Outlook: 17 Education & Technology Group Inc. American Depositary Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Time series to forecast n: 19 Jun 2023 for 1 Year
Methodology : Ensemble Learning (ML)

## Abstract

17 Education & Technology Group Inc. American Depositary Shares prediction model is evaluated with Ensemble Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the YQ stock is predictable in the short/long term. Ensemble learning is a machine learning (ML) technique that combines multiple models to create a single model that is more accurate than any of the individual models. This is done by combining the predictions of the individual models, typically using a voting scheme or a weighted average. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

## Key Points

1. Should I buy stocks now or wait amid such uncertainty?
2. Reaction Function
3. How do you know when a stock will go up or down?

## YQ Target Price Prediction Modeling Methodology

We consider 17 Education & Technology Group Inc. American Depositary Shares Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of YQ 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Ensemble Learning (ML)) X S(n):→ 1 Year $∑ i = 1 n a i$

n:Time series to forecast

p:Price signals of YQ stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Ensemble Learning (ML)

Ensemble learning is a machine learning (ML) technique that combines multiple models to create a single model that is more accurate than any of the individual models. This is done by combining the predictions of the individual models, typically using a voting scheme or a weighted average.

### Linear Regression

In statistics, linear regression is a method for estimating the relationship between a dependent variable and one or more independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Linear regression assumes that the relationship between the dependent variable and the independent variables is linear. This means that the dependent variable can be represented as a straight line function of the independent variables.

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?

## YQ Stock Forecast (Buy or Sell) for 1 Year

Sample Set: Neural Network
Stock/Index: YQ 17 Education & Technology Group Inc. American Depositary Shares
Time series to forecast n: 19 Jun 2023 for 1 Year

According to price forecasts for 1 Year 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 17 Education & Technology Group Inc. American Depositary Shares

1. There is a rebuttable presumption that unless inflation risk is contractually specified, it is not separately identifiable and reliably measurable and hence cannot be designated as a risk component of a financial instrument. However, in limited cases, it is possible to identify a risk component for inflation risk that is separately identifiable and reliably measurable because of the particular circumstances of the inflation environment and the relevant debt market
2. An entity shall apply Annual Improvements to IFRS Standards 2018–2020 to financial liabilities that are modified or exchanged on or after the beginning of the annual reporting period in which the entity first applies the amendment.
3. The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary
4. To be eligible for designation as a hedged item, a risk component must be a separately identifiable component of the financial or the non-financial item, and the changes in the cash flows or the fair value of the item attributable to changes in that risk component must be reliably measurable.

*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

17 Education & Technology Group Inc. American Depositary Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. 17 Education & Technology Group Inc. American Depositary Shares prediction model is evaluated with Ensemble Learning (ML) and Linear Regression1,2,3,4 and it is concluded that the YQ stock is predictable in the short/long term. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

### YQ 17 Education & Technology Group Inc. American Depositary Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2C
Balance SheetBaa2Baa2
Leverage RatiosCaa2Caa2
Cash FlowCaa2Baa2
Rates of Return and ProfitabilityCBaa2

*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 846 signals.

## References

1. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
2. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
3. Breiman L, Friedman J, Stone CJ, Olshen RA. 1984. Classification and Regression Trees. Boca Raton, FL: CRC Press
4. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
5. Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
6. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
7. J. Spall. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37(3):332–341, 1992.
Frequently Asked QuestionsQ: What is the prediction methodology for YQ stock?
A: YQ stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Linear Regression
Q: Is YQ stock a buy or sell?
A: The dominant strategy among neural network is to Buy YQ Stock.
Q: Is 17 Education & Technology Group Inc. American Depositary Shares stock a good investment?
A: The consensus rating for 17 Education & Technology Group Inc. American Depositary Shares is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of YQ stock?
A: The consensus rating for YQ is Buy.
Q: What is the prediction period for YQ stock?
A: The prediction period for YQ is 1 Year