Modelling A.I. in Economics

NSE GREAVESCOT Target Price Forecast (Forecast)

Prediction of stocks is complicated by the dynamic, complex, and chaotic environment of the stock market. Many studies predict stock price movements using deep learning models. Although the attention mechanism has gained popularity recently in neural machine translation, little focus has been devoted to attention-based deep learning models for stock prediction. We evaluate Greaves Cotton Limited prediction models with Active Learning (ML) and Statistical Hypothesis Testing1,2,3,4 and conclude that the NSE GREAVESCOT stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold NSE GREAVESCOT stock.


Keywords: NSE GREAVESCOT, Greaves Cotton Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. How do you pick a stock?
  2. Technical Analysis with Algorithmic Trading
  3. How accurate is machine learning in stock market?

NSE GREAVESCOT Target Price Prediction Modeling Methodology

Neural networks, as an intelligent data mining method, have been used in many different challenging pattern recognition problems such as stock market prediction. However, there is no formal method to determine the optimal neural network for prediction purpose in the literature. In this paper, two kinds of neural networks, a feed forward multi layer Perceptron (MLP) and an Elman recurrent network, are used to predict a company's stock value based on its stock share value history. We consider Greaves Cotton Limited Stock Decision Process with Statistical Hypothesis Testing where A is the set of discrete actions of NSE GREAVESCOT 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(Statistical Hypothesis Testing)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(Active Learning (ML)) X S(n):→ (n+4 weeks) i = 1 n a i

n:Time series to forecast

p:Price signals of NSE GREAVESCOT 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 GREAVESCOT Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: NSE GREAVESCOT Greaves Cotton Limited
Time series to forecast n: 30 Sep 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold NSE GREAVESCOT 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

Greaves Cotton Limited assigned short-term B2 & long-term B1 forecasted stock rating. We evaluate the prediction models Active Learning (ML) with Statistical Hypothesis Testing1,2,3,4 and conclude that the NSE GREAVESCOT stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold NSE GREAVESCOT stock.

Financial State Forecast for NSE GREAVESCOT Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2B1
Operational Risk 7083
Market Risk4583
Technical Analysis3440
Fundamental Analysis3460
Risk Unsystematic7732

Prediction Confidence Score

Trust metric by Neural Network: 80 out of 100 with 598 signals.

References

  1. Abadie A, Diamond A, Hainmueller J. 2010. Synthetic control methods for comparative case studies: estimat- ing the effect of California's tobacco control program. J. Am. Stat. Assoc. 105:493–505
  2. Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
  3. Breiman L. 2001b. Statistical modeling: the two cultures (with comments and a rejoinder by the author). Stat. Sci. 16:199–231
  4. Bessler, D. A. S. W. Fuller (1993), "Cointegration between U.S. wheat markets," Journal of Regional Science, 33, 481–501.
  5. 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.
  6. Pennington J, Socher R, Manning CD. 2014. GloVe: global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods on Natural Language Processing, pp. 1532–43. New York: Assoc. Comput. Linguist.
  7. A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.
Frequently Asked QuestionsQ: What is the prediction methodology for NSE GREAVESCOT stock?
A: NSE GREAVESCOT stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Statistical Hypothesis Testing
Q: Is NSE GREAVESCOT stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE GREAVESCOT Stock.
Q: Is Greaves Cotton Limited stock a good investment?
A: The consensus rating for Greaves Cotton Limited is Hold and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of NSE GREAVESCOT stock?
A: The consensus rating for NSE GREAVESCOT is Hold.
Q: What is the prediction period for NSE GREAVESCOT stock?
A: The prediction period for NSE GREAVESCOT is (n+4 weeks)

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.