Tag Archives: SSRN

On the Difference between Binary Prediction and True Exposure With Implications for Forecasting Tournaments and Prediction Markets by Nassim Nicholas Taleb, Philip E. Tetlock :: SSRN

On the Difference between Binary Prediction and True Exposure With Implications for Forecasting Tournaments and Prediction Markets

Nassim Nicholas Taleb

NYU-Poly; Université Paris I Panthéon-Sorbonne – Centre d’Economie de la Sorbonne (CES)

Philip E. Tetlock

University of California, Berkeley – Organizational Behavior & Industrial Relations Group; University of Pennsylvania – Management Department

June 25, 2013

Abstract:

There are serious differences between predictions, bets, and exposures that have a yes/no type of payoff, the “binaries”, and those that have varying payoffs, which we call the “vanilla”. Real world exposures tend to belong to the vanilla category, and are poorly captured by binaries. Vanilla exposures are sensitive to Black Swan effects, model errors, and prediction problems, while the binaries are largely immune to them. The binaries are mathematically tractable, while the vanilla are much less so. Hedging vanilla exposures with binary bets can be disastrous — and because of the human tendency to engage in attribute substitution when confronted by difficult questions, decision-makers and researchers often confuse the vanilla for the binary.

Number of Pages in PDF File: 7

Keywords: Predictions, Risk, Decision, Judgment and Decision Making, Fat Tails

working papers series

via On the Difference between Binary Prediction and True Exposure With Implications for Forecasting Tournaments and Prediction Markets by Nassim Nicholas Taleb, Philip E. Tetlock :: SSRN.

On the Difference between Binary Prediction and True Exposure, with Implications for Forecasting Tournaments and Prediction Markets by Nassim Nicholas Taleb, Philip E. Tetlock :: SSRN

On the Difference between Binary Prediction and True Exposure, with Implications for Forecasting Tournaments and Prediction Markets

Nassim Nicholas Taleb

NYU-Poly

Philip E. Tetlock

University of California, Berkeley – Organizational Behavior & Industrial Relations Group; University of Pennsylvania – Management Department

June 25, 2013

Abstract:

There are serious differences between predictions, bets, and exposures that have a yes/no type of payoff, the “binaries”, and those that have varying payoffs, which we call the “vanilla”. Real world exposures tend to belong to the vanilla category, and are poorly captured by binaries. Vanilla exposures are sensitive to Black Swan effects, model errors, and prediction problems, while the binaries are largely immune to them. The binaries are mathematically tractable, while the vanilla are much less so. Hedging vanilla exposures with binary bets can be disastrous–and because of the human tendency to engage in attribute substitution when confronted by difficult questions, decision-makers and researchers often confuse the vanilla for the binary.

Number of Pages in PDF File: 7

Keywords: Predictions, Risk, Decision, Judgment and Decision Making, Fat Tails

working papers series

via On the Difference between Binary Prediction and True Exposure, with Implications for Forecasting Tournaments and Prediction Markets by Nassim Nicholas Taleb, Philip E. Tetlock :: SSRN.

No, Small Probabilities are Not ‘Attractive to Sell’: A Comment by Nassim Taleb :: SSRN

No, Small Probabilities are Not ‘Attractive to Sell’: A Comment (revised)
Nassim Nicholas Taleb
NYU-Poly
January 5, 2013
Financial Analysts Journal, Forthcoming
Abstract: Owing to the convexity of the payoff of out-of-the money options, an extremely small probability of a large deviation unseen in past data justifies rationally buying them, or at least justifies excessive caution in not being exposed to them, particularly those options that are extremely nonlinear in response to market movement or changes in implied volatility. One needs, for instance, a minimum of 2000 years of stock market data to assert that some tail options are “expensive.” The paper presents errors in Ilmanen 2012, which provides an exhaustive list of all arguments in favor of selling insurance on small probability events. The paper goes beyond Ilmanen 2012 and suggests an approach to analyze the payoff and risks of options based on the nonlinearities in the tails.
Number of Pages in PDF File: 6

via No, Small Probabilities are Not ‘Attractive to Sell’: A Comment by Nassim Taleb :: SSRN.

No, Small Probabilities are Not ‘Attractive to Sell’: A Comment by Nassim Taleb :: SSRN

No, Small Probabilities are Not ‘Attractive to Sell’: A Comment
Nassim Nicholas Taleb
NYU-Poly
January 5, 2013
Financial Analysts Journal, Forthcoming

Abstract: Owing to the convexity of the payoff of out-of-the money options, an extremely small probability of a large deviation unseen in past data justifies rationally buying them, or at least justifies excessive caution in not being exposed to them, particularly those options that are extremely nonlinear in response to market movement or changes in implied volatility. One needs, for instance, a minimum of 2000 years of stock market data to assert that some tail options are “expensive”. The paper presents errors in Ilmanen 2012, which provides an exhaustive list of all arguments in favor of selling insurance on small probability events. The paper goes beyond Ilmanen 2012 and suggests an approach to analyze the payoff and risks of options based on the nonlinearities in the tails.
Number of Pages in PDF File: 5
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via No, Small Probabilities are Not ‘Attractive to Sell’: A Comment by Nassim Taleb :: SSRN.