Artificial intelligence applications in financial forecasting - a survey and some empirical results

Financial forecasting is an area of research which has been attracting a lot of attention recently from practitioners in the field of artificial intelligence. Apart from the economic benefits of accurate financial prediction, the inherent nonlinearities in financial data make the task of analyzing and forecasting an extremely challenging task. This paper presents a survey of more than 100 articles published over two centuries from 1933 up to 2013 in an attempt to identify the developments and trends in the field of financial forecasting with focus on application of artificial intelligence for the purpose. The findings from the survey indicate that artificial intelligence and signal processing based techniques are more efficient when compared to traditional financial forecasting techniques and these techniques appear well suited for the task of financial forecasting. Some of the issues that need addressing are discussed in brief. A novel technique for selection of the input dataset size for ensuring best possible forecast accuracy is also presented. The results confirm the effectiveness of the proposed technique in improving the accuracy of forecasts.

[1]  Yi-Ping Chen,et al.  The Efficacy of Neural Networks and Simple Technical Indicators in Predicting Stock Markets , 2007, 2007 International Conference on Convergence Information Technology (ICCIT 2007).

[2]  Rob J Hyndman,et al.  25 years of time series forecasting , 2006 .

[3]  Ingoo Han,et al.  Financial data mining using genetic algorithms technique: application to KOSPI 200 , 1998 .

[4]  Vassilis S. Kodogiannis,et al.  Forecasting Financial Time Series using Neural Network and Fuzzy System-based Techniques , 2002, Neural Computing & Applications.

[5]  Donald C. Wunsch,et al.  A fuzzy perspective towards technical analysis-case study of trend prediction using moving averages , 1999, Proceedings of the IEEE/IAFE 1999 Conference on Computational Intelligence for Financial Engineering (CIFEr) (IEEE Cat. No.99TH8408).

[6]  Rahmatollah Gholipour,et al.  Application of Fuzzy-neural networks in multi-ahead forecast of stock price , 2010 .

[7]  David Allan Umstead.  Forecasting Stock Market Prices , 1977 .

[8]  H. S. Ng,et al.  Intelligent trading advisor [for investment analysis] , 2000, Proceedings of the 2000 IEEE International Conference on Management of Innovation and Technology. ICMIT 2000. 'Management in the 21st Century' (Cat. No.00EX457).

[9]  Harry V. Roberts,et al.  STOCK‐MARKET “PATTERNS” AND FINANCIAL ANALYSIS: METHODOLOGICAL SUGGESTIONS , 1959 .

[10]  Tong-Seng Quah,et al.  Improving returns on stock investment through neural network selection , 1999 .

[11]  Edward Tsang,et al.  Investment decision making using FGP: a case study , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[12]  Mehdi Khashei,et al.  Exchange rate forecasting better with hybrid artificial neural networks models , 2012 .

[13]  Jianzhou Wang,et al.  Stock index forecasting based on a hybrid model , 2012 .

[14]  Keith C. C. Chan,et al.  Enhancing technical analysis in the forex market using neural networks , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[15]  Magdalene Marinaki,et al.  Ant colony and particle swarm optimization for financial classification problems , 2009, Expert Syst. Appl..

[16]  Michael Y. Hu,et al.  Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis , 1999, Eur. J. Oper. Res..

[17]  Po-Chang Ko,et al.  A Nonlinear Stock Valuation Using a Hybrid Model of Genetic Algorithm and Cubic Spline , 2007, Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007).

[18]  N. R. Sakthivel,et al.  Application of hybrid adaptive filters for stock market prediction , 2010, 2010 International Conference on Communication and Computational Intelligence (INCOCCI).

[19]  Rimvydas Simutis,et al.  Fuzzy logic based stock trading system , 2000, Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520).

[20]  Jin Li,et al.  EDDIE In Financial Decision Making , 2001 .

