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new_papers_of_our_group [2016/10/26 00:44]
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new_papers_of_our_group [2017/07/20 08:44] (current)
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 ==== New papers of our group ==== ==== New papers of our group ====
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 +Empirical economics-Exploring the influence of industries and randomness in stock prices-This study explores the behavior of time series of historical prices and makes two additional contributions to the literature. In summarized form, we present an overview of each of the financial theories that discuss the movements of stock prices and their connection with industry trends. Within this theoretical framework, we first propose that prices be distinguished by following stock prices and a random-walk approach, and second, that the analysis of historical prices be broken down by industries. Similarities among price series are extracted through a clustering methodology based on an approach to non-computable Kolmogorov complexity. We model price series by following geometric Brownian motion and compare them to historical series of stock prices. Our first contribution confirms the existence of hidden common patterns in time series of historical prices that are clearly distinguishable from simulated series. The second contribution claims strong connections among firms carrying out similar industrial activities. The results confirm that stock prices belonging to the same industry behave similarly, whereas they behave differently from those of firms in other industries. Our research sheds new light on the stylized feature of the non-randomness of stock prices by pointing at fundamental aspects related to the industry as partial explanatory factors behind price movements.
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 +GPEM- This study presents the implementation of an automated trading system that uses three critical analyses to determine time-decisions and portfolios for investment. The approach is based on a meta-grammatical evolution methodology that combines technical, fundamental and macroeconomic analysis on a hybrid top-down paradigm. First, the method provides a low-risk portfolio by analyzing countries and industries. Next, aiming to focus on the most robust companies, the system filters the portfolio by analyzing their economic variables. Finally, the system analyzes prices and volumes to optimize investment decisions during a given period. System validation involves a series of experiments in the European financial markets, which are reflected with a data set of over nine hundred companies. The final solutions have been compared with static strategies and other evolutionary implementations and the results show the effectiveness of the proposal.
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 {{: jifs.jpg?50|}} [[http://dx.doi.org/10.1016/j.asoc.2015.11.004| A hybrid automated trading system based on multi-objective grammatical evolution]] Journal of Intelligent and Fuzzy Systems. Volume XX, XXXX 2016, Pages XXX–XXX. {{: jifs.jpg?50|}} [[http://dx.doi.org/10.1016/j.asoc.2015.11.004| A hybrid automated trading system based on multi-objective grammatical evolution]] Journal of Intelligent and Fuzzy Systems. Volume XX, XXXX 2016, Pages XXX–XXX.
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new_papers_of_our_group.txt · Last modified: 2017/07/20 08:44 by J. Ignacio Hidalgo