BUSE First Busey Corporation Class A Common Stock

Outlook: First Busey Corporation Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 24 May 2023 for (n+3 month)
Methodology : Supervised Machine Learning (ML)

Abstract

First Busey Corporation Class A Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Stepwise Regression^1,2,3,4 and it is concluded that the BUSE stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

Key Points

1. Reaction Function
2. Trading Signals
3. How can neural networks improve predictions?

BUSE Target Price Prediction Modeling Methodology

We consider First Busey Corporation Class A Common Stock Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of BUSE 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(Stepwise 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(Supervised Machine Learning (ML)) X S(n):→ (n+3 month) $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of BUSE 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?

BUSE Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: BUSE First Busey Corporation Class A Common Stock
Time series to forecast n: 24 May 2023 for (n+3 month)

According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

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 Busey Corporation Class A Common Stock

1. When using historical credit loss experience in estimating expected credit losses, it is important that information about historical credit loss rates is applied to groups that are defined in a manner that is consistent with the groups for which the historical credit loss rates were observed. Consequently, the method used shall enable each group of financial assets to be associated with information about past credit loss experience in groups of financial assets with similar risk characteristics and with relevant observable data that reflects current conditions.
2. To be eligible for designation as a hedged item, a risk component must be a separately identifiable component of the financial or the non-financial item, and the changes in the cash flows or the fair value of the item attributable to changes in that risk component must be reliably measurable.
3. A contractually specified inflation risk component of the cash flows of a recognised inflation-linked bond (assuming that there is no requirement to account for an embedded derivative separately) is separately identifiable and reliably measurable, as long as other cash flows of the instrument are not affected by the inflation risk component.
4. 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).

*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 Busey Corporation Class A Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. First Busey Corporation Class A Common Stock prediction model is evaluated with Supervised Machine Learning (ML) and Stepwise Regression^1,2,3,4 and it is concluded that the BUSE stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

BUSE First Busey Corporation Class A Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Baa2	Caa2
Balance Sheet	Baa2	C
Leverage Ratios	B3	Baa2
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: 72 out of 100 with 513 signals.

References

1. Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
2. 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).
3. C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999
4. Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
5. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
6. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
7. Zubizarreta JR. 2015. Stable weights that balance covariates for estimation with incomplete outcome data. J. Am. Stat. Assoc. 110:910–22

Frequently Asked Questions

Q: What is the prediction methodology for BUSE stock?
A: BUSE stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Stepwise Regression
Q: Is BUSE stock a buy or sell?
A: The dominant strategy among neural network is to Buy BUSE Stock.
Q: Is First Busey Corporation Class A Common Stock stock a good investment?
A: The consensus rating for First Busey Corporation Class A Common Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BUSE stock?
A: The consensus rating for BUSE is Buy.
Q: What is the prediction period for BUSE stock?
A: The prediction period for BUSE is (n+3 month)

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