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Fibonacci Retracement

Additional Resources

  1. How To Use Fibonacci Retracement To Predict Forex Market []
  2. Fibonacci Retracements And Self-fulfilling Prophecy []
  3. "fibonacci Retracements And Self-fulfilling Prophecy" By Nikhil Gupta []
  4. How To Use Fibonacci Retracement In Binary Options ... []
  5. University Of Hawaii Department Of Economics []
  6. Forex Forecasting.pdf []


In finance, Fibonacci retracement is a method of technical analysis for determining support and resistance levels. They are named after their use of the Fibonacci sequence. Fibonacci retracement is based on the idea that markets will retrace a predictable portion of a move, after which they will continue to move in the original direction.

Source: Wikipedia
This Article has been Edited for Accessibility

Common Uses

Fibonacci retracement is a popular tool that technical traders use to help identify strategic places for transactions, stop losses or target prices to help traders get in at a good price. The retracement concept is used in many indicators such as Tirone levels, Gartley patterns, Elliott Wave theory and more. After a significant movement in price (be it up or down) the new support and resistance levels are often at these lines.

Unlike moving averages, Fibonacci retracement levels are static prices. They do not change. This allows quick and simple identification and allows traders and investors to react when price levels are tested. Because these levels are inflection points, traders expect some type of price action, either a break or a rejection. The 0.618 Fibonacci retracement that is often used by stock analysts approximates to the "golden ratio".

Academic studies

Bhattacharya, Sukanto and Kumar, Kuldeep (2006) A computational exploration of the efficacy of Fibonacci sequences in technical analysis and trading. Annals of Economics and Finance, Volume 7, Issue 1, May 2006, pp. 219–230.

Chatterjee, Amitava, O. Felix Ayadi, and Balasundram Maniam. "The Applications Of The Fibonacci Sequence And Elliott Wave Theory In Predicting The Security Price Movements: A Survey." Journal of Commercial Banking and Finance 1 (2002): 65–76.

Tai-Liang Chena, Ching-Hsue Chenga, Hia Jong Teoha. Fuzzy time-series based on Fibonacci sequence for stock price forecasting. Physica A: Statistical Mechanics and its Applications, Volume 380, 1 July 2007, Pages 377–390.