Outlook: Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities is assigned short-term Ba1 & long-term Ba1 estimated rating.
Time series to forecast n: 14 Jan 2023 for (n+8 weeks)
Methodology : Modular Neural Network (Market Direction Analysis)

## Abstract

Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the SCE^J stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy

## Key Points

1. Can neural networks predict stock market?
2. Understanding Buy, Sell, and Hold Ratings
3. What is a prediction confidence?

## SCE^J Target Price Prediction Modeling Methodology

We consider Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of SCE^J 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(Pearson Correlation)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+8 weeks) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of SCE^J 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?

## SCE^J Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: SCE^J Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities
Time series to forecast n: 14 Jan 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) 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 Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities

1. 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.
2. The assessment of whether lifetime expected credit losses should be recognised is based on significant increases in the likelihood or risk of a default occurring since initial recognition (irrespective of whether a financial instrument has been repriced to reflect an increase in credit risk) instead of on evidence of a financial asset being credit-impaired at the reporting date or an actual default occurring. Generally, there will be a significant increase in credit risk before a financial asset becomes credit-impaired or an actual default occurs.
3. If an entity previously accounted for a derivative liability that is linked to, and must be settled by, delivery of an equity instrument that does not have a quoted price in an active market for an identical instrument (ie a Level 1 input) at cost in accordance with IAS 39, it shall measure that derivative liability at fair value at the date of initial application. Any difference between the previous carrying amount and the fair value shall be recognised in the opening retained earnings of the reporting period that includes the date of initial application.
4. For hedges other than hedges of foreign currency risk, when an entity designates a non-derivative financial asset or a non-derivative financial liability measured at fair value through profit or loss as a hedging instrument, it may only designate the non-derivative financial instrument in its entirety or a proportion of it.

*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

Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities is assigned short-term Ba1 & long-term Ba1 estimated rating. Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Pearson Correlation1,2,3,4 and it is concluded that the SCE^J stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy

### SCE^J Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2Caa2
Balance SheetBaa2Baa2
Leverage RatiosBa1Caa2
Cash FlowCaa2C
Rates of Return and ProfitabilityCaa2Ba3

*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: 78 out of 100 with 574 signals.

## References

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3. J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017
4. D. Bertsekas. Dynamic programming and optimal control. Athena Scientific, 1995.
5. Clements, M. P. D. F. Hendry (1997), "An empirical study of seasonal unit roots in forecasting," International Journal of Forecasting, 13, 341–355.
6. V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
7. Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
Frequently Asked QuestionsQ: What is the prediction methodology for SCE^J stock?
A: SCE^J stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Pearson Correlation
Q: Is SCE^J stock a buy or sell?
A: The dominant strategy among neural network is to Buy SCE^J Stock.
Q: Is Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities stock a good investment?
A: The consensus rating for Southern California Edison Company 5.375% Fixed-to-Floating Rate Trust Preference Securities is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of SCE^J stock?
A: The consensus rating for SCE^J is Buy.
Q: What is the prediction period for SCE^J stock?
A: The prediction period for SCE^J is (n+8 weeks)