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Applied Economics Letters Volume 20, 2013 - Issue 2
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Original Articles

Do variable length moving average trading rules matter during a financial crisis period?

Yen-Sen Ni Department of Management Sciences, Tamkang University, No. 151, Yingzhuan Rd., Danshui Dist., New Taipei City, 25137, Taiwan, ROC
,
Jen-Tsai Lee Department of Management Sciences, Tamkang University, No. 151, Yingzhuan Rd., Danshui Dist., New Taipei City, 25137, Taiwan, ROCCorrespondence[email protected]
&
Yi-Ching Liao Department of Management Sciences, Tamkang University, No. 151, Yingzhuan Rd., Danshui Dist., New Taipei City, 25137, Taiwan, ROC
Pages 135-141 | Published online: 04 May 2012

Citations (13)

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Read on this site (3)

Min-Yuh Day, Paoyu Huang, Yirung Cheng, Yin-Tzu Lin & Yensen Ni. (2022) Profitable day trading Bitcoin futures following continuous bullish (bearish) candlesticks. Applied Economics Letters 29:10, pages 947-954.
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Eero Pätäri, Pasi Luukka, Elena Fedorova & Tatiana Garanina. (2017) The anatomy of returns from moving average trading rules in the Russian stock market. Applied Economics Letters 24:5, pages 311-318.
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Pasi Luukka, Eero Pätäri, Elena Fedorova & Tatiana Garanina. (2016) Performance of Moving Average Trading Rules in a Volatile Stock Market: The Russian Evidence. Emerging Markets Finance and Trade 52:10, pages 2434-2450.
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Articles from other publishers (10)

Min-Yuh Day & Yensen Ni. (2023) The profitability of seasonal trading timing: Insights from energy-related markets. Energy Economics 128, pages 107132.
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Chien-Liang Chiu, Yensen Ni, Hung-Ching Hu, Min-Yuh Day & Yuhsin Chen. (2023) Enhancing Crypto Success via Heatmap Visualization of Big Data Analytics for Numerous Variable Moving Average Strategies. Applied Sciences 13:23, pages 12805.
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Yuhsin Chen, Paoyu Huang, Min-Yuh Day, Yensen Ni & Mei-Chu Liang. (2023) Using Heatmap Visualization to assess the performance of the DJ30 and NASDAQ100 Indices under diverse VMA trading rules. PLOS ONE 18:5, pages e0284918.
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Camillo Lento & Nikola Gradojevic. (2022) The Profitability of Technical Analysis during the COVID-19 Market Meltdown. Journal of Risk and Financial Management 15:5, pages 192.
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Min-Yuh Day, Yensen Ni & Paoyu Huang. (2019) Trading as sharp movements in oil prices and technical trading signals emitted with big data concerns. Physica A: Statistical Mechanics and its Applications 525, pages 349-372.
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Lijun Wang, Haizhong An, Xiaojia Liu & Xuan Huang. (2016) Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach. Applied Energy 162, pages 1608-1618.
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Yensen Ni, Yi-Ching Liao & Paoyu Huang. (2015) MA trading rules, herding behaviors, and stock market overreaction. International Review of Economics & Finance 39, pages 253-265.
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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 2014, pages 1-10.
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Aistis Raudys, Vaidotas Lenčiauskas & Edmundas Malčius. 2013. Information and Software Technologies. Information and Software Technologies 34 45 .
Tshilidzi MarwalaTshilidzi Marwala. 2013. Economic Modeling Using Artificial Intelligence Methods. Economic Modeling Using Artificial Intelligence Methods 23 43 .

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