Survey on log-normally distributed market-technical trend data
Ren\'e Kempen, Stanislaus Maier-Paape

TL;DR
This survey reviews the recent discovery that market-technical trend data follow a log-normal distribution, demonstrating its advantages over daily returns for evaluating trading systems and providing an example of an anti-cyclic trading approach.
Contribution
It introduces the log-normal distribution as a better fit for market-technical trend data and demonstrates its application in evaluating trading systems.
Findings
Log-normal distribution fits market-technical trend data better than daily returns.
Statistical evaluation of trend variables supports the log-normal assumption.
An example of an anti-cyclic trading system based on this approach.
Abstract
In this survey, a short introduction in 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 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.
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Taxonomy
TopicsComplex Systems and Time Series Analysis · Stochastic processes and financial applications · Financial Risk and Volatility Modeling
