**Outlook:**FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.

**Dominant Strategy :**Hold

**Time series to forecast n: 08 Jun 2023**for 6 Month

**Methodology :**Inductive Learning (ML)

## Abstract

FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares prediction model is evaluated with Inductive Learning (ML) and Statistical Hypothesis Testing^{1,2,3,4}and it is concluded that the FTAIN stock is predictable in the short/long term. Inductive learning is a type of machine learning in which the model learns from a set of labeled data and makes predictions about new, unlabeled data. The model is trained on the labeled data and then used to make predictions on new data. Inductive learning is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of inductive learning algorithms, including decision trees, support vector machines, and neural networks. Each type of algorithm has its own strengths and weaknesses.

**According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold**

## Key Points

- What are main components of Markov decision process?
- What is Markov decision process in reinforcement learning?
- Fundemental Analysis with Algorithmic Trading

## FTAIN Target Price Prediction Modeling Methodology

We consider FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares Decision Process with Inductive Learning (ML) where A is the set of discrete actions of FTAIN 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(Statistical Hypothesis Testing)

^{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(Inductive Learning (ML)) X S(n):→ 6 Month $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of FTAIN stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Inductive learning is a type of machine learning in which the model learns from a set of labeled data and makes predictions about new, unlabeled data. The model is trained on the labeled data and then used to make predictions on new data. Inductive learning is a supervised learning algorithm, which means that it requires labeled data to train. The labeled data is used to train the model to make predictions about new data. There are many different types of inductive learning algorithms, including decision trees, support vector machines, and neural networks. Each type of algorithm has its own strengths and weaknesses.

Statistical hypothesis testing is a process used to determine whether there is enough evidence to support a claim about a population based on a sample. The process involves making two hypotheses, a null hypothesis and an alternative hypothesis, and then collecting data and using statistical tests to determine which hypothesis is more likely to be true. The null hypothesis is the statement that there is no difference between the population and the sample. The alternative hypothesis is the statement that there is a difference between the population and the sample. The statistical test is used to calculate a p-value, which is the probability of obtaining the observed data or more extreme data if the null hypothesis is true. A p-value of less than 0.05 is typically considered to be statistically significant, which means that there is less than a 5% chance of obtaining the observed data or more extreme data if the null hypothesis is true.

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?

## FTAIN Stock Forecast (Buy or Sell) for 6 Month

**Sample Set:**Neural Network

**Stock/Index:**FTAIN FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares

**Time series to forecast n: 08 Jun 2023**for 6 Month

**According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold**

**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 FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares

- An entity can also designate only changes in the cash flows or fair value of a hedged item above or below a specified price or other variable (a 'one-sided risk'). The intrinsic value of a purchased option hedging instrument (assuming that it has the same principal terms as the designated risk), but not its time value, reflects a one-sided risk in a hedged item. For example, an entity can designate the variability of future cash flow outcomes resulting from a price increase of a forecast commodity purchase. In such a situation, the entity designates only cash flow losses that result from an increase in the price above the specified level. The hedged risk does not include the time value of a purchased option, because the time value is not a component of the forecast transaction that affects profit or loss.
- For the purpose of applying the requirements in paragraphs 6.4.1(c)(i) and B6.4.4–B6.4.6, an entity shall assume that the interest rate benchmark on which the hedged cash flows and/or the hedged risk (contractually or noncontractually specified) are based, or the interest rate benchmark on which the cash flows of the hedging instrument are based, is not altered as a result of interest rate benchmark reform.
- For floating-rate financial assets and floating-rate financial liabilities, periodic re-estimation of cash flows to reflect the movements in the market rates of interest alters the effective interest rate. If a floating-rate financial asset or a floating-rate financial liability is recognised initially at an amount equal to the principal receivable or payable on maturity, re-estimating the future interest payments normally has no significant effect on the carrying amount of the asset or the liability.
- To calculate the change in the value of the hedged item for the purpose of measuring hedge ineffectiveness, an entity may use a derivative that would have terms that match the critical terms of the hedged item (this is commonly referred to as a 'hypothetical derivative'), and, for example for a hedge of a forecast transaction, would be calibrated using the hedged price (or rate) level. For example, if the hedge was for a two-sided risk at the current market level, the hypothetical derivative would represent a hypothetical forward contract that is calibrated to a value of nil at the time of designation of the hedging relationship. If the hedge was for example for a one-sided risk, the hypothetical derivative would represent the intrinsic value of a hypothetical option that at the time of designation of the hedging relationship is at the money if the hedged price level is the current market level, or out of the money if the hedged price level is above (or, for a hedge of a long position, below) the current market level. Using a hypothetical derivative is one possible way of calculating the change in the value of the hedged item. The hypothetical derivative replicates the hedged item and hence results in the same outcome as if that change in value was determined by a different approach. Hence, using a 'hypothetical derivative' is not a method in its own right but a mathematical expedient that can only be used to calculate the value of the hedged item. Consequently, a 'hypothetical derivative' cannot be used to include features in the value of the hedged item that only exist in the hedging instrument (but not in the hedged item). An example is debt denominated in a foreign currency (irrespective of whether it is fixed-rate or variable-rate debt). When using a hypothetical derivative to calculate the change in the value of such debt or the present value of the cumulative change in its cash flows, the hypothetical derivative cannot simply impute a charge for exchanging different currencies even though actual derivatives under which different currencies are exchanged might include such a charge (for example, cross-currency interest rate swaps).

*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

FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares prediction model is evaluated with Inductive Learning (ML) and Statistical Hypothesis Testing^{1,2,3,4} and it is concluded that the FTAIN stock is predictable in the short/long term. ** According to price forecasts for 6 Month period, the dominant strategy among neural network is: Hold**

### FTAIN FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares Financial Analysis*

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

Outlook* | Ba1 | Ba1 |

Income Statement | C | C |

Balance Sheet | Baa2 | C |

Leverage Ratios | Baa2 | Ba2 |

Cash Flow | C | Baa2 |

Rates of Return and Profitability | Caa2 | Baa2 |

*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

- S. Bhatnagar. An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes. Systems & Control Letters, 59(12):760–766, 2010
- T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
- Wooldridge JM. 2010. Econometric Analysis of Cross Section and Panel Data. Cambridge, MA: MIT Press
- Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
- P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
- Bessler, D. A. T. Covey (1991), "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, 11, 461–474.
- Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106

## Frequently Asked Questions

Q: What is the prediction methodology for FTAIN stock?A: FTAIN stock prediction methodology: We evaluate the prediction models Inductive Learning (ML) and Statistical Hypothesis Testing

Q: Is FTAIN stock a buy or sell?

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

Q: Is FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares stock a good investment?

A: The consensus rating for FTAI Aviation Ltd. 8.25% Fixed - Rate Reset Series C Cumulative Perpetual Redeemable Preferred Shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.

Q: What is the consensus rating of FTAIN stock?

A: The consensus rating for FTAIN is Hold.

Q: What is the prediction period for FTAIN stock?

A: The prediction period for FTAIN is 6 Month

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