Stock market or Share market is one of the most complicated and sophisticated way to do business. Small ownerships, brokerage corporations, banking sector, all depend on this very body to make revenue and divide risks; a very complicated model. However, this paper proposes to use machine learning algorithm to predict the future stock price for exchange by using open source libraries and preexisting algorithms to help make this unpredictable format of business a little more predictable. We evaluate Filatex India Limited prediction models with Multi-Task Learning (ML) and Spearman Correlation1,2,3,4 and conclude that the NSE FILATEX 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 Buy NSE FILATEX stock.
Keywords: NSE FILATEX, Filatex India Limited, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.
Key Points
- Stock Forecast Based On a Predictive Algorithm
- What are buy sell or hold recommendations?
- Buy, Sell and Hold Signals

NSE FILATEX 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 Filatex India Limited Stock Decision Process with Spearman Correlation where A is the set of discrete actions of NSE FILATEX 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(Spearman Correlation)5,6,7= X R(Multi-Task Learning (ML)) X S(n):→ (n+4 weeks)
n:Time series to forecast
p:Price signals of NSE FILATEX 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 FILATEX Stock Forecast (Buy or Sell) for (n+4 weeks)
Sample Set: Neural NetworkStock/Index: NSE FILATEX Filatex India Limited
Time series to forecast n: 02 Oct 2022 for (n+4 weeks)
According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy NSE FILATEX 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
Filatex India Limited assigned short-term B3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Multi-Task Learning (ML) with Spearman Correlation1,2,3,4 and conclude that the NSE FILATEX 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 Buy NSE FILATEX stock.
Financial State Forecast for NSE FILATEX Stock Options & Futures
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B3 | Ba3 |
Operational Risk | 60 | 38 |
Market Risk | 35 | 47 |
Technical Analysis | 42 | 78 |
Fundamental Analysis | 69 | 68 |
Risk Unsystematic | 51 | 89 |
Prediction Confidence Score
References
- 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.
- Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
- uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
- J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
- R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
- Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
- Athey S, Imbens G, Wager S. 2016a. Efficient inference of average treatment effects in high dimensions via approximate residual balancing. arXiv:1604.07125 [math.ST]
Frequently Asked Questions
Q: What is the prediction methodology for NSE FILATEX stock?A: NSE FILATEX stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Spearman Correlation
Q: Is NSE FILATEX stock a buy or sell?
A: The dominant strategy among neural network is to Buy NSE FILATEX Stock.
Q: Is Filatex India Limited stock a good investment?
A: The consensus rating for Filatex India Limited is Buy and assigned short-term B3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of NSE FILATEX stock?
A: The consensus rating for NSE FILATEX is Buy.
Q: What is the prediction period for NSE FILATEX stock?
A: The prediction period for NSE FILATEX is (n+4 weeks)