Neural networks (NNs), as artificial intelligence (AI) methods, have become very important in making stock market predictions. Much research on the applications of NNs for solving business problems have proven their advantages over statistical and other methods that do not include AI, although there is no optimal methodology for a certain problem. ** We evaluate Sun Pharma Advanced Research Company Limited prediction models with Modular Neural Network (Market Direction Analysis) and Factor ^{1,2,3,4} and conclude that the NSE SPARC stock is predictable in the short/long term. **

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold NSE SPARC stock.**

**NSE SPARC, Sun Pharma Advanced Research Company Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- Can machine learning predict?
- Trust metric by Neural Network
- Technical Analysis with Algorithmic Trading

## NSE SPARC Target Price Prediction Modeling Methodology

Neural networks, as an intelligent data mining method, have been used in many different challenging pattern recognition problems such as stock market prediction. However, there is no formal method to determine the optimal neural network for prediction purpose in the literature. In this paper, two kinds of neural networks, a feed forward multi layer Perceptron (MLP) and an Elman recurrent network, are used to predict a company's stock value based on its stock share value history. We consider Sun Pharma Advanced Research Company Limited Stock Decision Process with Factor where A is the set of discrete actions of NSE SPARC 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(Factor)

^{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(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+16 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of NSE SPARC 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 SPARC Stock Forecast (Buy or Sell) for (n+16 weeks)

**Sample Set:**Neural Network

**Stock/Index:**NSE SPARC Sun Pharma Advanced Research Company Limited

**Time series to forecast n: 29 Sep 2022**for (n+16 weeks)

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold NSE SPARC 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

Sun Pharma Advanced Research Company Limited assigned short-term Caa2 & long-term Ba2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Factor ^{1,2,3,4} and conclude that the NSE SPARC stock is predictable in the short/long term.**

**According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Hold NSE SPARC stock.**

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

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

Outlook* | Caa2 | Ba2 |

Operational Risk | 54 | 86 |

Market Risk | 54 | 87 |

Technical Analysis | 54 | 40 |

Fundamental Analysis | 35 | 68 |

Risk Unsystematic | 32 | 60 |

### Prediction Confidence Score

## References

- J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
- M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
- Mnih A, Teh YW. 2012. A fast and simple algorithm for training neural probabilistic language models. In Proceedings of the 29th International Conference on Machine Learning, pp. 419–26. La Jolla, CA: Int. Mach. Learn. Soc.
- Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
- N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011
- E. Collins. Using Markov decision processes to optimize a nonlinear functional of the final distribution, with manufacturing applications. In Stochastic Modelling in Innovative Manufacturing, pages 30–45. Springer, 1997
- S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014

## Frequently Asked Questions

Q: What is the prediction methodology for NSE SPARC stock?A: NSE SPARC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Factor

Q: Is NSE SPARC stock a buy or sell?

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

Q: Is Sun Pharma Advanced Research Company Limited stock a good investment?

A: The consensus rating for Sun Pharma Advanced Research Company Limited is Hold and assigned short-term Caa2 & long-term Ba2 forecasted stock rating.

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

A: The consensus rating for NSE SPARC is Hold.

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

A: The prediction period for NSE SPARC is (n+16 weeks)

- Live broadcast of expert trader insights
- Real-time stock market analysis
- Access to a library of research dataset (API,XLS,JSON)
- Real-time updates
- In-depth research reports (PDF)