Where Will CHMG Stock Be in 4 Weeks?

Name: Where Will CHMG Stock Be in 4 Weeks?
Uploaded: Tuesday, November 7, 2023
Duration: 37 min 14 s
Description: Where Will CHMG Stock Be in 4 Weeks?

Outlook: Chemung Financial Corp Common Stock is assigned short-term Baa2 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Speculative Trend
Time series to forecast n: for Weeks²
Methodology : Reinforcement Machine Learning (ML)
Hypothesis Testing : Ridge Regression
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

Chemung Financial Corp Common Stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Ridge Regression^1,2,3,4 and it is concluded that the CHMG stock is predictable in the short/long term. Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.⁵ According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Speculative Trend

Key Points

Reinforcement Machine Learning (ML) for CHMG stock price prediction process.
Ridge Regression
Trust metric by Neural Network
Dominated Move
Game Theory

CHMG Stock Price Forecast

We consider Chemung Financial Corp Common Stock Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of CHMG 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

Sample Set: Neural Network
Stock/Index: CHMG Chemung Financial Corp Common Stock
Time series to forecast: 4 Weeks

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

F(Ridge Regression)^6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Reinforcement Machine Learning (ML)) X S(n):→ 4 Weeks

\vec{S} = (s_{1}, s_{2}, s_{3})

n:Time series to forecast

p:Price signals of CHMG stock

j:Nash equilibria (Neural Network)

k:Dominated move of CHMG stock holders

a:Best response for CHMG target price

Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.⁵ Ridge regression is a type of regression analysis that adds a penalty to the least squares objective function in order to reduce the variance of the estimates. This is done by adding a term to the objective function that is proportional to the sum of the squares of the coefficients. The penalty term is called the "ridge" penalty, and it is controlled by a parameter called the "ridge constant". Ridge regression can be used to address the problem of multicollinearity in linear regression. Multicollinearity occurs when two or more independent variables are highly correlated. This can cause the standard errors of the coefficients to be large, and it can also cause the coefficients to be unstable. Ridge regression can help to reduce the standard errors of the coefficients and to make the coefficients more stable.^6,7

For further technical information as per how our model work we invite you to visit the article below:

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CHMG Stock Forecast (Buy or Sell) Strategic Interaction Table

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 Reinforcement Machine Learning (ML) based CHMG Stock Prediction Model

Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.
In almost every lending transaction the creditor's instrument is ranked relative to the instruments of the debtor's other creditors. An instrument that is subordinated to other instruments may have contractual cash flows that are payments of principal and interest on the principal amount outstanding if the debtor's non-payment is a breach of contract and the holder has a contractual right to unpaid amounts of principal and interest on the principal amount outstanding even in the event of the debtor's bankruptcy. For example, a trade receivable that ranks its creditor as a general creditor would qualify as having payments of principal and interest on the principal amount outstanding. This is the case even if the debtor issued loans that are collateralised, which in the event of bankruptcy would give that loan holder priority over the claims of the general creditor in respect of the collateral but does not affect the contractual right of the general creditor to unpaid principal and other amounts due.
The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary
The expected credit losses on a loan commitment shall be discounted using the effective interest rate, or an approximation thereof, that will be applied when recognising the financial asset resulting from the loan commitment. This is because for the purpose of applying the impairment requirements, a financial asset that is recognised following a draw down on a loan commitment shall be treated as a continuation of that commitment instead of as a new financial instrument. The expected credit losses on the financial asset shall therefore be measured considering the initial credit risk of the loan commitment from the date that the entity became a party to the irrevocable commitment.

*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.

CHMG Chemung Financial Corp Common Stock Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Baa2	B1
Income Statement	Baa2	Baa2
Balance Sheet	Baa2	C
Leverage Ratios	Baa2	Ba3
Cash Flow	Baa2	C
Rates of Return and Profitability	Baa2	Ba3

*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?

References

Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]
Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
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
Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
Mnih A, Kavukcuoglu K. 2013. Learning word embeddings efficiently with noise-contrastive estimation. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 2265–73. San Diego, CA: Neural Inf. Process. Syst. Found.
Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
Jiang N, Li L. 2016. Doubly robust off-policy value evaluation for reinforcement learning. In Proceedings of the 33rd International Conference on Machine Learning, pp. 652–61. La Jolla, CA: Int. Mach. Learn. Soc.

Frequently Asked Questions

Q: Is CHMG stock expected to rise?
A: CHMG stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Ridge Regression and it is concluded that dominant strategy for CHMG stock is Speculative Trend
Q: Is CHMG stock a buy or sell?
A: The dominant strategy among neural network is to Speculative Trend CHMG Stock.
Q: Is Chemung Financial Corp Common Stock stock a good investment?
A: The consensus rating for Chemung Financial Corp Common Stock is Speculative Trend and is assigned short-term Baa2 & long-term B1 estimated rating.
Q: What is the consensus rating of CHMG stock?
A: The consensus rating for CHMG is Speculative Trend.
Q: What is the forecast for CHMG stock?
A: CHMG target price forecast: Speculative Trend

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