LON:TED TED BAKER PLC

Outlook: TED BAKER PLC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 26 Mar 2023 for (n+6 month)
Methodology : Supervised Machine Learning (ML)

Abstract

TED BAKER PLC prediction model is evaluated with Supervised Machine Learning (ML) and Spearman Correlation^1,2,3,4 and it is concluded that the LON:TED stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

Key Points

1. Prediction Modeling
2. What is prediction model?
3. Can stock prices be predicted?

LON:TED Target Price Prediction Modeling Methodology

We consider TED BAKER PLC Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of LON:TED 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(Spearman 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(Supervised Machine Learning (ML)) X S(n):→ (n+6 month) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

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

Sample Set: Neural Network
Stock/Index: LON:TED TED BAKER PLC
Time series to forecast n: 26 Mar 2023 for (n+6 month)

According to price forecasts for (n+6 month) 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 TED BAKER PLC

1. Although the objective of an entity's business model may be to hold financial assets in order to collect contractual cash flows, the entity need not hold all of those instruments until maturity. Thus an entity's business model can be to hold financial assets to collect contractual cash flows even when sales of financial assets occur or are expected to occur in the future.
2. 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.
3. The characteristics of the hedged item, including how and when the hedged item affects profit or loss, also affect the period over which the forward element of a forward contract that hedges a time-period related hedged item is amortised, which is over the period to which the forward element relates. For example, if a forward contract hedges the exposure to variability in threemonth interest rates for a three-month period that starts in six months' time, the forward element is amortised during the period that spans months seven to nine.
4. For the purposes of applying the requirement in paragraph 5.7.7(a), credit risk is different from asset-specific performance risk. Asset-specific performance risk is not related to the risk that an entity will fail to discharge a particular obligation but instead it is related to the risk that a single asset or a group of assets will perform poorly (or not at all).

*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

TED BAKER PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. TED BAKER PLC prediction model is evaluated with Supervised Machine Learning (ML) and Spearman Correlation^1,2,3,4 and it is concluded that the LON:TED stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy

LON:TED TED BAKER PLC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Ba2	C
Balance Sheet	C	B3
Leverage Ratios	C	Ba1
Cash Flow	Baa2	Ba2
Rates of Return and Profitability	Caa2	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: 88 out of 100 with 660 signals.

References

1. Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press
2. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
3. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
4. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
5. Pennington J, Socher R, Manning CD. 2014. GloVe: global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods on Natural Language Processing, pp. 1532–43. New York: Assoc. Comput. Linguist.
6. Ruiz FJ, Athey S, Blei DM. 2017. SHOPPER: a probabilistic model of consumer choice with substitutes and complements. arXiv:1711.03560 [stat.ML]
7. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier

Frequently Asked Questions

Q: What is the prediction methodology for LON:TED stock?
A: LON:TED stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Spearman Correlation
Q: Is LON:TED stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:TED Stock.
Q: Is TED BAKER PLC stock a good investment?
A: The consensus rating for TED BAKER PLC is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:TED stock?
A: The consensus rating for LON:TED is Buy.
Q: What is the prediction period for LON:TED stock?
A: The prediction period for LON:TED is (n+6 month)

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