LON:LMP LONDONMETRIC PROPERTY PLC

Outlook: LONDONMETRIC PROPERTY PLC assigned short-term B1 & long-term B1 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 09 Dec 2022 for (n+6 month)
Methodology : Modular Neural Network (Market News Sentiment Analysis)

Abstract

Stock market prediction is a crucial and challenging task due to its nonlinear, evolutionary, complex, and dynamic nature. Research on the stock market has been an important issue for researchers in recent years. Companies invest in trading the stock market. Predicting the stock market trend accurately will minimize the risk and bring a maximum amount of profit for all the stakeholders. During the last several years, a lot of studies have been done to predict stock market trends using Traditional, Machine learning and deep learning techniques. (Singh, R. and Srivastava, S., 2017. Stock prediction using deep learning. Multimedia Tools and Applications, 76(18), pp.18569-18584.) We evaluate LONDONMETRIC PROPERTY PLC prediction models with Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation^1,2,3,4 and conclude that the LON:LMP stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

Key Points

1. How do predictive algorithms actually work?
2. Market Signals
3. Decision Making

LON:LMP Target Price Prediction Modeling Methodology

We consider LONDONMETRIC PROPERTY PLC Decision Process with Modular Neural Network (Market News Sentiment Analysis) where A is the set of discrete actions of LON:LMP 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(Pearson Correlation)^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 News Sentiment Analysis)) X S(n):→ (n+6 month) $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of LON:LMP 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:LMP Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:LMP LONDONMETRIC PROPERTY PLC
Time series to forecast n: 09 Dec 2022 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for LONDONMETRIC PROPERTY PLC

1. For the purpose of recognising foreign exchange gains and losses under IAS 21, a financial asset measured at fair value through other comprehensive income in accordance with paragraph 4.1.2A is treated as a monetary item. Accordingly, such a financial asset is treated as an asset measured at amortised cost in the foreign currency. Exchange differences on the amortised cost are recognised in profit or loss and other changes in the carrying amount are recognised in accordance with paragraph 5.7.10.
2. Unless paragraph 6.8.8 applies, for a hedge of a non-contractually specified benchmark component of interest rate risk, an entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component shall be separately identifiable—only at the inception of the hedging relationship.
3. Despite the requirement in paragraph 7.2.1, an entity that adopts the classification and measurement requirements of this Standard (which include the requirements related to amortised cost measurement for financial assets and impairment in Sections 5.4 and 5.5) shall provide the disclosures set out in paragraphs 42L–42O of IFRS 7 but need not restate prior periods. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application. However, if an entity restates prior periods, the restated financial statements must reflect all of the requirements in this Standard. If an entity's chosen approach to applying IFRS 9 results in more than one date of initial application for different requirements, this paragraph applies at each date of initial application (see paragraph 7.2.2). This would be the case, for example, if an entity elects to early apply only the requirements for the presentation of gains and losses on financial liabilities designated as at fair value through profit or loss in accordance with paragraph 7.1.2 before applying the other requirements in this Standard.
4. When determining whether the recognition of lifetime expected credit losses is required, an entity shall consider reasonable and supportable information that is available without undue cost or effort and that may affect the credit risk on a financial instrument in accordance with paragraph 5.5.17(c). An entity need not undertake an exhaustive search for information when determining whether credit risk has increased significantly since initial recognition.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

LONDONMETRIC PROPERTY PLC assigned short-term B1 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) with Pearson Correlation^1,2,3,4 and conclude that the LON:LMP stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Sell

Financial State Forecast for LON:LMP LONDONMETRIC PROPERTY PLC Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B1	B1
Operational Risk	33	82
Market Risk	78	48
Technical Analysis	40	69
Fundamental Analysis	64	47
Risk Unsystematic	82	41

Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 839 signals.

References

1. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
2. Athey S, Imbens G, Wager S. 2016a. Efficient inference of average treatment effects in high dimensions via approximate residual balancing. arXiv:1604.07125 [math.ST]
3. S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014
4. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
5. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
6. Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]
7. Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2016a. Double machine learning for treatment and causal parameters. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London

Frequently Asked Questions

Q: What is the prediction methodology for LON:LMP stock?
A: LON:LMP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market News Sentiment Analysis) and Pearson Correlation
Q: Is LON:LMP stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:LMP Stock.
Q: Is LONDONMETRIC PROPERTY PLC stock a good investment?
A: The consensus rating for LONDONMETRIC PROPERTY PLC is Sell and assigned short-term B1 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:LMP stock?
A: The consensus rating for LON:LMP is Sell.
Q: What is the prediction period for LON:LMP stock?
A: The prediction period for LON:LMP is (n+6 month)

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