Static, Dynamic, and Hybrid Neural Networks in Forecasting Inflation
Computational Economics
ICIS '00 Proceedings of the twenty first international conference on Information systems
A comparative assessment of classification methods
Decision Support Systems
Toward Global Optimization of Case-Based Reasoning Systems for Financial Forecasting
Applied Intelligence
Evolutionary Radial Basis Functions for Credit Assessment
Applied Intelligence
Computers and Operations Research
Computational intelligence in economics and finance: carrying on the legacy of Herbert Simon
Information Sciences: an International Journal - Special issue: Computational intelligence in economics and finance
Usable artificial intelligence
CHI '08 Extended Abstracts on Human Factors in Computing Systems
Prediction of corporate financial health by Artificial Neural Network
International Journal of Electronic Finance
The relationship between market sentiment and equity premium: an artificial neural network analysis
International Journal of Electronic Finance
Real estate valuation with artificial intelligence approaches
International Journal of Intelligent Systems Technologies and Applications
AIC'05 Proceedings of the 5th WSEAS International Conference on Applied Informatics and Communications
Applied Intelligence
Soft computing techniques applied to finance
Applied Intelligence
Consumer credit scoring models with limited data
Expert Systems with Applications: An International Journal
Usable intelligent interactive systems: CHI 2009 special interest group meeting
CHI '09 Extended Abstracts on Human Factors in Computing Systems
A hybrid trading system for defence procurement applications
SMO'09 Proceedings of the 9th WSEAS international conference on Simulation, modelling and optimization
Forecasting IPO price using GA and ANN simulation
ISCGAV'10 Proceedings of the 10th WSEAS international conference on Signal processing, computational geometry and artificial vision
Forecasting KOSPI based on a neural network with weighted fuzzy membership functions
Expert Systems with Applications: An International Journal
An empirical study of volatility predictions: stock market analysis using neural networks
WINE'05 Proceedings of the First international conference on Internet and Network Economics
Using Neural Nets To Combine Information Sets In Corporate Bankruptcy Prediction
International Journal of Intelligent Systems in Accounting and Finance Management
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From the Publisher:Neural networks are revolutionizing virtually every aspect of financial and investment decision making. Financial firms worldwide are employing neural networks to tackle difficult tasks involving intuitive judgement or requiring the detection of data patterns which elude conventional analytic techniques. Many observers believe neural networks will eventually outperform even the best traders and investors. Neural networks are already being used to trade the securities markets, to forecast the economy and to analyze credit risk. Indeed, apart from the U.S. Department of Defense, the financial services industry has invested more money in neural network research than any other industry or government body. Unlike other types of artificial intelligence, neural networks mimic to some extent the processing characteristics of the human brain. As a result, neural networks can draw conclusions from incomplete data, recognize patterns as they unfold in real time and forecast the future. They can even learn from past mistakes! In Neural Networks in Finance and Investing, Robert Trippi and Efraim Turban have assembled a stellar collection of articles by experts in industry and academia on the applications of neural networks in this important arena. They discuss neural network successes and failures, as well as identify the vast unrealized potential of neural networks in numerous specialized areas of financial decision making. Topics include neural network fundamentals and overview, analysis of financial condition, business failure prediction, debt risk assessment, security market applications, and neural network approaches to financial forecasting. Nowhere else will the finance professional find such an exciting and relevant in-depth examination of neural networks. Individual chapters discuss how to use neural networks to forecast the stock market, to trade commodities, to assess bond and mortgage risk, to predict bankruptcy and to implement investment strategies. Taken toge