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Design of stock trading system for historical market data using multiobjective particle swarm optimization of technical indicators

Antonio C. Briza, Prospero C. Naval Jr.
2008 Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08  
The performance of the system was compared to the performance of the technical indicators and the market itself.  ...  The system, using historical end-of-day market data, utilizes the trading signals from a set of financial technical indicators in order to develop a trading rule which is optimized for two objective functions  ...  MULTIOBJECTIVE OPTIMIZATION OF FINANCIAL TECHNICAL INDICATORS In this section, we describe the trading system and how it employs the multiobjective optimization of financial technical indicators.  ... 
doi:10.1145/1388969.1388992 dblp:conf/gecco/BrizaN08 fatcat:5gyh4feuafhflerd4b2mc3lg2i

A multiobjective optimization approach for market timing

Ismail Mohamed, Fernando E. B. Otero
2020 Proceedings of the 2020 Genetic and Evolutionary Computation Conference  
Bera et al [19] used PSO to only optimize the parameters of a single technical indicator.  ...  Although the authors used a multiobjective approach to optimize for Sharpe Ratio and Percentage of Return, the number of technical indicators was limited to five and the indicators used predefined values  ... 
doi:10.1145/3377930.3390156 dblp:conf/gecco/MohamedO20 fatcat:wnd7lplcf5gbphg6yt6zdu4ymq

Multiobjective algorithms for financial trading: Multiobjective out-trades single-objective

Dome Lohpetch, David Corne
2011 2011 IEEE Congress of Evolutionary Computation (CEC)  
One area of study is its use to discover effective rules for technical trading in the context of a portfolio of equities (or an index).  ...  Here we add a comprehensive study of multiobjective approaches to this investigation, and find that multiobjective strategies provide even more robustness in outperforming B&H, even in the context of more  ...  technical indicators.  ... 
doi:10.1109/cec.2011.5949618 dblp:conf/cec/LohpetchC11 fatcat:fyxmosz2dfbehl5j3h3gnftbey

Mean-semivariance portfolio optimization with multiobjective evolutionary algorithms and technical analysis rules

Luís Lobato Macedo, Pedro Godinho, Maria João Alves
2017 Expert systems with applications  
It also proposes the use and comparison of established Technical Analysis (TA) indicators in pursuing better outcomes within the risk-return relation.  ...  Recent work has been devoted to study the use of multiobjective evolutionary algorithms (MOEAs) in stock portfolio optimization, within a common mean-variance framework.  ...  through the use of a technical analysis (TA) indicator (Fu, Chung, & Chung, 2013 ).  ... 
doi:10.1016/j.eswa.2017.02.033 fatcat:yneh53qgsvbc3habw5i2zkjjk4

Greedy Strategies with Multiobjective Optimization for Investment Portfolio Problem Modeling

Xinchen Zhang, Linghao Zhang, Qincheng Zhou, Xu Jin, Shengrong Gong
2022 Computational Intelligence and Neuroscience  
We mainly use greedy strategies with multiobjective optimization models.  ...  For the purpose of obtaining the correct price trend, some popular trend indicator strategies are referred to predict the future price trend in the medium and long term.  ...  of the multiobjective optimization later.  ... 
doi:10.1155/2022/4862772 pmid:35634064 pmcid:PMC9135535 fatcat:sg5jdz2sjfdb5et7v2lsglyfyq

Artificial Intelligence applied to Stock Market Trading: A Review

Fernando G D C Ferreira, Amir H Gandomi, Rodrigo T N Cardoso
2021 IEEE Access  
technical indices as input variables  ...  The classifiers are fed by technical indicators data, and a validation step optimizes the classifiers' hyper-parameters. [11] surveyed Stock Market forecasting Machine Learning models.  ...  He has experience in Applied Mathematics, with emphasis on the following subjects: epidemics control, investment portfolios, multiobjective optimization, impulsive control. VOLUME 4, 2016  ... 
doi:10.1109/access.2021.3058133 fatcat:dlbri6wve5f7jdv7k6wclovzjm

Guest Editorial Special Issue on Fuzzy Techniques in Financial Modeling and Simulation

A. Serguieva, H. Ishibuchi, R. R. Yager, V. P. Alade
2017 IEEE transactions on fuzzy systems  
TRANSACTIONS ON FUZZY SYSTEMS, for accepting the proposal for this special issue and for his constant and effective support throughout the two years of putting the issue together.  ...  We hope that the readers will enjoy this special issue and find it stimulating and thought-provoking, and that it will inspire others to join the community of researchers in computational finance and economics  ...  Lin, Editor-in-Chief of the IEEE  ... 
doi:10.1109/tfuzz.2017.2682542 fatcat:hgo7djm3fzhonp5taaqnmspxjy

Asset management using genetic algorithm: Evidence from Tehran Stock Exchange

Abbas Sarijaloo, Aliakbar Moradbakloo
2014 Management Science Letters  
The results indicate that Tehran Stock Exchange has managed to perform much better than average world market in most years of studies especially on year 2009.  ...  This paper presents an empirical investigation to study the effect of market management using Markowitz theorem.  ...  Acknowledgement The authors would appreciate the comments made on earlier version of this paper, which has significantly improved the quality of the paper.  ... 
doi:10.5267/j.msl.2013.12.036 fatcat:u7my7khvczcvteomv7x35zo24a

