Forecasting the Impact of Racial Uprisings on Stocks

Last registered on January 03, 2023
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Pre-Trial

Trial Information

General Information

Title
Forecasting the Impact of Racial Uprisings on Stocks
RCT ID
AEARCTR-0010670
Initial registration date
December 19, 2022

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
January 03, 2023, 4:41 PM EST

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

Locations

Country
United States of America
Region

Primary Investigator

Name
bocar ba
Affiliation
duke
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Alexander Whitefield
PI Affiliation
Duke
Contact Investigator

Additional Trial Information

Status
In development
Start date
2022-12-20
End date
2023-02-20
Keywords
Finance & Microfinance, Governance
Additional Keywords
ethical investing
JEL code(s)
G17
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract
We survey an online sample of the U.S. population to understand their forecasts of the impact of social movements on stock prices. In an online survey experiment, we investigate how exposing respondents to narratives and products related to law enforcement impacts their forecast of stock prices and support for policy reform.
External Link(s)

Registration Citation

Citation
ba, bocar and Alexander Whitefield. 2023. "Forecasting the Impact of Racial Uprisings on Stocks." AEA RCT Registry. January 03. https://doi.org/10.1257/rct.10670-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
Intervention Start Date
2022-12-20
Intervention End Date
2023-02-20

Primary Outcomes

Primary Outcomes (end points)
Accuracy: the negative absolute value of the difference between the participant predicted price of the police portfolio 21 days (prediction) after the killing of George Floyd and the true value.

Increase: a binary variable that takes the value one if the respondent forecasts the price of the police portfolio increases 21 days after the killing of George Floyd, (i.e., > 100), and zero otherwise.

Accuracy for six Predictions: the negative absolute value of the difference between the participant predicted price of the police portfolio and five individual stocks 21 days (prediction) after the killing of George Floyd and the actual value. The five individual stocks are Axon Enterprise, Flir Systems Inc, Motorola Soution Inc, Shotspotter Inc, and Virtra Inc.
Primary Outcomes (explanation)
Our primary outcomes measure respondents’ forecast of George Floyd's death on the stock of firms contracting with law enforcement.

Accuracy: the negative absolute value of the difference between the participant predicted price of the police portfolio 21 days (prediction) after the killing of George Floyd and the true value.

Increase: a binary variable that takes the value one if the respondent forecasts the price of the police portfolio increases 21 days after the killing of George Floyd, (i.e., > 100), and zero otherwise.

Accuracy for six Predictions: the negative absolute value of the difference between the participant predicted price of the police portfolio and five individual stocks 21 days (prediction) after the killing of George Floyd and the actual value. The five individual stocks are Axon Enterprise, Flir Systems Inc, Motorola Soution Inc, Shotspotter Inc, and Virtra Inc.

Secondary Outcomes

Secondary Outcomes (end points)
Prediction: the predicted price of the police portfolio 21 days (prediction) after the killing of
George Floyd.

Recalibration: a binary variable that takes the value one if the participant chooses to redo the prediction and zero otherwise.

Final Prediction: initial prediction if no recalibration, and new prediction otherwise.

Any Donation: a binary variable that takes the value one if the participant donates some money to the non-profit and zero otherwise.

Donation Amount: the amount of money the participant chooses to donate to a non-profit organization.

Donation to Police Reform: a binary variable that takes the value one if the participant chose to donate to an organization focusing on police reform, and zero otherwise.

Donation to Police Wellness: a binary variable that takes the value one if the participant chose to donate to an organization focusing on police wellness, and zero otherwise.

Donation to Reduce the Scope of Policing: a binary variable that takes the value one if the participant chose to donate to an organization focusing on reducing the role of police in society, and zero otherwise.
Secondary Outcomes (explanation)
Prediction: the predicted price of the police portfolio 21 days (prediction) after the killing of
George Floyd.

Recalibration: a binary variable that takes the value one if the participant chooses to redo the prediction and zero otherwise.

Final Prediction: initial prediction if no recalibration, and new prediction otherwise.

Any Donation: a binary variable that takes the value one if the participant donates some money to the non-profit and zero otherwise.

Donation Amount: the amount of money the participant chooses to donate to a non-profit organization.

Donation to Police Reform: a binary variable that takes the value one if the participant chose to donate to an organization focusing on police reform, and zero otherwise.

Donation to Police Wellness: a binary variable that takes the value one if the participant chose to donate to an organization focusing on police wellness, and zero otherwise.

Donation to Reduce the Scope of Policing: a binary variable that takes the value one if the participant chose to donate to an organization focusing on reducing the role of police in society, and zero otherwise.

Experimental Design

Experimental Design
We randomize participants into four groups (25% in each treatment arm): (1) No narrative-No product information, (2) Narratives-No production information, (3) No narrative-Product information, and (4) Narratives-Product information. After exposing participants to interventions, we will collect outcomes via a survey.
Experimental Design Details
Participants will complete two surveys, separated by one week. We will recruit participants for the first survey in the first week using Prolific. We will aim to recruit 5000 participants in the first survey.

A week later, we will advertise the survey only to those who completed the first survey. We expect around 30% of the participants who complete the first survey to complete the second survey. To maximize the number of participants that complete the second survey, we will increase the incentive payment for the second survey and leave the second survey open for one week. We expect about 2000-2500 participants to complete the final survey. The main analysis only considers respondents who answered both surveys.

No randomization occurs in the first survey. We collect baseline characteristics of participants in the first survey, including views over ethical investments. In the second survey, we randomize participants into four groups (25% in each treatment arm): (1) No narrative-No product information, (2) Narratives-No production information, (3) No narrative-Product information, and (4) Narratives-Product information. After exposing participants to interventions, will will collect outcomes via the survey.
Randomization Method
To conduct randomization, we use the ‘evenly present
elements’ functionality in Qualtrics.
Randomization Unit
Individual
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
2000
Sample size: planned number of observations
2000
Sample size (or number of clusters) by treatment arms
500 individuals in each treatment combination.
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
0.18 Cohen's D
Supporting Documents and Materials

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IRB

Institutional Review Boards (IRBs)

IRB Name
Duke University Institutional Review Board
IRB Approval Date
2022-12-16
IRB Approval Number
2022-0505
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
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