BFC Stock: A Risky Investment, But One with a lot of Potential

Outlook: Bank First Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 13 Jun 2023 for 1 Year
Methodology : Transfer Learning (ML)

Abstract

Bank First Corporation Common Stock prediction model is evaluated with Transfer Learning (ML) and Polynomial Regression^1,2,3,4 and it is concluded that the BFC stock is predictable in the short/long term. Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Sell

Key Points

1. Technical Analysis with Algorithmic Trading
2. Can we predict stock market using machine learning?
3. Is it better to buy and sell or hold?

BFC Target Price Prediction Modeling Methodology

We consider Bank First Corporation Common Stock Decision Process with Transfer Learning (ML) where A is the set of discrete actions of BFC 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Transfer Learning (ML)) X S(n):→ 1 Year $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of BFC stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Transfer Learning (ML)

Transfer learning is a machine learning (ML) method where a model developed for one task is reused as the starting point for a model on a second task. This can be useful when the second task is similar to the first task, or when there is limited data available for the second task.

Polynomial Regression

Polynomial regression is a type of regression analysis that uses a polynomial function to model the relationship between a dependent variable and one or more independent variables. Polynomial functions are mathematical functions that have a polynomial term, which is a term that is raised to a power greater than 1. In polynomial regression, the dependent variable is modeled as a polynomial function of the independent variables. The degree of the polynomial function is determined by the researcher. The higher the degree of the polynomial function, the more complex the model will be.

 

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?

BFC Stock Forecast (Buy or Sell) for 1 Year

Sample Set: Neural Network
Stock/Index: BFC Bank First Corporation Common Stock
Time series to forecast n: 13 Jun 2023 for 1 Year

According to price forecasts for 1 Year 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%

IFRS Reconciliation Adjustments for Bank First Corporation Common Stock

1. Financial assets that are held within a business model whose objective is to hold assets in order to collect contractual cash flows are managed to realise cash flows by collecting contractual payments over the life of the instrument. That is, the entity manages the assets held within the portfolio to collect those particular contractual cash flows (instead of managing the overall return on the portfolio by both holding and selling assets). In determining whether cash flows are going to be realised by collecting the financial assets' contractual cash flows, it is necessary to consider the frequency, value and timing of sales in prior periods, the reasons for those sales and expectations about future sales activity. However sales in themselves do not determine the business model and therefore cannot be considered in isolation. Instead, information about past sales and expectations about future sales provide evidence related to how the entity's stated objective for managing the financial assets is achieved and, specifically, how cash flows are realised. An entity must consider information about past sales within the context of the reasons for those sales and the conditions that existed at that time as compared to current conditions.
2. When rebalancing a hedging relationship, an entity shall update its analysis of the sources of hedge ineffectiveness that are expected to affect the hedging relationship during its (remaining) term (see paragraph B6.4.2). The documentation of the hedging relationship shall be updated accordingly.
3. In some circumstances an entity does not have reasonable and supportable information that is available without undue cost or effort to measure lifetime expected credit losses on an individual instrument basis. In that case, lifetime expected credit losses shall be recognised on a collective basis that considers comprehensive credit risk information. This comprehensive credit risk information must incorporate not only past due information but also all relevant credit information, including forward-looking macroeconomic information, in order to approximate the result of recognising lifetime expected credit losses when there has been a significant increase in credit risk since initial recognition on an individual instrument level.
4. For loan commitments, an entity considers changes in the risk of a default occurring on the loan to which a loan commitment relates. For financial guarantee contracts, an entity considers the changes in the risk that the specified debtor will default on the contract.

*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

Bank First Corporation Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Bank First Corporation Common Stock prediction model is evaluated with Transfer Learning (ML) and Polynomial Regression^1,2,3,4 and it is concluded that the BFC stock is predictable in the short/long term. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Sell

BFC Bank First Corporation Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B2	B1
Balance Sheet	Caa2	Ba2
Leverage Ratios	Baa2	Ba3
Cash Flow	Baa2	Baa2
Rates of Return and Profitability	B3	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

Trust metric by Neural Network: 86 out of 100 with 473 signals.

References

1. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
2. Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
3. Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.
4. Hastie T, Tibshirani R, Tibshirani RJ. 2017. Extended comparisons of best subset selection, forward stepwise selection, and the lasso. arXiv:1707.08692 [stat.ME]
5. M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994
6. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
7. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London

Frequently Asked Questions

Q: What is the prediction methodology for BFC stock?
A: BFC stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Polynomial Regression
Q: Is BFC stock a buy or sell?
A: The dominant strategy among neural network is to Sell BFC Stock.
Q: Is Bank First Corporation Common Stock stock a good investment?
A: The consensus rating for Bank First Corporation Common Stock is Sell and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BFC stock?
A: The consensus rating for BFC is Sell.
Q: What is the prediction period for BFC stock?
A: The prediction period for BFC is 1 Year