Prediction of stock market is a long-time attractive topic to researchers from different fields. In particular, numerous studies have been conducted to predict the movement of stock market using machine learning algorithms such as support vector machine (SVM) and reinforcement learning. In this project, we propose a new prediction algorithm that exploits the temporal correlation among global stock markets and various financial products to predict the next-day stock trend. We evaluate NMDC Limited prediction models with Modular Neural Network (Financial Sentiment Analysis) and Multiple Regression1,2,3,4 and conclude that the NSE NMDC 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 NMDC stock.
Keywords: NSE NMDC, NMDC Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Which neural network is best for prediction?
- What is prediction model?
- What is the best way to predict stock prices?
NSE NMDC Target Price Prediction Modeling Methodology
How to predict stock price movements based on quantitative market data modeling is an attractive topic. In front of the market news and stock prices that are commonly believed as two important market data sources, how to extract and exploit the hidden information within the raw data and make both accurate and fast predictions simultaneously becomes a challenging problem. In this paper, we present the design and architecture of our trading signal mining platform that employs extreme learning machine (ELM) to make stock price prediction based on those two data sources concurrently. We consider NMDC Limited Stock Decision Process with Multiple Regression where A is the set of discrete actions of NSE NMDC 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(Multiple Regression)5,6,7= X R(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+3 month)
n:Time series to forecast
p:Price signals of NSE NMDC 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 NMDC Stock Forecast (Buy or Sell) for (n+3 month)
Sample Set: Neural NetworkStock/Index: NSE NMDC NMDC Limited
Time series to forecast n: 02 Oct 2022 for (n+3 month)
According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell NSE NMDC 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
NMDC Limited assigned short-term B2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Multiple Regression1,2,3,4 and conclude that the NSE NMDC 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 NMDC stock.
Financial State Forecast for NSE NMDC Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B2 | Ba3 |
| Operational Risk | 81 | 49 |
| Market Risk | 42 | 58 |
| Technical Analysis | 55 | 48 |
| Fundamental Analysis | 45 | 90 |
| Risk Unsystematic | 64 | 86 |
Prediction Confidence Score
References
- Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
- 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
- S. J. Russell and A. Zimdars. Q-decomposition for reinforcement learning agents. In Machine Learning, Proceedings of the Twentieth International Conference (ICML 2003), August 21-24, 2003, Washington, DC, USA, pages 656–663, 2003.
- Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
- L. Prashanth and M. Ghavamzadeh. Actor-critic algorithms for risk-sensitive MDPs. In Proceedings of Advances in Neural Information Processing Systems 26, pages 252–260, 2013.
- Jiang N, Li L. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In Proceedings of the 33rd International Conference on Machine Learning, pp. 652–61. La Jolla, CA: Int. Mach. Learn. Soc.
- Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
Frequently Asked Questions
Q: What is the prediction methodology for NSE NMDC stock?A: NSE NMDC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Multiple Regression
Q: Is NSE NMDC stock a buy or sell?
A: The dominant strategy among neural network is to Sell NSE NMDC Stock.
Q: Is NMDC Limited stock a good investment?
A: The consensus rating for NMDC Limited is Sell and assigned short-term B2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE NMDC stock?
A: The consensus rating for NSE NMDC is Sell.
Q: What is the prediction period for NSE NMDC stock?
A: The prediction period for NSE NMDC is (n+3 month)
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