AUC Score :
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n:
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.
Abstract
New Ireland Fund Inc (The) Common Stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Ridge Regression1,2,3,4 and it is concluded that the IRL 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. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Buy
Key Points
- What is the best way to predict stock prices?
- Stock Rating
- Market Outlook
IRL Target Price Prediction Modeling Methodology
We consider New Ireland Fund Inc (The) Common Stock Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of IRL 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(Ridge Regression)5,6,7= X R(Reinforcement Machine Learning (ML)) X S(n):→ 3 Month
n:Time series to forecast
p:Price signals of IRL stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Reinforcement Machine Learning (ML)
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.Ridge Regression
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.
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?
IRL Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: IRL New Ireland Fund Inc (The) Common Stock
Time series to forecast: 3 Month
According to price forecasts, the dominant strategy among neural network is: Buy
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 IRL Stock Prediction Model
- Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.
- Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
- When measuring hedge ineffectiveness, an entity shall consider the time value of money. Consequently, the entity determines the value of the hedged item on a present value basis and therefore the change in the value of the hedged item also includes the effect of the time value of money.
- If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess whether the fair value of a prepayment feature was insignificant in accordance with paragraph B4.1.12(c) on the basis of the facts and circumstances that existed at the initial recognition of the financial asset, an entity shall assess the contractual cash flow characteristics of that financial asset on the basis of the facts and circumstances that existed at the initial recognition of the financial asset without taking into account the exception for prepayment features in paragraph B4.1.12. (See also paragraph 42S of IFRS 7.)
*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.
IRL New Ireland Fund Inc (The) Common Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba3 | Ba3 |
Income Statement | Ba3 | Baa2 |
Balance Sheet | Caa2 | B3 |
Leverage Ratios | B2 | C |
Cash Flow | Baa2 | B1 |
Rates of Return and Profitability | Baa2 | Baa2 |
*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
New Ireland Fund Inc (The) Common Stock is assigned short-term Ba3 & long-term Ba3 estimated rating. New Ireland Fund Inc (The) Common Stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Ridge Regression1,2,3,4 and it is concluded that the IRL stock is predictable in the short/long term. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Buy
Prediction Confidence Score
References
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- Bengio Y, Schwenk H, Senécal JS, Morin F, Gauvain JL. 2006. Neural probabilistic language models. In Innovations in Machine Learning: Theory and Applications, ed. DE Holmes, pp. 137–86. Berlin: Springer
- 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
Frequently Asked Questions
Q: What is the prediction methodology for IRL stock?A: IRL stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Ridge Regression
Q: Is IRL stock a buy or sell?
A: The dominant strategy among neural network is to Buy IRL Stock.
Q: Is New Ireland Fund Inc (The) Common Stock stock a good investment?
A: The consensus rating for New Ireland Fund Inc (The) Common Stock is Buy and is assigned short-term Ba3 & long-term Ba3 estimated rating.
Q: What is the consensus rating of IRL stock?
A: The consensus rating for IRL is Buy.
Q: What is the prediction period for IRL stock?
A: The prediction period for IRL is 3 Month
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