Where Will NRIM Stock Be in 8 Weeks?

Outlook: Northrim BanCorp Inc Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 13 Jun 2023 for 8 Weeks
Methodology : Modular Neural Network (Financial Sentiment Analysis)

Abstract

Northrim BanCorp Inc Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the NRIM stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for financial sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of financial sentiment analysis, MNNs can be used to identify the sentiment of financial news articles, social media posts, and other forms of online content. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Buy

Key Points

1. Understanding Buy, Sell, and Hold Ratings
2. What is the best way to predict stock prices?
3. How do you pick a stock?

NRIM Target Price Prediction Modeling Methodology

We consider Northrim BanCorp Inc Common Stock Decision Process with Modular Neural Network (Financial Sentiment Analysis) where A is the set of discrete actions of NRIM 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(Wilcoxon Sign-Rank Test)^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(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ 8 Weeks $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of NRIM stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (Financial Sentiment Analysis)

Modular neural networks (MNNs) are a type of artificial neural network that can be used for financial sentiment analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of financial sentiment analysis, MNNs can be used to identify the sentiment of financial news articles, social media posts, and other forms of online content. This information can then be used to make investment decisions, to identify trends in the market, and to target investors with relevant advertising.

Wilcoxon Sign-Rank Test

The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that 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?

NRIM Stock Forecast (Buy or Sell) for 8 Weeks

Sample Set: Neural Network
Stock/Index: NRIM Northrim BanCorp Inc Common Stock
Time series to forecast n: 13 Jun 2023 for 8 Weeks

According to price forecasts for 8 Weeks 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 Northrim BanCorp Inc Common Stock

1. For example, when the critical terms (such as the nominal amount, maturity and underlying) of the hedging instrument and the hedged item match or are closely aligned, it might be possible for an entity to conclude on the basis of a qualitative assessment of those critical terms that the hedging instrument and the hedged item have values that will generally move in the opposite direction because of the same risk and hence that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6).
2. An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.
3. 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.
4. 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.

*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

Northrim BanCorp Inc Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Northrim BanCorp Inc Common Stock prediction model is evaluated with Modular Neural Network (Financial Sentiment Analysis) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the NRIM stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Buy

NRIM Northrim BanCorp Inc Common Stock Financial Analysis*

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

*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: 75 out of 100 with 597 signals.

References

1. N. B ̈auerle and J. Ott. Markov decision processes with average-value-at-risk criteria. Mathematical Methods of Operations Research, 74(3):361–379, 2011
2. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., GXO Options & Futures Prediction. AC Investment Research Journal, 101(3).
3. E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
4. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
5. T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000
6. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
7. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.

Frequently Asked Questions

Q: What is the prediction methodology for NRIM stock?
A: NRIM stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Wilcoxon Sign-Rank Test
Q: Is NRIM stock a buy or sell?
A: The dominant strategy among neural network is to Buy NRIM Stock.
Q: Is Northrim BanCorp Inc Common Stock stock a good investment?
A: The consensus rating for Northrim BanCorp Inc Common Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of NRIM stock?
A: The consensus rating for NRIM is Buy.
Q: What is the prediction period for NRIM stock?
A: The prediction period for NRIM is 8 Weeks