Papers of Cristian Păuna

Price Cyclicality. The music of price movement.

Price Cyclicality is a publishing project including 50 chapters presenting 13 original mathematical indicators, 33 quantified trading strategies, and 4 different risk and capital management strategies. This project is dedicated to every trader or investor who dares to risk their money in today's financial market conditions. All this work will help to reduce the risk and to make a more stable profit.

Each paper in this project presents a self-standing subject and includes two levels of scientific approach. The first level shows the general ideas, principles, and quantified rules of applying the theory in practice. The second level is the precise mathematical approach of each algorithm. In this way, this work is helpful for any trader or investor in financial markets at any level. The ones who use already-made software packages can read only the general theory to understand the basic idea and to check the rules and the results. At the same time, the mathematical approach and code examples included in every paper will help those who want to develop their own software tools and build performant automated trading software.

In 1990 I made my first simulations using the Price Cyclicality mathematical transformation for the exchange rate of Romanian currency against the US dollar. I was a poor student at that time reading the daily currency data published in a local newspaper. I made good money using this algorithm to trade dollars. Price Cyclicality became fast my favourite approach for financial trading. This model was the base of my first trading software in 1998. I developed it every day since then, and I have tested and used it in multiple markets with excellent results. After 2008 when the markets changed significantly, the Price Cyclicality model remained stable and profitable in the long-time run. In 2020 I finished my PhD in economic informatics, also based on the Price Cyclicality theory. After 33 years of work and individual research, everything is clear and functional. Now is the right time to share all I know about this fantastic subject.

1. Price Cyclicality
2. Relative Cyclicality
3. Adaptive Cyclicality
4. Compound Cyclicality
5. Volume Cyclicality
6. Price Prediction Line
7. Price Cyclicality Line
8. Price Action Line
9. Heikin-Ashi Trend Line
10. Smoothed Heikin-Ashi
11. Relative Heikin-Ashi
12. Relative Momentum
13. Z-Score Indicator
14. Extreme Points of Price Cyclicality
15. Extreme Points of Relative Cyclicality
16. Extreme Points of Adaptive Cyclicality
17. Extreme Points of Compound Cyclicality
18. Resonance of Price Cyclicality
19. Resonance of Compound Cyclicality
20. Fractals with Price Cyclicality
21. Breakouts with Price Cyclicality
22. Doji Candles with Price Cyclicality
23. Reversals with Price Cyclicality
24. Turtle Trades with Price Cyclicality
25. Singularities with Price Cyclicality

26. Extreme Price with Price Cyclicality
27. Parabolic SAR with Price Cyclicality
28. Super Trend with Price Cyclicality
29. Price Cyclicality Line Signals
30. Price Prediction Line Signals
31. RSI Resonance with Volume Cyclicality
32. Price, Compound, and Volume Cyclicality
33. Adaptive and Relative Cyclicality
34. Relative Smoothed Heikin-Ashi
35. Heikin-Ashi with Relative Cyclicality
36. Original Trades with Relative Cyclicality
37. Order Blocks with Relative Cyclicality
38. Relative Momentum with Relative Cyclicality
39. Price Convergence with Relative Cyclicality
40. US open session with Relative Cyclicality
41. US close session with Relative Cyclicality
42. Connors RSI with Volume Cyclicality
43. Connors RSI with Relative Cyclicality
44. Connors TPS with Relative Momentum
45. RSI PowerZone with Relative Momentum
46. Z-Score with Relative Cyclicality
47. Simple Risk Distribution
48. Linear Risk Distribution
49. Logarithmic Risk Distribution
50. Capital Recovery Management

All the above algorithms and strategies are perfectly functional and are included in my automated trading software Dow Jones Predictor and Dow Jones Trader. The quantified strategies presented in the chapters above are optimised for the market data after 01.01.2018. Each method and the obtained trading results are presented for my favourite market, Dow Jones Industrial Average, the main Wall Street index. Any algorithm can be optimised for any other financial market with good liquidity. These algorithms were developed with the main purpose of reducing the allocated risk. However, trading financial markets involves a high risk of losing money, if markets act unprecedented. For this reason, using a low-risk level is anytime good advice. Small profits are much better than large losses.

