Advances and Applications in Statistics
Volume 65, Issue 2, Pages 247 - 262
(December 2020) http://dx.doi.org/10.17654/AS065020247 |
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SUGGESTED STATISTICAL MODELS TO STUDY THE AFFECTING FACTORS ON THE PERFORMANCE OF SHARES AND FORECAST THE DAILY CLOSING PRICE (APPLIED STUDY ON THE SHARES OF GOOGLE COMPANY)
Essam Fawzy, Khaled Mohamed and Fatma Ibrahim
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Abstract: Based on a group of variables and data collected during the period 2001 to 2018, this paper aims to investigate the effect of some factors on stock performance.
Ridge regression and weighted least squares (WLS) regression are used for analysis where the dependent variable was stock performance (closing price). The independent variables were revenues, earning per share, corruption index, effective tax rate, total public debt, internal conflict, government stability and the interaction between some independent variables that have a common effect on the dependent variable. Notably, the variables that were most effective on the dependent variable were the earning per share, the variable of the interaction between the revenue logarithm and EPS, and the variable of the interaction between corruption index and the government stability. The data collected was analyzed using STATAGRAPHICS and Gretl. |
Keywords and phrases: closing price, Google company, revenues, earning per share, corruption index, effective tax rate, total public debt, internal conflict, government stability.
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