Mostly Calibrated

Stanford Graduate School of Business Working Paper No. 2090

11 Pages Posted: 6 Jan 2012

See all articles by Yossi Feinberg

Yossi Feinberg

Stanford Graduate School of Business

Nicolas S. Lambert

Stanford Graduate School of Business - Knight Management Center

Date Written: December 5, 2011

Abstract

Prequential testing of a forecaster is known to be manipulable if the test must pass an informed forecaster for all possible true distributions. Stewart (2011) provides a non- manipulable prequential likelihood test that only fails an informed forecaster on a small, category I, set of distributions. We present a prequential test based on calibration that also fails the informed forecaster on at most a category I set of true distributions and is non-manipulable. Our construction sheds light on the relationship between likelihood and calibration with respect to the distributions they reject.

Suggested Citation

Feinberg, Yossi and Lambert, Nicolas S., Mostly Calibrated (December 5, 2011). Stanford Graduate School of Business Working Paper No. 2090, Available at SSRN: https://ssrn.com/abstract=1980405 or http://dx.doi.org/10.2139/ssrn.1980405

Yossi Feinberg

Stanford Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States

Nicolas S. Lambert (Contact Author)

Stanford Graduate School of Business - Knight Management Center ( email )

655 Knight Way
Stanford, CA 94305-7298
United States

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