Prediction of future movement of stock prices has been a subject matter of many research work. In this work, we propose a hybrid approach for stock price prediction using machine learning and deep learning-based methods. We evaluate Dow Jones Industrial Average Index prediction models with Modular Neural Network (Social Media Sentiment Analysis) and Lasso Regression1,2,3,4 and conclude that the Dow Jones Industrial Average Index stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold Dow Jones Industrial Average Index stock.
Keywords: Dow Jones Industrial Average Index, Dow Jones Industrial Average Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- What are buy sell or hold recommendations?
- Can neural networks predict stock market?
- Reaction Function
Dow Jones Industrial Average Index Target Price Prediction Modeling Methodology
Stock market also called as equity market is the aggregation of the sellers and buyers. It is concerned with the domain where the shares of various public listed companies are traded. For predicting the growth of economy, stock market acts as an index. Due to the nonlinear nature, the prediction of the stock market becomes a difficult task. But the application of various machine learning techniques has been becoming a powerful source for the prediction. We consider Dow Jones Industrial Average Index Stock Decision Process with Lasso Regression where A is the set of discrete actions of Dow Jones Industrial Average Index stock holders, F is the set of discrete states, P : S × F × S → R is the transition probability distribution, R : S × F → R is the reaction function, and γ ∈ [0, 1] is a move factor for expectation.1,2,3,4
F(Lasso Regression)5,6,7= X R(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ (n+8 weeks)
n:Time series to forecast
p:Price signals of Dow Jones Industrial Average Index stock
j:Nash equilibria
k:Dominated move
a:Best response for target price
For further technical information as per how our model work we invite you to visit the article below:
How do AC Investment Research machine learning (predictive) algorithms actually work?
Dow Jones Industrial Average Index Stock Forecast (Buy or Sell) for (n+8 weeks)
Sample Set: Neural NetworkStock/Index: Dow Jones Industrial Average Index Dow Jones Industrial Average Index
Time series to forecast n: 24 Oct 2022 for (n+8 weeks)
According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold Dow Jones Industrial Average Index stock.
X axis: *Likelihood% (The higher the percentage value, the more likely the event will occur.)
Y axis: *Potential Impact% (The higher the percentage value, the more likely the price will deviate.)
Z axis (Yellow to Green): *Technical Analysis%
Conclusions
Dow Jones Industrial Average Index assigned short-term B1 & long-term Ba1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) with Lasso Regression1,2,3,4 and conclude that the Dow Jones Industrial Average Index stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold Dow Jones Industrial Average Index stock.
Financial State Forecast for Dow Jones Industrial Average Index Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B1 | Ba1 |
| Operational Risk | 68 | 86 |
| Market Risk | 80 | 85 |
| Technical Analysis | 41 | 35 |
| Fundamental Analysis | 82 | 90 |
| Risk Unsystematic | 35 | 56 |
Prediction Confidence Score
References
- Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
- Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
- L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
- J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
- Breusch, T. S. (1978), "Testing for autocorrelation in dynamic linear models," Australian Economic Papers, 17, 334–355.
- Bessler, D. A. S. W. Fuller (1993), "Cointegration between U.S. wheat markets," Journal of Regional Science, 33, 481–501.
- Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
Frequently Asked Questions
Q: What is the prediction methodology for Dow Jones Industrial Average Index stock?A: Dow Jones Industrial Average Index stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Lasso Regression
Q: Is Dow Jones Industrial Average Index stock a buy or sell?
A: The dominant strategy among neural network is to Hold Dow Jones Industrial Average Index Stock.
Q: Is Dow Jones Industrial Average Index stock a good investment?
A: The consensus rating for Dow Jones Industrial Average Index is Hold and assigned short-term B1 & long-term Ba1 forecasted stock rating.
Q: What is the consensus rating of Dow Jones Industrial Average Index stock?
A: The consensus rating for Dow Jones Industrial Average Index is Hold.
Q: What is the prediction period for Dow Jones Industrial Average Index stock?
A: The prediction period for Dow Jones Industrial Average Index is (n+8 weeks)
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