LON:MTVW MOUNTVIEW ESTATES PLC

Outlook: MOUNTVIEW ESTATES PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 30 Jan 2023 for (n+6 month)
Methodology : Modular Neural Network (Market Direction Analysis)

Abstract

MOUNTVIEW ESTATES PLC prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Polynomial Regression^1,2,3,4 and it is concluded that the LON:MTVW stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

1. Trading Signals
2. Is it better to buy and sell or hold?
3. Decision Making

LON:MTVW Target Price Prediction Modeling Methodology

We consider MOUNTVIEW ESTATES PLC Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of LON:MTVW 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(Polynomial Regression)^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):→ (n+6 month) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of LON:MTVW stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

 

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:MTVW Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:MTVW MOUNTVIEW ESTATES PLC
Time series to forecast n: 30 Jan 2023 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 MOUNTVIEW ESTATES PLC

1. An entity may manage and evaluate the performance of a group of financial liabilities or financial assets and financial liabilities in such a way that measuring that group at fair value through profit or loss results in more relevant information. The focus in this instance is on the way the entity manages and evaluates performance, instead of on the nature of its financial instruments.
2. 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.
3. 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).
4. An entity is not required to incorporate forecasts of future conditions over the entire expected life of a financial instrument. The degree of judgement that is required to estimate expected credit losses depends on the availability of detailed information. As the forecast horizon increases, the availability of detailed information decreases and the degree of judgement required to estimate expected credit losses increases. The estimate of expected credit losses does not require a detailed estimate for periods that are far in the future—for such periods, an entity may extrapolate projections from available, detailed information.

*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

MOUNTVIEW ESTATES PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. MOUNTVIEW ESTATES PLC prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Polynomial Regression^1,2,3,4 and it is concluded that the LON:MTVW stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

LON:MTVW MOUNTVIEW ESTATES PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Ba1	B1
Balance Sheet	Baa2	Baa2
Leverage Ratios	Caa2	B1
Cash Flow	B2	B3
Rates of Return and Profitability	Ba2	Ba2

*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: 83 out of 100 with 489 signals.

References

1. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
2. Hartigan JA, Wong MA. 1979. Algorithm as 136: a k-means clustering algorithm. J. R. Stat. Soc. Ser. C 28:100–8
3. E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999
4. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
5. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
6. Burgess, D. F. (1975), "Duality theory and pitfalls in the specification of technologies," Journal of Econometrics, 3, 105–121.
7. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.

Frequently Asked Questions

Q: What is the prediction methodology for LON:MTVW stock?
A: LON:MTVW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Polynomial Regression
Q: Is LON:MTVW stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes LON:MTVW Stock.
Q: Is MOUNTVIEW ESTATES PLC stock a good investment?
A: The consensus rating for MOUNTVIEW ESTATES PLC is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:MTVW stock?
A: The consensus rating for LON:MTVW is Wait until speculative trend diminishes.
Q: What is the prediction period for LON:MTVW stock?
A: The prediction period for LON:MTVW is (n+6 month)

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