Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. This paper will showcase how to perform stock prediction using Machine Learning algorithms. We evaluate Dow Jones Industrial Average Index prediction models with Modular Neural Network (Financial Sentiment Analysis) and Beta1,2,3,4 and conclude that the Dow Jones Industrial Average Index stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy 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

1. How do you decide buy or sell a stock?
2. Dominated Move
3. Stock Rating

## Dow Jones Industrial Average Index Target Price Prediction Modeling Methodology

Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on an exchange. The successful prediction of a stock's future price could yield significant profit. This paper will showcase how to perform stock prediction using Machine Learning algorithms. We consider Dow Jones Industrial Average Index Stock Decision Process with Beta 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(Beta)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+6 month) $\stackrel{\to }{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

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+6 month)

Sample Set: Neural Network
Stock/Index: Dow Jones Industrial Average Index Dow Jones Industrial Average Index
Time series to forecast n: 19 Sep 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy 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 Caa2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Beta1,2,3,4 and conclude that the Dow Jones Industrial Average Index stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy 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*Caa2Ba3
Operational Risk 5939
Market Risk3338
Technical Analysis3885
Fundamental Analysis3369
Risk Unsystematic6486

### Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 773 signals.

## References

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2. Armstrong, J. S. M. C. Grohman (1972), "A comparative study of methods for long-range market forecasting," Management Science, 19, 211–221.
3. J. Ott. A Markov decision model for a surveillance application and risk-sensitive Markov decision processes. PhD thesis, Karlsruhe Institute of Technology, 2010.
4. A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.
5. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
6. Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]
7. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
Frequently Asked QuestionsQ: 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 (Financial Sentiment Analysis) and Beta
Q: Is Dow Jones Industrial Average Index stock a buy or sell?
A: The dominant strategy among neural network is to Buy 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 Buy and assigned short-term Caa2 & long-term Ba3 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 Buy.
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+6 month)