How Is Machine Learning Used in Trading? (NSE JUBLFOOD Stock Forecast)

This paper surveys machine learning techniques for stock market prediction. The prediction of stock markets is regarded as a challenging task of financial time series prediction. We evaluate Jubilant Foodworks Limited prediction models with Deductive Inference (ML) and Stepwise Regression^1,2,3,4 and conclude that the NSE JUBLFOOD 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 JUBLFOOD stock.

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

Key Points

1. Reaction Function
2. Decision Making
3. Trading Signals

NSE JUBLFOOD Target Price Prediction Modeling Methodology

Market systems are so complex that they overwhelm the ability of any individual to predict. But it is crucial for the investors to predict stock market price to generate notable profit. We have taken into factors such as Commodity Prices (crude oil, gold, silver), Market History, and Foreign exchange rate (FEX) that influence the stock trend. We consider Jubilant Foodworks Limited Stock Decision Process with Stepwise Regression where A is the set of discrete actions of NSE JUBLFOOD 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(Stepwise 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(Deductive Inference (ML)) X S(n):→ (n+4 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

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

Sample Set: Neural Network
Stock/Index: NSE JUBLFOOD Jubilant Foodworks Limited
Time series to forecast n: 03 Oct 2022 for (n+4 weeks)

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

Jubilant Foodworks Limited assigned short-term Ba3 & long-term Baa2 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Stepwise Regression^1,2,3,4 and conclude that the NSE JUBLFOOD 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 JUBLFOOD stock.

Financial State Forecast for NSE JUBLFOOD Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	Baa2
Operational Risk	58	86
Market Risk	75	86
Technical Analysis	70	59
Fundamental Analysis	57	69
Risk Unsystematic	73	79

Prediction Confidence Score

Trust metric by Neural Network: 87 out of 100 with 772 signals.

References

1. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
2. M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
3. Arora S, Li Y, Liang Y, Ma T. 2016. RAND-WALK: a latent variable model approach to word embeddings. Trans. Assoc. Comput. Linguist. 4:385–99
4. Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
5. Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer
6. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
7. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71

Frequently Asked Questions

Q: What is the prediction methodology for NSE JUBLFOOD stock?
A: NSE JUBLFOOD stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Stepwise Regression
Q: Is NSE JUBLFOOD stock a buy or sell?
A: The dominant strategy among neural network is to Hold NSE JUBLFOOD Stock.
Q: Is Jubilant Foodworks Limited stock a good investment?
A: The consensus rating for Jubilant Foodworks Limited is Hold and assigned short-term Ba3 & long-term Baa2 forecasted stock rating.
Q: What is the consensus rating of NSE JUBLFOOD stock?
A: The consensus rating for NSE JUBLFOOD is Hold.
Q: What is the prediction period for NSE JUBLFOOD stock?
A: The prediction period for NSE JUBLFOOD 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