Disclaimer: Anyone interested in the above papers must know from the beginning:
1. No paper included in this site guarantees a profit or a particular profitable performance.
2. The author of these papers can not be held responsible for bed performance or any losses.
3. The price paid for any paper included in this site is not refundable in any way.
Anyone who does not agree with one of the above is asked to EXIT this site.

✔Volume Cyclicality. Reliable Capital Investment Signals Based on Trading Volume Information. Păuna, C. (2019). Timișoara, Romania: Timișoara Journal of Economics and Business. Volume 13, Issue 1/2020. ISSN: 2286-0991. West University of Timisoara. DOI: 10.2478/tjeb-2020-0003 Available at: tjeb.ro

✔Price Probability Predictor. Capital investments assisted by a probability field. Păuna, C. (2020). Bucharest, Romania: International Conference on Business Excellence ICBE2020. Published by Springer in Business Revolution in a Digital Era as part of the Springer Proceedings in Business and Economics book series. Păuna C. (2021) Price Probability Predictor. Capital Investments Assisted by a Probability Field. In: Dima A.M., D'Ascenzo F. (eds) Business Revolution in a Digital Era. Springer Proceedings in Business and Economics. Springer, Cham. DOI: 10.1007/978-3-030-59972-0_21

✔Informatics methods to include limit conditions into automated capital investment software systems. Păuna, C., Lungu, I. (2020). Bucharest, Romania. IE2020 19th International Conference on Economic Informatics. Academy of Economic Studies. DOI: 10.12948/ie2020.04.01 Available at: conferenceie.ase.ro

✔Behavioral patterns and fears in investor psychology. Păuna, C. (2020). Bucharest, Romania. DOI: 10.13140/RG.2.2.29367.47521 Available at: researchgate.net

✔Tipare comportamentale și frici în psihologia investitorului. Păuna, C. (2020). Bucharest, Romania. DOI: 10.13140/RG.2.2.33742.82241 Available at: researchgate.net

✔The psychology of using algorithms to automate decisions in financial information systems. (Psihologia folosirii algoritmilor pentru automatizarea deciziilor în sistemele informaționale financiare.) Păuna, C. (2020). Bucharest, Romania. DOI: 10.13140/RG.2.2.19901.61928 Available at: researchgate.net

✔Reliable Signals and Limit Conditions using Trigonometric Interpolation for Algorithmic Capital Investments. Păuna, C. (2020). Alicante, Spain: 7th Business Systems Laboratory International Symposium 2020. University of Alicante. Available at: bslab-symposium.net

✔Logarithmic Risk Distribution to build a stable capital growth for any business or investment. Păuna, C. (2019). Bucharest, Romania: 13th International Management Conference. Academy of Economic Studies. Available at: conference.management.ase.ro

✔Price Prediction Line. Investment Signals and Limit Conditions Applied for the German Financial Market. Păuna, C. (2019). International Journal of Computer and Information Engineering. Vol.13, No.9, 2019. World Academy of Science, Engineering and Technology. Available at: waset.org Best Paper Award - International Conference on Advances in Information Systems, ICAIS 2019, Rome, Italy.

✔Trading Fragmentation Methodology to Reduce the Capital Exposure with Algorithmic Trading. Păuna, C. (2019). Bucharest, Romania: Database Systems Journal. Volume X, Issue 2019. ISSN: 2069-3230. Academy of Economic Studies. Available at: dbjournal.ro

✔Additional Limit Conditions for Breakout Trading Strategies. Păuna, C. (2019). Bucharest, Romania: Informatica Economica Journal. Volume 23, Issue 2/2019. ISSN: 1453-1305. Academy of Economic Studies. DOI: 10.12948/issn14531305/23.2.2019.03 Available at: revistaie.ase.ro

