BZ KANZHUN LIMITED American Depository Shares

Outlook: KANZHUN LIMITED American Depository Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 25 Mar 2023 for (n+4 weeks)
Methodology : Modular Neural Network (CNN Layer)

Abstract

KANZHUN LIMITED American Depository Shares prediction model is evaluated with Modular Neural Network (CNN Layer) and Ridge Regression^1,2,3,4 and it is concluded that the BZ stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

Key Points

1. Stock Forecast Based On a Predictive Algorithm
2. Technical Analysis with Algorithmic Trading
3. What is Markov decision process in reinforcement learning?

BZ Target Price Prediction Modeling Methodology

We consider KANZHUN LIMITED American Depository Shares Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of BZ 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(Ridge 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(Modular Neural Network (CNN Layer)) X S(n):→ (n+4 weeks) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of BZ 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?

BZ Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: BZ KANZHUN LIMITED American Depository Shares
Time series to forecast n: 25 Mar 2023 for (n+4 weeks)

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

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 (Grey to Black): *Technical Analysis%

IFRS Reconciliation Adjustments for KANZHUN LIMITED American Depository Shares

1. An entity shall apply the amendments to IFRS 9 made by IFRS 17 as amended in June 2020 retrospectively in accordance with IAS 8, except as specified in paragraphs 7.2.37–7.2.42.
2. The definition of a derivative in this Standard includes contracts that are settled gross by delivery of the underlying item (eg a forward contract to purchase a fixed rate debt instrument). An entity may have a contract to buy or sell a non-financial item that can be settled net in cash or another financial instrument or by exchanging financial instruments (eg a contract to buy or sell a commodity at a fixed price at a future date). Such a contract is within the scope of this Standard unless it was entered into and continues to be held for the purpose of delivery of a non-financial item in accordance with the entity's expected purchase, sale or usage requirements. However, this Standard applies to such contracts for an entity's expected purchase, sale or usage requirements if the entity makes a designation in accordance with paragraph 2.5 (see paragraphs 2.4–2.7).
3. The accounting for the time value of options in accordance with paragraph 6.5.15 applies only to the extent that the time value relates to the hedged item (aligned time value). The time value of an option relates to the hedged item if the critical terms of the option (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the option and the hedged item are not fully aligned, an entity shall determine the aligned time value, ie how much of the time value included in the premium (actual time value) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.15). An entity determines the aligned time value using the valuation of the option that would have critical terms that perfectly match the hedged item.
4. A firm commitment to acquire a business in a business combination cannot be a hedged item, except for foreign currency risk, because the other risks being hedged cannot be specifically identified and measured. Those other risks are general business risks.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

Conclusions

KANZHUN LIMITED American Depository Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. KANZHUN LIMITED American Depository Shares prediction model is evaluated with Modular Neural Network (CNN Layer) and Ridge Regression^1,2,3,4 and it is concluded that the BZ stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Hold

BZ KANZHUN LIMITED American Depository Shares Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B1	C
Balance Sheet	B3	Caa2
Leverage Ratios	Caa2	B1
Cash Flow	Ba3	Baa2
Rates of Return and Profitability	Caa2	B2

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

Prediction Confidence Score

Trust metric by Neural Network: 80 out of 100 with 655 signals.

References

1. Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511
2. Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.
3. Athey S, Bayati M, Imbens G, Zhaonan Q. 2019. Ensemble methods for causal effects in panel data settings. NBER Work. Pap. 25675
4. Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
5. B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
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. Athey S, Blei D, Donnelly R, Ruiz F. 2017b. Counterfactual inference for consumer choice across many prod- uct categories. AEA Pap. Proc. 108:64–67

Frequently Asked Questions

Q: What is the prediction methodology for BZ stock?
A: BZ stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Ridge Regression
Q: Is BZ stock a buy or sell?
A: The dominant strategy among neural network is to Hold BZ Stock.
Q: Is KANZHUN LIMITED American Depository Shares stock a good investment?
A: The consensus rating for KANZHUN LIMITED American Depository Shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BZ stock?
A: The consensus rating for BZ is Hold.
Q: What is the prediction period for BZ stock?
A: The prediction period for BZ is (n+4 weeks)

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