As Silver observes prices had become untethered from supply and demand as

As silver observes prices had become untethered from

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your pockets are being lined. As Silver observes, “prices had become untethered from supply and demand, as lenders, brokers, and the ratings agencies—all of whom profited in one way or another from every home sale—strove to keep the party going”. TOWARDS BETTER PREDICTIONMAKING We have now seen some of the major difficulties involved with prediction (our discussion has focussed mainly on the economy, but the lessons here can be applied to virtually any field). Essentially, the difficulties can be reduced to 3 major themes: bias, overconfidence, and lack of attention to detail. Bias enters the picture when our particular interests (economic, political, reputation, selfimage etc.) color our predictions. Overconfidence enters the scene when we fail to account for the difficulties inherent in the practice of prediction. The inherent difficulties here differ from field to field, and are multiplied by things like the number of variables involved, the complexity of the relationships between these variables, and the degree to which these relationships change over time. Thomas Bayes was an English minister who lived in the 18 th century. Though Bayes was elected as a Fellow of the Royal Society and did publish during his lifetime, he did not achieve a good deal of influence until after his death; and today his influence is stronger than ever. Bayes’ influence comes mainly from a paper of his that was published after his death called ‘An Essay toward Solving a Problem in the Doctrine of Chances,’ which “concerned how we formulate probabilistic beliefs about the world when we encounter new data” .The paper was intended as a response to the famous philosopher and skeptic David
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A Summary of ‘The Signal and the Noise: Why So Many Predictions Fail–but Some Don’t’ by Nate Silver Hume, who argued that we could not truly predict anything with any amount of certainty. This is the case, according to Hume, because all of our information about the world comes from past experience, and just because something happened in the past (even with great frequency) does not mean we can logically deduce that it will happen again in the future. For instance, our knowledge that the sun rises in the morning is derived from the fact that on all previous occasions the sun has risen in the morning. However, because our sample size is necessarily limited, we have no way of knowing whether this is a matter of necessity or simply chance. This being the case, Hume “argued that since we could not be certain that the sun would rise again, a prediction that it would was inherently no more rational than one that it wouldn’t” . Bayes agreed with Hume that we can never predict anything with absolute certainty. However, he disagreed that this effectively made all prediction an irrational process. Instead, Bayes contended that prediction could be made rational by way of treating it as a matter of probability rather than certainty. For
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  • Spring '14
  • Dr.JacobADaniel
  • Forecasting, Futurology, Nate Silver, ‘The Signal

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