[21]  Bruce J Vanstone,et al.  A survey of the application of soft computing to investment and financial trading , 2003 .

[22]  Zuo Quan Xu,et al.  Thou shalt buy and hold , 2008 .

[23]  S. S. Lam.  A genetic fuzzy expert system for stock market timing , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[24]  Amit Mitra,et al.  Forecasting daily foreign exchange rates using genetically optimized neural networks , 2002 .

[25]  J. Poterba,et al.  What moves stock prices? , 1988 .

[26]  H. D. Ardakani,et al.  Application of data mining techniques in stock markets: A survey , 2010 .

[27]  V. P. Mohandas,et al.  Predicting the BSE Sensex: Performance comparison of adaptive linear element, feed forward and time delay neural networks , 2012, 2012 International Conference on Power, Signals, Controls and Computation.

[28]  Lavi Rizki Zuhal,et al.  Resolving multi objective stock portfolio optimization problem using genetic algorithm , 2010, 2010 The 2nd International Conference on Computer and Automation Engineering (ICCAE).

[29]  David G. McMillan,et al.  Non-linear forecasting of stock returns: Does volume help? , 2007 .

[30]  N. R. Sakthivel,et al.  A Decision Tree- Rough Set Hybrid System for Stock Market Trend Prediction , 2010 .

[31]  Goutam Dutta,et al.  Artificial Neural Network Models for Forecasting Stock Price Index in the Bombay Stock Exchange , 2006 .

[32]  Shu-Hui Lin,et al.  Applying Investment Satisfied Capability Index and Particle Swarm Optimization to Construct the Stocks Portfolio , 2008, 2008 3rd International Conference on Innovative Computing Information and Control.

[33]  Ping-Feng Pai,et al.  Predicting movement directions of stock index futures by support vector models with data preprocessing , 2007, 2007 IEEE International Conference on Industrial Engineering and Engineering Management.

[34]  Anthony Brabazon,et al.  An Introduction to Natural Computing in Finance , 2009, EvoWorkshops.

[35]  B. Mandelbrot.  A Multifractal Walk down Wall Street , 1999 .

[36]  Michael O'Neill,et al.  Biologically Inspired Algorithms for Financial Modelling (Natural Computing Series) , 2005 .

[37]  Jingtao Yao,et al.  A case study on using neural networks to perform technical forecasting of forex , 2000, Neurocomputing.

[38]  Jinwoo Park,et al.  Trading activity indicators and market timing , 1995 .

[39]  Muh-Cherng Wu,et al.  An effective application of decision tree to stock trading , 2006, Expert Syst. Appl..

[40]  Chen Ping,et al.  A Random Walk or Color Chaos on the Stock Market? Time-Frequency Analysis of S&P Indexes , 1996 .

[41]  E. Abbasi,et al.  Stock Price Forecast by Using Neuro-Fuzzy Inference System , 2008 .

[42]  F. E. James.  Monthly Moving Averages—An Effective Investment Tool? , 1968, Journal of Financial and Quantitative Analysis.

[43]  Shouyang Wang,et al.  Forecasting stock market movement direction with support vector machine , 2005, Comput. Oper. Res..

[44]  Binoy B. Nair,et al.  Stock Market Prediction Using a Hybrid Neuro-fuzzy System , 2010, 2010 International Conference on Advances in Recent Technologies in Communication and Computing.

[45]  Andrew Clare,et al.  A note on forecasting the CAC 40 and DAX stock index futures , 1995 .

[46]  S. Banik,et al.  Modeling chaotic behavior of Dhaka Stock Market Index values using the neuro-fuzzy model , 2007, 2007 10th international conference on computer and information technology.

[47]  Blake LeBaron,et al.  Chaos and nonlinear forecastability in economics and finance , 1994, Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences.

[48]  Yih-Luan Chyi,et al.  Nonlinear dynamics and daily stock returns on the Taiwan Stock Exchange , 1997 .

