Analyzing the Double Crossover Moving Averages Strategy Before, During and After the Lockdown Period
DOI:
https://doi.org/10.32890/ijbf2024.19.1.3Keywords:
technical analysis, double crossover moving averages strategy, minor trend, lockdownAbstract
Trading is a business, not an investment. Traders focus on minor to secondary trends, while investors focus on the primary trend. The
trading timeframe is crucial in technical analysis. As such a trader who trades with a minor trend timeframe, must have a trading strategy. We aim to examine the impact of the moving averages double crossover strategy on traders’ profit factor based on minor and secondary trend timeframes before, during and after the lockdown periods. Dow Theory was adopted for this study as a trend should be in effect until it gives a definite signal for a reversal. Data was collected from the Nasdaq Composite Index for a five-year period, from 2018 to 2022. During this time frame, the required data for the study was obtained at the point of the golden crossover and exiting at the dead crossover, in which 2018 to 2019 was the period before the lockdown, 2020 to 2021 was the period during lockdown, and 2022 was the year after lockdown. By using trading profits and loss for both longs and shorts, we back tested three strategies of double crossover moving averages that were as follows: i) EMA5 crossover EMA10, ii) EMA5 crossover EMA20 and iii) EMA20 crossover EMA50. A non-parametric analysis of independent samples was used. The result shows that there was a significant difference among those three strategies before the lockdown period, but no significant difference during and after the lockdown period.
References
Bessler, W., & Vendrasco, M. (2022). Journal of International Financial Markets, Short-selling restrictions and financial stability in Europe : Evidence from the Covid-19 crisis. Journal of International Financial Markets, Institutions & Money, 80(April), 101612. https://doi.org/10.1016/j. intfin.2022.101612
Brown, M. S., & Pelosi, M. J. (2019). Moving averages trading method applied to cryptocurrencies. Economics, Commerce and Trade Management: An International Journal, 2(1).
Chang, C. L., Ilomäki, J., Laurila, H., & McAleer, M. (2018). Moving average market timing in European energy markets: Production versus emissions. Energies, 11(12). https://doi.org/10.3390/ en11123281
David, J. L. (2022, June 19). Fed’s interest rate hikes may mark start of tough new economic climate. Washington Post, 5. https://www.washingtonpost.com/business/2022/06/19/fed-rates-economy-markets/
de Souza, M. J. S., Ramos, D. G. F., Pena, M. G., Sobreiro, V. A., & Kimura, H. (2018). Examination of the profitability of technical analysis based on moving average strategies in BRICS. Financial Innovation, 4(1). https://doi.org/10.1186/ s40854-018-0087-z
Ed Seykota. (n.d.). AZQuotes.com. Retrieved December 02, 2023, from AZQuotes.com Web site: https://www.azquotes.com/ quote/800909
Grinblatt, M., Keloharju, M., & Linnainmaa, J. T. (2012). IQ, trading behavior, and performance. Journal of Financial Economics, 104(2),339–362.https://doi.org/https://doi.org/10.1016/j. jfineco.2011.05.016
Gurrib, I. (2016). Optimization of the double crossover strategy for the S&P500 market index. Global Review of Accounting and Finance, 7(1), 92–107. https://doi.org/10.21102/ graf.2016.03.71.07
Haddad, V., Moreira, A., & Muir, T. (2021). When selling becomes viral: Disruptions in debt markets in the COVID-19 crisis and the fed’s response. Review of Financial Studies, 34(11), 5309–5351. https://doi.org/10.1093/rfs/hhaa145
Ishfaq Ahmad, M., Guohui, W., Yasir Rafiq, M., Hasan, M., Chohan, A.-U.-H., & Sattar, A. (2017). Assesing performance of moving average investment timing strategy over the UK stock market. The Journal of Developing Areas, 51(3), 349–362. https://doi.org/10.1353/jda.2017.0077
Jasemi, M., & Kimiagari, A. M. (2012). An investigation of model selection criteria for technical analysis of moving average. Journal of Industrial Engineering International, 8(1), 1–10. https://doi.org/10.1186/2251-712X-8-5
Khokhlova, A., Myachina, T., Volzhaninov, D., Butova, X., Kochurova, A., Berg, V., Gette, I., Moroz, G., Klinova, S., Minigalieva, I., Solovyova, O., Danilova, I., Sokolova, K., Kopylova, G., & Shchepkin, D. (2022). Type 1 Diabetes impairs cardiomyocyte contractility in the left and right ventricular free walls but preserves it in the interventricular septum. International Journal of Molecular Sciences, 23(3), 1–23. https://doi.org/10.3390/ijms23031719
Kusnic, P. (2021). 10 Markets that boomed in 2020 despite (or Because of) Covid-19. https://blog.marketresearch.com/10-markets-that-boomed-in-2020-despite-or-because-of-covid-19
Levine, A., & Pedersen, L. H. (2016). Which trend is your friend? Financial Analysts Journal, 72(3), 51–66. https://www. proquest.com/scholarly-journals/which-trend-is-your-friend/ docview/1794527950/se-2
Lim, M. A. (2016). The handbook of technical analysis - the practioner’s comprehensive guide to technical analysis. John Wiley & Sons.
