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Trading Fast and Slow
Last registered on May 04, 2018

Pre-Trial

Trial Information
General Information
Title
Trading Fast and Slow
RCT ID
AEARCTR-0002954
Initial registration date
May 04, 2018
Last updated
May 04, 2018 4:01 PM EDT
Location(s)
Region
Primary Investigator
Affiliation
LUMSA
Other Primary Investigator(s)
PI Affiliation
LUMSA
PI Affiliation
University of Trento
Additional Trial Information
Status
Completed
Start date
2015-06-01
End date
2017-06-01
Secondary IDs
Abstract
Financial bubbles cause misallocation of resources and even systemic crises. Experimental finance has long studied both the determinants of bubbles and institutional measures to prevent them. Within the framework of the dual process theory, we experimentally investigate whether traders under higher time pressure (Fast condition) behave differently than traders under lower time pressure (Slow condition). We show that the Slow condition heavily dampens market volatility relative to the Fast condition, and that the former generates prices that are overall consistent with the market's fundamental values, once risk aversion is accounted for. We also observe that traders in the Fast condition are prone to the gambler's fallacy, while those in the Slow condition are not.
External Link(s)
Registration Citation
Citation
Ferri, Giovanni, Matteo Ploner and Matteo Rizzolli. 2018. "Trading Fast and Slow." AEA RCT Registry. May 04. https://doi.org/10.1257/rct.2954-1.0.
Former Citation
Ferri, Giovanni et al. 2018. "Trading Fast and Slow." AEA RCT Registry. May 04. http://www.socialscienceregistry.org/trials/2954/history/29135.
Experimental Details
Interventions
Intervention(s)
Intervention Start Date
2015-07-01
Intervention End Date
2017-06-01
Primary Outcomes
Primary Outcomes (end points)
Bubble formation, prices, trade volumes
Primary Outcomes (explanation)
Secondary Outcomes
Secondary Outcomes (end points)
Secondary Outcomes (explanation)
Experimental Design
Experimental Design
The design follows Smith et al (1988) experimental double auction markets design.
Experimental Design Details
Randomization Method
voluntary registration to experimental sessions via ORSEE software
Randomization Unit
experimental session
Was the treatment clustered?
Yes
Experiment Characteristics
Sample size: planned number of clusters
20 sessions
Sample size: planned number of observations
200 subjects
Sample size (or number of clusters) by treatment arms
100 subjects for each treatment
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
IRB Approval Date
IRB Approval Number
Post-Trial
Post Trial Information
Study Withdrawal
Intervention
Is the intervention completed?
No
Is data collection complete?
Data Publication
Data Publication
Is public data available?
No
Program Files
Program Files
Reports, Papers & Other Materials
Relevant Paper(s)
REPORTS & OTHER MATERIALS