✔Silent Market Indicator. Methodology to Avoid the Risk in No Significant Price Movements. Păuna, C. (2019). Timișoara, Romania: Timișoara Journal of Economics and Business. Volume 12, Issue 1/2019. ISSN: 2286-0991. West University of Timisoara. DOI: 10.2478/tjeb-2018-0009 Available at: tjeb.ro

✔Progressive Management Methodology for Real-Time Business Intelligence Decision Systems. Păuna, C. (2019). Bucharest, Romania: 18th International Conference on Informatics in Economy IE2019 by Bucharest University of Economic Studies, Available at: conferenceie.ase.ro.org

✔A Prediction Model Using the Price Cyclicality Function Optimized for Algorithmic Trading in Financial Markets.Păuna, C. (2019). International Journal of Computer and Information Engineering Vol.13, No.4, 2019. World Academy of Science, Engineering and Technology. Paper Presented at International Conference on Intelligent Information Systems ICIIS 2019, Athens, Grece. Available at: waset.org Best Paper Award - International Conference on Intelligent Information Systems, ICIIS 2019, Athens, Greece.

✔Data Mining Methods on Time Price Series for Algorithmic Trading Systems. Păuna, C. (2019). Bucharest, Romania: Informatica Economica Journal. Volume 23, Issue 1/2019. ISSN: 1453-1305. Academy of Economic Studies DOI: 10.12948/issn14531305/23.1.2019.03 Available at: revistaie.ase.ro

✔Low risk trading algorithm based on the price cyclicality function for capital markets. Păuna, C. (2019). Bucharest, Romania: The 13th International Conference On Business Excellence ICBE 2019 Faculty of Business Administration, Bucharest Academy of Economic Studies. Society on Business Excellence. DOI: 10.2478/mmcks-2019-0006 Available at: bizexcellence.ro This paper was awarded with "Management and Marketing Award - Challenges for the Knowledge Society".

✔Reliable Signals Based on Fisher Transform for Algorithmic Trading. Păuna, C. (2019). Timișoara, Romania: Timișoara Journal of Economics and Business. Volume 11, Issue 1/2018. ISSN: 2286-0991. West University of Timisoara. DOI: 10.2478/tjeb-2018-0006 Available at: tjeb.ro

✔Reliable Signals and Limit Conditions for Automated Trading Systems. Păuna, C. (2018). Iași, 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: rebs.feaa.uaic.ro

✔Price Cyclicality Model for Financial Markets. Reliable Limit Conditions for Algorithmic Trading. Păuna, C., Lungu. I. (2018). Bucharest, Romania: Economic Computation and Economic Cybernetics Studies and Research Journal. Volume 52, Issue 4/2018. ISSN: 1842–3264. Academy of Economic Studies. DOI: 10.24818/18423264/52.4.18.10 Available at: ecocyb.ase.ro

✔Smoothed Heikin-Ashi Algorithms Optimised for Automated Trading Systems. Păuna, C. (2018). Graz, Austria: Proceeding of the 2nd International Scientific Conference on IT, Tourism, Economics, Management and Agriculture, ITEMA 2018, Nov. 2018, Graz University of Technology. Published by International Journal of Economics and Management Systems, Volume 4, 2019, ISSN: 2367-8925. Available at: iaras.org

✔The Quality Trading Coefficient. General Formula to Qualify a Trade and a Trading Methodology. Păuna, C. (2018). Bucharest, Romania: Informatica Economica Journal. Volume 22, Issue 3/2018. ISSN 1453-1305. Academy of Economic Studies. DOI: 10.12948/issn14531305/22.3.2018.09 Available at: revistaie.ase.ro

✔Arbitrage Trading Systems for Cryptocurrencies. Design Principles and Server Architecture. Păuna, C. (2018). Bucharest, Romania: Informatica Economica Journal. Volume 22, Issue 2/2018. ISSN: 1453-1305. Academy of Economic Studies. DOI: 10.12948/issn14531305/22.2.2018.04
Available at: revistaie.ase.ro

✔Capital and Risk Management for Automated Trading Systems. Păuna, C. (2018). Iași, Romania: Proceeding of the 17th International Conference on Informatics in Economy, May 2018, Alexandru Ioan Cuza University. Available at: conferenceie.ase.ro

✔Automated Trading Software. Design and Integration in Business Intelligence Systems. Păuna, C. (2018). Bucharest, Romania: Database Systems Journal. Volume IX, Issue 1/2018. ISSN: 2069-3230. Academy of Economic Studies. Available at: dbjournal.ro

✔International Conference on Business Excellence ICBE2020. Academy of Economic Studies, Bucharest, Romania, June 2020 Price Probability Predictor. Capital investments assisted by a probability field.