Monteiro, M. A., Grové, B., & Matthews, N. (2022). Developing a moving average crossover strategy as an alternative hedging strategy for the South Africa maize market. Agriculture, 12(8),1227. https://doi.org/https://doi.org/10.3390/agriculture12081227
Moosa, I. A., & Li, L. C. (2009). Modelling the behaviour of technicians and fundamentalists in the Shanghai stock market. International Journal of Banking and Finance, 6(2), 1–36. https://doi.org/10.32890/ijbf2009.6.2.8387
Murphy, J. J. (1999). Technical analysis of the financial markets - a comprehensive guide to trading methods and applications. New York Institute of Finance.
Ng, L., & Wu, F. (2007). The trading behavior of institutions and individuals in Chinese equity markets. Journal of Banking & Finance, 31(9), 2695–2710. https://doi.org/https://doi.org/10.1016/j.jbankfin.2006.10.029
Pramudya, R., & Pramudya, R. (2020). Technical analysis to determine buying and selling signal in stock trade. International Journal of Finance & Banking Studies (2147-4486), 9(1), 58–67. https://doi.org/10.20525/ijfbs.v9i1.666
Ren, L., & Ren, P. (2018). Applying a combined max-min simple moving average trading strategy to market indexes. Economics, Management, and Financial Markets, 13(2), 11–23. https://doi.org/10.22381/EMFM13220181
Ryu, D., Kim, H., & Yang, H. (2017). Investor sentiment, trading behavior and stock returns. Applied Economics Letters, 24(12), 826–830. https://doi.org/10.1080/13504851.2016.1231890
Sherwani, R. A. K., Shakeel, H., Awan, W. B., Faheem, M., & Aslam, M. (2021). Analysis of COVID-19 data using neutrosophic Kruskal Wallis H test. BMC Medical Research Methodology, 21(1), 1–8. https://doi.org/10.1186/s12874-021-01410-x
Tapa, A., Yean, S. C., & Ahmad, S. N. (2016). Modified moving-average crossover trading strategy: Evidence in Malaysia equity market. International Journal of Economics and Financial Issues, Suppl. Special Issue, 6(7S). https://www.proquest. com/scholarly-journals/modified-moving-average-crossover-trading/docview/1846291755/se-2
Thai Hung, N., Thi My Linh, N., & Vinh Vo, X. (2022). Exchange rate volatility connectedness during Covid-19 outbreak: DECO-GARCH and Transfer Entropy approaches. Journal of International Financial Markets, Institutions and Money, 101628. https://doi.org/https://doi.org/10.1016/j.intfin.2022.101628
Zakamulin, V. (2016). Market timing with moving averages: Anatomy and performance of trading rules. Available at SSRN 2585056.
Published
Issue
Section
How to Cite
Research impact
Harvested 2026-09-07Counts differ between services because each indexes a different body of literature. None of them is the whole picture.
