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Risks 2016, 4(3), 20;

Survey on Log-Normally Distributed Market-Technical Trend Data

Institut für Mathematik, RWTH Aachen, Templergraben 55, D-52062 Aachen, Germany
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Alexander Szimayer
Received: 5 May 2016 / Revised: 20 June 2016 / Accepted: 23 June 2016 / Published: 4 July 2016
(This article belongs to the Special Issue Applying Stochastic Models in Practice: Empirics and Numerics)
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In this survey, a short introduction of the recent discovery of log-normally-distributed market-technical trend data will be given. The results of the statistical evaluation of typical market-technical trend variables will be presented. It will be shown that the log-normal assumption fits better to empirical trend data than to daily returns of stock prices. This enables one to mathematically evaluate trading systems depending on such variables. In this manner, a basic approach to an anti-cyclic trading system will be given as an example. View Full-Text
Keywords: log-normal; market-technical trend; MinMax-process; trend statistics; market analysis; empirical distribution log-normal; market-technical trend; MinMax-process; trend statistics; market analysis; empirical distribution

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Brenner, R.; Maier-Paape, S. Survey on Log-Normally Distributed Market-Technical Trend Data. Risks 2016, 4, 20.

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