✔19th International Conference on Economic Informatics. Academy of Economic Studies, Bucharest, Romania, May 2020 Informatics methods to include limit conditions into automated capital investment software systems.

✔7th Business Systems Laboratory International Symposium 2020. University of Alicante, Alicante, Spain, January 2020 Reliable Signals and Limit Conditions using Trigonometric Interpolation for Algorithmic Capital Investments.

✔13th International Management Conference. IMC 2019. Academy of Economic Studies, Bucharest, Romania, November 2019 Logarithmic Risk Distribution to build a stable capital growth for any business or investment.

✔International Conference on Advances in Informatin Systems. ICAIS 2019. World Academy of Science, Engineering andTechnology, Rome, Italy, September 2019 Price Prediction Line. Investment signals and limit conditions applied for the German financial market.Best Paper Award - International Conference on Advances in Information Systems, ICAIS 2019, Rome, Italy.

✔18th International Conference on Informatics in Economy. ICIE 2019. Academy of Economic Studies, Bucharest, Romania, May 2019 Progressive Management Methodology for Real-Time Business Intellignece Decision Systems.

✔10th International Conference on on Intelligent Information Systems. ICIIS 2019. World Academy of Science, Engineering andTechnology, Athens, Grece, April 2019
A prediction model using the price cyclicality function optimized for algorithmic trading in financial markets.Best Paper Award - International Conference on Intelligent Information Systems, ICIIS 2019, Athens, Greece.

✔13th International Conference on Business Excellence. ICBE 2019. Faculty of Business Administreation, ASE, Bucharest, Romania, March 2019 Low-risk trading algorithm based on the price cyclicality function for capital markets.Management and Marketing Award - Challenges for the Knowledge Society, ICBE 2019, Bucharest, Romania.

✔2nd International Conference on IT, Tourism, Economy, Management and Agriculture. ITEMA 2018. Graz University of Technology, Graz, Austria, November 2018 Smoothed Heikin-Ashi Algorithms Optimized for Automated Trading Systems.

✔17th International Conference on Informatics in Economy. ICIE 2018. Alexandru Ioan Cuza University, Iași, Romania, May 2018 Capital and Risk Management for Automated Trading Systems.

✔WaitOnSignal model to increase capital efficiency. Method and Experimental Findings. Published on ResearchGate in August 2018. DOI: 10.13140/RG.2.2.34582.45122

✔How to measure Investment Risk Aversion. Method and experimental Findings. Published on ResearchGate in October 2018. DOI: 10.13140/RG.2.2.34819.86566

✔Determining the stiffness of the pressed assemblies. Păuna, C., Stanciu, Șt. (1994). București, România, Academia Română: Studii și Cercetări de Mecanică Aplicată, Volum 6, Tom 53, Nov-Dec. 1994, 613-624 (acad.ro)

✔Analysis of the functional characteristics of hydrostatic bearing nut screw type systems Păuna, C., Stanciu, Șt. (1994). București, România, Academia Română: Studii și Cercetări de Mecanică Aplicată, Volum 4, Tom 53, Jul-Aug. 1994, p. 357-365 (acad.ro)

✔Calculation and Influence of Geometric and Load Parameters on Functional Characteristics of Hydrostatic Radial Bearings Păuna, C., Stanciu, Șt., Suciu, C. (1994). București, România, Academia Română: Studii și Cercetări de Mecanică Aplicată, Volum 3, Tom 53, Mai-Jun. 1994, p. 243-263 (acad.ro)

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