Dominant Strategy : Hold
Time series to forecast n: 21 Jun 2023 for 16 Weeks
Methodology : Modular Neural Network (Social Media Sentiment Analysis)
Summary
GDS Holdings Limited ADS prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Factor1,2,3,4 and it is concluded that the GDS 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. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold
Key Points
- Can neural networks predict stock market?
- What statistical methods are used to analyze data?
- How can neural networks improve predictions?
GDS Target Price Prediction Modeling Methodology
We consider GDS Holdings Limited ADS Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of GDS 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(Factor)5,6,7= X R(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ 16 Weeks
n:Time series to forecast
p:Price signals of GDS stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Modular Neural Network (Social Media Sentiment Analysis)
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.Factor
In statistics, a factor is a variable that can influence the value of another variable. Factors can be categorical or continuous. Categorical factors have a limited number of possible values, such as gender (male or female) or blood type (A, B, AB, or O). Continuous factors can have an infinite number of possible values, such as height or weight. Factors can be used to explain the variation in a dependent variable. For example, a study might find that there is a relationship between gender and height. In this case, gender would be the independent variable, height would be the dependent variable, and the factor would be gender.
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?
GDS Stock Forecast (Buy or Sell) for 16 Weeks
Sample Set: Neural NetworkStock/Index: GDS GDS Holdings Limited ADS
Time series to forecast n: 21 Jun 2023 for 16 Weeks
According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold
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 GDS Holdings Limited ADS
- When designating risk components as hedged items, an entity considers whether the risk components are explicitly specified in a contract (contractually specified risk components) or whether they are implicit in the fair value or the cash flows of an item of which they are a part (noncontractually specified risk components). Non-contractually specified risk components can relate to items that are not a contract (for example, forecast transactions) or contracts that do not explicitly specify the component (for example, a firm commitment that includes only one single price instead of a pricing formula that references different underlyings)
- For the purpose of applying the requirements in paragraphs 6.4.1(c)(i) and B6.4.4–B6.4.6, an entity shall assume that the interest rate benchmark on which the hedged cash flows and/or the hedged risk (contractually or noncontractually specified) are based, or the interest rate benchmark on which the cash flows of the hedging instrument are based, is not altered as a result of interest rate benchmark reform.
- The business model may be to hold assets to collect contractual cash flows even if the entity sells financial assets when there is an increase in the assets' credit risk. To determine whether there has been an increase in the assets' credit risk, the entity considers reasonable and supportable information, including forward looking information. Irrespective of their frequency and value, sales due to an increase in the assets' credit risk are not inconsistent with a business model whose objective is to hold financial assets to collect contractual cash flows because the credit quality of financial assets is relevant to the entity's ability to collect contractual cash flows. Credit risk management activities that are aimed at minimising potential credit losses due to credit deterioration are integral to such a business model. Selling a financial asset because it no longer meets the credit criteria specified in the entity's documented investment policy is an example of a sale that has occurred due to an increase in credit risk. However, in the absence of such a policy, the entity may demonstrate in other ways that the sale occurred due to an increase in credit risk.
- When measuring the fair values of the part that continues to be recognised and the part that is derecognised for the purposes of applying paragraph 3.2.13, an entity applies the fair value measurement requirements in IFRS 13 Fair Value Measurement in addition to paragraph 3.2.14.
*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
GDS Holdings Limited ADS is assigned short-term B2 & long-term Ba2 estimated rating. GDS Holdings Limited ADS prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Factor1,2,3,4 and it is concluded that the GDS stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold
GDS GDS Holdings Limited ADS Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B2 | Ba2 |
Income Statement | B3 | B2 |
Balance Sheet | B1 | Baa2 |
Leverage Ratios | B1 | Baa2 |
Cash Flow | B2 | Ba1 |
Rates of Return and Profitability | B3 | B2 |
*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
References
- G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
- E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999
- D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
- Bierens HJ. 1987. Kernel estimators of regression functions. In Advances in Econometrics: Fifth World Congress, Vol. 1, ed. TF Bewley, pp. 99–144. Cambridge, UK: Cambridge Univ. Press
- Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer
- ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
- M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
Frequently Asked Questions
Q: What is the prediction methodology for GDS stock?A: GDS stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Factor
Q: Is GDS stock a buy or sell?
A: The dominant strategy among neural network is to Hold GDS Stock.
Q: Is GDS Holdings Limited ADS stock a good investment?
A: The consensus rating for GDS Holdings Limited ADS is Hold and is assigned short-term B2 & long-term Ba2 estimated rating.
Q: What is the consensus rating of GDS stock?
A: The consensus rating for GDS is Hold.
Q: What is the prediction period for GDS stock?
A: The prediction period for GDS is 16 Weeks
People also ask
⚐ What are the top stocks to invest in right now?☵ What happens to stocks when they're delisted?