AUC Score :
Short-Term Revised1 :
Dominant Strategy : Speculative Trend
Time series to forecast n:
Methodology : Reinforcement Machine Learning (ML)
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
CRH PLC prediction model is evaluated with Reinforcement Machine Learning (ML) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the LON:97GM stock is predictable in the short/long term. Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Speculative Trend
Key Points
- What is the best way to predict stock prices?
- Is Target price a good indicator?
- Operational Risk
LON:97GM Target Price Prediction Modeling Methodology
We consider CRH PLC Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of LON:97GM 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(Statistical Hypothesis Testing)5,6,7= X R(Reinforcement Machine Learning (ML)) X S(n):→ 3 Month
n:Time series to forecast
p:Price signals of LON:97GM stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Reinforcement Machine Learning (ML)
Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.Statistical Hypothesis Testing
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.
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?
LON:97GM Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: LON:97GM CRH PLC
Time series to forecast: 3 Month
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 Reinforcement Machine Learning (ML) based LON:97GM Stock Prediction Model
- A single hedging instrument may be designated as a hedging instrument of more than one type of risk, provided that there is a specific designation of the hedging instrument and of the different risk positions as hedged items. Those hedged items can be in different hedging relationships.
- Paragraph 6.3.6 states that in consolidated financial statements the foreign currency risk of a highly probable forecast intragroup transaction may qualify as a hedged item in a cash flow hedge, provided that the transaction is denominated in a currency other than the functional currency of the entity entering into that transaction and that the foreign currency risk will affect consolidated profit or loss. For this purpose an entity can be a parent, subsidiary, associate, joint arrangement or branch. If the foreign currency risk of a forecast intragroup transaction does not affect consolidated profit or loss, the intragroup transaction cannot qualify as a hedged item. This is usually the case for royalty payments, interest payments or management charges between members of the same group, unless there is a related external transaction. However, when the foreign currency risk of a forecast intragroup transaction will affect consolidated profit or loss, the intragroup transaction can qualify as a hedged item. An example is forecast sales or purchases of inventories between members of the same group if there is an onward sale of the inventory to a party external to the group. Similarly, a forecast intragroup sale of plant and equipment from the group entity that manufactured it to a group entity that will use the plant and equipment in its operations may affect consolidated profit or loss. This could occur, for example, because the plant and equipment will be depreciated by the purchasing entity and the amount initially recognised for the plant and equipment may change if the forecast intragroup transaction is denominated in a currency other than the functional currency of the purchasing entity.
- For the purpose of this Standard, reasonable and supportable information is that which is reasonably available at the reporting date without undue cost or effort, including information about past events, current conditions and forecasts of future economic conditions. Information that is available for financial reporting purposes is considered to be available without undue cost or effort.
- The following are examples of when the objective of the entity's business model may be achieved by both collecting contractual cash flows and selling financial assets. This list of examples is not exhaustive. Furthermore, the examples are not intended to describe all the factors that may be relevant to the assessment of the entity's business model nor specify the relative importance of the factors.
*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.
LON:97GM CRH PLC Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B2 | B2 |
Income Statement | C | Caa2 |
Balance Sheet | Ba1 | B2 |
Leverage Ratios | B1 | Baa2 |
Cash Flow | C | B2 |
Rates of Return and Profitability | Ba2 | C |
*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
CRH PLC is assigned short-term B2 & long-term B2 estimated rating. CRH PLC prediction model is evaluated with Reinforcement Machine Learning (ML) and Statistical Hypothesis Testing1,2,3,4 and it is concluded that the LON:97GM stock is predictable in the short/long term. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Speculative Trend
Prediction Confidence Score
References
- Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55
- D. Bertsekas. Nonlinear programming. Athena Scientific, 1999.
- Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
- White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
- uyer, S. Whiteson, B. Bakker, and N. A. Vlassis. Multiagent reinforcement learning for urban traffic control using coordination graphs. In Machine Learning and Knowledge Discovery in Databases, European Conference, ECML/PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I, pages 656–671, 2008.
- S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
- Knox SW. 2018. Machine Learning: A Concise Introduction. Hoboken, NJ: Wiley
Frequently Asked Questions
Q: What is the prediction methodology for LON:97GM stock?A: LON:97GM stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Statistical Hypothesis Testing
Q: Is LON:97GM stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend LON:97GM Stock.
Q: Is CRH PLC stock a good investment?
A: The consensus rating for CRH PLC is Speculative Trend and is assigned short-term B2 & long-term B2 estimated rating.
Q: What is the consensus rating of LON:97GM stock?
A: The consensus rating for LON:97GM is Speculative Trend.
Q: What is the prediction period for LON:97GM stock?
A: The prediction period for LON:97GM is 3 Month
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