Modelling A.I. in Economics

Can we predict stock market using machine learning? (LON:FCAP Stock Forecast)

Recently, a lot of interesting work has been done in the area of applying Machine Learning Algorithms for analyzing price patterns and predicting stock prices and index changes. Most stock traders nowadays depend on Intelligent Trading Systems which help them in predicting prices based on various situations and conditions, thereby helping them in making instantaneous investment decisions. We evaluate FINNCAP GROUP PLC prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Statistical Hypothesis Testing1,2,3,4 and conclude that the LON:FCAP 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 Buy LON:FCAP stock.


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

Key Points

  1. What are the most successful trading algorithms?
  2. Is now good time to invest?
  3. What is statistical models in machine learning?

LON:FCAP Target Price Prediction Modeling Methodology

Stock markets are affected by many uncertainties and interrelated economic and political factors at both local and global levels. The key to successful stock market forecasting is achieving best results with minimum required input data. To determine the set of relevant factors for making accurate predictions is a complicated task and so regular stock market analysis is very essential. More specifically, the stock market's movements are analyzed and predicted in order to retrieve knowledge that could guide investors on when to buy and sell. We consider FINNCAP GROUP PLC Stock Decision Process with Statistical Hypothesis Testing where A is the set of discrete actions of LON:FCAP 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 (Emotional Trigger/Responses Analysis)) X S(n):→ (n+6 month) e x rx

n:Time series to forecast

p:Price signals of LON:FCAP 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:FCAP Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: LON:FCAP FINNCAP GROUP PLC
Time series to forecast n: 13 Oct 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Buy LON:FCAP 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

FINNCAP GROUP PLC assigned short-term B3 & long-term Baa2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Statistical Hypothesis Testing1,2,3,4 and conclude that the LON:FCAP 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 Buy LON:FCAP stock.

Financial State Forecast for LON:FCAP Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B3Baa2
Operational Risk 3774
Market Risk4479
Technical Analysis3386
Fundamental Analysis5149
Risk Unsystematic6690

Prediction Confidence Score

Trust metric by Neural Network: 93 out of 100 with 773 signals.

References

  1. Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
  2. Bennett J, Lanning S. 2007. The Netflix prize. In Proceedings of KDD Cup and Workshop 2007, p. 35. New York: ACM
  3. M. J. Hausknecht. Cooperation and Communication in Multiagent Deep Reinforcement Learning. PhD thesis, The University of Texas at Austin, 2016
  4. J. G. Schneider, W. Wong, A. W. Moore, and M. A. Riedmiller. Distributed value functions. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 371–378, 1999.
  5. Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
  6. Hoerl AE, Kennard RW. 1970. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:55–67
  7. Artis, M. J. W. Zhang (1990), "BVAR forecasts for the G-7," International Journal of Forecasting, 6, 349–362.
Frequently Asked QuestionsQ: What is the prediction methodology for LON:FCAP stock?
A: LON:FCAP stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Statistical Hypothesis Testing
Q: Is LON:FCAP stock a buy or sell?
A: The dominant strategy among neural network is to Buy LON:FCAP Stock.
Q: Is FINNCAP GROUP PLC stock a good investment?
A: The consensus rating for FINNCAP GROUP PLC is Buy and assigned short-term B3 & long-term Baa2 forecasted stock rating.
Q: What is the consensus rating of LON:FCAP stock?
A: The consensus rating for LON:FCAP is Buy.
Q: What is the prediction period for LON:FCAP stock?
A: The prediction period for LON:FCAP is (n+6 month)



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