Modelling A.I. in Economics

RFA RARE FOODS AUSTRALIA LIMITED (Forecast)

RARE FOODS AUSTRALIA LIMITED Research Report

Summary

With the up-gradation of technology and exploration of new machine learning models, the stock market data analysis has gained attention as these models provide a platform for businessman and traders to choose more profitable stocks. As these data are in large volumes and highly complex so a need of more efficient machine learning model for daily predictions is always looked upon. We evaluate RARE FOODS AUSTRALIA LIMITED prediction models with Supervised Machine Learning (ML) and Factor1,2,3,4 and conclude that the RFA stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy RFA stock.

Key Points

  1. Probability Distribution
  2. Should I buy stocks now or wait amid such uncertainty?
  3. How do you decide buy or sell a stock?

RFA Target Price Prediction Modeling Methodology

We consider RARE FOODS AUSTRALIA LIMITED Decision Process with Supervised Machine Learning (ML) where A is the set of discrete actions of RFA 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(Factor)5,6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Supervised Machine Learning (ML)) X S(n):→ (n+3 month) i = 1 n r i

n:Time series to forecast

p:Price signals of RFA 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?

RFA Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: RFA RARE FOODS AUSTRALIA LIMITED
Time series to forecast n: 01 Dec 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy RFA stock.

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for RARE FOODS AUSTRALIA LIMITED

  1. Paragraph 5.7.5 permits an entity to make an irrevocable election to present in other comprehensive income subsequent changes in the fair value of particular investments in equity instruments. Such an investment is not a monetary item. Accordingly, the gain or loss that is presented in other comprehensive income in accordance with paragraph 5.7.5 includes any related foreign exchange component.
  2. An entity that first applies IFRS 17 as amended in June 2020 after it first applies this Standard shall apply paragraphs 7.2.39–7.2.42. The entity shall also apply the other transition requirements in this Standard necessary for applying these amendments. For that purpose, references to the date of initial application shall be read as referring to the beginning of the reporting period in which an entity first applies these amendments (date of initial application of these amendments).
  3. For example, Entity A, whose functional currency is its local currency, has a firm commitment to pay FC150,000 for advertising expenses in nine months' time and a firm commitment to sell finished goods for FC150,000 in 15 months' time. Entity A enters into a foreign currency derivative that settles in nine months' time under which it receives FC100 and pays CU70. Entity A has no other exposures to FC. Entity A does not manage foreign currency risk on a net basis. Hence, Entity A cannot apply hedge accounting for a hedging relationship between the foreign currency derivative and a net position of FC100 (consisting of FC150,000 of the firm purchase commitment—ie advertising services—and FC149,900 (of the FC150,000) of the firm sale commitment) for a nine-month period.
  4. At the date of initial application, an entity shall assess whether a financial asset meets the condition in paragraphs 4.1.2(a) or 4.1.2A(a) on the basis of the facts and circumstances that exist at that date. The resulting classification shall be applied retrospectively irrespective of the entity's business model in prior reporting periods.

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

RARE FOODS AUSTRALIA LIMITED assigned short-term Ba3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Supervised Machine Learning (ML) with Factor1,2,3,4 and conclude that the RFA stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Buy RFA stock.

Financial State Forecast for RFA RARE FOODS AUSTRALIA LIMITED Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba3
Operational Risk 3870
Market Risk6980
Technical Analysis8759
Fundamental Analysis3438
Risk Unsystematic9058

Prediction Confidence Score

Trust metric by Neural Network: 79 out of 100 with 747 signals.

References

  1. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
  2. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
  3. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
  4. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015
  5. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
  6. Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
  7. K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
Frequently Asked QuestionsQ: What is the prediction methodology for RFA stock?
A: RFA stock prediction methodology: We evaluate the prediction models Supervised Machine Learning (ML) and Factor
Q: Is RFA stock a buy or sell?
A: The dominant strategy among neural network is to Buy RFA Stock.
Q: Is RARE FOODS AUSTRALIA LIMITED stock a good investment?
A: The consensus rating for RARE FOODS AUSTRALIA LIMITED is Buy and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of RFA stock?
A: The consensus rating for RFA is Buy.
Q: What is the prediction period for RFA stock?
A: The prediction period for RFA is (n+3 month)

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