How do you predict if a stock will go up or down? (WIG20 Index Stock Prediction)

Abstract

We evaluate WIG20 Index prediction models with Deductive Inference (ML) and Chi-Square^1,2,3,4 and conclude that the WIG20 Index stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold WIG20 Index stock.

Keywords: WIG20 Index, WIG20 Index, 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. What are the most successful trading algorithms?
3. Is now good time to invest?

WIG20 Index Target Price Prediction Modeling Methodology

We consider WIG20 Index Stock Decision Process with Chi-Square where A is the set of discrete actions of WIG20 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(Chi-Square)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Deductive Inference (ML)) X S(n):→ (n+8 weeks) $\begin{array}{l}\int e^x\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of WIG20 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?

WIG20 Index Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: WIG20 Index WIG20 Index
Time series to forecast n: 02 Sep 2022 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold WIG20 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

WIG20 Index assigned short-term B2 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Deductive Inference (ML) with Chi-Square^1,2,3,4 and conclude that the WIG20 Index stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period: The dominant strategy among neural network is to Hold WIG20 Index stock.

Financial State Forecast for WIG20 Index Stock Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	Ba3
Operational Risk	55	40
Market Risk	34	87
Technical Analysis	46	69
Fundamental Analysis	76	87
Risk Unsystematic	76	48

Prediction Confidence Score

Trust metric by Neural Network: 73 out of 100 with 736 signals.

References

1. J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017
2. Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.
3. S. Proper and K. Tumer. Modeling difference rewards for multiagent learning (extended abstract). In Proceedings of the Eleventh International Joint Conference on Autonomous Agents and Multiagent Systems, Valencia, Spain, June 2012
4. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
5. Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.
6. Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
7. A. K. Agogino and K. Tumer. Analyzing and visualizing multiagent rewards in dynamic and stochastic environments. Journal of Autonomous Agents and Multi-Agent Systems, 17(2):320–338, 2008

Frequently Asked Questions

Q: What is the prediction methodology for WIG20 Index stock?
A: WIG20 Index stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Chi-Square
Q: Is WIG20 Index stock a buy or sell?
A: The dominant strategy among neural network is to Hold WIG20 Index Stock.
Q: Is WIG20 Index stock a good investment?
A: The consensus rating for WIG20 Index is Hold and assigned short-term B2 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of WIG20 Index stock?
A: The consensus rating for WIG20 Index is Hold.
Q: What is the prediction period for WIG20 Index stock?
A: The prediction period for WIG20 Index is (n+8 weeks)

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