Armstrong

“Prediction is very difficult, especially if it’s about the future.” – Nils Bohr

Experiments:

• Experiment 1. Prediction of
• Experiment 2.
• Experiment 3.
  • Create a Trading Signal that determines when to buy, hold and sell a stock. Train a ann to predict the Trading Signal.

References

1. Trend Following Algorithms for Technical Trading in Stock Market

2. Forecasting for the Generation of Trading Signals in Financial Markets KIN LAM1 AND KING CHUNG LAM, 2000.

3. A neural network with a case based dynamic window for stock trading prediction P. C. Chang et al., 2009.

4. Short-Term Forecasting of Financial Time Series with Deep Neural Networks

5. Using Artificial Neural Networks and Sentiment Analysis to Predict Upward Movements in Stock Price

6. A hybrid stock trading framework integrating technical analysis with machine learning techniques Dash R. and Dash P.K., 2016.

7. A dynamic threshold decision system for stock trading signal detection P.C. Chang, T.W. Liao, J.J. Lin, C.Y. Fan, 2011.

8. Predicting Stock Market Index Trading Signals Using Neural Networks C. D. Tilakaratne, S. A. Morris, M. A. Mammadov, C. P. Hurst, 2007.

9. Trading Signal Prediction Cha S-M. & Chan L., 2000.

10. Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model Qiu M. & Song Y., 2016.

11. Predictable Patterns in Stock Returns Hellström T. & Holmström K., 1998.

12. A Random Walk through the Stock Market Hellström T., 1998.

13. DESIGN AND IMPLEMENTATION OF AUTOMATED TRADING SYSTEMS M. Kecera, 2010.

14. Forecasting the Stock Market - A Neural Network Approach Nadersson M. & Palm J., 2009.

15. Classification-based Financial Markets Prediction using Deep Neural Networks Dixon M., Klabjan D. and Bang J. H., 2016. Talk https://www.youtube.com/watch?v=Kzz2-wAEK7A

16. Stock Market Index Data and indicators for Day Trading as a Binary Classification problem Bruni R., 2017. A lot of technical indicators and a useful S&P500 dataset.

17. STOCK MARKET DIRECTION PREDICTION USING DATA MINING CLASSIFICATION

18. Machine-learning classification techniques for the analysis and prediction of high-frequency stock direction

19. [Forecasting the direction of stock market index movement using three data mining techniques: the case of Tehran Stock Exchange] (https://pdfs.semanticscholar.org/2fe9/cd2e7e9a4c859d2ffbf39e1a2c54cb874f3c.pdf)

20. Predicting Stocks with Machine Learning

21. Artificial neural networks for financial time series prediction and portfolio optimization

22. Predictions in Financial Time Series Data

23. Improving Long Term Stock Market Prediction with Text Analysis

24. Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

25. On stock return prediction with LSTM networks

26. Artificial Intelligence in Finance: Forecasting stock market returs using neural networks

27. Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques, 2015

28. A hybrid stock trading framework integrating technical analysis with machine learning techniques

29. Equity Price Direction Prediction For Day Trading

30. Forecasting the Equity Risk Premium: The Role of Technical Indicators Neely, Christopher J.; Rapach, David E.; TU, Jun; and Zhou, Guofu. (2014). Management Science. 60, (7), 1772-1791. Research Collection Lee Kong Chian School Of Business.

31. A Study on Technical Indicators in Stock Price Movement Prediction Using Decision Tree Algorithms

32. Machine Learning for Technical Stock Analysis

33. Equity Price Direction Prediction For Day Trading Van den Poel, D., Chesterman, C., Koppen M., Ballings, M.

34. Using Artificial Neural Networks and Sentiment Analysis to Predict Upward Movements in Stock Price

35. Python For Finance: Algorithmic Trading Web page

36. Stock Prediction – A Neural Network Approach Karl Nygren 20041.

37. Stock Market Prediction Performance of Neural Networks: A Literature Review Özgür İcan & Taha Buğra Çelik 2017

#€ Other links

1, MEASURING HISTORICAL VOLATILITY