E-Book, Englisch, 77 Seiten, eBook
Gorgulho / Neves / Horta Intelligent Financial Portfolio Composition based on Evolutionary Computation Strategies
2013
ISBN: 978-3-642-32989-0
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, 77 Seiten, eBook
Reihe: SpringerBriefs in Applied Sciences and Technology
ISBN: 978-3-642-32989-0
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
The management of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. This subject is becoming popular among computer scientists which try to adapt known Intelligent Computation techniques to the market’s domain. This book proposes a potential system based on Genetic Algorithms, which aims to manage a financial portfolio by using technical analysis indicators. The results are promising since the approach clearly outperforms the remaining approaches during the recent market crash.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Preface.- Introduction.- Computational Finance .- Work’s Purpose.- General Goals.- Concrete Goals.- Book’s Structure.- Related Work.- Portfolio Theory.- Diversification.- Management.- Market Analysis.- Fundamental Analysis.- Technical Analysis.- Fundamental vs. Technical.- Evolutionary Computation.- Genetic Algorithms.- Individual Representation.- Initial Generation.- Selection.- Offspring Generation.- Genetic Programming.- Existing Solutions.- Portfolio Optimization Theory.- Markowitz’s Pioneer Work.- Alternative Models.- Solving Markowitz’s Model.- Quadratic Programming.- Modeling Real World.- Metaheuristics Approaches to Portfolio Optimization.- Single-objective Evolutionary Algorithms.- Multi-objective Evolutionary Algorithms.- Extensions to Genetic Algorithms.- Technical and Fundamental Analysis in Portfolio Management.- Solution’s Architecture.- Overall Architecture.- Data Flow.- Financial Data Processing Module.- Implementation and Functionality.- Technical Rules Module .- Extensibility and Technical Rules Module Implementation.- Exponential Moving Average (EMA).- Hull Moving Average (HMA).- Double Crossover.- Rate of Change (ROC).- Relative Strength Index (RSI).- Moving Average Convergence Divergence (MACD) .- On Balance Volume (OBV).- True Strength Index (TSI).- Optimization Module.- Chromosome Representation.- Selection.- Mutation.- Crossover.- Initial Generation.- Constraints Handling.- Evaluation Function.- Optimization Module Implementation.- Investment Simulator Module.- Implementation and Functionality.- System Validation.- Performance Measures.- Return on Investment (ROI).- Ratio.- Sortino Ratio.- Classification Parameters.- Strategies Employed.- Case Studies.- Conclusions and Future Work.- Appendixes.
