Modelling A.I. in Economics

FRI FINBAR GROUP LIMITED (Forecast)

FINBAR GROUP LIMITED Research Report

Summary

In this paper, we introduce a new prediction model depend on Bidirectional Gated Recurrent Unit (BGRU). Our predictive model relies on both online financial news and historical stock prices data to predict the stock movements in the future. We evaluate FINBAR GROUP LIMITED prediction models with Deductive Inference (ML) and Multiple Regression1,2,3,4 and conclude that the FRI stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold FRI stock.

Key Points

  1. What are the most successful trading algorithms?
  2. What is the best way to predict stock prices?
  3. Stock Rating

FRI Target Price Prediction Modeling Methodology

We consider FINBAR GROUP LIMITED Decision Process with Deductive Inference (ML) where A is the set of discrete actions of FRI 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(Multiple Regression)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(Deductive Inference (ML)) X S(n):→ (n+4 weeks) r s rs

n:Time series to forecast

p:Price signals of FRI 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?

FRI Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: FRI FINBAR GROUP LIMITED
Time series to forecast n: 01 Dec 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold FRI 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 FINBAR GROUP LIMITED

  1. The accounting for the forward element of forward contracts in accordance with paragraph 6.5.16 applies only to the extent that the forward element relates to the hedged item (aligned forward element). The forward element of a forward contract relates to the hedged item if the critical terms of the forward contract (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the forward contract and the hedged item are not fully aligned, an entity shall determine the aligned forward element, ie how much of the forward element included in the forward contract (actual forward element) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.16). An entity determines the aligned forward element using the valuation of the forward contract that would have critical terms that perfectly match the hedged item.
  2. In some cases, the qualitative and non-statistical quantitative information available may be sufficient to determine that a financial instrument has met the criterion for the recognition of a loss allowance at an amount equal to lifetime expected credit losses. That is, the information does not need to flow through a statistical model or credit ratings process in order to determine whether there has been a significant increase in the credit risk of the financial instrument. In other cases, an entity may need to consider other information, including information from its statistical models or credit ratings processes.
  3. In some circumstances an entity does not have reasonable and supportable information that is available without undue cost or effort to measure lifetime expected credit losses on an individual instrument basis. In that case, lifetime expected credit losses shall be recognised on a collective basis that considers comprehensive credit risk information. This comprehensive credit risk information must incorporate not only past due information but also all relevant credit information, including forward-looking macroeconomic information, in order to approximate the result of recognising lifetime expected credit losses when there has been a significant increase in credit risk since initial recognition on an individual instrument level.
  4. However, in some cases, the time value of money element may be modified (ie imperfect). That would be the case, for example, if a financial asset's interest rate is periodically reset but the frequency of that reset does not match the tenor of the interest rate (for example, the interest rate resets every month to a one-year rate) or if a financial asset's interest rate is periodically reset to an average of particular short- and long-term interest rates. In such cases, an entity must assess the modification to determine whether the contractual cash flows represent solely payments of principal and interest on the principal amount outstanding. In some circumstances, the entity may be able to make that determination by performing a qualitative assessment of the time value of money element whereas, in other circumstances, it may be necessary to perform a quantitative assessment.

*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

FINBAR GROUP LIMITED assigned short-term B3 & long-term B2 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Multiple Regression1,2,3,4 and conclude that the FRI stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Hold FRI stock.

Financial State Forecast for FRI FINBAR GROUP LIMITED Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B3B2
Operational Risk 3069
Market Risk8646
Technical Analysis7379
Fundamental Analysis3338
Risk Unsystematic3541

Prediction Confidence Score

Trust metric by Neural Network: 83 out of 100 with 669 signals.

References

  1. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
  2. Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.
  3. K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
  4. Bertsimas D, King A, Mazumder R. 2016. Best subset selection via a modern optimization lens. Ann. Stat. 44:813–52
  5. S. Bhatnagar. An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes. Systems & Control Letters, 59(12):760–766, 2010
  6. Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20
  7. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
Frequently Asked QuestionsQ: What is the prediction methodology for FRI stock?
A: FRI stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Multiple Regression
Q: Is FRI stock a buy or sell?
A: The dominant strategy among neural network is to Hold FRI Stock.
Q: Is FINBAR GROUP LIMITED stock a good investment?
A: The consensus rating for FINBAR GROUP LIMITED is Hold and assigned short-term B3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of FRI stock?
A: The consensus rating for FRI is Hold.
Q: What is the prediction period for FRI stock?
A: The prediction period for FRI is (n+4 weeks)

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