By Christian L. Dunis, Peter W. Middleton, Andreas Karathanasopolous, Konstantinos Theofilatos
As know-how development has elevated, so that you could have computational purposes for forecasting, modelling and buying and selling monetary markets and data, and practitioners are discovering ever extra complicated suggestions to monetary demanding situations. Neural networking is a powerful, trainable algorithmic technique which emulates sure facets of human mind capabilities, and is used generally in monetary forecasting bearing in mind fast funding choice making.
This ebook offers the main state-of-the-art man made intelligence (AI)/neural networking purposes for markets, resources and different components of finance. break up into 4 sections, the booklet first explores time sequence research for forecasting and buying and selling throughout various resources, together with derivatives, trade traded money, debt and fairness tools. This part will specialise in development attractiveness, industry timing types, forecasting and buying and selling of economic time sequence. part II offers insights into macro and microeconomics and the way AI options should be used to raised comprehend and are expecting financial variables. part III makes a speciality of company finance and credits research supplying an perception into company buildings and credits, and setting up a courting among financial plan research and the impact of assorted monetary eventualities. part IV makes a speciality of portfolio administration, exploring functions for portfolio idea, asset allocation and optimization.
This publication additionally offers a few of the newest learn within the box of synthetic intelligence and finance, and offers in-depth research and hugely acceptable instruments and strategies for practitioners and researchers during this box.
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40 S. Gadre-Patwardhan et al. P. (2004). Credit scoring using data mining techniques. Singapore Management Review, 26(2), 25–47. , & Roli, A. (2008). A neural network approach for credit risk evaluation. The Quarterly Review of Economics and Finance, 48(4), 733–755. , & Srivastava, R. (1995). Detection of management fraud: A neural network approach. Intelligent Systems in Accounting, Finance and Management, 4(2), 113–126. , et al. (2000). The efficacy of red flags in predicting the SEC’s targets: An artificial neural networks approach.
Christian Groll. (2011, August). Working with financial data: Regression analysis and curve fitting. MATLAB Academy. (2015). , & Hajmeer, M. (2000). Artificial neural networks: Fundamentals, computing, design, and application. Journal of Microbiological Methods, 43, 3–31. A. (1995). Determining mental state from EEG signals using parallel implementations of neural networks. Scientific Programming, special issue on applications analysis, 4(3), 171–183. Touzet, C. F. (1997). Neural reinforcement learning for behaviour synthesis.
Economic prediction using neural networks: The case of IBM daily stock returns. 451–458). , &Takeoka, M. (1990). Stock market prediction system with modular neural networks. In Proceedings of the international joint conference on neural networks (IJCNN) (Vol. ) San Diego. , et al. (1997). Stock price prediction using prior knowledge and neural networks. Intelligent systems in accounting, finance and management, 6(1), 11–22. -S. (2005). A hybrid ARIMA and support vector machines model in stock price forecasting.