Modelling A.I. in Economics

How accurate is machine learning in stock market? (NSE WHIRLPOOL Stock Forecast) (Forecast)

Financial markets are fascinating if you can predict them. Also, the traders acting on financial markets produce a vast amount of information to analyse the consequences of investing according to the current market trends. Stock Market prediction is the technique to determine whether stock value will go up or down as it plays an active role in the financial gain of nation's economic status. We evaluate Whirlpool of India Limited prediction models with Modular Neural Network (Market Volatility Analysis) and Factor1,2,3,4 and conclude that the NSE WHIRLPOOL stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold NSE WHIRLPOOL stock.


Keywords: NSE WHIRLPOOL, Whirlpool of India Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Operational Risk
  2. Market Signals
  3. Trading Interaction

NSE WHIRLPOOL Target Price Prediction Modeling Methodology

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 consider Whirlpool of India Limited Stock Decision Process with Factor where A is the set of discrete actions of NSE WHIRLPOOL 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(Factor)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(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+8 weeks) r s rs

n:Time series to forecast

p:Price signals of NSE WHIRLPOOL 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 WHIRLPOOL Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: NSE WHIRLPOOL Whirlpool of India Limited
Time series to forecast n: 01 Oct 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold NSE WHIRLPOOL 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

Whirlpool of India Limited assigned short-term B1 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with Factor1,2,3,4 and conclude that the NSE WHIRLPOOL stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold NSE WHIRLPOOL stock.

Financial State Forecast for NSE WHIRLPOOL Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1Ba3
Operational Risk 7388
Market Risk6647
Technical Analysis4389
Fundamental Analysis7352
Risk Unsystematic4235

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 555 signals.

References

  1. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
  2. D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.
  3. J. N. Foerster, Y. M. Assael, N. de Freitas, and S. Whiteson. Learning to communicate with deep multi-agent reinforcement learning. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, December 5-10, 2016, Barcelona, Spain, pages 2137–2145, 2016.
  4. G. Theocharous and A. Hallak. Lifetime value marketing using reinforcement learning. RLDM 2013, page 19, 2013
  5. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
  6. Schapire RE, Freund Y. 2012. Boosting: Foundations and Algorithms. Cambridge, MA: MIT Press
  7. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
Frequently Asked QuestionsQ: What is the prediction methodology for NSE WHIRLPOOL stock?
A: NSE WHIRLPOOL stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Factor
Q: Is NSE WHIRLPOOL stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE WHIRLPOOL Stock.
Q: Is Whirlpool of India Limited stock a good investment?
A: The consensus rating for Whirlpool of India Limited is Hold and assigned short-term B1 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE WHIRLPOOL stock?
A: The consensus rating for NSE WHIRLPOOL is Hold.
Q: What is the prediction period for NSE WHIRLPOOL stock?
A: The prediction period for NSE WHIRLPOOL is (n+8 weeks)

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