FTS:TSX Fortis Inc.

Outlook: Fortis Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 12 Jan 2023 for (n+6 month)
Methodology : Transductive Learning (ML)

Abstract

Fortis Inc. prediction model is evaluated with Transductive Learning (ML) and Spearman Correlation^1,2,3,4 and it is concluded that the FTS:TSX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

1. Technical Analysis with Algorithmic Trading
2. What is the use of Markov decision process?
3. Can we predict stock market using machine learning?

FTS:TSX Target Price Prediction Modeling Methodology

We consider Fortis Inc. Decision Process with Transductive Learning (ML) where A is the set of discrete actions of FTS:TSX 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(Transductive Learning (ML)) X S(n):→ (n+6 month) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of FTS:TSX 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?

FTS:TSX Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: FTS:TSX Fortis Inc.
Time series to forecast n: 12 Jan 2023 for (n+6 month)

According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 Fortis Inc.

1. When measuring the fair values of the part that continues to be recognised and the part that is derecognised for the purposes of applying paragraph 3.2.13, an entity applies the fair value measurement requirements in IFRS 13 Fair Value Measurement in addition to paragraph 3.2.14.
2. An entity can rebut this presumption. However, it can do so only when it has reasonable and supportable information available that demonstrates that even if contractual payments become more than 30 days past due, this does not represent a significant increase in the credit risk of a financial instrument. For example when non-payment was an administrative oversight, instead of resulting from financial difficulty of the borrower, or the entity has access to historical evidence that demonstrates that there is no correlation between significant increases in the risk of a default occurring and financial assets on which payments are more than 30 days past due, but that evidence does identify such a correlation when payments are more than 60 days past due.
3. Paragraphs 6.9.7–6.9.13 provide exceptions to the requirements specified in those paragraphs only. An entity shall apply all other hedge accounting requirements in this Standard, including the qualifying criteria in paragraph 6.4.1, to hedging relationships that were directly affected by interest rate benchmark reform.
4. Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.

*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

Fortis Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating. Fortis Inc. prediction model is evaluated with Transductive Learning (ML) and Spearman Correlation^1,2,3,4 and it is concluded that the FTS:TSX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

FTS:TSX Fortis Inc. Financial Analysis*

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

*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: 72 out of 100 with 852 signals.

References

1. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
2. M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
3. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
4. Sutton RS, Barto AG. 1998. Reinforcement Learning: An Introduction. Cambridge, MA: MIT Press
5. J. Baxter and P. Bartlett. Infinite-horizon policy-gradient estimation. Journal of Artificial Intelligence Re- search, 15:319–350, 2001.
6. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
7. F. A. Oliehoek and C. Amato. A Concise Introduction to Decentralized POMDPs. SpringerBriefs in Intelligent Systems. Springer, 2016

Frequently Asked Questions

Q: What is the prediction methodology for FTS:TSX stock?
A: FTS:TSX stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Spearman Correlation
Q: Is FTS:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes FTS:TSX Stock.
Q: Is Fortis Inc. stock a good investment?
A: The consensus rating for Fortis Inc. is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of FTS:TSX stock?
A: The consensus rating for FTS:TSX is Wait until speculative trend diminishes.
Q: What is the prediction period for FTS:TSX stock?
A: The prediction period for FTS:TSX is (n+6 month)

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