Commenced in January 2007
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Price Prediction Line, Investment Signals and Limit Conditions Applied for the German Financial Market

Authors: Cristian Păuna

Abstract:

In the first decades of the 21st century, in the electronic trading environment, algorithmic capital investments became the primary tool to make a profit by speculations in financial markets. A significant number of traders, private or institutional investors are participating in the capital markets every day using automated algorithms. The autonomous trading software is today a considerable part in the business intelligence system of any modern financial activity. The trading decisions and orders are made automatically by computers using different mathematical models. This paper will present one of these models called Price Prediction Line. A mathematical algorithm will be revealed to build a reliable trend line, which is the base for limit conditions and automated investment signals, the core for a computerized investment system. The paper will guide how to apply these tools to generate entry and exit investment signals, limit conditions to build a mathematical filter for the investment opportunities, and the methodology to integrate all of these in automated investment software. The paper will also present trading results obtained for the leading German financial market index with the presented methods to analyze and to compare different automated investment algorithms. It was found that a specific mathematical algorithm can be optimized and integrated into an automated trading system with good and sustained results for the leading German Market. Investment results will be compared in order to qualify the presented model. In conclusion, a 1:6.12 risk was obtained to reward ratio applying the trigonometric method to the DAX Deutscher Aktienindex on 24 months investment. These results are superior to those obtained with other similar models as this paper reveal. The general idea sustained by this paper is that the Price Prediction Line model presented is a reliable capital investment methodology that can be successfully applied to build an automated investment system with excellent results.

Keywords: Algorithmic trading, automated investment system, DAX Deutscher Aktienindex.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.3455749

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References:


[1] ISITC, International Securities Association for Institutional Trade Communication, 2011 Member Survey, March 12, 2012. Available on http://www.isitc.org
[2] Funke, N., Goldstein, A., Financial Market Volatility, Intereconomics Journal, volume 31, Issue 5, 1996, pp. 215-220. DOI: 10.1007/BF02927152
[3] Peters E., Chaos and Order in Capital Markets. A New View of Cycles, Prices and Market Volatility, 1996, John Wiley & Sons Inc., ISBN 0-471-13938-6
[4] Connors L., Alvarez C., Short term trading strategies that work. A Quantitative Guide to Stock Market Behavior, US: Trading Markets Publishing Group, 2009, ISBN 978-0-9819239-0-1
[5] Connors L., Sen C., How Markets Really Work – A Quantitative Guide to Stock Market Behavior, US: Connors Research Group, 2004, ISBN 978-0-9755513-1-8
[6] Connors L., Alvarez C., High Probability ETF Trading – 7 Professional Strategies to Improve Your ETF Trading, US: Connors Research, 2009, ISBN: 978-0-615-29741-5
[7] Connors L.A., Best Trading Patterns, The Best of the Professional Traders Journal, US: M. Gordon Publishing Group, 1999, ISBN: 0-9650461-0-2
[8] Lien K., Day Trading and Swing Trading the Currency Market. Technical and Fundamental Strategies to Profit the Market Moves. US: John Wiley & Sons, 2009, ISBN: 978-0-470-37736-0
[9] Lien K., The Little Book of Currency Trading. How to Make Big Profits in the World of Forex, US: John Wiley & Sons, 2011 ISBN: 978-0-470-77035-1
[10] Cheng G., 7 Winning Strategies for Trafing Forrex. Real and actionable techniques for profiting from the currency markets. GB: Hariman Trading, 2007 ISBN: 978-0-857190-90-1
[11] Păuna C., Reliable Signals Based on Fisher Transform for Algorithmic Trading. Romania: Timișoara Journal of Economics and Business. Volume 11, Issue 1/2018 ISSN: 2286-0991. West University of Timișoara. DOI: 10.2478/tjeb-2018-0006 Available at: https://tjeb.ro
[12] Păuna C., Reliable Signals and Limit Conditions for Automated Trading Systems. Romania: Review of economic and Business Studies. Volume XI, Issue 2/2018. ISSN: 1843-763X. Alexandru Ioan Cuza University Press. DOI: 10.1515/rebs-2018-0070 Available at: http://rebs.feaa.uaic.ro
[13] Păuna C., Smoothed Heikin-Ashi Algorithms Optimized for Automated Trading Systems, Austria: Proceeding of the 2nd International Scientific Conference on IT, Tourism, Economics, Management, and Agriculture. ITEMA 2018. Graz University of Technology. Available at: https://itema-conference.com
[14] Păuna C., Low risk trading algorithm based on the price cyclicality function for capital markets. Romania: 13th International Conference on Business ExcellenceAt: FABIZ, ASE, Bucharest DOI: 10.2478/mmcks-2019-0006
[15] Păuna C., Additional Limit Conditions for Breakout Trading Strategies. Romania: Informatica Economica Journal. Volume 23, Issue 2/2019. DOI: 10.12948/issn14531305/23.2.2019.03 Available at: http://revistaie.ase.ro
[16] Ward S., High Performance Trading. 35 Practicaal Strategies and Techniques to enhance Your Trading Psychology and Performance. GB: Hariman House 2010 ISBN: 978-1-905641-61-1
[17] Pauna C., Lungu, I., Price Cyclicality Model for Financial Markets. Reliable Limit Conditions for Algorithmic Trading, Romania: Economic computation and economic cybernetics studies and research, Volume 52, Issue 4/2018. DOI: 10.24818/18423264/52.4.18.10 Available at: http://ecocyb.ase.ro
[18] Cox, D.R. Sir, Prediction by Exponentially Weighted moving Averages and Related Methods, 1961, Journal of the royal Statistical Society, Series B, Vol. 23, No. 2, pp. 414-422
[19] Börse, Frankfurt, Frankfurt Stock Exchange Deutscher Aktienindex DAX30 Components, 2019. Available on: http://www.boerse-frankfurt.de/index/dax
[20] Reinsch, C., Smoothing by Spline functions, Numerische Mathematik, Volume 10, Issue 3, pp 177–183, ISSN 0945-3245, 1967, DOI https://doi.org/ 10.1007/BF02162161
[21] Berbente, C., Mitran, S., Zancu, S., Metode Numerice, romania: Editura Tehnică,1997, ISBN 973-31-1135-X
[22] Andrei T., Statistică și econometrie, Romania: Editura Economică, București, 2003. ISBN: 973-590-764-X
[23] MetaQuotes Language, 2019, – Available at: https://www. metatrader4.com/en/automated-trading/mql4-programming
[24] Brexit, The prospective withdrawal of the United Kingdom (UK) from the European Union (EU), 2016, Available at: https://en.wikipedia.org/wiki/Brexit
[25] Păuna C., TheDaxTrader automated trading system, online software presentation. 2010, Available at: https://pauna.biz/ thedaxtrader
[26] Păuna, C., Capital and Risk Management for Automated Trading Systems, Proceedings of the 17th International Conference on Informatics in Economy, May 2018, pp 183-188. Available at: https://pauna.biz/ideas