Can stock prices be predicted? (LON:SRE Stock Forecast) (Forecast)

SIRIUS REAL ESTATE LD Research Report

Summary

The research reported in the paper focuses on the stock market prediction problem, the main aim being the development of a methodology to forecast the stock closing price. The methodology is based on some novel variable selection methods and an analysis of neural network and support vector machines based prediction models. Also, a hybrid approach which combines the use of the variables derived from technical and fundamental analysis of stock market indicators in order to improve prediction results of the proposed approaches is reported in this paper. We evaluate SIRIUS REAL ESTATE LD prediction models with Modular Neural Network (News Feed Sentiment Analysis) and Wilcoxon Rank-Sum Test^1,2,3,4 and conclude that the LON:SRE stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to SellWait until speculative trend diminishes LON:SRE stock.

Key Points

1. Market Outlook
2. Probability Distribution
3. Prediction Modeling

LON:SRE Target Price Prediction Modeling Methodology

We consider SIRIUS REAL ESTATE LD Stock Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of LON:SRE 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 Rank-Sum 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 (News Feed Sentiment Analysis)) X S(n):→ (n+8 weeks) $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of LON:SRE 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:SRE Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: LON:SRE SIRIUS REAL ESTATE LD
Time series to forecast n: 19 Nov 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to SellWait until speculative trend diminishes LON:SRE stock.

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 SIRIUS REAL ESTATE LD

1. If an entity has applied paragraph 7.2.6 then at the date of initial application the entity shall recognise any difference between the fair value of the entire hybrid contract at the date of initial application and the sum of the fair values of the components of the hybrid contract at the date of initial application in the opening retained earnings (or other component of equity, as appropriate) of the reporting period that includes the date of initial application.
2. For the avoidance of doubt, the effects of replacing the original counterparty with a clearing counterparty and making the associated changes as described in paragraph 6.5.6 shall be reflected in the measurement of the hedging instrument and therefore in the assessment of hedge effectiveness and the measurement of hedge effectiveness
3. If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess whether the fair value of a prepayment feature was insignificant in accordance with paragraph B4.1.12(c) on the basis of the facts and circumstances that existed at the initial recognition of the financial asset, an entity shall assess the contractual cash flow characteristics of that financial asset on the basis of the facts and circumstances that existed at the initial recognition of the financial asset without taking into account the exception for prepayment features in paragraph B4.1.12. (See also paragraph 42S of IFRS 7.)
4. If items are hedged together as a group in a cash flow hedge, they might affect different line items in the statement of profit or loss and other comprehensive income. The presentation of hedging gains or losses in that statement depends on the group of items

*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

SIRIUS REAL ESTATE LD assigned short-term Ba3 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with Wilcoxon Rank-Sum Test^1,2,3,4 and conclude that the LON:SRE stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to SellWait until speculative trend diminishes LON:SRE stock.

Financial State Forecast for LON:SRE SIRIUS REAL ESTATE LD Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B1
Operational Risk	75	40
Market Risk	63	43
Technical Analysis	79	65
Fundamental Analysis	51	76
Risk Unsystematic	58	57

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 732 signals.

References

1. E. Altman. Constrained Markov decision processes, volume 7. CRC Press, 1999
2. Hartigan JA, Wong MA. 1979. Algorithm as 136: a k-means clustering algorithm. J. R. Stat. Soc. Ser. C 28:100–8
3. 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]
4. M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.
5. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
6. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
7. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]

Frequently Asked Questions

Q: What is the prediction methodology for LON:SRE stock?
A: LON:SRE stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Wilcoxon Rank-Sum Test
Q: Is LON:SRE stock a buy or sell?
A: The dominant strategy among neural network is to SellWait until speculative trend diminishes LON:SRE Stock.
Q: Is SIRIUS REAL ESTATE LD stock a good investment?
A: The consensus rating for SIRIUS REAL ESTATE LD is SellWait until speculative trend diminishes and assigned short-term Ba3 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:SRE stock?
A: The consensus rating for LON:SRE is SellWait until speculative trend diminishes.
Q: What is the prediction period for LON:SRE stock?
A: The prediction period for LON:SRE is (n+8 weeks)

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