Biologically Inspired Algorithms for Financial Modelling [electronic resource] /by Anthony Brabazon, Michael O’Neill.
by Brabazon, Anthony [author.]; O’Neill, Michael [author.]; SpringerLink (Online service).
Material type:
BookSeries: Natural Computing Series: Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.Description: XV, 269 p., 92 illus. online resource.ISBN: 9783540313076.Subject(s): Computer science | Information theory | Computer simulation | Finance | Banks and banking | Computer Science | Theory of Computation | Quantitative Finance | Simulation and Modeling | Operations Research/Decision Theory | Finance /Banking | Computer ApplicationsDDC classification: 004.0151 Online resources: Click here to access online | Item type | Current location | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| MAIN LIBRARY | QA75.5-76.95 (Browse shelf) | Available |
Browsing MAIN LIBRARY Shelves Close shelf browser
| RL1-803 Contact Dermatitis | G1-922 Frontiers of Geographic Information Technology | QA75.5-76.95 Differential Evolution | QA75.5-76.95 Biologically Inspired Algorithms for Financial Modelling | QA276-280 From Data and Information Analysis to Knowledge Engineering | HD28-70 Customising Stakeholder Management Strategies | QD415-436 Radicals in Synthesis II |
Methodologies -- Neural Network Methodologies -- Evolutionary Methodologies -- Grammatical Evolution -- The Particle Swarm Model -- Ant Colony Models -- Artificial Immune Systems -- Model Development -- Model Development Process -- Technical Analysis -- Case Studies -- Overview of Case Studies -- Index Prediction Using MLPs -- Index Prediction Using a MLP-GA Hybrid -- Index Trading Using Grammatical Evolution -- Adaptive Trading Using Grammatical Evolution -- Intra-day Trading Using Grammatical Evolution -- Automatic Generation of Foreign Exchange Trading Rules -- Corporate Failure Prediction Using Grammatical Evolution -- Corporate Failure Prediction Using an Ant Model -- Bond Rating Using Grammatical Evolution -- Bond Rating Using AIS -- Wrap-up.
Predicting the future for financial gain is a difficult, sometimes profitable activity. The focus of this book is the application of biologically inspired algorithms (BIAs) to financial modelling. In a detailed introduction, the authors explain computer trading on financial markets and the difficulties faced in financial market modelling. Then Part I provides a thorough guide to the various bioinspired methodologies – neural networks, evolutionary computing (particularly genetic algorithms and grammatical evolution), particle swarm and ant colony optimization, and immune systems. Part II brings the reader through the development of market trading systems. Finally, Part III examines real-world case studies where BIA methodologies are employed to construct trading systems in equity and foreign exchange markets, and for the prediction of corporate bond ratings and corporate failures. The book was written for those in the finance community who want to apply BIAs in financial modelling, and for computer scientists who want an introduction to this growing application domain.
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