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Multiscale analysis of foreign exchange order flows and technical trading profitability

Author

Listed:
  • Nikola Gradojevic

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Camillo Lento

Abstract

This paper investigates the multiscale (frequency-dependent) relationship between technical trading profitability and feedback trading effects in the Canada/U.S. dollar foreign exchange market. The results suggest that technical trading activities of financial customers drive frequent violations of the FX market microstructure assumption that exchange rate movements are driven by order flow. After controlling for transaction costs, we find that the contribution of financial customers in feedback trading dominates the contribution of non-financial customers, especially at lower frequencies. An additional, novel contribution is that technical indicators constructed from order flows can be profitable.

Suggested Citation

  • Nikola Gradojevic & Camillo Lento, 2015. "Multiscale analysis of foreign exchange order flows and technical trading profitability," Post-Print hal-01563053, HAL.
    • Handle: RePEc:hal:journl:hal-01563053
    DOI: 10.1016/j.econmod.2015.02.028
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    Cited by:

    1. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    2. Day, Min-Yuh & Ni, Yensen & Huang, Paoyu, 2019. "Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 349-372.
    3. Muhammad A. Cheema & Gilbert V. Nartea & Yimei Man, 2018. "Cross‐Sectional and Time Series Momentum Returns and Market States," International Review of Finance, International Review of Finance Ltd., vol. 18(4), pages 705-715, December.
    4. Osman Kilic & Joseph M. Marks & Kiseok Nam, 2022. "Predictable asset price dynamics, risk-return tradeoff, and investor behavior," Review of Quantitative Finance and Accounting, Springer, vol. 59(2), pages 749-791, August.
    5. Syed Jawad Hussain Shahzad & Jose Arreola‐Hernandez & Md Lutfur Rahman & Gazi Salah Uddin & Muhammad Yahya, 2021. "Asymmetric interdependence between currency markets' volatilities across frequencies and time scales," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2436-2457, April.
    6. Ni, Yensen & Liao, Yi-Ching & Huang, Paoyu, 2015. "MA trading rules, herding behaviors, and stock market overreaction," International Review of Economics & Finance, Elsevier, vol. 39(C), pages 253-265.
    7. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Does investor attention matter? The attention-return relationships in FX markets," Economic Modelling, Elsevier, vol. 68(C), pages 644-660.
    8. Fotini Economou & Konstantinos Gavriilidis & Bartosz Gebka & Vasileios Kallinterakis, 2022. "Feedback trading: a review of theory and empirical evidence," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 15(4), pages 429-476, February.
    9. Bouoiyour, Jamal & Selmi, Refk, 2015. "Is the Internet Search Driving Oil Market? A Revisit through Time-Frequency approaches," MPRA Paper 66214, University Library of Munich, Germany.
    10. Jin, Xiaoye, 2021. "What do we know about the popularity of technical analysis in foreign exchange markets? A skewness preference perspective," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 71(C).
    11. Konstandinos Chourmouziadis & Dimitra K. Chourmouziadou & Prodromos D. Chatzoglou, 2021. "Embedding Four Medium-Term Technical Indicators to an Intelligent Stock Trading Fuzzy System for Predicting: A Portfolio Management Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1183-1216, April.
    12. Burak Sencer Atasoy & Timur Han Gür, 2016. "Does the Wagner’s Hypothesis Hold for China? Evidence from Static and Dynamic Analyses," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 63(1), pages 45-60, March.
    13. Tzu‐Pu Chang, 2021. "Buy Low and Sell High: The 52‐Week Price Range and Predictability of Returns," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 336-344, March.

    More about this item

    Keywords

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    JEL classification:

    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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