AUC Score :
Short-Term Revised1 :
Dominant Strategy : Hold
Time series to forecast n:
Methodology : Modular Neural Network (Emotional Trigger/Responses Analysis)
Hypothesis Testing : Independent T-Test
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.
Abstract
AMCIL LIMITED prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Independent T-Test1,2,3,4 and it is concluded that the AMH 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 emotional trigger/responses 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 emotional trigger/responses analysis, MNNs can be used to identify the emotional triggers that cause people to experience certain emotions, and to identify the responses that people typically exhibit when they experience those emotions. This information can then be used to develop more effective emotional support systems, to improve the accuracy of artificial intelligence systems, and to create more engaging and immersive entertainment experiences. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Hold
Key Points
- Game Theory
- What is prediction model?
- Operational Risk
AMH Target Price Prediction Modeling Methodology
We consider AMCIL LIMITED Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of AMH 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= X R(Modular Neural Network (Emotional Trigger/Responses Analysis)) X S(n):→ 4 Weeks
n:Time series to forecast
p:Price signals of AMH stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Modular Neural Network (Emotional Trigger/Responses Analysis)
A modular neural network (MNN) is a type of artificial neural network that can be used for emotional trigger/responses 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 emotional trigger/responses analysis, MNNs can be used to identify the emotional triggers that cause people to experience certain emotions, and to identify the responses that people typically exhibit when they experience those emotions. This information can then be used to develop more effective emotional support systems, to improve the accuracy of artificial intelligence systems, and to create more engaging and immersive entertainment experiences.Independent T-Test
An independent t-test is a statistical test that compares the means of two independent samples. In an independent t-test, the data points in each sample are not related to each other. The independent t-test is a parametric test, which means that it assumes that the data is normally distributed. The independent t-test is also a two-sample test, which means that it compares the means of two independent samples.
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?
AMH Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: AMH AMCIL LIMITED
Time series to forecast: 4 Weeks
According to price forecasts, the dominant strategy among neural network is: Hold
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 (Emotional Trigger/Responses Analysis) based AMH Stock Prediction Model
- Changes in market conditions that give rise to market risk include changes in a benchmark interest rate, the price of another entity's financial instrument, a commodity price, a foreign exchange rate or an index of prices or rates.
- Hedging relationships that qualified for hedge accounting in accordance with IAS 39 that also qualify for hedge accounting in accordance with the criteria of this Standard (see paragraph 6.4.1), after taking into account any rebalancing of the hedging relationship on transition (see paragraph 7.2.25(b)), shall be regarded as continuing hedging relationships.
- The decision of an entity to designate a financial asset or financial liability as at fair value through profit or loss is similar to an accounting policy choice (although, unlike an accounting policy choice, it is not required to be applied consistently to all similar transactions). When an entity has such a choice, paragraph 14(b) of IAS 8 requires the chosen policy to result in the financial statements providing reliable and more relevant information about the effects of transactions, other events and conditions on the entity's financial position, financial performance or cash flows. For example, in the case of designation of a financial liability as at fair value through profit or loss, paragraph 4.2.2 sets out the two circumstances when the requirement for more relevant information will be met. Accordingly, to choose such designation in accordance with paragraph 4.2.2, the entity needs to demonstrate that it falls within one (or both) of these two circumstances.
- An entity shall apply the amendments to IFRS 9 made by IFRS 17 as amended in June 2020 retrospectively in accordance with IAS 8, except as specified in paragraphs 7.2.37–7.2.42.
*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.
AMH AMCIL LIMITED Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba3 |
Income Statement | Baa2 | Caa2 |
Balance Sheet | C | Baa2 |
Leverage Ratios | Baa2 | Baa2 |
Cash Flow | Baa2 | Caa2 |
Rates of Return and Profitability | Baa2 | Caa2 |
*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
AMCIL LIMITED is assigned short-term Ba1 & long-term Ba3 estimated rating. AMCIL LIMITED prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Independent T-Test1,2,3,4 and it is concluded that the AMH stock is predictable in the short/long term. According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Hold
Prediction Confidence Score
References
- Künzel S, Sekhon J, Bickel P, Yu B. 2017. Meta-learners for estimating heterogeneous treatment effects using machine learning. arXiv:1706.03461 [math.ST]
- Breusch, T. S. A. R. Pagan (1979), "A simple test for heteroskedasticity and random coefficient variation," Econometrica, 47, 1287–1294.
- R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
- A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
- Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
- M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
- Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
Frequently Asked Questions
Q: What is the prediction methodology for AMH stock?A: AMH stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Independent T-Test
Q: Is AMH stock a buy or sell?
A: The dominant strategy among neural network is to Hold AMH Stock.
Q: Is AMCIL LIMITED stock a good investment?
A: The consensus rating for AMCIL LIMITED is Hold and is assigned short-term Ba1 & long-term Ba3 estimated rating.
Q: What is the consensus rating of AMH stock?
A: The consensus rating for AMH is Hold.
Q: What is the prediction period for AMH stock?
A: The prediction period for AMH is 4 Weeks
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