Information Aggregation and P-hacking

55 Pages Posted: 20 Dec 2016 Last revised: 29 Aug 2018

See all articles by Oleg Rytchkov

Oleg Rytchkov

Temple University - Department of Finance

Xun Zhong

Fordham University - Finance Area

Date Written: August 21, 2018

Abstract

This paper studies the interplay between information aggregation and p-hacking in the context of predicting stock returns. The standard information aggregation techniques exacerbate p-hacking by increasing the probability of the type I error. We propose an aggregation technique, which is a simple modification of 3PRF/PLS, with an opposite property: the predictability tests applied to the combined predictor become more conservative in the presence of p-hacking. Using simulations, we quantify the advantages of our approach relative to the standard information aggregation techniques. We also apply our aggregation technique to three sets of return predictors proposed in the literature and find that the forecasting ability of combined predictors in two cases cannot be explained by p-hacking.

Keywords: predictability of returns, p-hacking, forecast combination, 3PRF, PLS

JEL Classification: G17, C58

Suggested Citation

Rytchkov, Oleg and Zhong, Xun, Information Aggregation and P-hacking (August 21, 2018). Fox School of Business Research Paper No. 17-004, Available at SSRN: https://ssrn.com/abstract=2858619 or http://dx.doi.org/10.2139/ssrn.2858619

Oleg Rytchkov (Contact Author)

Temple University - Department of Finance ( email )

Fox School of Business and Management
Philadelphia, PA 19122
United States

Xun Zhong

Fordham University - Finance Area ( email )

45 Columbus Avenue, Room 620
New York, NY 10023
United States

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