AUC Score :
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n:
Methodology : Supervised Machine Learning (ML)
Hypothesis Testing : Pearson Correlation
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
RETAIL FOOD GROUP LIMITED prediction model is evaluated with Supervised Machine Learning (ML) and Pearson Correlation1,2,3,4 and it is concluded that the RFG stock is predictable in the short/long term. Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell
Key Points
- How do you know when a stock will go up or down?
- What is Markov decision process in reinforcement learning?
- Operational Risk
RFG Target Price Prediction Modeling Methodology
We consider RETAIL FOOD GROUP LIMITED Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of RFG 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(Pearson Correlation)5,6,7= X R(Supervised Machine Learning (ML)) X S(n):→ 3 Month
n:Time series to forecast
p:Price signals of RFG stock
j:Nash equilibria (Neural Network)
k:Dominated move
a:Best response for target price
Supervised Machine Learning (ML)
Supervised machine learning (ML) is a type of machine learning where a model is trained on labeled data. This means that the data has been tagged with the correct output for the input data. The model learns to predict the output for new input data based on the labeled data. Supervised ML is a powerful tool that can be used for a variety of tasks, including classification, regression, and forecasting. Classification tasks involve predicting the category of an input data, such as whether an email is spam or not. Regression tasks involve predicting a numerical value for an input data, such as the price of a house. Forecasting tasks involve predicting future values for a time series, such as the sales of a product.Pearson Correlation
Pearson correlation, also known as Pearson's product-moment correlation, is a measure of the linear relationship between two variables. It is a statistical measure that assesses the strength and direction of a linear relationship between two variables. The sign of the correlation coefficient indicates the direction of the relationship, while the magnitude of the correlation coefficient indicates the strength of the relationship. A correlation coefficient of 0.9 indicates a strong positive correlation, while a correlation coefficient of 0.2 indicates a weak positive correlation.
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?
RFG Stock Forecast (Buy or Sell)
Sample Set: Neural NetworkStock/Index: RFG RETAIL FOOD GROUP LIMITED
Time series to forecast: 3 Month
According to price forecasts, the dominant strategy among neural network is: Sell
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 Supervised Machine Learning (ML) based RFG Stock Prediction Model
- The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding
- When designating a group of items as the hedged item, or a combination of financial instruments as the hedging instrument, an entity shall prospectively cease applying paragraphs 6.8.4–6.8.6 to an individual item or financial instrument in accordance with paragraphs 6.8.9, 6.8.10, or 6.8.11, as relevant, when the uncertainty arising from interest rate benchmark reform is no longer present with respect to the hedged risk and/or the timing and the amount of the interest rate benchmark-based cash flows of that item or financial instrument.
- 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.)
- When designating a risk component as a hedged item, the hedge accounting requirements apply to that risk component in the same way as they apply to other hedged items that are not risk components. For example, the qualifying criteria apply, including that the hedging relationship must meet the hedge effectiveness requirements, and any hedge ineffectiveness must be measured and recognised.
*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.
RFG RETAIL FOOD GROUP LIMITED Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba3 | Ba1 |
Income Statement | Baa2 | B3 |
Balance Sheet | Ba2 | Ba3 |
Leverage Ratios | C | Baa2 |
Cash Flow | Baa2 | Baa2 |
Rates of Return and Profitability | Caa2 | 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
RETAIL FOOD GROUP LIMITED is assigned short-term Ba3 & long-term Ba1 estimated rating. RETAIL FOOD GROUP LIMITED prediction model is evaluated with Supervised Machine Learning (ML) and Pearson Correlation1,2,3,4 and it is concluded that the RFG stock is predictable in the short/long term. According to price forecasts for 3 Month period, the dominant strategy among neural network is: Sell
Prediction Confidence Score
References
- C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
- P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
- Chamberlain G. 2000. Econometrics and decision theory. J. Econom. 95:255–83
- S. Bhatnagar. An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes. Systems & Control Letters, 59(12):760–766, 2010
- Hastie T, Tibshirani R, Wainwright M. 2015. Statistical Learning with Sparsity: The Lasso and Generalizations. New York: CRC Press
- Bessler, D. A. S. W. Fuller (1993), "Cointegration between U.S. wheat markets," Journal of Regional Science, 33, 481–501.
- ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. The Dow Jones Industrial Average (No. Stock Analysis). AC Investment Research.
Frequently Asked Questions
Q: What is the prediction methodology for RFG stock?A: RFG stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Pearson Correlation
Q: Is RFG stock a buy or sell?
A: The dominant strategy among neural network is to Sell RFG Stock.
Q: Is RETAIL FOOD GROUP LIMITED stock a good investment?
A: The consensus rating for RETAIL FOOD GROUP LIMITED is Sell and is assigned short-term Ba3 & long-term Ba1 estimated rating.
Q: What is the consensus rating of RFG stock?
A: The consensus rating for RFG is Sell.
Q: What is the prediction period for RFG stock?
A: The prediction period for RFG is 3 Month
People also ask
⚐ What are the top stocks to invest in right now?☵ What happens to stocks when they're delisted?