur. Put differently, if someone is told the odds of an events and then have to sample or experience the same event, your perception of the event or outcome will be different. The description-experience gap is real and needs to be understand and addressed regardless of what information that is presented to us.
More formally, a description of risks is a set of a priori probabilities. The experience of risk is statistical probabilities because there is sampling. There is a continuum between these two. If you only sample and do nothing else, you are at one extreme. If you just describe a set of probabilities without sampling you are at the other extreme. Take the extremes in an experienced risk. If we sample a distribution and we do not experience a rare event, we will give the chance of a rare event occurring very little weight. It was not in the sample, so it will not or cannot occur. The other extreme is placing a probability on a rare event where we have limited or no evidence, only a description.
When compared under testing, the description-experienced gap always occurs. We will choose the riskier option when desirable option occurs with higher probability and choose the safer option if the desirable option occurs with lower probability. Experience makes us give lower weight to rare events than objective probabilities. Descriptions will cause us to overweight the rare events which is just the opposite of experienced decision-making.
We will overweight rare events described to us and we will overweight the mean or likely result if we sample or experience. We are over-sensitive to rare events that we are told may occur. This has played havoc with decision researchers and cause some food for thought on how you make actual decisions. If there is no descriptive evidence and we have to rely on our experience only, we will underweight rare events. If you mix and match you will get smoothing in between the two results.
So what doe this mean for disciplined decision-making an the systematic manager?
1. Look at long sample. Use as much data as possible to experience rare events.
2. Generate scenarios of rare events that may not have been sampled.
3. Acknowledge that there is a gap and adjust to potential rare events.
4. Always diversify so that the chance of a rare event will not knock you out of the game.
No comments:
Post a Comment