LON:TEP TELECOM PLUS PLC

Outlook: TELECOM PLUS PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 16 Feb 2023 for (n+4 weeks)
Methodology : Supervised Machine Learning (ML)

Abstract

TELECOM PLUS PLC prediction model is evaluated with Supervised Machine Learning (ML) and Ridge Regression^1,2,3,4 and it is concluded that the LON:TEP stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Buy

Key Points

1. Can neural networks predict stock market?
2. How do predictive algorithms actually work?
3. Is now good time to invest?

LON:TEP Target Price Prediction Modeling Methodology

We consider TELECOM PLUS PLC Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of LON:TEP 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(Ridge 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(Supervised Machine Learning (ML)) X S(n):→ (n+4 weeks) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of LON:TEP 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:TEP Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: LON:TEP TELECOM PLUS PLC
Time series to forecast n: 16 Feb 2023 for (n+4 weeks)

According to price forecasts for (n+4 weeks) 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 TELECOM PLUS PLC

1. The accounting for the time value of options in accordance with paragraph 6.5.15 applies only to the extent that the time value relates to the hedged item (aligned time value). The time value of an option relates to the hedged item if the critical terms of the option (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the option and the hedged item are not fully aligned, an entity shall determine the aligned time value, ie how much of the time value included in the premium (actual time value) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.15). An entity determines the aligned time value using the valuation of the option that would have critical terms that perfectly match the hedged item.
2. The following are examples of when the objective of the entity's business model may be achieved by both collecting contractual cash flows and selling financial assets. This list of examples is not exhaustive. Furthermore, the examples are not intended to describe all the factors that may be relevant to the assessment of the entity's business model nor specify the relative importance of the factors.
3. 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.
4. When designating a group of items as the hedged item, or a combination of financial instruments as the hedging instrument, an entity shall prospectively cease applying paragraphs 6.8.4–6.8.6 to an individual item or financial instrument in accordance with paragraphs 6.8.9, 6.8.10, or 6.8.11, as relevant, when the uncertainty arising from interest rate benchmark reform is no longer present with respect to the hedged risk and/or the timing and the amount of the interest rate benchmark-based cash flows of that item or financial instrument.

*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

TELECOM PLUS PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. TELECOM PLUS PLC prediction model is evaluated with Supervised Machine Learning (ML) and Ridge Regression^1,2,3,4 and it is concluded that the LON:TEP stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period, the dominant strategy among neural network is: Buy

LON:TEP TELECOM PLUS PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B2	Baa2
Balance Sheet	B3	Baa2
Leverage Ratios	B3	Baa2
Cash Flow	Caa2	Baa2
Rates of Return and Profitability	B1	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: 73 out of 100 with 801 signals.

References

1. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
2. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
3. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
4. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
5. Burgess, D. F. (1975), "Duality theory and pitfalls in the specification of technologies," Journal of Econometrics, 3, 105–121.
6. R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000
7. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.

Frequently Asked Questions

Q: What is the prediction methodology for LON:TEP stock?
A: LON:TEP stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Ridge Regression
Q: Is LON:TEP stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:TEP Stock.
Q: Is TELECOM PLUS PLC stock a good investment?
A: The consensus rating for TELECOM PLUS PLC is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:TEP stock?
A: The consensus rating for LON:TEP is Buy.
Q: What is the prediction period for LON:TEP stock?
A: The prediction period for LON:TEP is (n+4 weeks)

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