Modelling A.I. in Economics

Buy, sell or hold: LON:BMD Stock Forecast

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 BARONSMEAD SECOND VENTURE TRUST PLC prediction models with Modular Neural Network (Speculative Sentiment Analysis) and Statistical Hypothesis Testing1,2,3,4 and conclude that the LON:BMD stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell LON:BMD stock.


Keywords: LON:BMD, BARONSMEAD SECOND VENTURE TRUST PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Is it better to buy and sell or hold?
  2. How do predictive algorithms actually work?
  3. What is a prediction confidence?

LON:BMD Target Price Prediction Modeling Methodology

In this paper a Bayesian regularized artificial neural network is proposed as a novel method to forecast financial market behavior. Daily market prices and financial technical indicators are utilized as inputs to predict the one day future closing price of individual stocks. The prediction of stock price movement is generally considered to be a challenging and important task for financial time series analysis. We consider BARONSMEAD SECOND VENTURE TRUST PLC Stock Decision Process with Statistical Hypothesis Testing where A is the set of discrete actions of LON:BMD 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(Statistical Hypothesis Testing)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 (Speculative Sentiment Analysis)) X S(n):→ (n+1 year) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of LON:BMD 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:BMD Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: LON:BMD BARONSMEAD SECOND VENTURE TRUST PLC
Time series to forecast n: 16 Oct 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell LON:BMD 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%


Conclusions

BARONSMEAD SECOND VENTURE TRUST PLC assigned short-term B1 & long-term B3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) with Statistical Hypothesis Testing1,2,3,4 and conclude that the LON:BMD stock is predictable in the short/long term. According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell LON:BMD stock.

Financial State Forecast for LON:BMD Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B1B3
Operational Risk 6631
Market Risk5261
Technical Analysis3347
Fundamental Analysis6745
Risk Unsystematic8839

Prediction Confidence Score

Trust metric by Neural Network: 74 out of 100 with 792 signals.

References

  1. Hirano K, Porter JR. 2009. Asymptotics for statistical treatment rules. Econometrica 77:1683–701
  2. M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001
  3. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
  4. Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
  5. Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
  6. A. Tamar and S. Mannor. Variance adjusted actor critic algorithms. arXiv preprint arXiv:1310.3697, 2013.
  7. M. Ono, M. Pavone, Y. Kuwata, and J. Balaram. Chance-constrained dynamic programming with application to risk-aware robotic space exploration. Autonomous Robots, 39(4):555–571, 2015
Frequently Asked QuestionsQ: What is the prediction methodology for LON:BMD stock?
A: LON:BMD stock prediction methodology: We evaluate the prediction models Modular Neural Network (Speculative Sentiment Analysis) and Statistical Hypothesis Testing
Q: Is LON:BMD stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:BMD Stock.
Q: Is BARONSMEAD SECOND VENTURE TRUST PLC stock a good investment?
A: The consensus rating for BARONSMEAD SECOND VENTURE TRUST PLC is Sell and assigned short-term B1 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of LON:BMD stock?
A: The consensus rating for LON:BMD is Sell.
Q: What is the prediction period for LON:BMD stock?
A: The prediction period for LON:BMD is (n+1 year)

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