Machine Learning stock prediction: NSE FLUOROCHEM Stock Prediction

Prediction of stock prices has been an important area of research for a long time. While supporters of the efficient market hypothesis believe that it is impossible to predict stock prices accurately, there are formal propositions demonstrating that accurate modeling and designing of appropriate variables may lead to models using which stock prices and stock price movement patterns can be very accurately predicted. We evaluate Gujarat Fluorochemicals Limited prediction models with Statistical Inference (ML) and Logistic Regression^1,2,3,4 and conclude that the NSE FLUOROCHEM 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 Buy NSE FLUOROCHEM stock.

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

Key Points

1. Which neural network is best for prediction?
2. What is a prediction confidence?
3. What are the most successful trading algorithms?

NSE FLUOROCHEM 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 Gujarat Fluorochemicals Limited Stock Decision Process with Logistic Regression where A is the set of discrete actions of NSE FLUOROCHEM 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(Logistic Regression)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Statistical Inference (ML)) X S(n):→ (n+16 weeks) $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of NSE FLUOROCHEM 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 FLUOROCHEM Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: NSE FLUOROCHEM Gujarat Fluorochemicals Limited
Time series to forecast n: 27 Sep 2022 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period: The dominant strategy among neural network is to Buy NSE FLUOROCHEM 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

Gujarat Fluorochemicals Limited assigned short-term Ba3 & long-term B1 forecasted stock rating. We evaluate the prediction models Statistical Inference (ML) with Logistic Regression^1,2,3,4 and conclude that the NSE FLUOROCHEM 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 Buy NSE FLUOROCHEM stock.

Financial State Forecast for NSE FLUOROCHEM Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B1
Operational Risk	76	48
Market Risk	86	32
Technical Analysis	43	87
Fundamental Analysis	72	62
Risk Unsystematic	38	61

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 460 signals.

References

1. Breiman L, Friedman J, Stone CJ, Olshen RA. 1984. Classification and Regression Trees. Boca Raton, FL: CRC Press
2. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
3. Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
4. Athey S, Bayati M, Doudchenko N, Imbens G, Khosravi K. 2017a. Matrix completion methods for causal panel data models. arXiv:1710.10251 [math.ST]
5. Chen, C. L. Liu (1993), "Joint estimation of model parameters and outlier effects in time series," Journal of the American Statistical Association, 88, 284–297.
6. Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
7. Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM

Frequently Asked Questions

Q: What is the prediction methodology for NSE FLUOROCHEM stock?
A: NSE FLUOROCHEM stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Logistic Regression
Q: Is NSE FLUOROCHEM stock a buy or sell?
A: The dominant strategy among neural network is to Buy NSE FLUOROCHEM Stock.
Q: Is Gujarat Fluorochemicals Limited stock a good investment?
A: The consensus rating for Gujarat Fluorochemicals Limited is Buy and assigned short-term Ba3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of NSE FLUOROCHEM stock?
A: The consensus rating for NSE FLUOROCHEM is Buy.
Q: What is the prediction period for NSE FLUOROCHEM stock?
A: The prediction period for NSE FLUOROCHEM is (n+16 weeks)

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