Optimal trading frequency for active asset management: Evidence from technical trading rules
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Christian L. Dunis* is Professor of Banking and Finance at Liverpool John Moores University, and Director of its Centre for International Banking, Economics and Finance (CIBEF). He is also a consultant to asset management firms and an editor of the European Journal of Finance. He has published widely in the field of financial markets analysis and forecasting. He has organised the annual Forecasting Financial Markets Conference since 1994.
Jia Miao is an Associate Researcher at CIBEF and a PhD student at Liverpool John Moores University, where he also works as a teaching assistant. Jia holds a MSc in International Banking and Finance from Liverpool John Moores University. *CIBEF — Center for International Banking, Economics and Finance, JMU, John Foster Building, 98 Mount Pleasant, Liverpool L3 5UZ, UK e-mail: [email protected]
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. Keywords: trading frequency, active asset management, technical rules, confirmation filter, volatility filter, switch strategy
Introduction Most financial modelling techniques require large numbers of observations to
䉷 Henry Stewart Publications 1479-179X (2005)
keep the model statistically efficient. This suggests that models should use more frequent data, which in turn generate
Vol. 5, 5, 305–326
Journal of Asset Management
305
Dunis and Miao
forecasts and implies market position changes at almost the same high frequency. But practically, in some markets, trading on a high-frequency basis is not feasible simply because of transaction costs. Transaction costs are less crucial in FX markets where transaction costs are quite low, but they become a more important factor when investing in markets such as the stoc
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