Modelling A.I. in Economics

PFTAU Portage Fintech Acquisition Corporation Unit (Forecast)

Outlook: Portage Fintech Acquisition Corporation Unit is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 12 Apr 2023 for (n+6 month)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

Portage Fintech Acquisition Corporation Unit prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Polynomial Regression1,2,3,4 and it is concluded that the PFTAU 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. Market Signals
  2. Stock Rating
  3. Can stock prices be predicted?

PFTAU Target Price Prediction Modeling Methodology

We consider Portage Fintech Acquisition Corporation Unit Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of PFTAU 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(Polynomial Regression)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 (Market Volatility Analysis)) X S(n):→ (n+6 month) i = 1 n r i

n:Time series to forecast

p:Price signals of PFTAU 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?

PFTAU Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: PFTAU Portage Fintech Acquisition Corporation Unit
Time series to forecast n: 12 Apr 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 Portage Fintech Acquisition Corporation Unit

  1. If a call option right retained by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the asset continues to be measured at its fair value. The associated liability is measured at (i) the option exercise price less the time value of the option if the option is in or at the money, or (ii) the fair value of the transferred asset less the time value of the option if the option is out of the money. The adjustment to the measurement of the associated liability ensures that the net carrying amount of the asset and the associated liability is the fair value of the call option right. For example, if the fair value of the underlying asset is CU80, the option exercise price is CU95 and the time value of the option is CU5, the carrying amount of the associated liability is CU75 (CU80 – CU5) and the carrying amount of the transferred asset is CU80 (ie its fair value)
  2. The credit risk on a financial instrument is considered low for the purposes of paragraph 5.5.10, if the financial instrument has a low risk of default, the borrower has a strong capacity to meet its contractual cash flow obligations in the near term and adverse changes in economic and business conditions in the longer term may, but will not necessarily, reduce the ability of the borrower to fulfil its contractual cash flow obligations. Financial instruments are not considered to have low credit risk when they are regarded as having a low risk of loss simply because of the value of collateral and the financial instrument without that collateral would not be considered low credit risk. Financial instruments are also not considered to have low credit risk simply because they have a lower risk of default than the entity's other financial instruments or relative to the credit risk of the jurisdiction within which an entity operates.
  3. 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.
  4. 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.

*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

Portage Fintech Acquisition Corporation Unit is assigned short-term Ba1 & long-term Ba1 estimated rating. Portage Fintech Acquisition Corporation Unit prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Polynomial Regression1,2,3,4 and it is concluded that the PFTAU 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

PFTAU Portage Fintech Acquisition Corporation Unit Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2Baa2
Balance SheetCaa2Baa2
Leverage RatiosBa2Caa2
Cash FlowB1Baa2
Rates of Return and ProfitabilityCB1

*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: 82 out of 100 with 473 signals.

References

  1. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
  2. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
  3. S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014
  4. Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
  5. Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
  6. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. How is the price of gold determined? (No. Stock Analysis). AC Investment Research.
  7. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
Frequently Asked QuestionsQ: What is the prediction methodology for PFTAU stock?
A: PFTAU stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Polynomial Regression
Q: Is PFTAU stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes PFTAU Stock.
Q: Is Portage Fintech Acquisition Corporation Unit stock a good investment?
A: The consensus rating for Portage Fintech Acquisition Corporation Unit is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of PFTAU stock?
A: The consensus rating for PFTAU is Wait until speculative trend diminishes.
Q: What is the prediction period for PFTAU stock?
A: The prediction period for PFTAU is (n+6 month)

Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.