Predicting key reversal points through Fibonacci retracements

Main Article Content

Khalid Mumtaz Khan
Waiza Rehman
Osman Bin Saif


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.

Article Details

How to Cite
Khan, K. M., Waiza Rehman, & Osman Bin Saif. (2022). Predicting key reversal points through Fibonacci retracements. Journal of Management Info, 9(3), 299–310.
Author Biographies

Khalid Mumtaz Khan, Department of Business Studies, Bahria Business School, Bahria University, Islamabad, Pakistan

Bahria Business School, Bahria University, Islamabad, Pakistan

Waiza Rehman, Department of Management Studies, Bahria Business School, Bahria University, Islamabad, Pakistan

Bahria Business School, Bahria University, Islamabad, Pakistan

Osman Bin Saif, Department of Business Studies, Bahria Business School, Bahria University, Islamabad, Pakistan

Bahria Business School, Bahria University, Islamabad, Pakistan


Ali, B. J., & Anwar, G. (2021). Stock Exchange Investment: A Study of Factors That Influence Stock Exchange Investment. Ali, BJ, & Anwar, G. (2021). Stock Exchange Investment: A Study of Factors That Influence Stock Exchange Investment. International Journal of Engineering, Business and Management, 5(3), 39-46. DOI:

Alici, A., & Sevil, G. (2022). Analysis of sector-specific operational performance metrics affecting stock prices of traditional airlines. Independent Journal of Management & Production, 13(2), 488-506. DOI:

Archontakis, F., & Osborne, E. (2007). Playing it safe? A Fibonacci strategy for soccer betting. Journal of Sports Economics, 8(3), 295-308. DOI:

Bahcivan, H., & Karahan, C. C. (2022). High frequency correlation dynamics and day-of-the-week effect: A score-driven approach in an emerging market stock exchange. International Review of Financial Analysis, 80, 102008. DOI:

Barauskaite, G., & Streimikiene, D. (2021). Corporate social responsibility and financial performance of companies: The puzzle of concepts, definitions and assessment methods. Corporate Social Responsibility and Environmental Management, 28(1), 278-287. DOI:

Bolton, P., Kacperczyk, M., Hong, H. G., & Vives, X. (2021). Resilience of the financial system to natural disasters. Centre for Economic Policy Research.

Chen, T. L., Cheng, C. H., & Teoh, H. J. (2007). Fuzzy time-series based on Fibonacci sequence for stock price forecasting. Physica A: Statistical Mechanics and its Applications, 380, 377-390. DOI:

Dini, S., Amelia, A., Hutabarat, R. V. B., & Pasaribu, P. A. (2022). The Influence of Fundamental, Technical and Inflation Factors on Stock Prices in Food and Beverages Companies Listed on IDX. Journal Research of Social, Science, Economics, and Management, 1(6), 736-746. DOI:

Dongrey, S. (2022). Study of market indicators used for technical analysis. International Journal of Engineering and Management Research, 12(2), 64-83. DOI:

Douglas, L. (2001). The memory of judgment. Making Law and History in the Trials of Holocaust.

Gehm, Fred. "Who is RN Elliott and Why is He Making Waves?" Financial Analysts Journal 39, no. 1 (1983): 51-58. DOI:

Giusti, E. (2017). The Twelfth Chapter of Fibonacci's Liber Abaci in its 1202 version/. The Twelfth Chapter of Fibonacci's Liber Abaci in its 1202 version/., 1-228.

Goetzmann, W. N. (2004). Fibonacci and the financial revolution. DOI:

Goeyardi, G. M. (2021). Financial Analysis Method Based on Astrology, Fibonacci, And Astronacci To Find A Date Of Direction Inversion Base Information Technology-Jci And Future Gold Prices. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(4), 1583-1595. DOI:

Hajkova, D., & Hurník, J. (2007). Cobb-Douglas production function: the case of a converging economy. Czech Journal of Economics and Finance (Finance a uver), 57(9-10), 465-476.

Indahwati, I., & Agustini, N. K. Y. (2022). Behavior of Investors VS Traders in Determining Share Prices with Intrinsic Value Moderation (Evidence of Random Walk Hypothesis) in the Indonesian Pandemic Time 2019-2021. Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences, 5(2).

Jindal, G., & Kumar, A. (2022). An Empirical Analysis of Stock Price Indices and Foreign Investment in India. Journal of Positive School Psychology, 6(2), 4605-4613.

Kamara, A. F., Chen, E., & Pan, Z. (2022). An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices. Information Sciences, 594, 1-19. DOI:

Kirkpatrick, C., & Dahlquist, J. (2007). Technical Analysis, 4. publikácia.

Lee, C. C., Yahya, F., & Razzaq, A. (2022). The asymmetric effect of temperature, exchange rate, metals, and investor sentiments on solar stock price performance in China: evidence from QARDL approach. Environmental Science and Pollution Research, 1-15. DOI:

Li, Y. (2021). Improving the Accuracy of Estimated Intrinsic Value Through Industry-Specific Valuation Models. Review of Business & Finance Studies, 12(1), 79-89.

MacLean, G. (2005). Fibonacci and Gann applications in financial markets: practical applications of natural and synthetic ratios in technical analysis. John Wiley & Sons.

Murphy, J. J. (1999). Technical analysis of the financial markets: A comprehensive guide to trading methods and applications. Penguin.

Mustafa, S., Bajwa, A. A., & Iqbal, S. (2022). A new fuzzy grach model to forecast stock market technical analysis. Operational Research in Engineering Sciences: Theory and Applications, 5(1), 185-204. DOI:

Okumu, A. B., Olweny, T., & Muturi, W. (2021). Theoretical Review of Effect of Firm Specific Factors on Performance of Initial Public Offering Stocks at the Nairobi Securities Exchange in Kenya. DOI:

Persaud, D., & O'Leary, J. P. (2015). Fibonacci series, golden proportions, and the human biology.

Poplavskaya, K., Lago, J., Strömer, S., & De Vries, L. (2021). Making the most of short-term flexibility in the balancing market: Opportunities and challenges of voluntary bids in the new balancing market design. Energy Policy, 158, 112522. DOI:

Prechter Jr, R. R. (2005). Elliott Waves, Fibonacci and Statistics.

Pring, M. J. (2002). Technical analysis explained: The successful investor's guide to spotting investment trends and turning points. McGraw-Hill Professional.

Tattersall, R. (2013). The Hum: log-normal distribution and planetary–solar resonance. Pattern Recognition in Physics, 1(1), 185-198. DOI:

Tien, N. H., Jose, R. J. S., Ullah, S. E., & Thang, H. V. (2021). The Impact of World Market on Ho Chi Minh City Stock Exchange in Context of Covid-19 Pandemic. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(14), 4252-4264.

Yusuf, N. M., & Samir, H. (2021). Using Primary and Secondary Market Movements to Construct an Optimal Time-Series Momentum Strategy: A Replication Study (Master's thesis, University of Agder).