Modelling A.I. in Economics

Can stock prices be predicted? (FTSE 100 Index Stock Forecast)

The stock market has been an attractive field for a large number of organizers and investors to derive useful predictions. Fundamental knowledge of stock market can be utilised with technical indicators to investigate different perspectives of the financial market; also, the influence of various events, financial news, and/or opinions on investors' decisions and hence, market trends have been observed. Such information can be exploited to make reliable predictions and achieve higher profitability. Computational intelligence has emerged with various deep neural network (DNN) techniques to address complex stock market problems. We evaluate FTSE 100 Index prediction models with Ensemble Learning (ML) and Logistic Regression1,2,3,4 and conclude that the FTSE 100 Index 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 Sell FTSE 100 Index stock.


Keywords: FTSE 100 Index, FTSE 100 Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Market Risk
  2. Operational Risk
  3. Technical Analysis with Algorithmic Trading

FTSE 100 Index Target Price Prediction Modeling Methodology

Stock market forecasting is considered to be a challenging topic among time series forecasting. This study proposes a novel two-stage ensemble machine learning model named SVR-ENANFIS for stock price prediction by combining features of support vector regression (SVR) and ensemble adaptive neuro fuzzy inference system (ENANFIS). We consider FTSE 100 Index Stock Decision Process with Logistic Regression where A is the set of discrete actions of FTSE 100 Index 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(Logistic 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(Ensemble Learning (ML)) X S(n):→ (n+4 weeks) R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of FTSE 100 Index 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?

FTSE 100 Index Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: FTSE 100 Index FTSE 100 Index
Time series to forecast n: 25 Sep 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell FTSE 100 Index 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

FTSE 100 Index assigned short-term Ba3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Ensemble Learning (ML) with Logistic Regression1,2,3,4 and conclude that the FTSE 100 Index 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 Sell FTSE 100 Index stock.

Financial State Forecast for FTSE 100 Index Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba3
Operational Risk 6349
Market Risk8957
Technical Analysis5977
Fundamental Analysis6066
Risk Unsystematic6673

Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 807 signals.

References

  1. 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
  2. Chernozhukov V, Demirer M, Duflo E, Fernandez-Val I. 2018b. Generic machine learning inference on heteroge- nous treatment effects in randomized experiments. NBER Work. Pap. 24678
  3. H. Khalil and J. Grizzle. Nonlinear systems, volume 3. Prentice hall Upper Saddle River, 2002.
  4. M. J. Hausknecht and P. Stone. Deep recurrent Q-learning for partially observable MDPs. CoRR, abs/1507.06527, 2015
  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. Dudik M, Langford J, Li L. 2011. Doubly robust policy evaluation and learning. In Proceedings of the 28th International Conference on Machine Learning, pp. 1097–104. La Jolla, CA: Int. Mach. Learn. Soc.
  7. K. Tuyls and G. Weiss. Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3): 41–52, 2012
Frequently Asked QuestionsQ: What is the prediction methodology for FTSE 100 Index stock?
A: FTSE 100 Index stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Logistic Regression
Q: Is FTSE 100 Index stock a buy or sell?
A: The dominant strategy among neural network is to Sell FTSE 100 Index Stock.
Q: Is FTSE 100 Index stock a good investment?
A: The consensus rating for FTSE 100 Index is Sell and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of FTSE 100 Index stock?
A: The consensus rating for FTSE 100 Index is Sell.
Q: What is the prediction period for FTSE 100 Index stock?
A: The prediction period for FTSE 100 Index is (n+4 weeks)



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