Stock market is a promising financial investment that can generate great wealth. However, the volatile nature of the stock market makes it a very high risk investment. Thus, a lot of researchers have contributed their efforts to forecast the stock market pricing and average movement. Researchers have used various methods in computer science and economics in their quests to gain a piece of this volatile information and make great fortune out of the stock market investment. This paper investigates various techniques for the stock market prediction using artificial neural network (ANN). We evaluate Natco Pharma Limited prediction models with Modular Neural Network (Social Media Sentiment Analysis) and Logistic Regression1,2,3,4 and conclude that the NSE NATCOPHARM 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 Buy NSE NATCOPHARM stock.
Keywords: NSE NATCOPHARM, Natco Pharma Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Can statistics predict the future?
- Short/Long Term Stocks
- What is the use of Markov decision process?
NSE NATCOPHARM 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 Natco Pharma Limited Stock Decision Process with Logistic Regression where A is the set of discrete actions of NSE NATCOPHARM 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(Logistic Regression)5,6,7= X R(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ (n+3 month)
n:Time series to forecast
p:Price signals of NSE NATCOPHARM 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 NATCOPHARM Stock Forecast (Buy or Sell) for (n+3 month)
Sample Set: Neural NetworkStock/Index: NSE NATCOPHARM Natco Pharma Limited
Time series to forecast n: 27 Sep 2022 for (n+3 month)
According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy NSE NATCOPHARM 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
Natco Pharma Limited assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) with Logistic Regression1,2,3,4 and conclude that the NSE NATCOPHARM 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 Buy NSE NATCOPHARM stock.
Financial State Forecast for NSE NATCOPHARM Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B1 | Ba3 |
| Operational Risk | 81 | 76 |
| Market Risk | 90 | 36 |
| Technical Analysis | 36 | 50 |
| Fundamental Analysis | 64 | 83 |
| Risk Unsystematic | 41 | 70 |
Prediction Confidence Score
References
- P. Marbach. Simulated-Based Methods for Markov Decision Processes. PhD thesis, Massachusetts Institute of Technology, 1998
- 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
- T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000
- Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
- Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
- Pennington J, Socher R, Manning CD. 2014. GloVe: global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods on Natural Language Processing, pp. 1532–43. New York: Assoc. Comput. Linguist.
- J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
Frequently Asked Questions
Q: What is the prediction methodology for NSE NATCOPHARM stock?A: NSE NATCOPHARM stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Logistic Regression
Q: Is NSE NATCOPHARM stock a buy or sell?
A: The dominant strategy among neural network is to Buy NSE NATCOPHARM Stock.
Q: Is Natco Pharma Limited stock a good investment?
A: The consensus rating for Natco Pharma Limited is Buy and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE NATCOPHARM stock?
A: The consensus rating for NSE NATCOPHARM is Buy.
Q: What is the prediction period for NSE NATCOPHARM stock?
A: The prediction period for NSE NATCOPHARM is (n+3 month)
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