This paper aims to develop an innovative neural network approach to achieve better stock market predictions. Data were obtained from the live stock market for real-time and off-line analysis and results of visualizations and analytics to demonstrate Internet of Multimedia of Things for stock analysis. To study the influence of market characteristics on stock prices, traditional neural network algorithms may incorrectly predict the stock market, since the initial weight of the random selection problem can be easily prone to incorrect predictions. We evaluate Glenmark Pharmaceuticals Limited prediction models with Deductive Inference (ML) and Pearson Correlation1,2,3,4 and conclude that the NSE GLENMARK 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 Sell NSE GLENMARK stock.
Keywords: NSE GLENMARK, Glenmark Pharmaceuticals Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Short/Long Term Stocks
- What is Markov decision process in reinforcement learning?
- Is now good time to invest?
NSE GLENMARK Target Price Prediction Modeling Methodology
Security indices are the main tools for evaluation of the status of financial markets. Moreover, a main part of the economy of any country is constituted of investment in stock markets. Therefore, investors could maximize the return of investment if it becomes possible to predict the future trend of stock market with appropriate methods. The nonlinearity and nonstationarity of financial series make their prediction complicated. This study seeks to evaluate the prediction power of machine-learning models in a stock market. We consider Glenmark Pharmaceuticals Limited Stock Decision Process with Pearson Correlation where A is the set of discrete actions of NSE GLENMARK 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= X R(Deductive Inference (ML)) X S(n):→ (n+3 month)
n:Time series to forecast
p:Price signals of NSE GLENMARK 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 GLENMARK Stock Forecast (Buy or Sell) for (n+3 month)
Sample Set: Neural NetworkStock/Index: NSE GLENMARK Glenmark Pharmaceuticals Limited
Time series to forecast n: 26 Sep 2022 for (n+3 month)
According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell NSE GLENMARK 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
Glenmark Pharmaceuticals Limited assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Pearson Correlation1,2,3,4 and conclude that the NSE GLENMARK 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 Sell NSE GLENMARK stock.
Financial State Forecast for NSE GLENMARK Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B1 | Ba3 |
| Operational Risk | 44 | 46 |
| Market Risk | 49 | 36 |
| Technical Analysis | 88 | 69 |
| Fundamental Analysis | 63 | 75 |
| Risk Unsystematic | 46 | 86 |
Prediction Confidence Score
References
- Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
- R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
- L. Busoniu, R. Babuska, and B. D. Schutter. A comprehensive survey of multiagent reinforcement learning. IEEE Transactions of Systems, Man, and Cybernetics Part C: Applications and Reviews, 38(2), 2008.
- Hornik K, Stinchcombe M, White H. 1989. Multilayer feedforward networks are universal approximators. Neural Netw. 2:359–66
- A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
- Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
- Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
Frequently Asked Questions
Q: What is the prediction methodology for NSE GLENMARK stock?A: NSE GLENMARK stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Pearson Correlation
Q: Is NSE GLENMARK stock a buy or sell?
A: The dominant strategy among neural network is to Sell NSE GLENMARK Stock.
Q: Is Glenmark Pharmaceuticals Limited stock a good investment?
A: The consensus rating for Glenmark Pharmaceuticals Limited is Sell and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE GLENMARK stock?
A: The consensus rating for NSE GLENMARK is Sell.
Q: What is the prediction period for NSE GLENMARK stock?
A: The prediction period for NSE GLENMARK is (n+3 month)
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