Outlook: National Bank Holdings Corporation Common Stock is assigned short-term B1 & long-term Ba1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Transductive Learning (ML)
Hypothesis Testing : Beta
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.

## Summary

National Bank Holdings Corporation Common Stock prediction model is evaluated with Transductive Learning (ML) and Beta1,2,3,4 and it is concluded that the NBHC stock is predictable in the short/long term. Transductive learning is a supervised machine learning (ML) method in which the model is trained on both labeled and unlabeled data. The goal of transductive learning is to predict the labels of the unlabeled data. Transductive learning is a hybrid of inductive and semi-supervised learning. Inductive learning algorithms are trained on labeled data only, while semi-supervised learning algorithms are trained on a combination of labeled and unlabeled data. Transductive learning algorithms can achieve better performance than inductive learning algorithms on tasks where there is a small amount of labeled data. This is because transductive learning algorithms can use the unlabeled data to help them learn the relationships between the features and the labels. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell

## Key Points

1. How can neural networks improve predictions?
2. What are the most successful trading algorithms?
3. Game Theory

## NBHC Target Price Prediction Modeling Methodology

We consider National Bank Holdings Corporation Common Stock Decision Process with Transductive Learning (ML) where A is the set of discrete actions of NBHC 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(Beta)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(Transductive Learning (ML)) X S(n):→ 3 Month $∑ i = 1 n s i$

n:Time series to forecast

p:Price signals of NBHC stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

### Transductive Learning (ML)

Transductive learning is a supervised machine learning (ML) method in which the model is trained on both labeled and unlabeled data. The goal of transductive learning is to predict the labels of the unlabeled data. Transductive learning is a hybrid of inductive and semi-supervised learning. Inductive learning algorithms are trained on labeled data only, while semi-supervised learning algorithms are trained on a combination of labeled and unlabeled data. Transductive learning algorithms can achieve better performance than inductive learning algorithms on tasks where there is a small amount of labeled data. This is because transductive learning algorithms can use the unlabeled data to help them learn the relationships between the features and the labels.

### Beta

In statistics, beta (β) is a measure of the strength of the relationship between two variables. It is calculated as the slope of the line of best fit in a regression analysis. Beta can range from -1 to 1, with a value of 0 indicating no relationship between the two variables. A positive beta indicates that as one variable increases, the other variable also increases. A negative beta indicates that as one variable increases, the other variable decreases. For example, a study might find that there is a positive relationship between height and weight. This means that taller people tend to weigh more. The beta coefficient for this relationship would be positive.

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?

## NBHC Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: NBHC National Bank Holdings Corporation Common Stock
Time series to forecast: 3 Month

According to price forecasts, the dominant strategy among neural network is: Sell

Strategic Interaction Table Legend:

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%

### Financial Data Adjustments for Transductive Learning (ML) based NBHC Stock Prediction Model

1. For purchased or originated credit-impaired financial assets, expected credit losses shall be discounted using the credit-adjusted effective interest rate determined at initial recognition.
2. For the purposes of applying the requirement in paragraph 5.7.7(a), credit risk is different from asset-specific performance risk. Asset-specific performance risk is not related to the risk that an entity will fail to discharge a particular obligation but instead it is related to the risk that a single asset or a group of assets will perform poorly (or not at all).
3. For some types of fair value hedges, the objective of the hedge is not primarily to offset the fair value change of the hedged item but instead to transform the cash flows of the hedged item. For example, an entity hedges the fair value interest rate risk of a fixed-rate debt instrument using an interest rate swap. The entity's hedge objective is to transform the fixed-interest cash flows into floating interest cash flows. This objective is reflected in the accounting for the hedging relationship by accruing the net interest accrual on the interest rate swap in profit or loss. In the case of a hedge of a net position (for example, a net position of a fixed-rate asset and a fixed-rate liability), this net interest accrual must be presented in a separate line item in the statement of profit or loss and other comprehensive income. This is to avoid the grossing up of a single instrument's net gains or losses into offsetting gross amounts and recognising them in different line items (for example, this avoids grossing up a net interest receipt on a single interest rate swap into gross interest revenue and gross interest expense).
4. For a financial guarantee contract, the entity is required to make payments only in the event of a default by the debtor in accordance with the terms of the instrument that is guaranteed. Accordingly, cash shortfalls are the expected payments to reimburse the holder for a credit loss that it incurs less any amounts that the entity expects to receive from the holder, the debtor or any other party. If the asset is fully guaranteed, the estimation of cash shortfalls for a financial guarantee contract would be consistent with the estimations of cash shortfalls for the asset subject to the guarantee

*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.

### NBHC National Bank Holdings Corporation Common Stock Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B1Ba1
Income StatementBa3Baa2
Balance SheetCBa2
Leverage RatiosCB1
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityBaa2B2

*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?

## Conclusions

National Bank Holdings Corporation Common Stock is assigned short-term B1 & long-term Ba1 estimated rating. National Bank Holdings Corporation Common Stock prediction model is evaluated with Transductive Learning (ML) and Beta1,2,3,4 and it is concluded that the NBHC stock is predictable in the short/long term. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell

### Prediction Confidence Score

Trust metric by Neural Network: 88 out of 100 with 531 signals.

## References

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3. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
4. Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106
5. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
6. Abadie A, Diamond A, Hainmueller J. 2010. Synthetic control methods for comparative case studies: estimat- ing the effect of California's tobacco control program. J. Am. Stat. Assoc. 105:493–505
7. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
Frequently Asked QuestionsQ: What is the prediction methodology for NBHC stock?
A: NBHC stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Beta
Q: Is NBHC stock a buy or sell?
A: The dominant strategy among neural network is to Sell NBHC Stock.
Q: Is National Bank Holdings Corporation Common Stock stock a good investment?
A: The consensus rating for National Bank Holdings Corporation Common Stock is Sell and is assigned short-term B1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of NBHC stock?
A: The consensus rating for NBHC is Sell.
Q: What is the prediction period for NBHC stock?
A: The prediction period for NBHC is 3 Month