Social media comments have in the past had an instantaneous effect on stock markets. This paper investigates the sentiments expressed on the social media platform Twitter and their pr edictive impact on the Stock Market. We evaluate WIG20 Index prediction models with Ensemble Learning (ML) and Beta1,2,3,4 and conclude that the WIG20 Index stock is predictable in the short/long term. According to price forecasts for (n+3 month) 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. How can neural networks improve predictions?
2. What is neural prediction?
3. What are main components of Markov decision process?

## WIG20 Index Target Price Prediction Modeling Methodology

With the up-gradation of technology and exploration of new machine learning models, the stock market data analysis has gained attention as these models provide a platform for businessman and traders to choose more profitable stocks. As these data are in large volumes and highly complex so a need of more efficient machine learning model for daily predictions is always looked upon. We consider WIG20 Index Stock Decision Process with Beta 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(Beta)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Ensemble Learning (ML)) X S(n):→ (n+3 month) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

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+3 month)

Sample Set: Neural Network
Stock/Index: WIG20 Index WIG20 Index
Time series to forecast n: 14 Oct 2022 for (n+3 month)

According to price forecasts for (n+3 month) 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 B3 & long-term B2 forecasted stock rating. We evaluate the prediction models Ensemble Learning (ML) with Beta1,2,3,4 and conclude that the WIG20 Index stock is predictable in the short/long term. According to price forecasts for (n+3 month) 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*B3B2
Operational Risk 7270
Market Risk7044
Technical Analysis3469
Fundamental Analysis3450
Risk Unsystematic4237

### Prediction Confidence Score

Trust metric by Neural Network: 73 out of 100 with 864 signals.

## References

1. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
2. V. Mnih, A. P. Badia, M. Mirza, A. Graves, T. P. Lillicrap, T. Harley, D. Silver, and K. Kavukcuoglu. Asynchronous methods for deep reinforcement learning. In Proceedings of the 33nd International Conference on Machine Learning, ICML 2016, New York City, NY, USA, June 19-24, 2016, pages 1928–1937, 2016
3. J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
4. L. Panait and S. Luke. Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434, 2005.
5. Candès E, Tao T. 2007. The Dantzig selector: statistical estimation when p is much larger than n. Ann. Stat. 35:2313–51
6. V. Borkar. An actor-critic algorithm for constrained Markov decision processes. Systems & Control Letters, 54(3):207–213, 2005.
7. Batchelor, R. P. Dua (1993), "Survey vs ARCH measures of inflation uncertainty," Oxford Bulletin of Economics Statistics, 55, 341–353.
Frequently Asked QuestionsQ: What is the prediction methodology for WIG20 Index stock?
A: WIG20 Index stock prediction methodology: We evaluate the prediction models Ensemble Learning (ML) and Beta
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 B3 & long-term B2 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+3 month)