Teaching mathematical modeling software for multiobjective optimization in chemical engineering courses

Norberto García, Rubén Ruiz-Femenia, José A. Caballero
2012 Education for Chemical Engineers  
Acknowledgments The authors wish to acknowledge support from the Spanish 581 Ministry of Education and Science (CTQ2009-14420).  ...  Thus, the solution of the multiobjective problem 391 is not unique but rather a set of alternative optimal designs 392 (i.e., Pareto-optimal points) representing the trade-off among 393 the two objectives  ...  It includes utilities such as electricity, The main purpose of this example is to the introduce concept 373 of multiobjective optimization to undergraduate students. 374 Consequently, the supply chain  ... 
doi:10.1016/j.ece.2012.07.001 fatcat:cchj4nwsxvdjbe6thcsh4sytz4

Generating Investment Strategies Using Multiobjective Genetic Programming And Internet Term Popularity Data

Martin Jakubéci
2015 Analele Ştiinţifice ale Universităţii "Al.I. Cuza" din Iaşi: Ştiinţe Economice  
Because of the conflicting nature of these objectives, we have to find Pareto optimal solutions.  ...  Searching for stock picking strategies can be modelled as a multiobjective optimization problem. The objectives are mostly the profit and risk.  ...  Most of the research always concentrated on historical prices and different technical and fundamental indicators.  ... 
doi:10.1515/aicue-2015-0004 fatcat:v7ep3pulojhtlatr3c7oq7mjz4

Channel Optimization of Marketing Based on Users' Social Network Information

Chaolin Peng, Wei Wang
2020 Complexity  
problem, and proposes a multiobjective maximization of influence (MOIM) model.  ...  Based on this, this paper considers factors such as the scale of information diffusion, user interest preferences, and corporate budgets, takes the influence maximization model as a multiobjective optimization  ...  Since the method in this paper comprehensively optimizes the indicators such as influence index, interest index, and cost index, it can provide enterprises with a more flexible set of marketing decision  ... 
doi:10.1155/2020/8833780 fatcat:secvajfhrjbtrku2wr6meygzt4

Multi-objective optimization with an evolutionary artificial neural network for financial forecasting

Matthew Butler, Ali Daniyal
2009 Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO '09  
In this paper, we attempt to make accurate predictions of the movement of the stock market with the aid of an evolutionary artificial neural network (EANN).  ...  To facilitate this objective we constructed an EANN for multi-objective optimization (MOO) that was trained with macro-economic data and its effect on market performance.  ...  Their model optimized on two objective functions, the Sharpe ratio and percent profit and was able to outperform the technical indicators under study, however during the testing periods the market itself  ... 
doi:10.1145/1569901.1570096 dblp:conf/gecco/ButlerD09 fatcat:6rc4lc4jrfamlecxczubrdlc2y

Enterprise Performance Optimization Management Decision-Making and Coordination Mechanism Based on Multiobjective Optimization

Tao Zou, Sijun Bai, Sang-Bing Tsai
2021 Mathematical Problems in Engineering  
This article will give a brief theoretical overview of the combination of system management theory and behavior management theory, MBO target management, and KPI indicators, build a multiobjective optimization  ...  of the company's management and employees, and puts forward the best corporate performance considering the needs of employees; among them, the multiobjective optimization of corporate performance increased  ...  Experimental Model of Enterprise Performance Optimization Management Decision-Making and Coordination Mechanism Based on Multiobjective Optimization Multiobjective Optimization Model.  ... 
doi:10.1155/2021/5510362 fatcat:qdffesbuqnegxii577exig3iaa

Stochastic reactive power market with volatility of wind power considering voltage security

A. Kargarian, M. Raoofat
2011 Energy  
The proposed optimization algorithm uses a multiobjective nonlinear programming technique to minimize market payment and simultaneously maximize voltage security margin.  ...  The paper presents a novel stochastic method for optimal reactive power market clearing considering voltage security and volatile nature of the wind.  ...  Using the proposed threestage multiobjective market algorithm, the optimal operating point is calculated for each simulation and finally, Average Deviation (AD) of different indices is calculated for different  ... 
doi:10.1016/j.energy.2011.01.051 fatcat:cg5lnmuz4ffetmydtjflckcopi

Technical market indicators optimization using evolutionary algorithms

Pablo Fernández-Blanco, Diego J. Bodas-Sagi, Francisco J. Soltero, J. Ignacio Hidalgo
2008 Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation - GECCO '08  
Technical indicators are applied to interpret stock market trending and investing decision.  ...  The main difficulty of an indicator usage is deciding its appropriate parameter values, as number of days of the periods or quantity and kind of indicators.  ...  Thus, the optimization of technical indicators for trading must be adaptive to changes of the fitness, and create new instances of the indicator as needed.  ... 
doi:10.1145/1388969.1388989 dblp:conf/gecco/Fernandez-BlancoBSH08 fatcat:dp3bi7jjrbczhcpjtnl7b6enka
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