**Outlook:**Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Hold

**Time series to forecast n: 04 Mar 2023**for (n+8 weeks)

**Methodology :**Modular Neural Network (Market Direction Analysis)

## Abstract

Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Beta^{1,2,3,4}and it is concluded that the EMP stock is predictable in the short/long term.

## Key Points

- How do you know when a stock will go up or down?
- Probability Distribution
- Operational Risk

## EMP Target Price Prediction Modeling Methodology

We consider Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of EMP 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(Beta)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ 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 EMP 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?

## EMP Stock Forecast (Buy or Sell) for (n+8 weeks)

**Sample Set:**Neural Network

**Stock/Index:**EMP Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066

**Time series to forecast n: 04 Mar 2023**for (n+8 weeks)

**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 Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066

- In some cases, the qualitative and non-statistical quantitative information available may be sufficient to determine that a financial instrument has met the criterion for the recognition of a loss allowance at an amount equal to lifetime expected credit losses. That is, the information does not need to flow through a statistical model or credit ratings process in order to determine whether there has been a significant increase in the credit risk of the financial instrument. In other cases, an entity may need to consider other information, including information from its statistical models or credit ratings processes.
- If an entity originates a loan that bears an off-market interest rate (eg 5 per cent when the market rate for similar loans is 8 per cent), and receives an upfront fee as compensation, the entity recognises the loan at its fair value, ie net of the fee it receives.
- It would not be acceptable to designate only some of the financial assets and financial liabilities giving rise to the inconsistency as at fair value through profit or loss if to do so would not eliminate or significantly reduce the inconsistency and would therefore not result in more relevant information. However, it would be acceptable to designate only some of a number of similar financial assets or similar financial liabilities if doing so achieves a significant reduction (and possibly a greater reduction than other allowable designations) in the inconsistency. For example, assume an entity has a number of similar financial liabilities that sum to CU100 and a number of similar financial assets that sum to CU50 but are measured on a different basis. The entity may significantly reduce the measurement inconsistency by designating at initial recognition all of the assets but only some of the liabilities (for example, individual liabilities with a combined total of CU45) as at fair value through profit or loss. However, because designation as at fair value through profit or loss can be applied only to the whole of a financial instrument, the entity in this example must designate one or more liabilities in their entirety. It could not designate either a component of a liability (eg changes in value attributable to only one risk, such as changes in a benchmark interest rate) or a proportion (ie percentage) of a liability.
- 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.

*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

Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 is assigned short-term Ba1 & long-term Ba1 estimated rating. Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Beta^{1,2,3,4} and it is concluded that the EMP stock is predictable in the short/long term.

### EMP Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Ba1 | Ba1 |

Income Statement | Caa2 | Baa2 |

Balance Sheet | B1 | B3 |

Leverage Ratios | B3 | Ba3 |

Cash Flow | Ba2 | Baa2 |

Rates of Return and Profitability | Caa2 | 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?

### Prediction Confidence Score

## References

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- Matzkin RL. 1994. Restrictions of economic theory in nonparametric methods. In Handbook of Econometrics, Vol. 4, ed. R Engle, D McFadden, pp. 2523–58. Amsterdam: Elsevier
- E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
- Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
- Athey S, Imbens G. 2016. Recursive partitioning for heterogeneous causal effects. PNAS 113:7353–60
- 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

## Frequently Asked Questions

Q: What is the prediction methodology for EMP stock?A: EMP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Beta

Q: Is EMP stock a buy or sell?

A: The dominant strategy among neural network is to Hold EMP Stock.

Q: Is Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 stock a good investment?

A: The consensus rating for Entergy Mississippi LLC First Mortgage Bonds 4.90% Series Due October 1 2066 is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of EMP stock?

A: The consensus rating for EMP is Hold.

Q: What is the prediction period for EMP stock?

A: The prediction period for EMP is (n+8 weeks)