[49]  Robert A. Levy,et al.  RELATIVE STRENGTH AS A CRITERION FOR INVESTMENT SELECTION , 1967 .

[50]  E. Fama.  Random Walks in Stock Market Prices , 1965 .

[51]  Wei Yang.  Stock Price Prediction Based on Fuzzy Logic , 2007, 2007 International Conference on Machine Learning and Cybernetics.

[52]  Nguyen Quoc Viet Hung,et al.  Combining SAX and Piecewise Linear Approximation to Improve Similarity Search on Financial Time Series , 2007, 2007 International Symposium on Information Technology Convergence (ISITC 2007).

[53]  Walt McKibben,et al.  Econometric Forecasting of Common Stock Investment Returns: A New Methodology Using Fundamental Operating Data , 1972 .

[54]  Gary R. Weckman,et al.  An Integrated Stock Market Forecasting Model Using Neural Networks , 2008 .

[55]  Binoy B. Nair,et al.  A Genetic Algorithm Optimized Decision Tree- SVM based Stock Market Trend Prediction System , 2010 .

[56]  Kin Keung Lai,et al.  Mining Stock Market Tendency Using GA-Based Support Vector Machines , 2005, WINE.

[57]  Marcelo Portes Albuquerque,et al.  Predicting the Brazilian stock market through neural networks and adaptive exponential smoothing methods , 2009, Expert Syst. Appl..

[58]  Bo Luo,et al.  Empirical study of trading rule discovery in China stock market , 2005, Expert Syst. Appl..

[59]  Binoy B. Nair,et al.  A Stock Market Trend Prediction System Using a Hybrid Decision Tree-Neuro-Fuzzy System , 2010, 2010 International Conference on Advances in Recent Technologies in Communication and Computing.

[60]  An-Pin Chen,et al.  A Hybrid Forecasting Model for Foreign Exchange Rate Based on a Multi-neural Network , 2008, 2008 Fourth International Conference on Natural Computation.

[61]  Chi-Jie Lu,et al.  Combining nonlinear independent component analysis and neural network for the prediction of Asian stock market indexes , 2012, Expert Syst. Appl..

[62]  Kyung-shik Shin,et al.  A hybrid approach based on neural networks and genetic algorithms for detecting temporal patterns in stock markets , 2007, Appl. Soft Comput..

[63]  Chung-Ming Kuan,et al.  Forecasting exchange rates using feedforward and recurrent neural networks , 1992 .

[64]  Pei-Chann Chang,et al.  A neural network with a case based dynamic window for stock trading prediction , 2009, Expert Syst. Appl..

[65]  Byung Ro Moon,et al.  A Hybrid Neurogenetic Approach for Stock Forecasting , 2007, IEEE Transactions on Neural Networks.

[66]  N. R. Sakthivel,et al.  Predicting stock market trends using hybrid ant-colony-based data mining algorithms: an empirical validation on the Bombay Stock Exchange , 2011 .

[67]  Binoy B. Nair,et al.  A GA-artificial neural network hybrid system for financial time series forecasting , 2011 .

[68]  Pedram Sadeghian,et al.  The time diversification monitoring of a stock portfolio: an approach based on the fractal dimension , 2004, SAC '04.

[69]  Nohpill Park,et al.  Performance Analysis of Hybrid Forecasting Model In Stock Market Forecasting , 2012, ArXiv.

[70]  A. Cowles.  Can Stock Market Forecasters Forecast , 1933 .

[71]  A. Brabazon,et al.  An Introduction to Evolutionary Computation in Finance , 2008, IEEE Computational Intelligence Magazine.

[72]  Chih-Chou Chiu,et al.  Forecasting stock price using Nonlinear independent component analysis and support vector regression , 2009, 2009 IEEE International Conference on Industrial Engineering and Engineering Management.

[73]  Chokri Slim,et al.  Neuro-Fuzzy Network Based On Extended Kalman Filtering for Financial Time Series , 2008 .

