Is YALA Stock Expected to Go Up?

Jorgenson, Dale W.; Weitzman, Martin L.; ZXhang, Yoshua X; Haxo, Yann M; Mat , Ying X

Outlook: Yalla Group Limited American Depositary Shares each representing one Class A Ordinary Share is assigned short-term B3 & long-term Ba2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : SellBuy
Time series to forecast n: for Weeks²
Methodology : Modular Neural Network (Social Media Sentiment Analysis)
Hypothesis Testing : Statistical Hypothesis Testing
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

Yalla Group Limited American Depositary Shares each representing one Class A Ordinary Share prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Statistical Hypothesis Testing^1,2,3,4 and it is concluded that the YALA stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for social media 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 social media sentiment analysis, MNNs can be used to identify the sentiment of social media posts, such as tweets, Facebook posts, and Instagram stories. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.⁵ According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: SellBuy

Key Points

Modular Neural Network (Social Media Sentiment Analysis) for YALA stock price prediction process.
Statistical Hypothesis Testing
Stock Rating
Understanding Buy, Sell, and Hold Ratings
Can statistics predict the future?

YALA Stock Price Forecast

We consider Yalla Group Limited American Depositary Shares each representing one Class A Ordinary Share Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of YALA 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

Sample Set: Neural Network
Stock/Index: YALA Yalla Group Limited American Depositary Shares each representing one Class A Ordinary Share
Time series to forecast: 4 Weeks

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

F(Statistical Hypothesis Testing)^6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ 4 Weeks

\vec{R} = (r_{1}, r_{2}, r_{3})

n:Time series to forecast

p:Price signals of YALA stock

j:Nash equilibria (Neural Network)

k:Dominated move of YALA stock holders

a:Best response for YALA target price

A modular neural network (MNN) is a type of artificial neural network that can be used for social media 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 social media sentiment analysis, MNNs can be used to identify the sentiment of social media posts, such as tweets, Facebook posts, and Instagram stories. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.⁵ Statistical hypothesis testing is a process used to determine whether there is enough evidence to support a claim about a population based on a sample. The process involves making two hypotheses, a null hypothesis and an alternative hypothesis, and then collecting data and using statistical tests to determine which hypothesis is more likely to be true. The null hypothesis is the statement that there is no difference between the population and the sample. The alternative hypothesis is the statement that there is a difference between the population and the sample. The statistical test is used to calculate a p-value, which is the probability of obtaining the observed data or more extreme data if the null hypothesis is true. A p-value of less than 0.05 is typically considered to be statistically significant, which means that there is less than a 5% chance of obtaining the observed data or more extreme data if the null hypothesis is true.^6,7

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YALA Stock Forecast (Buy or Sell) Strategic Interaction Table

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 (Social Media Sentiment Analysis) based YALA Stock Prediction Model

Paragraph 6.3.4 permits an entity to designate as hedged items aggregated exposures that are a combination of an exposure and a derivative. When designating such a hedged item, an entity assesses whether the aggregated exposure combines an exposure with a derivative so that it creates a different aggregated exposure that is managed as one exposure for a particular risk (or risks). In that case, the entity may designate the hedged item on the basis of the aggregated exposure
Conversely, if the critical terms of the hedging instrument and the hedged item are not closely aligned, there is an increased level of uncertainty about the extent of offset. Consequently, the hedge effectiveness during the term of the hedging relationship is more difficult to predict. In such a situation it might only be possible for an entity to conclude on the basis of a quantitative assessment that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6). In some situations a quantitative assessment might also be needed to assess whether the hedge ratio used for designating the hedging relationship meets the hedge effectiveness requirements (see paragraphs B6.4.9–B6.4.11). An entity can use the same or different methods for those two different purposes.
Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.
If a guarantee provided by an entity to pay for default losses on a transferred asset prevents the transferred asset from being derecognised to the extent of the continuing involvement, the transferred asset at the date of the transfer is measured at the lower of (i) the carrying amount of the asset and (ii) the maximum amount of the consideration received in the transfer that the entity could be required to repay ('the guarantee amount'). The associated liability is initially measured at the guarantee amount plus the fair value of the guarantee (which is normally the consideration received for the guarantee). Subsequently, the initial fair value of the guarantee is recognised in profit or loss when (or as) the obligation is satisfied (in accordance with the principles of IFRS 15) and the carrying value of the asset is reduced by any loss allowance.

*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.

YALA Yalla Group Limited American Depositary Shares each representing one Class A Ordinary Share Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B3	Ba2
Income Statement	Caa2	B3
Balance Sheet	B3	Baa2
Leverage Ratios	C	B2
Cash Flow	Caa2	B1
Rates of Return and Profitability	B1	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?

References

E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999
Nie X, Wager S. 2019. Quasi-oracle estimation of heterogeneous treatment effects. arXiv:1712.04912 [stat.ML]
Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Apple's Stock Price: How News Affects Volatility. AC Investment Research Journal, 220(44).
Breiman L. 1993. Better subset selection using the non-negative garotte. Tech. Rep., Univ. Calif., Berkeley
M. Ono, M. Pavone, Y. Kuwata, and J. Balaram. Chance-constrained dynamic programming with application to risk-aware robotic space exploration. Autonomous Robots, 39(4):555–571, 2015

Frequently Asked Questions

Q: Is YALA stock expected to rise?
A: YALA stock prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Statistical Hypothesis Testing and it is concluded that dominant strategy for YALA stock is SellBuy
Q: Is YALA stock a buy or sell?
A: The dominant strategy among neural network is to SellBuy YALA Stock.
Q: Is Yalla Group Limited American Depositary Shares each representing one Class A Ordinary Share stock a good investment?
A: The consensus rating for Yalla Group Limited American Depositary Shares each representing one Class A Ordinary Share is SellBuy and is assigned short-term B3 & long-term Ba2 estimated rating.
Q: What is the consensus rating of YALA stock?
A: The consensus rating for YALA is SellBuy.
Q: What is the forecast for YALA stock?
A: YALA target price forecast: SellBuy

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