JMSB John Marshall Bancorp Inc. Common Stock

Outlook: John Marshall Bancorp Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 30 Jan 2023 for (n+8 weeks)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

John Marshall Bancorp Inc. Common Stock prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Lasso Regression^1,2,3,4 and it is concluded that the JMSB stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy

Key Points

1. What are the most successful trading algorithms?
2. Prediction Modeling
3. Can statistics predict the future?

JMSB Target Price Prediction Modeling Methodology

We consider John Marshall Bancorp Inc. Common Stock Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of JMSB 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(Lasso 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(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+8 weeks) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of JMSB 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?

JMSB Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: JMSB John Marshall Bancorp Inc. Common Stock
Time series to forecast n: 30 Jan 2023 for (n+8 weeks)

According to price forecasts for (n+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 John Marshall Bancorp Inc. Common Stock

1. An alternative benchmark rate designated as a non-contractually specified risk component that is not separately identifiable (see paragraphs 6.3.7(a) and B6.3.8) at the date it is designated shall be deemed to have met that requirement at that date, if, and only if, the entity reasonably expects the alternative benchmark rate will be separately identifiable within 24 months. The 24-month period applies to each alternative benchmark rate separately and starts from the date the entity designates the alternative benchmark rate as a non-contractually specified risk component for the first time (ie the 24- month period applies on a rate-by-rate basis).
2. However, in some cases, the time value of money element may be modified (ie imperfect). That would be the case, for example, if a financial asset's interest rate is periodically reset but the frequency of that reset does not match the tenor of the interest rate (for example, the interest rate resets every month to a one-year rate) or if a financial asset's interest rate is periodically reset to an average of particular short- and long-term interest rates. In such cases, an entity must assess the modification to determine whether the contractual cash flows represent solely payments of principal and interest on the principal amount outstanding. In some circumstances, the entity may be able to make that determination by performing a qualitative assessment of the time value of money element whereas, in other circumstances, it may be necessary to perform a quantitative assessment.
3. IFRS 15, issued in May 2014, amended paragraphs 3.1.1, 4.2.1, 5.1.1, 5.2.1, 5.7.6, B3.2.13, B5.7.1, C5 and C42 and deleted paragraph C16 and its related heading. Paragraphs 5.1.3 and 5.7.1A, and a definition to Appendix A, were added. An entity shall apply those amendments when it applies IFRS 15.
4. An entity is not required to restate prior periods to reflect the application of these amendments. 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 of these amendments in the opening retained earnings (or other component of equity, as appropriate) of the annual reporting period that includes the date of initial application of these amendments.

*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

John Marshall Bancorp Inc. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. John Marshall Bancorp Inc. Common Stock prediction model is evaluated with Modular Neural Network (Market Volatility Analysis) and Lasso Regression^1,2,3,4 and it is concluded that the JMSB stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Buy

JMSB John Marshall Bancorp Inc. Common Stock Financial Analysis*

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

*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 540 signals.

References

1. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
2. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., How do you know when a stock will go up or down?(STJ Stock Forecast). AC Investment Research Journal, 101(3).
3. E. Collins. Using Markov decision processes to optimize a nonlinear functional of the final distribution, with manufacturing applications. In Stochastic Modelling in Innovative Manufacturing, pages 30–45. Springer, 1997
4. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
5. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
6. Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106
7. D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.

Frequently Asked Questions

Q: What is the prediction methodology for JMSB stock?
A: JMSB stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Lasso Regression
Q: Is JMSB stock a buy or sell?
A: The dominant strategy among neural network is to Buy JMSB Stock.
Q: Is John Marshall Bancorp Inc. Common Stock stock a good investment?
A: The consensus rating for John Marshall Bancorp Inc. Common Stock is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of JMSB stock?
A: The consensus rating for JMSB is Buy.
Q: What is the prediction period for JMSB stock?
A: The prediction period for JMSB is (n+8 weeks)

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