Modelling A.I. in Economics

Buy or Sell: LON:ZCC Stock

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 ZCCM INVESTMENTS HOLDINGS PLC prediction models with Modular Neural Network (Market Volatility Analysis) and Paired T-Test1,2,3,4 and conclude that the LON:ZCC 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:ZCC stock.


Keywords: LON:ZCC, ZCCM INVESTMENTS HOLDINGS PLC, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. How useful are statistical predictions?
  2. Game Theory
  3. How do you pick a stock?

LON:ZCC Target Price Prediction Modeling Methodology

This paper tries to address the problem of stock market prediction leveraging artificial intelligence (AI) strategies. The stock market prediction can be modeled based on two principal analyses called technical and fundamental. In the technical analysis approach, the regression machine learning (ML) algorithms are employed to predict the stock price trend at the end of a business day based on the historical price data. In contrast, in the fundamental analysis, the classification ML algorithms are applied to classify the public sentiment based on news and social media. We consider ZCCM INVESTMENTS HOLDINGS PLC Stock Decision Process with Paired T-Test where A is the set of discrete actions of LON:ZCC 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(Paired T-Test)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 (Market Volatility Analysis)) X S(n):→ (n+1 year) e x rx

n:Time series to forecast

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

Sample Set: Neural Network
Stock/Index: LON:ZCC ZCCM INVESTMENTS HOLDINGS 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:ZCC 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

ZCCM INVESTMENTS HOLDINGS PLC assigned short-term B2 & long-term B3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with Paired T-Test1,2,3,4 and conclude that the LON:ZCC 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:ZCC stock.

Financial State Forecast for LON:ZCC Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2B3
Operational Risk 3258
Market Risk6838
Technical Analysis5637
Fundamental Analysis7645
Risk Unsystematic3935

Prediction Confidence Score

Trust metric by Neural Network: 86 out of 100 with 621 signals.

References

  1. Hill JL. 2011. Bayesian nonparametric modeling for causal inference. J. Comput. Graph. Stat. 20:217–40
  2. Candès EJ, Recht B. 2009. Exact matrix completion via convex optimization. Found. Comput. Math. 9:717
  3. Belloni A, Chernozhukov V, Hansen C. 2014. High-dimensional methods and inference on structural and treatment effects. J. Econ. Perspect. 28:29–50
  4. Semenova V, Goldman M, Chernozhukov V, Taddy M. 2018. Orthogonal ML for demand estimation: high dimensional causal inference in dynamic panels. arXiv:1712.09988 [stat.ML]
  5. Friedberg R, Tibshirani J, Athey S, Wager S. 2018. Local linear forests. arXiv:1807.11408 [stat.ML]
  6. Varian HR. 2014. Big data: new tricks for econometrics. J. Econ. Perspect. 28:3–28
  7. Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
Frequently Asked QuestionsQ: What is the prediction methodology for LON:ZCC stock?
A: LON:ZCC stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Paired T-Test
Q: Is LON:ZCC stock a buy or sell?
A: The dominant strategy among neural network is to Sell LON:ZCC Stock.
Q: Is ZCCM INVESTMENTS HOLDINGS PLC stock a good investment?
A: The consensus rating for ZCCM INVESTMENTS HOLDINGS PLC is Sell and assigned short-term B2 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of LON:ZCC stock?
A: The consensus rating for LON:ZCC is Sell.
Q: What is the prediction period for LON:ZCC stock?
A: The prediction period for LON:ZCC is (n+1 year)



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