Buy or Sell: LON:FIF Stock

FINSBURY FOOD GROUP PLC Research Report

Summary

Impact of many factors on the stock prices makes the stock prediction a difficult and highly complicated task. In this paper, machine learning techniques have been applied for the stock price prediction in order to overcome such difficulties. In the implemented work, five models have been developed and their performances are compared in predicting the stock market trends. We evaluate FINSBURY FOOD GROUP PLC prediction models with Ensemble Learning (ML) and Factor1,2,3,4 and conclude that the LON:FIF stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:FIF stock.

Key Points

  1. Is now good time to invest?
  2. How do you know when a stock will go up or down?
  3. Short/Long Term Stocks

LON:FIF Target Price Prediction Modeling Methodology

We consider FINSBURY FOOD GROUP PLC Stock Decision Process with Ensemble Learning (ML) where A is the set of discrete actions of LON:FIF 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(Ensemble Learning (ML)) X S(n):→ (n+6 month) i = 1 n r i

n:Time series to forecast

p:Price signals of LON:FIF stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

 

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How do AC Investment Research machine learning (predictive) algorithms actually work?

LON:FIF Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:FIF FINSBURY FOOD GROUP PLC
Time series to forecast n: 19 Nov 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:FIF 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 FINSBURY FOOD GROUP PLC

  1. As noted in paragraph B4.3.1, when an entity becomes a party to a hybrid contract with a host that is not an asset within the scope of this Standard and with one or more embedded derivatives, paragraph 4.3.3 requires the entity to identify any such embedded derivative, assess whether it is required to be separated from the host contract and, for those that are required to be separated, measure the derivatives at fair value at initial recognition and subsequently. These requirements can be more complex, or result in less reliable measures, than measuring the entire instrument at fair value through profit or loss. For that reason this Standard permits the entire hybrid contract to be designated as at fair value through profit or loss.
  2. If a financial instrument is designated in accordance with paragraph 6.7.1 as measured at fair value through profit or loss after its initial recognition, or was previously not recognised, the difference at the time of designation between the carrying amount, if any, and the fair value shall immediately be recognised in profit or loss. For financial assets measured at fair value through other comprehensive income in accordance with paragraph 4.1.2A, the cumulative gain or loss previously recognised in other comprehensive income shall immediately be reclassified from equity to profit or loss as a reclassification adjustment.
  3. An entity may manage and evaluate the performance of a group of financial liabilities or financial assets and financial liabilities in such a way that measuring that group at fair value through profit or loss results in more relevant information. The focus in this instance is on the way the entity manages and evaluates performance, instead of on the nature of its financial instruments.
  4. An entity's estimate of expected credit losses on loan commitments shall be consistent with its expectations of drawdowns on that loan commitment, ie it shall consider the expected portion of the loan commitment that will be drawn down within 12 months of the reporting date when estimating 12-month expected credit losses, and the expected portion of the loan commitment that will be drawn down over the expected life of the loan commitment when estimating lifetime expected credit losses.

*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

FINSBURY FOOD GROUP PLC assigned short-term B3 & long-term B2 forecasted stock rating. We evaluate the prediction models Ensemble Learning (ML) with Factor1,2,3,4 and conclude that the LON:FIF stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold LON:FIF stock.

Financial State Forecast for LON:FIF FINSBURY FOOD GROUP PLC Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B3B2
Operational Risk 4651
Market Risk8158
Technical Analysis3847
Fundamental Analysis3784
Risk Unsystematic3933

Prediction Confidence Score

Trust metric by Neural Network: 84 out of 100 with 685 signals.

References

  1. Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
  2. S. Bhatnagar. An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes. Systems & Control Letters, 59(12):760–766, 2010
  3. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
  4. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
  5. Akgiray, V. (1989), "Conditional heteroscedasticity in time series of stock returns: Evidence and forecasts," Journal of Business, 62, 55–80.
  6. B. Derfer, N. Goodyear, K. Hung, C. Matthews, G. Paoni, K. Rollins, R. Rose, M. Seaman, and J. Wiles. Online marketing platform, August 17 2007. US Patent App. 11/893,765
  7. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:FIF stock?
A: LON:FIF stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Factor
Q: Is LON:FIF stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:FIF Stock.
Q: Is FINSBURY FOOD GROUP PLC stock a good investment?
A: The consensus rating for FINSBURY FOOD GROUP PLC is Hold and assigned short-term B3 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of LON:FIF stock?
A: The consensus rating for LON:FIF is Hold.
Q: What is the prediction period for LON:FIF stock?
A: The prediction period for LON:FIF is (n+6 month)

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