BON Bon Natural Life Limited Ordinary Shares

Outlook: Bon Natural Life Limited Ordinary Shares assigned short-term Ba3 & long-term B2 forecasted stock rating.
Dominant Strategy : Buy
Time series to forecast n: 07 Dec 2022 for (n+8 weeks)
Methodology : Statistical Inference (ML)

Abstract

The main objective of this research is to predict the market performance on day closing using different machine learning techniques. The prediction model uses different attributes as an input and predicts market as Positive & Negative. (Leung, C.K.S., MacKinnon, R.K. and Wang, Y., 2014, July. A machine learning approach for stock price prediction. In Proceedings of the 18th International Database Engineering & Applications Symposium (pp. 274-277).) We evaluate Bon Natural Life Limited Ordinary Shares prediction models with Statistical Inference (ML) and Polynomial Regression^1,2,3,4 and conclude that the BON 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 Buy BON stock.

Key Points

1. Short/Long Term Stocks
2. Market Signals
3. How do you pick a stock?

BON Target Price Prediction Modeling Methodology

We consider Bon Natural Life Limited Ordinary Shares Decision Process with Statistical Inference (ML) where A is the set of discrete actions of BON 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(Polynomial 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+8 weeks) $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of BON stock

j:Nash equilibria (Neural Network)

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?

BON Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: BON Bon Natural Life Limited Ordinary Shares
Time series to forecast n: 07 Dec 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Buy BON 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%

Adjusted IFRS* Prediction Methods for Bon Natural Life Limited Ordinary Shares

1. The decision of an entity to designate a financial asset or financial liability as at fair value through profit or loss is similar to an accounting policy choice (although, unlike an accounting policy choice, it is not required to be applied consistently to all similar transactions). When an entity has such a choice, paragraph 14(b) of IAS 8 requires the chosen policy to result in the financial statements providing reliable and more relevant information about the effects of transactions, other events and conditions on the entity's financial position, financial performance or cash flows. For example, in the case of designation of a financial liability as at fair value through profit or loss, paragraph 4.2.2 sets out the two circumstances when the requirement for more relevant information will be met. Accordingly, to choose such designation in accordance with paragraph 4.2.2, the entity needs to demonstrate that it falls within one (or both) of these two circumstances.
2. An entity shall apply this Standard for annual periods beginning on or after 1 January 2018. Earlier application is permitted. If an entity elects to apply this Standard early, it must disclose that fact and apply all of the requirements in this Standard at the same time (but see also paragraphs 7.1.2, 7.2.21 and 7.3.2). It shall also, at the same time, apply the amendments in Appendix C.
3. The assessment of whether lifetime expected credit losses should be recognised is based on significant increases in the likelihood or risk of a default occurring since initial recognition (irrespective of whether a financial instrument has been repriced to reflect an increase in credit risk) instead of on evidence of a financial asset being credit-impaired at the reporting date or an actual default occurring. Generally, there will be a significant increase in credit risk before a financial asset becomes credit-impaired or an actual default occurs.
4. In addition to those hedging relationships specified in paragraph 6.9.1, an entity shall apply the requirements in paragraphs 6.9.11 and 6.9.12 to new hedging relationships in which an alternative benchmark rate is designated as a non-contractually specified risk component (see paragraphs 6.3.7(a) and B6.3.8) when, because of interest rate benchmark reform, that risk component is not separately identifiable at the date it is designated.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Bon Natural Life Limited Ordinary Shares assigned short-term Ba3 & long-term B2 forecasted stock rating. We evaluate the prediction models Statistical Inference (ML) with Polynomial Regression^1,2,3,4 and conclude that the BON 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 Buy BON stock.

Financial State Forecast for BON Bon Natural Life Limited Ordinary Shares Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B2
Operational Risk	84	41
Market Risk	40	68
Technical Analysis	69	59
Fundamental Analysis	83	46
Risk Unsystematic	46	48

Prediction Confidence Score

Trust metric by Neural Network: 81 out of 100 with 547 signals.

References

1. R. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Ma- chine learning, 8(3-4):229–256, 1992
2. Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.
3. Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
4. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
5. A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
6. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
7. Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221

Frequently Asked Questions

Q: What is the prediction methodology for BON stock?
A: BON stock prediction methodology: We evaluate the prediction models Statistical Inference (ML) and Polynomial Regression
Q: Is BON stock a buy or sell?
A: The dominant strategy among neural network is to Buy BON Stock.
Q: Is Bon Natural Life Limited Ordinary Shares stock a good investment?
A: The consensus rating for Bon Natural Life Limited Ordinary Shares is Buy and assigned short-term Ba3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of BON stock?
A: The consensus rating for BON is Buy.
Q: What is the prediction period for BON stock?
A: The prediction period for BON is (n+8 weeks)

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