INDB Independent Bank Corp. Common Stock

Outlook: Independent Bank Corp. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 12 Jan 2023 for (n+1 year)
Methodology : Transductive Learning (ML)

Abstract

Independent Bank Corp. Common Stock prediction model is evaluated with Transductive Learning (ML) and Statistical Hypothesis Testing^1,2,3,4 and it is concluded that the INDB stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

Key Points

1. Short/Long Term Stocks
2. Trading Signals
3. Short/Long Term Stocks

INDB Target Price Prediction Modeling Methodology

We consider Independent Bank Corp. Common Stock Decision Process with Transductive Learning (ML) where A is the set of discrete actions of INDB 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(Statistical Hypothesis Testing)^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(Transductive Learning (ML)) X S(n):→ (n+1 year) $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of INDB 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?

INDB Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: INDB Independent Bank Corp. Common Stock
Time series to forecast n: 12 Jan 2023 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

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 Independent Bank Corp. Common Stock

1. When determining whether the recognition of lifetime expected credit losses is required, an entity shall consider reasonable and supportable information that is available without undue cost or effort and that may affect the credit risk on a financial instrument in accordance with paragraph 5.5.17(c). An entity need not undertake an exhaustive search for information when determining whether credit risk has increased significantly since initial recognition.
2. An entity's estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, ie it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.
3. An entity's estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, ie it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.
4. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.

*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

Independent Bank Corp. Common Stock is assigned short-term Ba1 & long-term Ba1 estimated rating. Independent Bank Corp. Common Stock prediction model is evaluated with Transductive Learning (ML) and Statistical Hypothesis Testing^1,2,3,4 and it is concluded that the INDB stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

INDB Independent Bank Corp. Common Stock Financial Analysis*

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

*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 609 signals.

References

1. Wan M, Wang D, Goldman M, Taddy M, Rao J, et al. 2017. Modeling consumer preferences and price sensitiv- ities from large-scale grocery shopping transaction logs. In Proceedings of the 26th International Conference on the World Wide Web, pp. 1103–12. New York: ACM
2. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
3. T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
4. A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
5. Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
6. Chow, G. C. (1960), "Tests of equality between sets of coefficients in two linear regressions," Econometrica, 28, 591–605.
7. Scott SL. 2010. A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26:639–58

Frequently Asked Questions

Q: What is the prediction methodology for INDB stock?
A: INDB stock prediction methodology: We evaluate the prediction models Transductive Learning (ML) and Statistical Hypothesis Testing
Q: Is INDB stock a buy or sell?
A: The dominant strategy among neural network is to Hold INDB Stock.
Q: Is Independent Bank Corp. Common Stock stock a good investment?
A: The consensus rating for Independent Bank Corp. Common Stock is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of INDB stock?
A: The consensus rating for INDB is Hold.
Q: What is the prediction period for INDB stock?
A: The prediction period for INDB is (n+1 year)

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