OG Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share)

Outlook: Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 12 Mar 2023 for (n+4 weeks)
Methodology : Modular Neural Network (Financial Sentiment Analysis)

Abstract

Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Independent T-Test^1,2,3,4 and it is concluded that the OG stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Buy

Key Points

1. Trading Signals
2. Short/Long Term Stocks
3. Buy, Sell and Hold Signals

OG Target Price Prediction Modeling Methodology

We consider Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of OG 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(Independent T-Test)^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 (Financial Sentiment Analysis)) X S(n):→ (n+4 weeks) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of OG 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?

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

Sample Set: Neural Network
Stock/Index: OG Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share)
Time series to forecast n: 12 Mar 2023 for (n+4 weeks)

According to price forecasts for (n+4 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 Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share)

1. The following example describes a situation in which an accounting mismatch would be created in profit or loss if the effects of changes in the credit risk of the liability were presented in other comprehensive income. A mortgage bank provides loans to customers and funds those loans by selling bonds with matching characteristics (eg amount outstanding, repayment profile, term and currency) in the market. The contractual terms of the loan permit the mortgage customer to prepay its loan (ie satisfy its obligation to the bank) by buying the corresponding bond at fair value in the market and delivering that bond to the mortgage bank. As a result of that contractual prepayment right, if the credit quality of the bond worsens (and, thus, the fair value of the mortgage bank's liability decreases), the fair value of the mortgage bank's loan asset also decreases. The change in the fair value of the asset reflects the mortgage customer's contractual right to prepay the mortgage loan by buying the underlying bond at fair value (which, in this example, has decreased) and delivering the bond to the mortgage bank. Consequently, the effects of changes in the credit risk of the liability (the bond) will be offset in profit or loss by a corresponding change in the fair value of a financial asset (the loan). If the effects of changes in the liability's credit risk were presented in other comprehensive income there would be an accounting mismatch in profit or loss. Consequently, the mortgage bank is required to present all changes in fair value of the liability (including the effects of changes in the liability's credit risk) in profit or loss.
2. If there are changes in circumstances that affect hedge effectiveness, an entity may have to change the method for assessing whether a hedging relationship meets the hedge effectiveness requirements in order to ensure that the relevant characteristics of the hedging relationship, including the sources of hedge ineffectiveness, are still captured.
3. For lifetime expected credit losses, an entity shall estimate the risk of a default occurring on the financial instrument during its expected life. 12-month expected credit losses are a portion of the lifetime expected credit losses and represent the lifetime cash shortfalls that will result if a default occurs in the 12 months after the reporting date (or a shorter period if the expected life of a financial instrument is less than 12 months), weighted by the probability of that default occurring. Thus, 12-month expected credit losses are neither the lifetime expected credit losses that an entity will incur on financial instruments that it predicts will default in the next 12 months nor the cash shortfalls that are predicted over the next 12 months.
4. In applying the effective interest method, an entity identifies fees that are an integral part of the effective interest rate of a financial instrument. The description of fees for financial services may not be indicative of the nature and substance of the services provided. Fees that are an integral part of the effective interest rate of a financial instrument are treated as an adjustment to the effective interest rate, unless the financial instrument is measured at fair value, with the change in fair value being recognised in profit or loss. In those cases, the fees are recognised as revenue or expense when the instrument is initially recognised.

*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

Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) is assigned short-term Ba1 & long-term Ba1 estimated rating. Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Independent T-Test^1,2,3,4 and it is concluded that the OG stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Buy

OG Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) Financial Analysis*

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

*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: 76 out of 100 with 826 signals.

References

1. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
2. Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
3. N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011
4. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
5. S. Bhatnagar, R. Sutton, M. Ghavamzadeh, and M. Lee. Natural actor-critic algorithms. Automatica, 45(11): 2471–2482, 2009
6. Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
7. M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.

Frequently Asked Questions

Q: What is the prediction methodology for OG stock?
A: OG stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Independent T-Test
Q: Is OG stock a buy or sell?
A: The dominant strategy among neural network is to Buy OG Stock.
Q: Is Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) stock a good investment?
A: The consensus rating for Onion Global Limited American Depositary Shares (each ten (10) ADSs representing one (1) Class A Ordinary Share) is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of OG stock?
A: The consensus rating for OG is Buy.
Q: What is the prediction period for OG stock?
A: The prediction period for OG is (n+4 weeks)

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