LON:TXP TOUCHSTONE EXPLORATION INC

Outlook: TOUCHSTONE EXPLORATION INC is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 10 Feb 2023 for (n+3 month)
Methodology : Multi-Task Learning (ML)

Abstract

TOUCHSTONE EXPLORATION INC prediction model is evaluated with Multi-Task Learning (ML) and ElasticNet Regression^1,2,3,4 and it is concluded that the LON:TXP stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

Key Points

1. Game Theory
2. Can machine learning predict?
3. How can neural networks improve predictions?

LON:TXP Target Price Prediction Modeling Methodology

We consider TOUCHSTONE EXPLORATION INC Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of LON:TXP 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(ElasticNet 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(Multi-Task Learning (ML)) X S(n):→ (n+3 month) $\begin{array}{l}\int e^x\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of LON:TXP 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:TXP Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: LON:TXP TOUCHSTONE EXPLORATION INC
Time series to forecast n: 10 Feb 2023 for (n+3 month)

According to price forecasts for (n+3 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 (Grey to Black): *Technical Analysis%

IFRS Reconciliation Adjustments for TOUCHSTONE EXPLORATION INC

1. If a variable-rate financial liability bears interest of (for example) three-month LIBOR minus 20 basis points (with a floor at zero basis points), an entity can designate as the hedged item the change in the cash flows of that entire liability (ie three-month LIBOR minus 20 basis points—including the floor) that is attributable to changes in LIBOR. Hence, as long as the three-month LIBOR forward curve for the remaining life of that liability does not fall below 20 basis points, the hedged item has the same cash flow variability as a liability that bears interest at three-month LIBOR with a zero or positive spread. However, if the three-month LIBOR forward curve for the remaining life of that liability (or a part of it) falls below 20 basis points, the hedged item has a lower cash flow variability than a liability that bears interest at threemonth LIBOR with a zero or positive spread.
2. An entity may manage and evaluate the performance of a group of financial liabilities or financial assets and financial liabilities in such a way that measuring that group at fair value through profit or loss results in more relevant information. The focus in this instance is on the way the entity manages and evaluates performance, instead of on the nature of its financial instruments.
3. Adjusting the hedge ratio by increasing the volume of the hedging instrument does not affect how the changes in the value of the hedged item are measured. The measurement of the changes in the fair value of the hedging instrument related to the previously designated volume also remains unaffected. However, from the date of rebalancing, the changes in the fair value of the hedging instrument also include the changes in the value of the additional volume of the hedging instrument. The changes are measured starting from, and by reference to, the date of rebalancing instead of the date on which the hedging relationship was designated. For example, if an entity originally hedged the price risk of a commodity using a derivative volume of 100 tonnes as the hedging instrument and added a volume of 10 tonnes on rebalancing, the hedging instrument after rebalancing would comprise a total derivative volume of 110 tonnes. The change in the fair value of the hedging instrument is the total change in the fair value of the derivatives that make up the total volume of 110 tonnes. These derivatives could (and probably would) have different critical terms, such as their forward rates, because they were entered into at different points in time (including the possibility of designating derivatives into hedging relationships after their initial recognition).
4. For example, Entity A, whose functional currency is its local currency, has a firm commitment to pay FC150,000 for advertising expenses in nine months' time and a firm commitment to sell finished goods for FC150,000 in 15 months' time. Entity A enters into a foreign currency derivative that settles in nine months' time under which it receives FC100 and pays CU70. Entity A has no other exposures to FC. Entity A does not manage foreign currency risk on a net basis. Hence, Entity A cannot apply hedge accounting for a hedging relationship between the foreign currency derivative and a net position of FC100 (consisting of FC150,000 of the firm purchase commitment—ie advertising services—and FC149,900 (of the FC150,000) of the firm sale commitment) for a nine-month period.

*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

TOUCHSTONE EXPLORATION INC is assigned short-term Ba1 & long-term Ba1 estimated rating. TOUCHSTONE EXPLORATION INC prediction model is evaluated with Multi-Task Learning (ML) and ElasticNet Regression^1,2,3,4 and it is concluded that the LON:TXP stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Sell

LON:TXP TOUCHSTONE EXPLORATION INC Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Baa2	B2
Balance Sheet	C	Caa2
Leverage Ratios	B3	Baa2
Cash Flow	Caa2	Caa2
Rates of Return and Profitability	C	B3

*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: 90 out of 100 with 627 signals.

References

1. Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55
2. Hirano K, Porter JR. 2009. Asymptotics for statistical treatment rules. Econometrica 77:1683–701
3. Bessler, D. A. R. A. Babula, (1987), "Forecasting wheat exports: Do exchange rates matter?" Journal of Business and Economic Statistics, 5, 397–406.
4. 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.
5. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
6. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
7. V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001

Frequently Asked Questions

Q: What is the prediction methodology for LON:TXP stock?
A: LON:TXP stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and ElasticNet Regression
Q: Is LON:TXP stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:TXP Stock.
Q: Is TOUCHSTONE EXPLORATION INC stock a good investment?
A: The consensus rating for TOUCHSTONE EXPLORATION INC is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:TXP stock?
A: The consensus rating for LON:TXP is Sell.
Q: What is the prediction period for LON:TXP stock?
A: The prediction period for LON:TXP is (n+3 month)

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