Revision to "algorithmic trader experiment"

Last registered on April 15, 2025
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Pre-Trial

Trial Information

General Information

Title
Revision to "algorithmic trader experiment"
RCT ID
AEARCTR-0015631
Initial registration date
April 07, 2025

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
April 15, 2025, 1:17 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

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Primary Investigator

Name
Christoph Siemroth
Affiliation
University of Essex
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Other Primary Investigator(s)

PI Name
Brice Corgnet
PI Affiliation
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PI Name
Mark DeSantis
PI Affiliation
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Additional Trial Information

Status
In development
Start date
2025-04-09
End date
2025-10-31
Keywords
Finance & Microfinance
Additional Keywords
JEL code(s)
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
This pre-registration describes a new experiment for a journal revision. The original experiment was https://www.socialscienceregistry.org/trials/9001
External Link(s)

Registration Citation

Citation
Corgnet, Brice, Mark DeSantis and Christoph Siemroth. 2025. "Revision to "algorithmic trader experiment"." AEA RCT Registry. April 15. https://doi.org/10.1257/rct.15631-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2025-04-09
Intervention End Date
2025-10-31

Primary Outcomes

Primary Outcomes (end points)
Welfare, price efficiency, liquidity
Primary Outcomes (explanation)
Outcomes on market level:

1. Welfare, measured as the sum of welfare gains,
2. Price efficiency, measured as the share of transaction prices between the asset
valuations of the low type and the high type traders, where the valuation prior to news release
is the expected asset value for the type,
3. Liquidity, measured as the inverse of the time-weighted bid ask spread

Secondary Outcomes

Secondary Outcomes (end points)
4. Number of trades,

5. Number of trades immediately (within 1 sec) after news release.

6. Price volatility, as the variance of the prices

7. Non-Intermediary Welfare: Welfare excluding the medium value trader, measured as sum of welfare gains of all players except the medium value trader
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
See hidden design.
Experimental Design Details
Not available
Randomization Method
Ztree determines the random variables, with the exception of the asset common value realizations, which have been drawn via matlab random number generators beforehand, so the same sequence of common value realizations can be used in all sessions.
Randomization Unit
We cluster at the group level (11 traders).
Was the treatment clustered?
Yes

Experiment Characteristics

Sample size: planned number of clusters
9 per treatment, 27 overall (we have 3 treatments). A cluster is a group, consisting of 11 traders.
Sample size: planned number of observations
On market level, an observation is one round. 3 treatments, 9 groups per treatment, each with 20 rounds. 3*9*20=540 rounds, 180 rounds per treatment.
Sample size (or number of clusters) by treatment arms
9 groups in control
9 groups in market order algo treatment
9 groups in limit order algo treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
We use the same power calculation as for the original study: According to Stata, we need 9 clusters per treatment. The command: power twomeans 0 25, m1(20) m2(20) sd(25) rho(0.5) cluster
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
Emlyon Business School Ethical Review Board
IRB Approval Date
2025-03-12
IRB Approval Number
BC #104
Analysis Plan

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