TCBPW TC BioPharm (Holdings) plc Warrants (Forecast)

Outlook: TC BioPharm (Holdings) plc Warrants is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 19 Apr 2023 for (n+1 year)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

TC BioPharm (Holdings) plc Warrants prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Chi-Square^1,2,3,4 and it is concluded that the TCBPW stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

Key Points

1. What is a prediction confidence?
2. What are the most successful trading algorithms?
3. What are the most successful trading algorithms?

TCBPW Target Price Prediction Modeling Methodology

We consider TC BioPharm (Holdings) plc Warrants Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of TCBPW 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(Chi-Square)^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 Volatility Analysis)) X S(n):→ (n+1 year) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of TCBPW 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?

TCBPW Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: TCBPW TC BioPharm (Holdings) plc Warrants
Time series to forecast n: 19 Apr 2023 for (n+1 year)

According to price forecasts for (n+1 year) 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 TC BioPharm (Holdings) plc Warrants

1. A firm commitment to acquire a business in a business combination cannot be a hedged item, except for foreign currency risk, because the other risks being hedged cannot be specifically identified and measured. Those other risks are general business risks.
2. Hedge effectiveness is the extent to which changes in the fair value or the cash flows of the hedging instrument offset changes in the fair value or the cash flows of the hedged item (for example, when the hedged item is a risk component, the relevant change in fair value or cash flows of an item is the one that is attributable to the hedged risk). Hedge ineffectiveness is the extent to which the changes in the fair value or the cash flows of the hedging instrument are greater or less than those on the hedged item.
3. An entity shall apply Annual Improvements to IFRS Standards 2018–2020 to financial liabilities that are modified or exchanged on or after the beginning of the annual reporting period in which the entity first applies the amendment.
4. In almost every lending transaction the creditor's instrument is ranked relative to the instruments of the debtor's other creditors. An instrument that is subordinated to other instruments may have contractual cash flows that are payments of principal and interest on the principal amount outstanding if the debtor's non-payment is a breach of contract and the holder has a contractual right to unpaid amounts of principal and interest on the principal amount outstanding even in the event of the debtor's bankruptcy. For example, a trade receivable that ranks its creditor as a general creditor would qualify as having payments of principal and interest on the principal amount outstanding. This is the case even if the debtor issued loans that are collateralised, which in the event of bankruptcy would give that loan holder priority over the claims of the general creditor in respect of the collateral but does not affect the contractual right of the general creditor to unpaid principal and other amounts due.

*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

TC BioPharm (Holdings) plc Warrants is assigned short-term Ba1 & long-term Ba1 estimated rating. TC BioPharm (Holdings) plc Warrants prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Chi-Square^1,2,3,4 and it is concluded that the TCBPW stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

TCBPW TC BioPharm (Holdings) plc Warrants Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Baa2	C
Balance Sheet	B3	Baa2
Leverage Ratios	Baa2	Ba2
Cash Flow	Ba3	Baa2
Rates of Return and Profitability	Caa2	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: 89 out of 100 with 534 signals.

References

1. Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.
2. Matzkin RL. 2007. Nonparametric identification. In Handbook of Econometrics, Vol. 6B, ed. J Heckman, E Learner, pp. 5307–68. Amsterdam: Elsevier
3. 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.
4. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
5. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
6. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
7. J. G. Schneider, W. Wong, A. W. Moore, and M. A. Riedmiller. Distributed value functions. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 371–378, 1999.

Frequently Asked Questions

Q: What is the prediction methodology for TCBPW stock?
A: TCBPW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Chi-Square
Q: Is TCBPW stock a buy or sell?
A: The dominant strategy among neural network is to Buy TCBPW Stock.
Q: Is TC BioPharm (Holdings) plc Warrants stock a good investment?
A: The consensus rating for TC BioPharm (Holdings) plc Warrants is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of TCBPW stock?
A: The consensus rating for TCBPW is Buy.
Q: What is the prediction period for TCBPW stock?
A: The prediction period for TCBPW is (n+1 year)

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