This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency.
Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.
The various chapters present and compare new techniques from many areas including data mining, information systems, machine learning, and statistical artificial intelligence. The volume focuses on evaluating their usefulness for problems in computational finance and financial engineering.
Applications — risk management; asset allocation; dynamic trading and hedging; forecasting; trading cost control. Markets — equity; foreign exchange; bond; commodity; derivatives; Approaches — data mining; statistical AI; machine learning; Monte Carlo simulation; bootstrapping; genetic algorithms; nonparametric methods; fuzzy logic.
The chapters emphasizes in-depth and comparative evaluation with established approaches.
Contents:Decision Technologies:Optimization of Trading Systems and Portfolios (J E Moody & L Z Wu)Nonlinear versus Linear Techniques for Selecting Individual Stocks (S Mahfoud et al.)Soft Prediction of Stock Behavior (Y Baram)Risk Management:Validating a Connectionist Model of Financial Diagnosis (P E Pedersen)Neural Networks for Risk Analysis in Stock Price Forecasts (M Klenin)Optimizing Neural Network Classifiers for Bond Rating (A N Skurikhin & A J Surkan)Statistical Learning for Financial Problems:Forecasting Volatility Mispricing (P J Bolland & A N Burgess)Intraday Modeling of the Term Structure of Interest Rates (J T Connor et al.)Modeling of Nonstationary Financial Time Series by Nonparametric Data Selection (G Deco et al.)Foreign Exchange Trading and Analysis:Principal Components Analysis for Modeling Multi-Currency Porfolios (J Utans et al.)Quantization Effects and Cluster Analysis on Foreign Exchange Rates (W M Leung et al.)A Computer Simulation of Currency Market Participantsand other papers
Readership: Practitioners and academics who are interested in developments and applications of data mining to finance.
This book outlines how best to make use of neural networks. It enables newcomers to the technology to construct robust and meaningful non-linear models and classifiers and benefits the more experienced practitioner who, through over familiarity, might otherwise be inclined to jump to unwarranted conclusions. The book is an invaluable resource not only for those in industry who are interested in neural computing solutions, but also for final year undergraduates or graduate students who are working on neural computing projects. It provides advice which will help make the best use of the growing number of commercial and public domain neural network software products, freeing the specialist from dependence upon external consultants.
The volume features chapters of theoretical and practical relevance clarifying recent advances in the associated applied field from different standpoints, relying on similar valuation problems and, as mentioned, facilitating a mutual and beneficial methodological and theoretical knowledge transfer. The distinctive aspects of the volume can be summarized as follows:Strong benchmarking philosophy, with contributors explicitly asked to underline current limits and desirable developments in their areas.
Theoretical contributions, aimed at advancing the state-of-the-art in the given domain with a clear potential for applications
The inclusion of an algorithmic-computational discussion of issues arising on similar valuation problems across different methods.
Variety of applications: rarely is it possible within a single volume to consider and analyze different, and possibly competing, alternative optimization techniques applied to well-identified financial valuation problems.
Clear definition of the current state-of-the-art in each methodological and applied area to facilitate future research directions.