Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/167888 
Year of Publication: 
2016
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 4 [Issue:] 3 [Publisher:] MDPI [Place:] Basel [Year:] 2016 [Pages:] 1-18
Publisher: 
MDPI, Basel
Abstract: 
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.
Subjects: 
log-normal
market-technical trend
MinMax-process
trend statistics
market analysis
empirical distribution
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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