[74]  Ganapati Panda,et al.  On the development of improved adaptive models for efficient prediction of stock indices using clonal-PSO (CPSO) and PSO techniques , 2008 .

[75]  K.V. Nesbitt,et al.  Finding trading patterns in stock market data , 2004, IEEE Computer Graphics and Applications.

[76]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[77]  Michel Verleysen,et al.  Forecasting Financial Time Series through Intrinsic Dimension Estimation and Non-Linear Data Projection , 1999, IWANN.

[78]  E. Prescott,et al.  Postwar U.S. Business Cycles: An Empirical Investigation , 1997 .

[79]  Jar-Long Wang,et al.  Stock market trading rule discovery using two-layer bias decision tree , 2006, Expert Syst. Appl..

[80]  Michael A. H. Dempster,et al.  Computational learning techniques for intraday FX trading using popular technical indicators , 2001, IEEE Trans. Neural Networks.

[81]  Andrew W. Lo,et al.  Computational finance , 1999, Comput. Sci. Eng..

[82]  H. S. Ng,et al.  Incremental genetic fuzzy expert trading system for derivatives market timing , 2003, 2003 IEEE International Conference on Computational Intelligence for Financial Engineering, 2003. Proceedings..

[83]  Mohammad Hossein Fazel Zarandi,et al.  A new fuzzy functions model tuned by hybridizing imperialist competitive algorithm and simulated annealing. Application: Stock price prediction , 2013, Inf. Sci..

[84]  Mu-Hsing Kuo,et al.  An ETF Trading Decision Support System by Using Neural Network and Technical Indicators , 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

[85]  P. Samuelson.  Proof that Properly Anticipated Prices Fluctuate Randomly , 2015 .

[86]  B. LeBaron,et al.  Simple Technical Trading Rules and the Stochastic Properties of Stock Returns , 1992 .

[87]  Michel Verleysen,et al.  Input data reduction for the prediction of financial time series , 2001, ESANN.

[88]  T.B. Trafalis,et al.  Kernel principal component analysis and support vector machines for stock price prediction , 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

[89]  Byung Ro Moon,et al.  Stock prediction based on financial correlation , 2005, GECCO '05.

[90]  Kimon P. Valavanis,et al.  Surveying stock market forecasting techniques - Part II: Soft computing methods , 2009, Expert Syst. Appl..

[91]  E. Fama.  EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* , 1970 .

[92]  J. Clendenin,et al.  GROWTH AND COMMON STOCK VALUES , 1954 .

[93]  F.A. Badawy,et al.  Genetic Algorithms for Predicting the Egyptian Stock Market , 2005, 2005 International Conference on Information and Communication Technology.

[94]  Pritam Radheshyam Charkha.  Stock Price Prediction and Trend Prediction Using Neural Networks , 2008, 2008 First International Conference on Emerging Trends in Engineering and Technology.

[95]  E. Fama.  The Behavior of Stock-Market Prices , 1965 .

[96]  Marc-André Mittermayer,et al.  Forecasting Intraday stock price trends with text mining techniques , 2004, 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the.

[97]  A. Cowles,et al.  Stock Market Forecasting , 1944 .

[98]  Chung-Chian Hsu,et al.  Pattern recognition in time series database: A case study on financial database , 2007, Expert Syst. Appl..

[99]  Kimon P. Valavanis,et al.  Forecasting stock market short-term trends using a neuro-fuzzy based methodology , 2009, Expert Syst. Appl..

[100]  Ramazan Gençay,et al.  Optimization of technical trading strategies and the profitability in security markets , 1998 .

[101]  Xi Chen,et al.  Integrating piecewise linear representation and weighted support vector machine for stock trading signal prediction , 2013, Appl. Soft Comput..

[102]  Arthur Kraft,et al.  Determinants of Common Stock Prices: A Time Series Analysis , 1977 .