Profitability of technical trading rules in the Chinese yuan-based foreign exchange market
Shenyi Song,
O-Chia Chuang and
Hsuan Fu
Pacific-Basin Finance Journal, 2025, vol. 92, issue C
Abstract:
This study provides a comprehensive analysis of technical trading rules in the Chinese yuan-based foreign exchange market. Utilizing daily data spanning seven years for 14 developed and 10 emerging market currencies, we examine a universe of 41,660 trading rules, significantly expanding the scope of previous research. To address data-snooping bias, we employ the Step-SPA(k) tests, revealing excess profitability in at least half of the developed and emerging currencies, indicating heterogeneous market efficiency across currencies. To ensure the robustness of our findings, we conducted a series of checks, including the Step-SPA test for conservative data-snooping bias control, break-even transaction cost analysis to evaluate profitability under trading costs, out-of-sample performance evaluation to assess generalizability, and an examination of bank intervention effects to account for potential market distortions.
Keywords: Chinese foreign exchange; Technical analysis; Trading rules; Data-snooping bias; Emerging country (search for similar items in EconPapers)
JEL-codes: C3 F3 G15 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0927538X25001416
Full text for ScienceDirect subscribers only
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:eee:pacfin:v:92:y:2025:i:c:s0927538x25001416
DOI: 10.1016/j.pacfin.2025.102804
Access Statistics for this article
Pacific-Basin Finance Journal is currently edited by K. Chan and S. Ghon Rhee
More articles in Pacific-Basin Finance Journal from Elsevier
Bibliographic data for series maintained by Catherine Liu ().