With the up-gradation of technology and exploration of new machine learning models, the stock market data analysis has gained attention as these models provide a platform for businessman and traders to choose more profitable stocks. As these data are in large volumes and highly complex so a need of more efficient machine learning model for daily predictions is always looked upon. We evaluate Owens Corning prediction models with Modular Neural Network (DNN Layer) and Pearson Correlation1,2,3,4 and conclude that the OC 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 Hold OC stock.

Keywords: OC, Owens Corning, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

## Key Points

1. Stock Forecast Based On a Predictive Algorithm
2. Market Signals
3. How do you know when a stock will go up or down?

## OC Target Price Prediction Modeling Methodology

The nature of stock market movement has always been ambiguous for investors because of various influential factors. This study aims to significantly reduce the risk of trend prediction with machine learning and deep learning algorithms. We consider Owens Corning Stock Decision Process with Pearson Correlation where A is the set of discrete actions of OC 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(Pearson Correlation)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 (DNN Layer)) X S(n):→ (n+6 month) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of OC 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?

## OC Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: OC Owens Corning
Time series to forecast n: 05 Oct 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold OC 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

Owens Corning assigned short-term B2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (DNN Layer) with Pearson Correlation1,2,3,4 and conclude that the OC 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 Hold OC stock.

### Financial State Forecast for OC Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2Ba3
Operational Risk 3884
Market Risk4552
Technical Analysis7644
Fundamental Analysis8354
Risk Unsystematic4481

### Prediction Confidence Score

Trust metric by Neural Network: 81 out of 100 with 646 signals.

## References

1. Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
2. G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
3. Bai J, Ng S. 2017. Principal components and regularized estimation of factor models. arXiv:1708.08137 [stat.ME]
4. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
5. Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.
6. Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
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 OC stock?
A: OC stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Pearson Correlation
Q: Is OC stock a buy or sell?
A: The dominant strategy among neural network is to Hold OC Stock.
Q: Is Owens Corning stock a good investment?
A: The consensus rating for Owens Corning is Hold and assigned short-term B2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of OC stock?
A: The consensus rating for OC is Hold.
Q: What is the prediction period for OC stock?
A: The prediction period for OC is (n+6 month)