Paper Title
Value of Information in the Binary Case and Confusion Matrix
Journal
Research Impact Tools
Publication Info
Volume: 5 | Issue: 1 | Pages: 1-9
Published On
November, 2022
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Abstract
The simplest Bayesian system used to illustrate ideas of probability theory is a coin and a boolean utility function. To illustrate ideas of hypothesis testing, estimation or optimal control, one needs to use at least two coins and a confusion matrix accounting for the utilities of four possible outcomes. Here we use such a system to illustrate the main ideas of Stratonovich’s value of information (VoI) theory in the context of a financial time-series forecast. We demonstrate how VoI can provide a theoretical upper bound on the accuracy of the forecasts facilitating the analysis and optimization of models.
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