Outlook: First Interstate BancSystem Inc. Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 31 May 2023 for (n+1 year)
Methodology : Modular Neural Network (Speculative Sentiment Analysis)

## Abstract

First Interstate BancSystem Inc. Class A Common Stock prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Multiple Regression1,2,3,4 and it is concluded that the FIBK stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

## Key Points

1. Dominated Move
2. Fundemental Analysis with Algorithmic Trading
3. How useful are statistical predictions?

## FIBK Target Price Prediction Modeling Methodology

We consider First Interstate BancSystem Inc. Class A Common Stock Decision Process with Modular Neural Network (Speculative Sentiment Analysis) where A is the set of discrete actions of FIBK 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(Multiple Regression)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Modular Neural Network (Speculative Sentiment Analysis)) X S(n):→ (n+1 year) $∑ i = 1 n r i$

n:Time series to forecast

p:Price signals of FIBK 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?

## FIBK Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: FIBK First Interstate BancSystem Inc. Class A Common Stock
Time series to forecast n: 31 May 2023 for (n+1 year)

According to price forecasts for (n+1 year) 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 First Interstate BancSystem Inc. Class A Common Stock

1. If a put option written by an entity prevents a transferred asset from being derecognised and the entity measures the transferred asset at fair value, the associated liability is measured at the option exercise price plus the time value of the option. The measurement of the asset at fair value is limited to the lower of the fair value and the option exercise price because the entity has no right to increases in the fair value of the transferred asset above the exercise price of the option. This ensures that the net carrying amount of the asset and the associated liability is the fair value of the put option obligation. For example, if the fair value of the underlying asset is CU120, the option exercise price is CU100 and the time value of the option is CU5, the carrying amount of the associated liability is CU105 (CU100 + CU5) and the carrying amount of the asset is CU100 (in this case the option exercise price).
2. When measuring the fair values of the part that continues to be recognised and the part that is derecognised for the purposes of applying paragraph 3.2.13, an entity applies the fair value measurement requirements in IFRS 13 Fair Value Measurement in addition to paragraph 3.2.14.
3. Despite the requirement in paragraph 7.2.1, an entity that adopts the classification and measurement requirements of this Standard (which include the requirements related to amortised cost measurement for financial assets and impairment in Sections 5.4 and 5.5) shall provide the disclosures set out in paragraphs 42L–42O of IFRS 7 but need not restate prior periods. The entity may restate prior periods if, and only if, it is possible without the use of hindsight. If an entity does not restate prior periods, the entity shall recognise any difference between the previous carrying amount and the carrying amount at the beginning of the annual reporting period that includes the date of initial application in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application. However, if an entity restates prior periods, the restated financial statements must reflect all of the requirements in this Standard. If an entity's chosen approach to applying IFRS 9 results in more than one date of initial application for different requirements, this paragraph applies at each date of initial application (see paragraph 7.2.2). This would be the case, for example, if an entity elects to early apply only the requirements for the presentation of gains and losses on financial liabilities designated as at fair value through profit or loss in accordance with paragraph 7.1.2 before applying the other requirements in this Standard.
4. 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

First Interstate BancSystem Inc. Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. First Interstate BancSystem Inc. Class A Common Stock prediction model is evaluated with Modular Neural Network (Speculative Sentiment Analysis) and Multiple Regression1,2,3,4 and it is concluded that the FIBK stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

### FIBK First Interstate BancSystem Inc. Class A Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB3Caa2
Balance SheetCaa2C
Leverage RatiosB3Caa2
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityBa3B1

*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: 86 out of 100 with 696 signals. ## References

1. Burkov A. 2019. The Hundred-Page Machine Learning Book. Quebec City, Can.: Andriy Burkov
2. G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
3. V. Borkar. Stochastic approximation: a dynamical systems viewpoint. Cambridge University Press, 2008
4. Imbens GW, Lemieux T. 2008. Regression discontinuity designs: a guide to practice. J. Econom. 142:615–35
5. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
6. C. Szepesvári. Algorithms for Reinforcement Learning. Synthesis Lectures on Artificial Intelligence and Machine Learning. Morgan & Claypool Publishers, 2010
7. Clements, M. P. D. F. Hendry (1996), "Intercept corrections and structural change," Journal of Applied Econometrics, 11, 475–494.
Frequently Asked QuestionsQ: What is the prediction methodology for FIBK stock?
A: FIBK stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Multiple Regression
Q: Is FIBK stock a buy or sell?
A: The dominant strategy among neural network is to Hold FIBK Stock.
Q: Is First Interstate BancSystem Inc. Class A Common Stock stock a good investment?
A: The consensus rating for First Interstate BancSystem Inc. Class A Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of FIBK stock?
A: The consensus rating for FIBK is Hold.
Q: What is the prediction period for FIBK stock?
A: The prediction period for FIBK is (n+1 year)