Transactions on Data Analysis in Social Science

Transactions on Data Analysis in Social Science

Comparison of New Models to Predict Prices and Stock Returns

Document Type : Original Article

Authors
T. Azizzadeh
P. Rezaei Mameghani
Department of Accounting, Ilkhchi Branch, Islamic Azad University, Ilkhchi, Iran
10.47176/TDASS/2019.24
Abstract
During the twentieth century, numerous financial professionals introduced various models and analytical frameworks for forecasting share prices and supporting investment decision-making. The central objective of this study is to develop a comprehensive pricing behavior chart and to analyze the effects of inflation on stock market dynamics. Understanding the sensitivities of long-term market behavior and projecting future trends are crucial for identifying investment opportunities and mitigating financial risk. This research focuses on the perspective of technical analysts, or chartists, who emphasize the analysis of price movements through graphical representations and time-series data. These analysts argue that price fluctuations are primarily driven by the forces of supply and demand, which, in turn, are influenced by a complex set of economic and behavioral factors. By examining historical price trends and transaction volumes, they attempt to detect recurring patterns that may signal future price movements. Unlike fundamental analysts, technical analysts believe that long-term price behavior can be better understood through empirical observation of past data rather than through macroeconomic or accounting-based indicators.
Keywords
Share Price
Stock Return
Predict Models
future prediction
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Transactions on Data Analysis in Social Science
Volume 1, Issue 1
Winter 2019
Pages 24-32

  • Receive Date 06 November 2018
  • Revise Date 12 December 2018
  • Accept Date 02 March 2019