THE PREDICTIVE POWER OF TECHNICAL ANALYSIS: EVIDENCE FROM THE GBP/USD EXCHANGE RATE

Miguel Lampreia (), Fernando Teixeira () and Susana Pescada ()
Additional contact information
Miguel Lampreia: Ivo Garcias, Sociedade de Embalagens, Lda., Portugal
Fernando Teixeira: Professor Assistant, Instituto Politécnico de Beja, Portugal; Smart Cities Research Center
Susana Pescada: Professor Assistant, Faculty of Economy, University of Algarve, Portugal; Cin Turs - Research Center for Tourism, Sustainability and Well-being

Sustainable Regional Development Scientific Journal, 2024, vol. III, issue 5, 91-98

Abstract: This study examines the effectiveness of technical analysis in the foreign exchange market, focusing on the GBP/USD currency pair in 2019. By combining historical and granular analysis, the research leverages various technical tools, including trendlines, support and resistance levels, Fibonacci retracements, chart patterns, and candlestick formations. The study demonstrates the predictive power of these tools in identifying market trends, pinpointing potential reversals, and uncovering trading opportunities. This highlights the value of technical analysis for informed decision-making in the complex foreign exchange market.

Keywords: Technical analysis; Forex market; GBP/USD exchange rate; Predictive tools; Market trends (search for similar items in EconPapers)
JEL-codes: D50 D53 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.srdsjournal.eu/articles/files/2024-3-5.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bfb:srdjou:2024-12_5

Access Statistics for this article

More articles in Sustainable Regional Development Scientific Journal from Sustainable Regional Development Scientific Journal
Bibliographic data for series maintained by Filip Ruxho ().