Can neural networks predict stock market? (NSE SUPRAJIT Stock Forecast)

Suprajit Engineering Limited Research Report

Summary

With technological advancements, big data can be easily generated and collected in many applications. Embedded in these big data are useful information and knowledge that can be discovered by machine learning and data mining models, techniques or algorithms. We evaluate Suprajit Engineering Limited prediction models with Transfer Learning (ML) and Linear Regression1,2,3,4 and conclude that the NSE SUPRAJIT stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NSE SUPRAJIT stock.

Key Points

  1. Can stock prices be predicted?
  2. Which neural network is best for prediction?
  3. Which neural network is best for prediction?

NSE SUPRAJIT Target Price Prediction Modeling Methodology

We consider Suprajit Engineering Limited Stock Decision Process with Transfer Learning (ML) where A is the set of discrete actions of NSE SUPRAJIT 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(Linear Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Transfer Learning (ML)) X S(n):→ (n+6 month) r s rs

n:Time series to forecast

p:Price signals of NSE SUPRAJIT stock

j:Nash equilibria (Neural Network)

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 SUPRAJIT Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: NSE SUPRAJIT Suprajit Engineering Limited
Time series to forecast n: 20 Nov 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NSE SUPRAJIT 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%

Adjusted IFRS* Prediction Methods for Suprajit Engineering Limited

  1. Rebalancing refers to the adjustments made to the designated quantities of the hedged item or the hedging instrument of an already existing hedging relationship for the purpose of maintaining a hedge ratio that complies with the hedge effectiveness requirements. Changes to designated quantities of a hedged item or of a hedging instrument for a different purpose do not constitute rebalancing for the purpose of this Standard
  2. Fluctuation around a constant hedge ratio (and hence the related hedge ineffectiveness) cannot be reduced by adjusting the hedge ratio in response to each particular outcome. Hence, in such circumstances, the change in the extent of offset is a matter of measuring and recognising hedge ineffectiveness but does not require rebalancing.
  3. Conversely, if the critical terms of the hedging instrument and the hedged item are not closely aligned, there is an increased level of uncertainty about the extent of offset. Consequently, the hedge effectiveness during the term of the hedging relationship is more difficult to predict. In such a situation it might only be possible for an entity to conclude on the basis of a quantitative assessment that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6). In some situations a quantitative assessment might also be needed to assess whether the hedge ratio used for designating the hedging relationship meets the hedge effectiveness requirements (see paragraphs B6.4.9–B6.4.11). An entity can use the same or different methods for those two different purposes.
  4. A regular way purchase or sale gives rise to a fixed price commitment between trade date and settlement date that meets the definition of a derivative. However, because of the short duration of the commitment it is not recognised as a derivative financial instrument. Instead, this Standard provides for special accounting for such regular way contracts (see paragraphs 3.1.2 and B3.1.3–B3.1.6).

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Suprajit Engineering Limited assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Transfer Learning (ML) with Linear Regression1,2,3,4 and conclude that the NSE SUPRAJIT stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold NSE SUPRAJIT stock.

Financial State Forecast for NSE SUPRAJIT Suprajit Engineering Limited Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Operational Risk 4166
Market Risk3178
Technical Analysis8654
Fundamental Analysis5356
Risk Unsystematic8475

Prediction Confidence Score

Trust metric by Neural Network: 77 out of 100 with 615 signals.

References

  1. 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.
  2. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
  3. M. Babes, E. M. de Cote, and M. L. Littman. Social reward shaping in the prisoner's dilemma. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3, pages 1389–1392, 2008.
  4. Brailsford, T.J. R.W. Faff (1996), "An evaluation of volatility forecasting techniques," Journal of Banking Finance, 20, 419–438.
  5. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
  6. Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
  7. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
Frequently Asked QuestionsQ: What is the prediction methodology for NSE SUPRAJIT stock?
A: NSE SUPRAJIT stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Linear Regression
Q: Is NSE SUPRAJIT stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE SUPRAJIT Stock.
Q: Is Suprajit Engineering Limited stock a good investment?
A: The consensus rating for Suprajit Engineering Limited is Hold and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE SUPRAJIT stock?
A: The consensus rating for NSE SUPRAJIT is Hold.
Q: What is the prediction period for NSE SUPRAJIT stock?
A: The prediction period for NSE SUPRAJIT is (n+6 month)

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