Cristian Păuna
 

Economic Informatics Doctoral School, Bucharest Academy of Economic Studies, 11th Tache Ionesc Str., Bucharest, Romania, This paper was co-financed by the Bucharest Academy of Economic Studies during the PhD program

DOI: https://doi.org/10.31410/ITEMA.2018.514

2nd International Scientific Conference on Recent Advances in Information Technology, Tourism, Economics, Management and Agriculture – ITEMA 2018 – Graz, Austria, November 8, 2018, CONFERENCE PROCEEDINGS published by the Association of Economists and Managers of the Balkans, Belgrade, Serbia; ISBN 978-86-80194-13-4

Abstract

Heikin-Ashi is the Japanese term for “average bar”. This methodology is well known as one of the methods to identify and follow the trends using a price time series in financial markets. Nowadays, in the first decades of the 21st century, in the electronic trading environment, with very volatile price market conditions, using the Heikin-Ashi method gets new and special connotations especially when it is about the high-frequency trading. It was found that combining the classical Heikin-Ashi candlesticks with modern limit conditions reliable trading algorithms can be generated in order to produce a good trading return with automated trading systems. This paper will present several trading algorithms based on Heikin-Ashi method for algorithmic trading especially adapted for high-frequency trading systems. It will be revealed how the trading signals can be automatically built and used in order to automate the trading decisions and orders. Exit signals will also be discussed. Trading results obtained with the presented algorithms for Frankfurt Stock Exchange Deutscher Aktienindex Market will be displayed in order to qualify the methods and to compare them with any other trading strategies for high-frequency trading. As conclusions, Heikin-Ashi combined with special limit conditions can generate reliable trading models for algorithmic trading.

Key words
algorithmic trading, automated trading systems, Heikin-Ashi
References
[1] Dănăiață, D., Margea, C., Hurbean, L., Artene, A.S. (2014) Electronic services for business environment, Procedia – Social and Behavioral Sciences 124, Published by Elsevier Ltd., pp. 351-360, ISSN: 1877-0428, doi: 10.1016/j.sbspro. 2014.02.496
[2] Ghilic-Micu, B., Mircea, M., Stoica, M. (2010) The Audit of Business Intelligence Solutions, Informatica Economică vol. 14, no. 1/2010, pp. 66-77, ISSN 1453-1305
[3] Nuti, G., Mirghaemi, M., Traleaven, P., Yingsaeree, C. (2011) Algorithmic trading, IEEE Journal, Volume 44, Issue 11, pp. 22
[4] Aldridge, I. (2013) High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems, 2nd edition, Wiley, ISBN 1-118-34350-6
[5] Hendershott, T., Riordan, R. (2013) Algorithmic Trading and the Market for Liquidity, Journal of Financial and Quantitative Analysis, 48(4), pp. 1001-1024. DOI:10.1017/S0022109013000471
[6] Connors, L., Alvarez, C. (2009) Short Term Trading Strategies That Work, A Quantitative Guide to Trading Stocks and ETFs, Trading Markets Publishing Group, New Jersey, US, ISBN: 978-0-0919239-0-1
[7] Connors L., Alvarez, C. (2009) High Probability ETF Trading 7 Professional Strategies to Improve Your ETF Trading, Connors Research. ISBN: 978-0-615-29741-5
[8] Yong, H., Kang, L., Xiangzhou, Z., Lijun, S., Ngai, E.W.T., Mei, L. (2015) Application of evolutionary computation for rule discovery in stock algorithmic trading: A literature review, Applied Soft Computing, Applied Soft Computing, 36, 534-551. DOI: https://doi.org/10.1016/j.asoc.2015.07.008
[9] Berutich, J.M., Francisco, L., Francisco, l., Quintana, D. (2016) Robust technical trading strategies using GP for algorithmic portfolio selection, Expert Systems with Applications, Volume 46 Issue C, March 2016 pp. 307-315, Pergamon Press, Inc. Tarrytown, NY, USA. DOI: 10.1016/j.eswa.2015.10.040
[10] Youngmin, K., Wonbin, A., Kyong J.O., Enke, D. (2017) An intelligent hybrid trading system for discovering trading rules for the futures market using rough sets and genetic algorithms, Applied Soft Computing Archive, Volume 55 Issue C, June 2017, pp. 127-140. Elsevier Science Publishers B. V. Amsterdam, The Netherlands, DOI: 10.1016/j.asoc.2017.02.006
[11] Lien. K. (2009) Day Trading & Swing Trading the Currency Market. Technical and Fundamental Strategies to Profit from market Moves, John Wiley & Sons. ISBN: 978-0-470-37736-9
[12] Lien, K. (2011) The Little Book of Currency Trading. How to make big Profits in the World of Forex, John Wiley & Sons. ISBN:978-0-470-77035-1
[13] Börse, Frankfurt. (2018) Frankfurt Stock Exchange Deutsche Aktienindex DAX30 Components. Retrieved from https://www. boerse-frankfurt.de/index/dax
[14] Wikipedia encyclopedia. (2018) Candle sticks chart presentation. Available at: https://en. wikipedia.org/wiki/Candlestick_chart
[15] Morris, G.L. (2006) Candlestick Charting Explained: Timeless Techniques for Trading Stocks and Futures, McGraw-Hill, ISBN 0-07-146154-X
[16] Cox, D.R.Sir. (1961) Prediction by Exponentially Weighted moving Averages and Related Methods, Journal of the royal Statistical Society, Series B, Vol. 23, No. 2, pp. 414-422
[17] Meta Quotes. (2018) Online presentation Meta Quotes Language 4. Available at: https://www. metatrader4.com/en/automated-trading/mql4-programming.
[18] Păuna, C., Lungu, I. (2018) Price Cyclicality Model for Financial Market. Reliable Limit Conditions for Algorithmic Trading, Journal of Studies and Researches of Economic Calculation and Economic Cybernetics, 4/2018, ISSN: 0585-7511
[19] Păuna, C. (2010) TheDaxTrader. Automated trading system. Online software presentation. Available at: https://pauna.biz/thedaxtrader
[20] Păuna, C. (2018) Capital and Risk Management for Automated Trading Systems, Proceedings of the 17th International Conference on Informatics in Economy, pp 183-188. Available at: https://pauna.biz/Capital_and_ Risk_Management
[21] Wilder, W. Jr. (1978). New Concepts in Technical Trading Systems. Greensboro, NC: Trend Research. ISBN 978-0894590276

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