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Do technical trading profits remain in the foreign exchange market? Evidence from 14 currencies

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  • Cialenco, Igor
  • Protopapadakis, Aris

Abstract

We examine the in- and out-of-sample behavior of two popular trading systems, Alexander and Double MA filters, for 14 developed-country currencies using daily data with bid-ask spreads. We find significant in-sample returns in the early periods. But out-of-sample returns are lower and only occasionally significant. We show that a currency risk factor proposed in the literature is systematically related to these returns. We find no support for the hypotheses that falling transactions costs are responsible for declining trading profits or for the Adaptive Market hypothesis. Importantly, we show that algorithms that simulate out-of-sample returns have serious instability difficulties.

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  • Cialenco, Igor & Protopapadakis, Aris, 2011. "Do technical trading profits remain in the foreign exchange market? Evidence from 14 currencies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(2), pages 176-206, April.
    • Handle: RePEc:eee:intfin:v:21:y:2011:i:2:p:176-206
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    Cited by:

    1. Ülkü, Numan & Prodan, Eugeniu, 2013. "Drivers of technical trend-following rules' profitability in world stock markets," International Review of Financial Analysis, Elsevier, vol. 30(C), pages 214-229.
    2. Hassanniakalager, Arman & Sermpinis, Georgios & Stasinakis, Charalampos, 2021. "Trading the foreign exchange market with technical analysis and Bayesian Statistics," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 230-251.
    3. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    4. Liu, Xiaojia & An, Haizhong & Wang, Lijun & Jia, Xiaoliang, 2017. "An integrated approach to optimize moving average rules in the EUA futures market based on particle swarm optimization and genetic algorithms," Applied Energy, Elsevier, vol. 185(P2), pages 1778-1787.
    5. Lijun Wang & Haizhong An & Xiaohua Xia & Xiaojia Liu & Xiaoqi Sun & Xuan Huang, 2014. "Generating Moving Average Trading Rules on the Oil Futures Market with Genetic Algorithms," Mathematical Problems in Engineering, Hindawi, vol. 2014, pages 1-10, May.
    6. Dockery, Everton & Todorov, Ivan, 2023. "Further evidence on the returns to technical trading rules: Insights from fourteen currencies," Journal of Multinational Financial Management, Elsevier, vol. 69(C).
    7. Martin Scholtus & Dick van Dijk, 2012. "High-Frequency Technical Trading: The Importance of Speed," Tinbergen Institute Discussion Papers 12-018/4, Tinbergen Institute.

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