**Outlook:**Glenfarne Merger Corp. Warrant assigned short-term Ba3 & long-term Ba2 forecasted stock rating.

**Dominant Strategy :**Sell

**Time series to forecast n: 17 Dec 2022**for (n+8 weeks)

**Methodology :**Modular Neural Network (Social Media Sentiment Analysis)

## Abstract

Stock prediction is a very hot topic in our life. However, in the early time, because of some reasons and the limitation of the device, only a few people had the access to the study. Thanks to the rapid development of science and technology, in recent years more and more people are devoted to the study of the prediction and it becomes easier and easier for us to make stock prediction by using different ways now, including machine learning, deep learning and so on. (Zhang, J., Li, L. and Chen, W., 2021. Predicting stock price using two-stage machine learning techniques. Computational Economics, 57(4), pp.1237-1261.)** We evaluate Glenfarne Merger Corp. Warrant prediction models with Modular Neural Network (Social Media Sentiment Analysis) and Chi-Square ^{1,2,3,4} and conclude that the GGMCW stock is predictable in the short/long term. **

**According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell**

## Key Points

- Can neural networks predict stock market?
- What is the best way to predict stock prices?
- What is prediction in deep learning?

## GGMCW Target Price Prediction Modeling Methodology

We consider Glenfarne Merger Corp. Warrant Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of GGMCW 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(Chi-Square)

^{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 (Social Media Sentiment Analysis)) X S(n):→ (n+8 weeks) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of GGMCW 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?

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

**Sample Set:**Neural Network

**Stock/Index:**GGMCW Glenfarne Merger Corp. Warrant

**Time series to forecast n: 17 Dec 2022**for (n+8 weeks)

**According to price forecasts for (n+8 weeks) 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%**

## Adjusted IFRS* Prediction Methods for Glenfarne Merger Corp. Warrant

- Lifetime expected credit losses are generally expected to be recognised before a financial instrument becomes past due. Typically, credit risk increases significantly before a financial instrument becomes past due or other lagging borrower-specific factors (for example, a modification or restructuring) are observed. Consequently when reasonable and supportable information that is more forward-looking than past due information is available without undue cost or effort, it must be used to assess changes in credit risk.
- When a group of items that constitute a net position is designated as a hedged item, an entity shall designate the overall group of items that includes the items that can make up the net position. An entity is not permitted to designate a non-specific abstract amount of a net position. For example, an entity has a group of firm sale commitments in nine months' time for FC100 and a group of firm purchase commitments in 18 months' time for FC120. The entity cannot designate an abstract amount of a net position up to FC20. Instead, it must designate a gross amount of purchases and a gross amount of sales that together give rise to the hedged net position. An entity shall designate gross positions that give rise to the net position so that the entity is able to comply with the requirements for the accounting for qualifying hedging relationships.
- 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.
- Contractual cash flows that are solely payments of principal and interest on the principal amount outstanding are consistent with a basic lending arrangement. In a basic lending arrangement, consideration for the time value of money (see paragraphs B4.1.9A–B4.1.9E) and credit risk are typically the most significant elements of interest. However, in such an arrangement, interest can also include consideration for other basic lending risks (for example, liquidity risk) and costs (for example, administrative costs) associated with holding the financial asset for a particular period of time. In addition, interest can include a profit margin that is consistent with a basic lending arrangement. In extreme economic circumstances, interest can be negative if, for example, the holder of a financial asset either explicitly or implicitly pays for the deposit of its money for a particular period of time (and that fee exceeds the consideration that the holder receives for the time value of money, credit risk and other basic lending risks and costs).

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

## Conclusions

Glenfarne Merger Corp. Warrant assigned short-term Ba3 & long-term Ba2 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) with Chi-Square ^{1,2,3,4} and conclude that the GGMCW stock is predictable in the short/long term.**

**According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell**

### Financial State Forecast for GGMCW Glenfarne Merger Corp. Warrant Options & Futures

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

Outlook* | Ba3 | Ba2 |

Operational Risk | 49 | 64 |

Market Risk | 37 | 86 |

Technical Analysis | 82 | 41 |

Fundamental Analysis | 67 | 87 |

Risk Unsystematic | 83 | 63 |

### Prediction Confidence Score

## References

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## Frequently Asked Questions

Q: What is the prediction methodology for GGMCW stock?A: GGMCW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Chi-Square

Q: Is GGMCW stock a buy or sell?

A: The dominant strategy among neural network is to Sell GGMCW Stock.

Q: Is Glenfarne Merger Corp. Warrant stock a good investment?

A: The consensus rating for Glenfarne Merger Corp. Warrant is Sell and assigned short-term Ba3 & long-term Ba2 forecasted stock rating.

Q: What is the consensus rating of GGMCW stock?

A: The consensus rating for GGMCW is Sell.

Q: What is the prediction period for GGMCW stock?

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