Modelling A.I. in Economics

ZH Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) (Forecast)

Outlook: Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 26 Jan 2023 for (n+16 weeks)
Methodology : Active Learning (ML)

Abstract

Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) prediction model is evaluated with Active Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the ZH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

Key Points

  1. Why do we need predictive models?
  2. What is prediction model?
  3. Is Target price a good indicator?

ZH Target Price Prediction Modeling Methodology

We consider Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) Decision Process with Active Learning (ML) where A is the set of discrete actions of ZH 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(Linear Regression)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Active Learning (ML)) X S(n):→ (n+16 weeks) e x rx

n:Time series to forecast

p:Price signals of ZH 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?

ZH Stock Forecast (Buy or Sell) for (n+16 weeks)

Sample Set: Neural Network
Stock/Index: ZH Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share)
Time series to forecast n: 26 Jan 2023 for (n+16 weeks)

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

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 Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share)

  1. An entity's documentation of the hedging relationship includes how it will assess the hedge effectiveness requirements, including the method or methods used. The documentation of the hedging relationship shall be updated for any changes to the methods (see paragraph B6.4.17).
  2. Paragraph 4.1.1(b) requires an entity to classify a financial asset on the basis of its contractual cash flow characteristics if the financial asset is held within a business model whose objective is to hold assets to collect contractual cash flows or within a business model whose objective is achieved by both collecting contractual cash flows and selling financial assets, unless paragraph 4.1.5 applies. To do so, the condition in paragraphs 4.1.2(b) and 4.1.2A(b) requires an entity to determine whether the asset's contractual cash flows are solely payments of principal and interest on the principal amount outstanding.
  3. Such designation may be used whether paragraph 4.3.3 requires the embedded derivatives to be separated from the host contract or prohibits such separation. However, paragraph 4.3.5 would not justify designating the hybrid contract as at fair value through profit or loss in the cases set out in paragraph 4.3.5(a) and (b) because doing so would not reduce complexity or increase reliability.
  4. An entity can rebut this presumption. However, it can do so only when it has reasonable and supportable information available that demonstrates that even if contractual payments become more than 30 days past due, this does not represent a significant increase in the credit risk of a financial instrument. For example when non-payment was an administrative oversight, instead of resulting from financial difficulty of the borrower, or the entity has access to historical evidence that demonstrates that there is no correlation between significant increases in the risk of a default occurring and financial assets on which payments are more than 30 days past due, but that evidence does identify such a correlation when payments are more than 60 days past due.

*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

Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) is assigned short-term Ba1 & long-term Ba1 estimated rating. Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) prediction model is evaluated with Active Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the ZH stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy

ZH Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2Baa2
Balance SheetBaa2Caa2
Leverage RatiosCaa2C
Cash FlowBaa2B1
Rates of Return and ProfitabilityBa3Baa2

*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 671 signals.

References

  1. Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
  2. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
  3. Zeileis A, Hothorn T, Hornik K. 2008. Model-based recursive partitioning. J. Comput. Graph. Stat. 17:492–514 Zhou Z, Athey S, Wager S. 2018. Offline multi-action policy learning: generalization and optimization. arXiv:1810.04778 [stat.ML]
  4. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
  5. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
  6. M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
  7. D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
Frequently Asked QuestionsQ: What is the prediction methodology for ZH stock?
A: ZH stock prediction methodology: We evaluate the prediction models Active Learning (ML) and Linear Regression
Q: Is ZH stock a buy or sell?
A: The dominant strategy among neural network is to Buy ZH Stock.
Q: Is Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) stock a good investment?
A: The consensus rating for Zhihu Inc. American Depositary Shares (every two of each representing one Class A ordinary share) is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ZH stock?
A: The consensus rating for ZH is Buy.
Q: What is the prediction period for ZH stock?
A: The prediction period for ZH is (n+16 weeks)

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