Modelling A.I. in Economics

Is WWE stock expected to rise?

Recently, numerous investigations for stock price prediction and portfolio management using machine learning have been trying to develop efficient mechanical trading systems. But these systems have a limitation in that they are mainly based on the supervised learning which is not so adequate for learning problems with long-term goals and delayed rewards. This paper proposes a method of applying reinforcement learning, suitable for modeling and learning various kinds of interactions in real situations, to the problem of stock price prediction. We evaluate World Wrestling Entertainment prediction models with Modular Neural Network (Market Volatility Analysis) and ElasticNet Regression1,2,3,4 and conclude that the WWE 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 WWE stock.


Keywords: WWE, World Wrestling Entertainment, stock forecast, machine learning based prediction, risk rating, buy-sell behaviour, stock analysis, target price analysis, options and futures.

Key Points

  1. Why do we need predictive models?
  2. Is it better to buy and sell or hold?
  3. Market Outlook

WWE Target Price Prediction Modeling Methodology

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 consider World Wrestling Entertainment Stock Decision Process with ElasticNet Regression where A is the set of discrete actions of WWE 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(ElasticNet 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(Modular Neural Network (Market Volatility Analysis)) X S(n):→ (n+1 year) i = 1 n a i

n:Time series to forecast

p:Price signals of WWE 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?

WWE Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: WWE World Wrestling Entertainment
Time series to forecast n: 08 Oct 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell WWE 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

World Wrestling Entertainment assigned short-term B2 & long-term Ba2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with ElasticNet Regression1,2,3,4 and conclude that the WWE 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 WWE stock.

Financial State Forecast for WWE Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*B2Ba2
Operational Risk 5171
Market Risk6287
Technical Analysis3353
Fundamental Analysis4657
Risk Unsystematic8772

Prediction Confidence Score

Trust metric by Neural Network: 76 out of 100 with 848 signals.

References

  1. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
  2. Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
  3. Athey S, Imbens GW. 2017b. The state of applied econometrics: causality and policy evaluation. J. Econ. Perspect. 31:3–32
  4. T. Morimura, M. Sugiyama, M. Kashima, H. Hachiya, and T. Tanaka. Nonparametric return distribution ap- proximation for reinforcement learning. In Proceedings of the 27th International Conference on Machine Learning, pages 799–806, 2010
  5. Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
  6. J. Filar, D. Krass, and K. Ross. Percentile performance criteria for limiting average Markov decision pro- cesses. IEEE Transaction of Automatic Control, 40(1):2–10, 1995.
  7. Mikolov T, Sutskever I, Chen K, Corrado GS, Dean J. 2013b. Distributed representations of words and phrases and their compositionality. In Advances in Neural Information Processing Systems, Vol. 26, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 3111–19. San Diego, CA: Neural Inf. Process. Syst. Found.
Frequently Asked QuestionsQ: What is the prediction methodology for WWE stock?
A: WWE stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and ElasticNet Regression
Q: Is WWE stock a buy or sell?
A: The dominant strategy among neural network is to Sell WWE Stock.
Q: Is World Wrestling Entertainment stock a good investment?
A: The consensus rating for World Wrestling Entertainment is Sell and assigned short-term B2 & long-term Ba2 forecasted stock rating.
Q: What is the consensus rating of WWE stock?
A: The consensus rating for WWE is Sell.
Q: What is the prediction period for WWE stock?
A: The prediction period for WWE is (n+1 year)



Stop Guessing, Start Winning.
Get Today's AI-Driven Picks.

Click here to see what the AI recommends.




Premium

  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

Login
This project is licensed under the license; additional terms may apply.