Neural Networks for Financial Applications

Topics: Stock market, Neural network, Technical analysis Pages: 16 (4265 words) Published: January 18, 2013
Neural Networks for Financial Application
J.T Gunasekara Index Number:09002006 Registration Number:2009cs200 Email: jgtharindu@gmail.com Phone:0714771759 Supervisor: H.D Premarathne University of Colombo School of Computing September 6, 2012

Declaration I hear by declare that this literature survey report has been prepared by J.T Gunasekara based on mainly the reference material listed under the bibliography of this report. No major components (sentences/paragraphs etc. ) of other publications are directly into this report without being duly cited. Name of Candidate: J.T Gunasekara Signature of Candidate :............................... Date :..............

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Abstract The survey is on Neural Networks for Financial Application. Artificial Neural Network usage for finance has broadly discussed on three major areas of Financial Applications. Financial fraud Detection, Financial Forecasting and Financial Risk Management are three main sections considered here. Credit card fraud Detection, Tax Fraud Detection, Stock Market Predictions, Cash Forecasting Bankruptcy Predictions, Risk Management of finance and Foreign Exchange Rate forecasting are the financial applications considered on this survey. Other options available in solving applications are discussed and accuracy and efficiency compare with Neural Network approach models. How to further develop designed model are address in this survey and what is best Neural Network architecture and best input parameters selection has considered in this review.

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Acknowledgement I would like to express my deepest gratitude to my thesis supervisor Dr. H.D Premarathne for his valuable guidance, motivation and support throughout this thesis study. My special thanks goes out to all wonderful people who have committed their lives for great research on these areas and always trying to build a better world for others with science, without whom I would be in trouble writing this survey.

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Contents
Declaration Abstract Acknowledgement List of Figures List of Abbreviations 1 Financial Fraud Detection Using Neural Networks 1.1 Credit Card Fraud . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Credit Card Fraud Detection . . . . . . . . . . . . . 1.1.2 Credit Card Fraud Detection Using Neural Networks 1.2 Tax Fraud Detection . . . . . . . . . . . . . . . . . . . . . . 1.2.1 Neural Networks for Tax Fraud Detection . . . . . . 2 Financial Forecasting Using Neural Networks 2.1 Bankruptcy predictions . . . . . . . . . . . . . . . . . . . . 2.1.1 Neural Network Approaches . . . . . . . . . . . . . 2.2 Cash Forecasting . . . . . . . . . . . . . . . . . . . . . . . 2.2.1 Neural Network model in Cash Forecasting . . . . . 2.3 Stock Market Predictions . . . . . . . . . . . . . . . . . . . 2.3.1 Stock value prediction based on Technical Analysis 2.3.2 Stock value prediction based on Hybrid Analysis . . 2.3.3 Stock market volatility predictions . . . . . . . . . i ii iii v v 1 1 1 2 5 5 7 7 7 9 9 10 11 13 14

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List of Figures
1.1 1.2 1.3 1.4 1.5 1.6 2.1 2.2 2.3 2.4 2.5 2.6 2.7 2.8 2.9 Input Descriptors NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture NN Architecture 3 crests . . . . . . NN Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ....

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