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Optimal trading frequency for active asset management: Evidence from technical trading rules

Author

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  • Christian L Dunis

    (CIBEF – Center for International Banking, Economics and Finanace, JMU, John Foster Building)

  • Jia Miao

Abstract

The investment horizon or expected trading frequency is an important factor in investment decision making, but there is little literature in this field. The primary motivation for this paper is to find the optimal trading frequency for different assets in the context of active asset management by applying technical trading rules, the most widely used forecasting technique in financial markets. In addition to the simple moving average crossover system, two volatility filters are also applied, where a different trading strategy is proposed when market volatility is high. A model switch strategy is also introduced, where signals from different technical rules are adopted at different levels of market volatility. The results show that the addition of the two volatility filters and the introduction of a model switch strategy add value to the model's performance in terms of annualised return, Sharpe ratio and maximum drawdown. Significant improvement is found at both the single asset and portfolio levels. Although the results for the optimal trading frequencies differ for different assets, similar results have been achieved between the two stock indexes S&P500 and STOXX50 and between FX currency rates. In the case of stock indexes, the optimal trading frequency is about two to four trades per year, while for the FX currency rates, it is about ten to 20 trades per year.

Suggested Citation

  • Christian L Dunis & Jia Miao, 2005. "Optimal trading frequency for active asset management: Evidence from technical trading rules," Journal of Asset Management, Palgrave Macmillan, vol. 5(5), pages 305-326, February.
  • Handle: RePEc:pal:assmgt:v:5:y:2005:i:5:d:10.1057_palgrave.jam.2240149
    DOI: 10.1057/palgrave.jam.2240149
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    Citations

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    Cited by:

    1. Wang, Wei & Lan, Yingjie, 2022. "Robust one-way trading with limited number of transactions and heuristics for fixed transaction costs," International Journal of Production Economics, Elsevier, vol. 247(C).
    2. Manolis Kavussanos & Ilias Visvikis, 2008. "Hedging effectiveness of the Athens stock index futures contracts," The European Journal of Finance, Taylor & Francis Journals, vol. 14(3), pages 243-270.
    3. Christian Dunis & Jia Miao, 2007. "Trading foreign exchange portfolios with volatility filters: the carry model revisited," Applied Financial Economics, Taylor & Francis Journals, vol. 17(3), pages 249-255.
    4. Sermpinis, Georgios & Theofilatos, Konstantinos & Karathanasopoulos, Andreas & Georgopoulos, Efstratios F. & Dunis, Christian, 2013. "Forecasting foreign exchange rates with adaptive neural networks using radial-basis functions and Particle Swarm Optimization," European Journal of Operational Research, Elsevier, vol. 225(3), pages 528-540.
    5. Cristiana Tudor, 2023. "Enhancing Sustainable Finance through Green Hydrogen Equity Investments: A Multifaceted Risk-Return Analysis," Risks, MDPI, vol. 11(12), pages 1-22, December.

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