Modelling A.I. in Economics

LON:BHMG BH MACRO LIMITED (Forecast)

Outlook: BH MACRO LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 26 May 2023 for (n+1 year)
Methodology : Modular Neural Network (Emotional Trigger/Responses Analysis)

Abstract

BH MACRO LIMITED prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Factor1,2,3,4 and it is concluded that the LON:BHMG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

  1. Is Target price a good indicator?
  2. What are the most successful trading algorithms?
  3. What are main components of Markov decision process?

LON:BHMG Target Price Prediction Modeling Methodology

We consider BH MACRO LIMITED Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of LON:BHMG 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(Modular Neural Network (Emotional Trigger/Responses Analysis)) X S(n):→ (n+1 year) S = s 1 s 2 s 3

n:Time series to forecast

p:Price signals of LON:BHMG 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?

LON:BHMG Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: LON:BHMG BH MACRO LIMITED
Time series to forecast n: 26 May 2023 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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%

IFRS Reconciliation Adjustments for BH MACRO 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. If an entity previously accounted at cost (in accordance with IAS 39), for an investment in an equity instrument that does not have a quoted price in an active market for an identical instrument (ie a Level 1 input) (or for a derivative asset that is linked to and must be settled by delivery of such an equity instrument) it shall measure that instrument at fair value at the date of initial application. Any difference between the previous carrying amount and the fair value shall be recognised in the opening retained earnings (or other component of equity, as appropriate) of the reporting period that includes the date of initial application.
  3. Conversely, if changes in the extent of offset indicate that the fluctuation is around a hedge ratio that is different from the hedge ratio that is currently used for that hedging relationship, or that there is a trend leading away from that hedge ratio, hedge ineffectiveness can be reduced by adjusting the hedge ratio, whereas retaining the hedge ratio would increasingly produce hedge ineffectiveness. Hence, in such circumstances, an entity must evaluate whether the hedging relationship reflects an imbalance between the weightings of the hedged item and the hedging instrument that would create hedge ineffectiveness (irrespective of whether recognised or not) that could result in an accounting outcome that would be inconsistent with the purpose of hedge accounting. If the hedge ratio is adjusted, it also affects the measurement and recognition of hedge ineffectiveness because, on rebalancing, the hedge ineffectiveness of the hedging relationship must be determined and recognised immediately before adjusting the hedging relationship in accordance with paragraph B6.5.8.
  4. That the transferee is unlikely to sell the transferred asset does not, of itself, mean that the transferor has retained control of the transferred asset. However, if a put option or guarantee constrains the transferee from selling the transferred asset, then the transferor has retained control of the transferred asset. For example, if a put option or guarantee is sufficiently valuable it constrains the transferee from selling the transferred asset because the transferee would, in practice, not sell the transferred asset to a third party without attaching a similar option or other restrictive conditions. Instead, the transferee would hold the transferred asset so as to obtain payments under the guarantee or put option. Under these circumstances the transferor has retained control of the transferred asset.

*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.

Conclusions

BH MACRO LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. BH MACRO LIMITED prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Factor1,2,3,4 and it is concluded that the LON:BHMG stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

LON:BHMG BH MACRO LIMITED Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2B3
Balance SheetCaa2Caa2
Leverage RatiosBa3Ba3
Cash FlowBaa2B2
Rates of Return and ProfitabilityCaa2Ba3

*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?

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 599 signals.

References

  1. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
  2. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
  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. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
  5. D. S. Bernstein, S. Zilberstein, and N. Immerman. The complexity of decentralized control of Markov Decision Processes. In UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30 - July 3, 2000, pages 32–37, 2000.
  6. ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market? (No. Stock Analysis). AC Investment Research.
  7. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
Frequently Asked QuestionsQ: What is the prediction methodology for LON:BHMG stock?
A: LON:BHMG stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Factor
Q: Is LON:BHMG stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes LON:BHMG Stock.
Q: Is BH MACRO LIMITED stock a good investment?
A: The consensus rating for BH MACRO LIMITED is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:BHMG stock?
A: The consensus rating for LON:BHMG is Wait until speculative trend diminishes.
Q: What is the prediction period for LON:BHMG stock?
A: The prediction period for LON:BHMG is (n+1 year)

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