Social media comments have in the past had an instantaneous effect on stock markets. This paper investigates the sentiments expressed on the social media platform Twitter and their pr edictive impact on the Stock Market. ** We evaluate JK Tyre & Industries Limited prediction models with Multi-Task Learning (ML) and Chi-Square ^{1,2,3,4} and conclude that the NSE JKTYRE stock is predictable in the short/long term. **

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold NSE JKTYRE stock.**

**NSE JKTYRE, JK Tyre & Industries Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Which neural network is best for prediction?
- Market Signals
- Operational Risk

## NSE JKTYRE Target Price Prediction Modeling Methodology

Predicting stock index with traditional time series analysis has proven to be difficult an Artificial Neural network may be suitable for the task. A Neural Network has the ability to extract useful information from large set of data. This paper presents a review of literature application of Artificial Neural Network for stock market predictions and from this literature found that Artificial Neural Network is very useful for predicting world stock markets. We consider JK Tyre & Industries Limited Stock Decision Process with Chi-Square where A is the set of discrete actions of NSE JKTYRE 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(Chi-Square)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Multi-Task Learning (ML)) X S(n):→ (n+3 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 NSE JKTYRE 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?

## NSE JKTYRE Stock Forecast (Buy or Sell) for (n+3 month)

**Sample Set:**Neural Network

**Stock/Index:**NSE JKTYRE JK Tyre & Industries Limited

**Time series to forecast n: 29 Sep 2022**for (n+3 month)

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold NSE JKTYRE 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

JK Tyre & Industries Limited assigned short-term B2 & long-term B3 forecasted stock rating.** We evaluate the prediction models Multi-Task Learning (ML) with Chi-Square ^{1,2,3,4} and conclude that the NSE JKTYRE stock is predictable in the short/long term.**

**According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Hold NSE JKTYRE stock.**

### Financial State Forecast for NSE JKTYRE Stock Options & Futures

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | B2 | B3 |

Operational Risk | 40 | 80 |

Market Risk | 44 | 43 |

Technical Analysis | 36 | 34 |

Fundamental Analysis | 76 | 36 |

Risk Unsystematic | 76 | 35 |

### Prediction Confidence Score

## References

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- V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
- C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
- Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]
- Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
- C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999
- J. G. Schneider, W. Wong, A. W. Moore, and M. A. Riedmiller. Distributed value functions. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 371–378, 1999.

## Frequently Asked Questions

Q: What is the prediction methodology for NSE JKTYRE stock?A: NSE JKTYRE stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Chi-Square

Q: Is NSE JKTYRE stock a buy or sell?

A: The dominant strategy among neural network is to Hold NSE JKTYRE Stock.

Q: Is JK Tyre & Industries Limited stock a good investment?

A: The consensus rating for JK Tyre & Industries Limited is Hold and assigned short-term B2 & long-term B3 forecasted stock rating.

Q: What is the consensus rating of NSE JKTYRE stock?

A: The consensus rating for NSE JKTYRE is Hold.

Q: What is the prediction period for NSE JKTYRE stock?

A: The prediction period for NSE JKTYRE is (n+3 month)