Business & Economics
An Examination of Earnings and Stock Price Movement
Document Type
Poster Presentation
Location
Indianapolis, IN
Subject Area
Business & Economics
Start Date
13-4-2018 8:30 AM
End Date
13-4-2018 10:00 AM
Sponsor
Brock Vaughters (Anderson University)
Description
The intent of this study is to identify any potential patterns in stock price movement relating to earnings announcements. Data was collected for 72 companies across various industries and sectors. The data was collected for each of the previous eight fiscal quarters for each company. All 72 companies display high market liquidity and relatively volatile price movement. Variables for each stock include: stock price seven days before the earnings report, stock price one day before the report, the closing stock price before the report, the closing stock price the day of the announcement and the closing stock price seven days following the report. An individual regression equation was created for each company to estimate a 30-day price after the earnings announcement. Our level of significance for each regression equation was .05. Using the regression equation, the intent is to utilize an option investment strategy that would take advantage of these estimated price movements. After testing the data, our findings show that in order to predict stock price, it is necessary to include stock movement prior to the earnings announcement to determine if the price is inflated by investors.
An Examination of Earnings and Stock Price Movement
Indianapolis, IN
The intent of this study is to identify any potential patterns in stock price movement relating to earnings announcements. Data was collected for 72 companies across various industries and sectors. The data was collected for each of the previous eight fiscal quarters for each company. All 72 companies display high market liquidity and relatively volatile price movement. Variables for each stock include: stock price seven days before the earnings report, stock price one day before the report, the closing stock price before the report, the closing stock price the day of the announcement and the closing stock price seven days following the report. An individual regression equation was created for each company to estimate a 30-day price after the earnings announcement. Our level of significance for each regression equation was .05. Using the regression equation, the intent is to utilize an option investment strategy that would take advantage of these estimated price movements. After testing the data, our findings show that in order to predict stock price, it is necessary to include stock movement prior to the earnings announcement to determine if the price is inflated by investors.