Should You Buy Now or Wait? LON:MORE Stock Forecast

Outlook: HOSTMORE PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 09 Jun 2023 for 1 Year
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

HOSTMORE PLC prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the LON:MORE stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for market direction analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

Key Points

1. Short/Long Term Stocks
2. Trading Signals
3. Operational Risk

LON:MORE Target Price Prediction Modeling Methodology

We consider HOSTMORE PLC Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of LON:MORE 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(Wilcoxon Sign-Rank Test)^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 (Market Direction Analysis)) X S(n):→ 1 Year $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of LON:MORE stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular neural networks (MNNs) are a type of artificial neural network that can be used for market direction analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements.

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that 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:MORE Stock Forecast (Buy or Sell) for 1 Year

Sample Set: Neural Network
Stock/Index: LON:MORE HOSTMORE PLC
Time series to forecast n: 09 Jun 2023 for 1 Year

According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

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 HOSTMORE PLC

1. A firm commitment to acquire a business in a business combination cannot be a hedged item, except for foreign currency risk, because the other risks being hedged cannot be specifically identified and measured. Those other risks are general business risks.
2. 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.
3. Although the objective of an entity's business model may be to hold financial assets in order to collect contractual cash flows, the entity need not hold all of those instruments until maturity. Thus an entity's business model can be to hold financial assets to collect contractual cash flows even when sales of financial assets occur or are expected to occur in the future.
4. For the purpose of applying paragraphs B4.1.11(b) and B4.1.12(b), irrespective of the event or circumstance that causes the early termination of the contract, a party may pay or receive reasonable compensation for that early termination. For example, a party may pay or receive reasonable compensation when it chooses to terminate the contract early (or otherwise causes the early termination to occur).

*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

HOSTMORE PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. HOSTMORE PLC prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the LON:MORE stock is predictable in the short/long term. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

LON:MORE HOSTMORE PLC Financial Analysis*

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

Prediction Confidence Score

Trust metric by Neural Network: 90 out of 100 with 620 signals.

References

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2. L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
3. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
4. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
5. M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994
6. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
7. Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]

Frequently Asked Questions

Q: What is the prediction methodology for LON:MORE stock?
A: LON:MORE stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Wilcoxon Sign-Rank Test
Q: Is LON:MORE stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:MORE Stock.
Q: Is HOSTMORE PLC stock a good investment?
A: The consensus rating for HOSTMORE PLC is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:MORE stock?
A: The consensus rating for LON:MORE is Buy.
Q: What is the prediction period for LON:MORE stock?
A: The prediction period for LON:MORE is 1 Year