SY Stock: The Stock Market Bubble Is About to Burst

Outlook: So-Young International Inc. American Depository Shares is assigned short-term B1 & long-term Ba3 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks²
Methodology : Modular Neural Network (Financial Sentiment Analysis)
Hypothesis Testing : ElasticNet Regression
Surveillance : Major exchange and OTC

¹The accuracy of the model is being monitored on a regular basis.(15-minute period)

²Time series is updated based on short-term trends.

Summary

So-Young International Inc. American Depository Shares prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and ElasticNet Regression^1,2,3,4 and it is concluded that the SY stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for financial sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of financial sentiment analysis, MNNs can be used to identify the sentiment of financial news articles, social media posts, and other forms of online content. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend

Key Points

1. How do you decide buy or sell a stock?
2. Nash Equilibria
3. Can machine learning predict?

SY Target Price Prediction Modeling Methodology

We consider So-Young International Inc. American Depository Shares Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of SY 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(ElasticNet 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 (Financial Sentiment Analysis)) X S(n):→ 8 Weeks $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of SY stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Financial Sentiment Analysis)

Modular neural networks (MNNs) are a type of artificial neural network that can be used for financial sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of financial sentiment analysis, MNNs can be used to identify the sentiment of financial news articles, social media posts, and other forms of online content. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising.

ElasticNet Regression

Elastic net regression is a type of regression analysis that combines the benefits of ridge regression and lasso regression. It is a regularized regression method that adds a penalty to the least squares objective function in order to reduce the variance of the estimates, induce sparsity in the model, and reduce overfitting. This is done by adding a term to the objective function that is proportional to the sum of the squares of the coefficients and the sum of the absolute values of the coefficients. The penalty terms are controlled by two parameters, called the ridge constant and the lasso constant. Elastic net regression can be used to address the problems of multicollinearity, overfitting, and sensitivity to outliers. It is a more flexible method than ridge regression or lasso regression, and it can often achieve better results.

 

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?

SY Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: SY So-Young International Inc. American Depository Shares
Time series to forecast: 8 Weeks

According to price forecasts, the dominant strategy among neural network is: Speculative Trend

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Modular Neural Network (Financial Sentiment Analysis) based SY Stock Prediction Model

1. For the purposes of applying the requirements in paragraphs 5.7.7 and 5.7.8, an accounting mismatch is not caused solely by the measurement method that an entity uses to determine the effects of changes in a liability's credit risk. An accounting mismatch in profit or loss would arise only when the effects of changes in the liability's credit risk (as defined in IFRS 7) are expected to be offset by changes in the fair value of another financial instrument. A mismatch that arises solely as a result of the measurement method (ie because an entity does not isolate changes in a liability's credit risk from some other changes in its fair value) does not affect the determination required by paragraphs 5.7.7 and 5.7.8. For example, an entity may not isolate changes in a liability's credit risk from changes in liquidity risk. If the entity presents the combined effect of both factors in other comprehensive income, a mismatch may occur because changes in liquidity risk may be included in the fair value measurement of the entity's financial assets and the entire fair value change of those assets is presented in profit or loss. However, such a mismatch is caused by measurement imprecision, not the offsetting relationship described in paragraph B5.7.6 and, therefore, does not affect the determination required by paragraphs 5.7.7 and 5.7.8.
2. Adjusting the hedge ratio by increasing the volume of the hedging instrument does not affect how the changes in the value of the hedged item are measured. The measurement of the changes in the fair value of the hedging instrument related to the previously designated volume also remains unaffected. However, from the date of rebalancing, the changes in the fair value of the hedging instrument also include the changes in the value of the additional volume of the hedging instrument. The changes are measured starting from, and by reference to, the date of rebalancing instead of the date on which the hedging relationship was designated. For example, if an entity originally hedged the price risk of a commodity using a derivative volume of 100 tonnes as the hedging instrument and added a volume of 10 tonnes on rebalancing, the hedging instrument after rebalancing would comprise a total derivative volume of 110 tonnes. The change in the fair value of the hedging instrument is the total change in the fair value of the derivatives that make up the total volume of 110 tonnes. These derivatives could (and probably would) have different critical terms, such as their forward rates, because they were entered into at different points in time (including the possibility of designating derivatives into hedging relationships after their initial recognition).
3. 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.
4. The assessment of whether an economic relationship exists includes an analysis of the possible behaviour of the hedging relationship during its term to ascertain whether it can be expected to meet the risk management objective. The mere existence of a statistical correlation between two variables does not, by itself, support a valid conclusion that an economic relationship exists.

*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.

SY So-Young International Inc. American Depository Shares Financial Analysis*

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

Conclusions

So-Young International Inc. American Depository Shares is assigned short-term B1 & long-term Ba3 estimated rating. So-Young International Inc. American Depository Shares prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and ElasticNet Regression^1,2,3,4 and it is concluded that the SY stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Speculative Trend

Prediction Confidence Score

Trust metric by Neural Network: 73 out of 100 with 841 signals.

References

1. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
2. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
3. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
4. G. J. Laurent, L. Matignon, and N. L. Fort-Piat. The world of independent learners is not Markovian. Int. J. Know.-Based Intell. Eng. Syst., 15(1):55–64, 2011
5. K. Boda and J. Filar. Time consistent dynamic risk measures. Mathematical Methods of Operations Research, 63(1):169–186, 2006
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. Arora S, Li Y, Liang Y, Ma T. 2016. RAND-WALK: a latent variable model approach to word embeddings. Trans. Assoc. Comput. Linguist. 4:385–99

Frequently Asked Questions

Q: What is the prediction methodology for SY stock?
A: SY stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and ElasticNet Regression
Q: Is SY stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend SY Stock.
Q: Is So-Young International Inc. American Depository Shares stock a good investment?
A: The consensus rating for So-Young International Inc. American Depository Shares is Speculative Trend and is assigned short-term B1 & long-term Ba3 estimated rating.
Q: What is the consensus rating of SY stock?
A: The consensus rating for SY is Speculative Trend.
Q: What is the prediction period for SY stock?
A: The prediction period for SY is 8 Weeks

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