IDEAS home Printed from https://ideas.repec.org/r/taf/quantf/v17y2017i3p405-421.html

Time series momentum and moving average trading rules

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Risks, MDPI, vol. 6(4), pages 1-18, September.
  2. Yafeng Qin & Guoyao Pan & Min Bai, 2020. "Improving market timing of time series momentum in the Chinese stock market," Applied Economics, Taylor & Francis Journals, vol. 52(43), pages 4711-4725, September.
  3. Hung, Chiayu & Lai, Hung-Neng, 2022. "Information asymmetry and the profitability of technical analysis," Journal of Banking & Finance, Elsevier, vol. 134(C).
  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. Hutchinson, Mark C. & Kyziropoulos, Panagiotis E. & O’Brien, John & O’Reilly, Philip & Sharma, Tripti, 2022. "Technical trading rule profitability in currencies: It’s all about momentum," Research in International Business and Finance, Elsevier, vol. 63(C).
  6. Massoud Metghalchi & Linda A. Hayes & Farhang Niroomand, 2019. "A technical approach to equity investing in emerging markets," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 389-403, July.
  7. Marco Corazza & Claudio Pizzi & Andrea Marchioni, 2024. "A financial trading system with optimized indicator setting, trading rule definition, and signal aggregation through Particle Swarm Optimization," Computational Management Science, Springer, vol. 21(1), pages 1-29, June.
  8. Hubert Dichtl, 2020. "Investing in the S&P 500 index: Can anything beat the buy‐and‐hold strategy?," Review of Financial Economics, John Wiley & Sons, vol. 38(2), pages 352-378, April.
  9. Abudy, Menachem Meni & Kaplanski, Guy & Mugerman, Yevgeny, 2024. "Market timing with moving average distance: International evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 97(C).
  10. Gao, Jie & Fan, Chunguo & Liu, Ting & Bai, Xiuran & Li, Wenyong & Tan, Huimin, 2025. "Embracing market dynamics in the post-COVID era: A data-driven analysis of investor sentiment and behavioral characteristics in stock index futures returns," Omega, Elsevier, vol. 131(C).
  11. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "Asymmetric Risk Impacts of Chinese Tourists to Taiwan," Econometric Institute Research Papers EI2018-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  12. Teruko Takada & Takahiro Kitajima, 2022. "Trend-following with better adaptation to large downside risks," PLOS ONE, Public Library of Science, vol. 17(10), pages 1-31, October.
  13. Jukka Ilomaki & Hannu Laurila & Michael McAleer, 2018. "Simple Market Timing with Moving Averages," Tinbergen Institute Discussion Papers 18-048/III, Tinbergen Institute.
  14. Andreas Thomann, 2021. "Multi-asset scenario building for trend-following trading strategies," Annals of Operations Research, Springer, vol. 299(1), pages 293-315, April.
  15. Day, Min-Yuh & Ni, Yensen, 2023. "Be greedy when others are fearful: Evidence from a two-decade assessment of the NDX 100 and S&P 500 indexes," International Review of Financial Analysis, Elsevier, vol. 90(C).
  16. Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Market Timing with Moving Averages," Sustainability, MDPI, vol. 10(7), pages 1-25, June.
  17. Zakamulin, Valeriy & Giner, Javier, 2022. "Time series momentum in the US stock market: Empirical evidence and theoretical analysis," International Review of Financial Analysis, Elsevier, vol. 82(C).
  18. Valeriy Zakamulin & Javier Giner, 2020. "Trend following with momentum versus moving averages: a tale of differences," Quantitative Finance, Taylor & Francis Journals, vol. 20(6), pages 985-1007, June.
  19. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
  20. Ergun, Lerby & Molchanov, Alexander & Stork, Philip, 2023. "Technical trading rules, loss avoidance, and the business cycle," Pacific-Basin Finance Journal, Elsevier, vol. 82(C).
  21. You-Shyang Chen & Arun Kumar Sangaiah & Yu-Pei Lin, 2024. "Hyperautomation on fuzzy data dredging on four advanced industrial forecasting models to support sustainable business management," Annals of Operations Research, Springer, vol. 342(1), pages 215-264, November.
  22. Robert Hudson & Andrew Urquhart, 2021. "Technical trading and cryptocurrencies," Annals of Operations Research, Springer, vol. 297(1), pages 191-220, February.
  23. Kerstin Lamert & Benjamin R. Auer & Ralf Wunderlich, 2023. "Discretization of continuous-time arbitrage strategies in financial markets with fractional Brownian motion," Papers 2311.15635, arXiv.org, revised Dec 2024.
  24. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Moving Average Market Timing in European Energy Markets: Production Versus Emissions," Energies, MDPI, vol. 11(12), pages 1-24, November.
  25. Kerstin Lamert & Benjamin R. Auer & Ralf Wunderlich, 2025. "Discretization of continuous-time arbitrage strategies in financial markets with fractional Brownian motion," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 101(2), pages 163-218, April.
  26. Zakamulin, Valeriy & Giner, Javier, 2023. "Optimal trend-following with transaction costs," International Review of Financial Analysis, Elsevier, vol. 90(C).
  27. Hu, Shicheng & Zhang, Weijie & Li, Danping & Wu, Bing, 2023. "Incorporating improved directional change and regime change detection to formulate trading strategies in foreign exchange markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.