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Predicting key reversal points through Fibonacci retracements


Article Information

Title: Predicting key reversal points through Fibonacci retracements

Authors: Khalid Mumtaz Khan, Waiza Rehman, Osman Bin Saif

Journal: Journal of Management Info (JMI)

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30

Publisher: Advance Educational Institute & Research Centre

Country: Pakistan

Year: 2022

Volume: 9

Issue: 3

Language: English

Keywords: Technical analysisFundamental AnalysisSelected:Fibonacci RetracementsKey Reversal Points

Categories

Abstract

Anticipation of the key reversal points in trading markets is of key interest to the portfolio managers, investors, researchers, technical Analysts. These points trigger investment or divestment for investors’ holdings within the financial markets. Many techniques are used to anticipate these points. Use of Fibonacci numbers has gained significant importance in this context. The tools like ‘Fibonacci Retracements’ are available to investors; however, another important determinant in the value of an investment is the ‘timings’ within a certain time frame. This study aims to understand whether such a predictive relationship exists between the Fibonacci time horizons and the modern-day financial markets. For this purpose, two renowned indices i.e., Dow Jones Industrial Average (DJIA) and Dow Jones Transport Average (DJTA) have been taken as the population. Data of these averages, since their inception in 1896, till 2020, has been taken in to account, in order to remove any speculative sentiments, in the long run. The observation periods of data have been classified into daily, monthly and yearly time frames. Charting package, ‘meta stocks’ version 8.0 has been used to map the Fibonacci sequence against the actual reversal points placed on the data from the first day of trading on DJIA and DJTA. The results reveal striking similarity between the reversal points inferred from Fibonacci sequence, and the actual reversal points. The study concludes with a recommendation to trace this similarity against the technical analysis and charting for further investigation by the future studies. These findings are of significant importance for the portfolio managers, technical analysists, and researchers interested in forecasting the movement of the market index.


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