Economics and Finance

   

Harvard Q-Guide Predictions Market

Authors: Luis Perez, Haotian Wu

Given the announcement by Harvard College to stop publishing difficulty rating for courses \cite{crimson}, a need has arisen for alternative methods of information gathering among undergraduates. In this paper, we propose different prediction market mechanisms, detailing user input/output, contract definitions, and payment rules for each of the proposed mechanisms. The goal of each mechanism is to obtain accurate predictions that could replace Q-guide data (overall course quality, difficulty rating, and workload rating). We further discuss properties of each prediction market, such as the truthfulness incentives of for individual agents, individual agent's optimal policies, and expected results from each market. We conclude with a discussion and explanation of a simple toy implementation of the market, detailing design consideration that might affect user behaviour in our market, and laying the groundwork for future expansion and testing.

Comments: 14 Pages.

Download: PDF

Submission history

[v1] 2017-12-15 23:44:57

Unique-IP document downloads: 9 times

Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus