Replication data for: Call Market Experiments: Efficiency and Price Discovery through Multiple Calls and Emergent Newton Adjustments

Name: Replication data for: Call Market Experiments: Efficiency and Price Discovery through Multiple Calls and Emergent Newton Adjustments
Published: Wed Nov 01 00:00:00 EDT 2017
License: This work is licensed under an Other license created by the data depositor. Please refer to the LICENSE file, which should be located alongside the project data and documentation.
Keywords: Laboratory experiment

Principal Investigator(s): View help for Principal Investigator(s) Charles R. Plott; Kirill Pogorelskiy

Version: View help for Version V1

Name	File Type	Size	Last Modified
MIC2015-0201_data			10/25/2021 03:29:PM
LICENSE.txt	text/plain	14.6 KB	10/12/2019 06:46:PM

Project Citation:

Plott, Charles R., and Pogorelskiy, Kirill. Replication data for: Call Market Experiments: Efficiency and Price Discovery through Multiple Calls and Emergent Newton Adjustments. Nashville, TN: American Economic Association [publisher], 2017. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E114345V1

Project Description

Summary: We study multiple-unit, laboratory experimental call markets in which orders are cleared by a single price at a scheduled "call." The markets are independent trading "days" with two calls each day preceded by a continuous and public order flow. Markets approach the competitive equilibrium over time. The price formation dynamics operate through the flow of bids and asks configured as the "jaws" of the order book with contract execution featuring elements of an underlying mathematical principle, the Newton-Raphson method for solving systems of equations. Both excess demand and its slope play a systematic role in call market price discovery.

Scope of Project

Subject Terms: Laboratory experiment

JEL Classification:
      C92 Design of Experiments: Laboratory, Group Behavior
      D41 Market Structure, Pricing, and Design: Perfect Competition
      D44 Auctions
      G14 Information and Market Efficiency; Event Studies; Insider Trading

Data Type(s): experimental data

Methodology

Data Source: student subjects

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Published Versions

V1 [2019-10-12]

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