Abstract
Prediction markets provide a unique and compelling way to sell and aggregate information, yet a good understanding of optimal strategies for agents participating in such markets remains elusive. To model this complex setting, prior work proposes a three stages game called the Alice Bob Alice (ABA) game  Alice participates in the market first, then Bob joins, and then Alice has a chance to participate again. While prior work has made progress in classifying the optimal strategy for certain interesting edge cases, it remained an open question to calculate Alice's best strategy in the ABA game for a general information structure.
In this paper, we analyze the ABA game for a general information structure and (1) show a "revelationprinciple" style result: it is enough for Alice to use her private signal space as her announced signal space, that is, Alice cannot gain more by revealing her information more "finely"; (2) provide a FPTAS to compute the optimal information revelation strategy with additive error when Alice's information is a signal from a constantsized set; (3) show that sometimes it is better for Alice to reveal partial information in the first stage even if Alice's information is a single binary bit.
BibTeX  Entry
@InProceedings{kong_et_al:LIPIcs:2018:8319,
author = {Yuqing Kong and Grant Schoenebeck},
title = {{Optimizing Bayesian Information Revelation Strategy in Prediction Markets: the Alice Bob Alice Case}},
booktitle = {9th Innovations in Theoretical Computer Science Conference (ITCS 2018)},
pages = {14:114:20},
series = {Leibniz International Proceedings in Informatics (LIPIcs)},
ISBN = {9783959770606},
ISSN = {18688969},
year = {2018},
volume = {94},
editor = {Anna R. Karlin},
publisher = {Schloss DagstuhlLeibnizZentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2018/8319},
URN = {urn:nbn:de:0030drops83191},
doi = {10.4230/LIPIcs.ITCS.2018.14},
annote = {Keywords: prediction market, information revelation, optimization}
}
Keywords: 

prediction market, information revelation, optimization 
Collection: 

9th Innovations in Theoretical Computer Science Conference (ITCS 2018) 
Issue Date: 

2018 
Date of publication: 

12.01.2018 