Regression Analysis of Stock Returns By Filtering with Simple Moving Averages

Ahmet Sekreter

doi:10.23918/ijsses.v3i4p98

Authors

Ahmet Sekreter Business and Management Department, Faculty of Administrative Sciences and Economics, Tishk International University, Erbil, Kurdistan Region, Iraq

DOI:

https://doi.org/10.23918/ijsses.v3i4p98

Keywords:

Stock Prices, Regression Analysis, Filtering, Simple Moving Averages

Abstract

Stock market prices are affected by industry performance, company news, and world news, political and economic changes. News from company and news about world events play an important role in the direction of stock markets. The analysts have different opinions about estimation of stock prices and stock returns. Some techniques have been used for filtering series in time series analysis, using these methods can give more accurate estimations of stock returns before using regression methods to predict stock returns.

References

Chatfield, C. (2016). The analysis of time series: an introduction. CRC press.

Falkenberry, T. N. (2002). High frequency data filtering. White paper, Tick Data Inc.

Goonatilake, R., & Herath, S. (2007). The volatility of the stock market and news. International Research Journal of Finance and Economics, 3(11), 53-65.

Internet Sources

https://investopedia.com/ask/answers/06/USdollarcorrelation. asp#axzz1p4PMct9z

https://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_averages

https://ipredict.it/Methods/MovingAverage.aspx

https://howthemarketworks.com/popular-topics/stock-pricefactors. php

https://finance.yahoo.com/q?s=GOOG