TRP Stock Price Prediction

Outlook: TC Energy Corporation Common Stock is assigned short-term Baa2 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Hold
Time series to forecast n: for Weeks²
Methodology : Supervised Machine Learning (ML)
Hypothesis Testing : Multiple Regression
Surveillance : Major exchange and OTC

¹The accuracy of the model is being monitored on a regular basis.(15-minute period)

²Time series is updated based on short-term trends.

Summary

TC Energy Corporation Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Multiple Regression^1,2,3,4 and it is concluded that the TRP stock is predictable in the short/long term. Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product.⁵ According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Hold

Key Points

1. Supervised Machine Learning (ML) for TRP stock price prediction process.
2. Multiple Regression
3. Operational Risk
4. Market Outlook
5. How do you know when a stock will go up or down?

TRP Stock Price Forecast

We consider TC Energy Corporation Common Stock Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of TRP 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

Sample Set: Neural Network
Stock/Index: TRP TC Energy Corporation Common Stock
Time series to forecast: 4 Weeks

According to price forecasts, the dominant strategy among neural network is: Hold

F(Multiple Regression)^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):→ 4 Weeks $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of TRP stock

j:Nash equilibria (Neural Network)

k:Dominated move of TRP stock holders

a:Best response for TRP target price

Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product.⁵ Multiple regression is a statistical method that analyzes the relationship between a dependent variable and multiple independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Multiple regression is a more complex statistical method than simple linear regression, which only analyzes the relationship between a dependent variable and one independent variable. Multiple regression can be used to analyze more complex relationships between variables, and it can also be used to control for confounding variables. A confounding variable is a variable that is correlated with both the dependent variable and one or more of the independent variables. Confounding variables can distort the relationship between the dependent variable and the independent variables. Multiple regression can be used to control for confounding variables by including them in the model.^6,7

 

For further technical information as per how our model work we invite you to visit the article below: 

How do Predictive A.I. algorithms actually work?

TRP Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Supervised Machine Learning (ML) based TRP Stock Prediction Model

1. If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess a modified time value of money element in accordance with paragraphs B4.1.9B–B4.1.9D 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 requirements related to the modification of the time value of money element in paragraphs B4.1.9B–B4.1.9D. (See also paragraph 42R of IFRS 7.)
2. A hedge of a firm commitment (for example, a hedge of the change in fuel price relating to an unrecognised contractual commitment by an electric utility to purchase fuel at a fixed price) is a hedge of an exposure to a change in fair value. Accordingly, such a hedge is a fair value hedge. However, in accordance with paragraph 6.5.4, a hedge of the foreign currency risk of a firm commitment could alternatively be accounted for as a cash flow hedge.
3. In some circumstances, the renegotiation or modification of the contractual cash flows of a financial asset can lead to the derecognition of the existing financial asset in accordance with this Standard. When the modification of a financial asset results in the derecognition of the existing financial asset and the subsequent recognition of the modified financial asset, the modified asset is considered a 'new' financial asset for the purposes of this Standard.
4. A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.

*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.

TRP TC Energy Corporation Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Baa2	B1
Income Statement	B2	B3
Balance Sheet	Ba1	Baa2
Leverage Ratios	Baa2	Ba1
Cash Flow	Baa2	Caa2
Rates of Return and Profitability	Baa2	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?

References

1. Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
2. Efron B, Hastie T. 2016. Computer Age Statistical Inference, Vol. 5. Cambridge, UK: Cambridge Univ. Press
3. Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
4. Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
5. C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999
6. Clements, M. P. D. F. Hendry (1995), "Forecasting in cointegrated systems," Journal of Applied Econometrics, 10, 127–146.
7. Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.

Frequently Asked Questions

Q: Is TRP stock expected to rise?
A: TRP stock prediction model is evaluated with Supervised Machine Learning (ML) and Multiple Regression and it is concluded that dominant strategy for TRP stock is Hold
Q: Is TRP stock a buy or sell?
A: The dominant strategy among neural network is to Hold TRP Stock.
Q: Is TC Energy Corporation Common Stock stock a good investment?
A: The consensus rating for TC Energy Corporation Common Stock is Hold and is assigned short-term Baa2 & long-term B1 estimated rating.
Q: What is the consensus rating of TRP stock?
A: The consensus rating for TRP is Hold.
Q: What is the forecast for TRP stock?
A: TRP target price forecast: Hold