LON:MSMN Stock: A Risky Investment, But One with a lot of Potential

Outlook: MOSMAN OIL AND GAS LIMITED is assigned short-term Ba3 & long-term Ba3 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 23 Jun 2023 for 16 Weeks
Methodology : Modular Neural Network (Market Volatility Analysis)

Summary

MOSMAN OIL AND GAS LIMITED prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Beta^1,2,3,4 and it is concluded that the LON:MSMN 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 volatility 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 volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

Key Points

1. How do you decide buy or sell a stock?
2. What is prediction model?
3. Which neural network is best for prediction?

LON:MSMN Target Price Prediction Modeling Methodology

We consider MOSMAN OIL AND GAS LIMITED Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of LON:MSMN 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(Beta)^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 Volatility Analysis)) X S(n):→ 16 Weeks $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of LON:MSMN stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Market Volatility Analysis)

Modular neural networks (MNNs) are a type of artificial neural network that can be used for market volatility 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 volatility analysis, MNNs can be used to identify patterns in market data that suggest that the market is becoming more or less volatile. This information can then be used to make predictions about future price movements.

Beta

In statistics, beta (β) is a measure of the strength of the relationship between two variables. It is calculated as the slope of the line of best fit in a regression analysis. Beta can range from -1 to 1, with a value of 0 indicating no relationship between the two variables. A positive beta indicates that as one variable increases, the other variable also increases. A negative beta indicates that as one variable increases, the other variable decreases. For example, a study might find that there is a positive relationship between height and weight. This means that taller people tend to weigh more. The beta coefficient for this relationship would be positive.

 

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:MSMN Stock Forecast (Buy or Sell) for 16 Weeks

Sample Set: Neural Network
Stock/Index: LON:MSMN MOSMAN OIL AND GAS LIMITED
Time series to forecast n: 23 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 MOSMAN OIL AND GAS LIMITED

1. For the purpose of determining whether a forecast transaction (or a component thereof) is highly probable as required by paragraph 6.3.3, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.
2. For example, an entity hedges an exposure to Foreign Currency A using a currency derivative that references Foreign Currency B and Foreign Currencies A and B are pegged (ie their exchange rate is maintained within a band or at an exchange rate set by a central bank or other authority). If the exchange rate between Foreign Currency A and Foreign Currency B were changed (ie a new band or rate was set), rebalancing the hedging relationship to reflect the new exchange rate would ensure that the hedging relationship would continue to meet the hedge effectiveness requirement for the hedge ratio in the new circumstances. In contrast, if there was a default on the currency derivative, changing the hedge ratio could not ensure that the hedging relationship would continue to meet that hedge effectiveness requirement. Hence, rebalancing does not facilitate the continuation of a hedging relationship in situations in which the relationship between the hedging instrument and the hedged item changes in a way that cannot be compensated for by adjusting the hedge ratio
3. In applying the effective interest method, an entity identifies fees that are an integral part of the effective interest rate of a financial instrument. The description of fees for financial services may not be indicative of the nature and substance of the services provided. Fees that are an integral part of the effective interest rate of a financial instrument are treated as an adjustment to the effective interest rate, unless the financial instrument is measured at fair value, with the change in fair value being recognised in profit or loss. In those cases, the fees are recognised as revenue or expense when the instrument is initially recognised.
4. For example, an entity hedges an exposure to Foreign Currency A using a currency derivative that references Foreign Currency B and Foreign Currencies A and B are pegged (ie their exchange rate is maintained within a band or at an exchange rate set by a central bank or other authority). If the exchange rate between Foreign Currency A and Foreign Currency B were changed (ie a new band or rate was set), rebalancing the hedging relationship to reflect the new exchange rate would ensure that the hedging relationship would continue to meet the hedge effectiveness requirement for the hedge ratio in the new circumstances. In contrast, if there was a default on the currency derivative, changing the hedge ratio could not ensure that the hedging relationship would continue to meet that hedge effectiveness requirement. Hence, rebalancing does not facilitate the continuation of a hedging relationship in situations in which the relationship between the hedging instrument and the hedged item changes in a way that cannot be compensated for by adjusting the hedge ratio

*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

MOSMAN OIL AND GAS LIMITED is assigned short-term Ba3 & long-term Ba3 estimated rating. MOSMAN OIL AND GAS LIMITED prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Beta^1,2,3,4 and it is concluded that the LON:MSMN stock is predictable in the short/long term. According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Hold

LON:MSMN MOSMAN OIL AND GAS LIMITED Financial Analysis*

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

*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: 85 out of 100 with 780 signals.

References

1. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
2. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
3. J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
4. D. Bertsekas. Nonlinear programming. Athena Scientific, 1999.
5. V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
6. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
7. E. van der Pol and F. A. Oliehoek. Coordinated deep reinforcement learners for traffic light control. NIPS Workshop on Learning, Inference and Control of Multi-Agent Systems, 2016.

Frequently Asked Questions

Q: What is the prediction methodology for LON:MSMN stock?
A: LON:MSMN stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Beta
Q: Is LON:MSMN stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:MSMN Stock.
Q: Is MOSMAN OIL AND GAS LIMITED stock a good investment?
A: The consensus rating for MOSMAN OIL AND GAS LIMITED is Hold and is assigned short-term Ba3 & long-term Ba3 estimated rating.
Q: What is the consensus rating of LON:MSMN stock?
A: The consensus rating for LON:MSMN is Hold.
Q: What is the prediction period for LON:MSMN stock?
A: The prediction period for LON:MSMN is 16 Weeks

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