Modelling A.I. in Economics

GGMCW Glenfarne Merger Corp. Warrant

Outlook: Glenfarne Merger Corp. Warrant assigned short-term Ba2 & long-term B2 forecasted stock rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 08 Dec 2022 for (n+6 month)
Methodology : Modular Neural Network (Financial Sentiment Analysis)

Abstract

Accurate prediction of stock market returns is a very challenging task due to volatile and non-linear nature of the financial stock markets. With the introduction of artificial intelligence and increased computational capabilities, programmed methods of prediction have proved to be more efficient in predicting stock prices.(Vadlamudi, S., 2017. Stock Market Prediction using Machine Learning: A Systematic Literature Review. American Journal of Trade and Policy, 4(3), pp.123-128.) We evaluate Glenfarne Merger Corp. Warrant prediction models with Modular Neural Network (Financial Sentiment Analysis) and Wilcoxon Rank-Sum Test1,2,3,4 and conclude that the GGMCW 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. How do you decide buy or sell a stock?
  2. What is a prediction confidence?
  3. Decision Making

GGMCW Target Price Prediction Modeling Methodology

We consider Glenfarne Merger Corp. Warrant Decision Process with Modular Neural Network (Financial 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(Wilcoxon Rank-Sum Test)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+6 month) i = 1 n r i

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+6 month)

Sample Set: Neural Network
Stock/Index: GGMCW Glenfarne Merger Corp. Warrant
Time series to forecast n: 08 Dec 2022 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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Glenfarne Merger Corp. Warrant

  1. For a financial guarantee contract, the entity is required to make payments only in the event of a default by the debtor in accordance with the terms of the instrument that is guaranteed. Accordingly, cash shortfalls are the expected payments to reimburse the holder for a credit loss that it incurs less any amounts that the entity expects to receive from the holder, the debtor or any other party. If the asset is fully guaranteed, the estimation of cash shortfalls for a financial guarantee contract would be consistent with the estimations of cash shortfalls for the asset subject to the guarantee
  2. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
  3. For example, when the critical terms (such as the nominal amount, maturity and underlying) of the hedging instrument and the hedged item match or are closely aligned, it might be possible for an entity to conclude on the basis of a qualitative assessment of those critical terms that the hedging instrument and the hedged item have values that will generally move in the opposite direction because of the same risk and hence that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6).
  4. An entity may use practical expedients when measuring expected credit losses if they are consistent with the principles in paragraph 5.5.17. An example of a practical expedient is the calculation of the expected credit losses on trade receivables using a provision matrix. The entity would use its historical credit loss experience (adjusted as appropriate in accordance with paragraphs B5.5.51–B5.5.52) for trade receivables to estimate the 12-month expected credit losses or the lifetime expected credit losses on the financial assets as relevant. A provision matrix might, for example, specify fixed provision rates depending on the number of days that a trade receivable is past due (for example, 1 per cent if not past due, 2 per cent if less than 30 days past due, 3 per cent if more than 30 days but less than 90 days past due, 20 per cent if 90–180 days past due etc). Depending on the diversity of its customer base, the entity would use appropriate groupings if its historical credit loss experience shows significantly different loss patterns for different customer segments. Examples of criteria that might be used to group assets include geographical region, product type, customer rating, collateral or trade credit insurance and type of customer (such as wholesale or retail)

*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 Ba2 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Wilcoxon Rank-Sum Test1,2,3,4 and conclude that the GGMCW 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

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

Rating Short-Term Long-Term Senior
Outlook*Ba2B2
Operational Risk 7069
Market Risk3750
Technical Analysis6437
Fundamental Analysis8848
Risk Unsystematic8845

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 626 signals.

References

  1. D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
  2. Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
  3. Doudchenko N, Imbens GW. 2016. Balancing, regression, difference-in-differences and synthetic control methods: a synthesis. NBER Work. Pap. 22791
  4. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
  5. Bickel P, Klaassen C, Ritov Y, Wellner J. 1998. Efficient and Adaptive Estimation for Semiparametric Models. Berlin: Springer
  6. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
  7. Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
Frequently Asked QuestionsQ: What is the prediction methodology for GGMCW stock?
A: GGMCW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Wilcoxon Rank-Sum Test
Q: Is GGMCW stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes GGMCW Stock.
Q: Is Glenfarne Merger Corp. Warrant stock a good investment?
A: The consensus rating for Glenfarne Merger Corp. Warrant is Wait until speculative trend diminishes and assigned short-term Ba2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of GGMCW stock?
A: The consensus rating for GGMCW is Wait until speculative trend diminishes.
Q: What is the prediction period for GGMCW stock?
A: The prediction period for GGMCW is (n+6 month)

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