Using the exponential moving average without delay for stock market timing
DOI:
https://doi.org/10.58564/EASJ/1.2.2022.7Keywords:
Financial market, accelerated moving averageAbstract
The purpose of this research is to test the ability of the zero-lag Exponential moving average indicator timing trading in the financial market to select the best stocks and achieve a higher return than buying and holding. The research relied on two main hypotheses, the first being the timing of trading using the zero-lag Exponential moving average indicator that can achieve higher returns than buying and holding. The second hypothesis is the performance of the zero-lag Exponential moving average indicator does not differ by using different methods of signal generation and the timing of trading according to it. The research community has been identified with all stocks listed on the Iraq Stock Exchange. The implementation of the financial research tests requires choosing a deliberate sample from the research community that fulfills the requirements of testing indicators of technical analysis according to a number of conditions, so (38) companies were nominated to be the research sample and were distributed by (17) companies in the banking sector, and (2) companies in The insurance sector, (4) companies in the services sector, (7) companies in the industrial sector, (6) companies in the hotel and tourism sector, one company in the telecommunications sector, and one company in the agricultural sector, and this sample formed Approximately (30%) of the research community of (128) companies. The duration of the study extended from the specified time period from (2/1/2016) to (31/12/2021), and by using financial and statistical methods, algorithms, and computer programs, the research reached a number of conclusions, the most important of which are. The market can be timed successfully using the zero-lag Exponential moving average indicator.
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Copyright (c) 2022 Assistant Teacher Wissam Shafeeq Hassan, Assistant Prof. Dr. Ayad Taher Mohammed

This work is licensed under a Creative Commons Attribution 4.0 International License.