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An Algorithm for Testing the Efficient Market Hypothesis

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Stren...

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Detalles Bibliográficos
Autores principales: Boboc, Ioana-Andreea, Dinică, Mihai-Cristian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3812129/
https://www.ncbi.nlm.nih.gov/pubmed/24205148
http://dx.doi.org/10.1371/journal.pone.0078177
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author Boboc, Ioana-Andreea
Dinică, Mihai-Cristian
author_facet Boboc, Ioana-Andreea
Dinică, Mihai-Cristian
author_sort Boboc, Ioana-Andreea
collection PubMed
description The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH).
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spelling pubmed-38121292013-11-07 An Algorithm for Testing the Efficient Market Hypothesis Boboc, Ioana-Andreea Dinică, Mihai-Cristian PLoS One Research Article The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH). Public Library of Science 2013-10-29 /pmc/articles/PMC3812129/ /pubmed/24205148 http://dx.doi.org/10.1371/journal.pone.0078177 Text en © 2013 Boboc, Dinică http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Boboc, Ioana-Andreea
Dinică, Mihai-Cristian
An Algorithm for Testing the Efficient Market Hypothesis
title An Algorithm for Testing the Efficient Market Hypothesis
title_full An Algorithm for Testing the Efficient Market Hypothesis
title_fullStr An Algorithm for Testing the Efficient Market Hypothesis
title_full_unstemmed An Algorithm for Testing the Efficient Market Hypothesis
title_short An Algorithm for Testing the Efficient Market Hypothesis
title_sort algorithm for testing the efficient market hypothesis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3812129/
https://www.ncbi.nlm.nih.gov/pubmed/24205148
http://dx.doi.org/10.1371/journal.pone.0078177
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