Modelling A.I. in Economics

Can neural networks predict stock market? (LON:BMTO Stock Forecast)

This study aims to predict the direction of stock prices by integrating time-varying effective transfer entropy (ETE) and various machine learning algorithms. At first, we explore that the ETE based on 3 and 6 months moving windows can be regarded as the market explanatory variable by analyzing the association between the financial crises and Granger-causal relationships among the stocks. We evaluate BRAIME GROUP PLC prediction models with Modular Neural Network (Financial Sentiment Analysis) and Linear Regression1,2,3,4 and conclude that the LON:BMTO 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 Buy LON:BMTO stock.


Keywords: LON:BMTO, BRAIME GROUP PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Should I buy stocks now or wait amid such uncertainty?
  2. Market Signals
  3. What are the most successful trading algorithms?

LON:BMTO Target Price Prediction Modeling Methodology

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 consider BRAIME GROUP PLC Stock Decision Process with Linear Regression where A is the set of discrete actions of LON:BMTO 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(Linear 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(Modular Neural Network (Financial Sentiment Analysis)) X S(n):→ (n+4 weeks) R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of LON:BMTO stock

j:Nash equilibria

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

Sample Set: Neural Network
Stock/Index: LON:BMTO BRAIME GROUP PLC
Time series to forecast n: 26 Oct 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Buy LON:BMTO 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 BRAIME GROUP PLC

  1. An entity's business model is determined at a level that reflects how groups of financial assets are managed together to achieve a particular business objective. The entity's business model does not depend on management's intentions for an individual instrument. Accordingly, this condition is not an instrument-by-instrument approach to classification and should be determined on a higher level of aggregation. However, a single entity may have more than one business model for managing its financial instruments. Consequently, classification need not be determined at the reporting entity level. For example, an entity may hold a portfolio of investments that it manages in order to collect contractual cash flows and another portfolio of investments that it manages in order to trade to realise fair value changes. Similarly, in some circumstances, it may be appropriate to separate a portfolio of financial assets into subportfolios in order to reflect the level at which an entity manages those financial assets. For example, that may be the case if an entity originates or purchases a portfolio of mortgage loans and manages some of the loans with an objective of collecting contractual cash flows and manages the other loans with an objective of selling them.
  2. If a financial instrument that was previously recognised as a financial asset is measured at fair value through profit or loss and its fair value decreases below zero, it is a financial liability measured in accordance with paragraph 4.2.1. However, hybrid contracts with hosts that are assets within the scope of this Standard are always measured in accordance with paragraph 4.3.2.
  3. An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.
  4. If a financial instrument that was previously recognised as a financial asset is measured at fair value through profit or loss and its fair value decreases below zero, it is a financial liability measured in accordance with paragraph 4.2.1. However, hybrid contracts with hosts that are assets within the scope of this Standard are always measured in accordance with paragraph 4.3.2.

*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

BRAIME GROUP PLC assigned short-term Ba2 & long-term B1 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) with Linear Regression1,2,3,4 and conclude that the LON:BMTO 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 Buy LON:BMTO stock.

Financial State Forecast for LON:BMTO BRAIME GROUP PLC Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba2B1
Operational Risk 7332
Market Risk3368
Technical Analysis8576
Fundamental Analysis8444
Risk Unsystematic6875

Prediction Confidence Score

Trust metric by Neural Network: 82 out of 100 with 477 signals.

References

  1. Byron, R. P. O. Ashenfelter (1995), "Predicting the quality of an unborn grange," Economic Record, 71, 40–53.
  2. Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
  3. Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
  4. T. Shardlow and A. Stuart. A perturbation theory for ergodic Markov chains and application to numerical approximations. SIAM journal on numerical analysis, 37(4):1120–1137, 2000
  5. A. Eck, L. Soh, S. Devlin, and D. Kudenko. Potential-based reward shaping for finite horizon online POMDP planning. Autonomous Agents and Multi-Agent Systems, 30(3):403–445, 2016
  6. Jacobs B, Donkers B, Fok D. 2014. Product Recommendations Based on Latent Purchase Motivations. Rotterdam, Neth.: ERIM
  7. Ashley, R. (1983), "On the usefulness of macroeconomic forecasts as inputs to forecasting models," Journal of Forecasting, 2, 211–223.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:BMTO stock?
A: LON:BMTO stock prediction methodology: We evaluate the prediction models Modular Neural Network (Financial Sentiment Analysis) and Linear Regression
Q: Is LON:BMTO stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:BMTO Stock.
Q: Is BRAIME GROUP PLC stock a good investment?
A: The consensus rating for BRAIME GROUP PLC is Buy and assigned short-term Ba2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of LON:BMTO stock?
A: The consensus rating for LON:BMTO is Buy.
Q: What is the prediction period for LON:BMTO stock?
A: The prediction period for LON:BMTO is (n+4 weeks)



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