TAILIEUCHUNG - Neural Network Predictions of Stock Price Fluctuations

The traditional view that expected nominal rates of return on assets should move one-for- one with expected inflation is first attributed to Irving Fisher (1930). Financial economists have also argued that, because stocks are claims on physical, or “real”, assets, stock returns ought to co-vary positively with actual inflation, thereby making them a possible hedge against unexpected inflation. During the mid to late 1970s, however, investors found that little could be further from the truth; at least in the short and intermediate run, stocks prices were apparently quite negatively affected by inflation, expected or not. The earliest studies mainly document the negative covariation between actual. | Neural Network Predictions of Stock Price Fluctuations By Wojciech Gryc wojciech@ Table of Contents Part 1 The Stock Market Stock Market Technical Variable Moving Average VMA .9 Trading Range Breakout TRB .9 Bollinger Money Flow Index MFI .10 Temporal Fundamental Analysis of Consumer Price Index CPI .13 Consumer Sentiment Consumer Confidence New Orders Diffusion Leading Indicators Interest Rate of the 30-Year Conventional Federal Funds Price-Earnings P E Target Part 2 Neural Networks Neurons and Neural Input Summing and Activation Output Feedforward Backpropagati Backpropagation Threshold Recurrent Elman Part 3 Results Statistical Feedforward Networks and Types of Other Network Architectures for 1-Day Neural Network Predictions of Stock Price Fluctuations 1 42 Longer Term Predictions and Fundamental Conclusion and Future Appendix A Overview of Appendix B Overview of Custom Appendix C Effects of Random Weights on Network Works Neural Network Predictions of Stock Price Fluctuations 2 .

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