Using a recently developed method of noise level estimation [1] that makes use of properties of the coarse grained-entropy we have analyzed the noise level for the Dow Jones index and some stocks from the New York Stock Exchange as well as Warsaw Stock Exchange. We have found that the noise level ranges from 40 to 100 percent of the signal variance. The condition of the minimal noise level has been applied to construct optimal portfolios from selected shares [2]. We have observed that the level of noise is statistically correlated with the stock price changes and this fact has been used to create our investment strategy.

Using our method we have calculated 40000 recommendations for portofolio optimalization for periods 4-7 days at Warsaw Stock Exchange. The annual return received in such a way after substracting commissions was around 23%.

[1] K. Urbanowicz and J. A. Holyst, Phys. Rev. E 67, 046218 (2003).
[2] K. Urbanowicz and J.A. Holyst, Proceedings of the Conference Application of Physics in Financial Analysis 4, Physica A (2004).

• Legal notice:
  

  Copyright (c) Pielaszek Research, all rights reserved.
  The above materials, including auxiliary resources, are subject to Publisher's copyright and the Author(s) intellectual rights. Without limiting Author(s) rights under respective Copyright Transfer Agreement, no part of the above documents may be reproduced without the express written permission of Pielaszek Research, the Publisher. Express permission from the Author(s) is required to use the above materials for academic purposes, such as lectures or scientific presentations.
  In every case, proper references including Author(s) name(s) and URL of this webpage: https://science24.com/paper/2449 must be provided.

1. Heider balance in bilayer networks
2. How are World Events Similar to Contagions?
3. Hierarchical Partitions of Social Networks Between Rivaling Leaders
4. New constant of motion for coevolving voter model
5. Fast rumour source detection in large social networks
6. Is there group  impact on study records?  Data mining analysis of students’ scores at Faculty of Physics, WUT
7. How much information is in New York Times articles ? 
8. Co-evolution of the Potts model and topology of interactions
9. Noise enhances information transfer in hierarchical networks
10. Modeling of scientific paradigms spreading
11. Fluctuation-dissipation relations in physiological data collected during emotional stimulation
12. Emotional clusters observed in Internet communities
13. Transition due to preferential cluster growth of collective emotions in online communities
14. Sentiment and activity analysis of Manchester United football forum
15. Collective emotions in Cyberspace, short review of Cyberemotions Project results  
16. Online discussions modelled by an evolving Ising-like dynamics
17. Sentiment and activity analysis of Manchester United football forum.
18. Emotional clusters observed in Internet communities
19.  Multidimensional analysis of emotions based on physiological signals
20. Entropy-growth-based model of emotionally charged online dialogues
21. Diffusion processes on coupled complex networks
22. Analytical approach to model of scientific revolutions
23. Stochastic resonance for information flows on hierarchical networks
24. The Lehman Brothers Effect and Bankruptcy Cascades
25. Observations of extreme events at Warsaw Stock Market
26. Analysis and simulation of emotional states in Internet communities
27. Emotional Agents at the Square Lattice
28. Nonequilibrium phase transition due to social group isolation
29. Scaling of human behavior in the portal browsing.
30. Fluctuation scaling of quotation activities in the foreign exchange market
31. Analysis of scientific productivity using maximum entropy principle and fluctuation-dissipation theorem
32. Scaling of clusters in a one-dimensional system
33. Scaling of human activity at several Web portal
34. Properites of correlations in commodity markets
35. Characteristic periodicities of collective behavior at the foreign exchange market
36. Fluctuation scaling of quotation activities in the foreign exchange market
37. Who wins in competition of social networks ?
38. Networks of companies and branches in Poland
39. Competing networks
40. A threshold Potts model of financial markets
41. Transition to Coherent Oscillatory Behaviour in a Route Choice Game
42. Voter model on Sierpinski fractals