## 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.**

**WIG20 Index, WIG20 Index, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.**

*Keywords:*## Key Points

- What are the most successful trading algorithms?
- What are the most successful trading algorithms?
- 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}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ 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

## References

- 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
- Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.
- 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
- Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
- Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.
- Imbens G, Wooldridge J. 2009. Recent developments in the econometrics of program evaluation. J. Econ. Lit. 47:5–86
- 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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