Stock market predictions are one of the challenging tasks for financial investors across the globe. This challenge is due to the uncertainty and volatility of the stock prices in the market. Due to technology and globalization of business and financial markets it is important to predict the stock prices more quickly and accurately. Last few years there has been much improvement in the field of Neural Network (NN) applications in business and financial markets. Artificial Neural Network (ANN) methods are mostly implemented and play a vital role in decision making for stock market predictions. We evaluate Vodafone Idea Limited prediction models with Modular Neural Network (Speculative Sentiment Analysis) and Paired T-Test1,2,3,4 and conclude that the NSE IDEA 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 IDEA stock.
Keywords: NSE IDEA, Vodafone Idea Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Operational Risk
- Which neural network is best for prediction?
- How do you decide buy or sell a stock?
NSE IDEA Target Price Prediction Modeling Methodology
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 consider Vodafone Idea Limited Stock Decision Process with Paired T-Test where A is the set of discrete actions of NSE IDEA 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(Paired T-Test)5,6,7= X R(Modular Neural Network (Speculative Sentiment Analysis)) X S(n):→ (n+16 weeks)
n:Time series to forecast
p:Price signals of NSE IDEA stock
j:Nash equilibria
k:Dominated move
a:Best response for target price
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NSE IDEA Stock Forecast (Buy or Sell) for (n+16 weeks)
Sample Set: Neural NetworkStock/Index: NSE IDEA Vodafone Idea Limited
Time series to forecast n: 26 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 IDEA 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
Vodafone Idea Limited assigned short-term B2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) with Paired T-Test1,2,3,4 and conclude that the NSE IDEA 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 IDEA stock.
Financial State Forecast for NSE IDEA Stock Options & Futures
| Rating | Short-Term | Long-Term Senior |
|---|---|---|
| Outlook* | B2 | Ba3 |
| Operational Risk | 43 | 71 |
| Market Risk | 77 | 32 |
| Technical Analysis | 62 | 75 |
| Fundamental Analysis | 38 | 81 |
| Risk Unsystematic | 68 | 71 |
Prediction Confidence Score
References
- V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
- M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.
- Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
- S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
- Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
- Bastani H, Bayati M. 2015. Online decision-making with high-dimensional covariates. Work. Pap., Univ. Penn./ Stanford Grad. School Bus., Philadelphia/Stanford, CA
- Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
Frequently Asked Questions
Q: What is the prediction methodology for NSE IDEA stock?A: NSE IDEA stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Paired T-Test
Q: Is NSE IDEA stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE IDEA Stock.
Q: Is Vodafone Idea Limited stock a good investment?
A: The consensus rating for Vodafone Idea Limited is Hold and assigned short-term B2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE IDEA stock?
A: The consensus rating for NSE IDEA is Hold.
Q: What is the prediction period for NSE IDEA stock?
A: The prediction period for NSE IDEA is (n+16 weeks)
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