Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 09 Dec 2022 for (n+16 weeks)
Methodology : Modular Neural Network (Social Media Sentiment Analysis)
Abstract
Stock market prediction is the act of trying to determine the future value of a company stock or other financial instrument traded on a financial exchange. The successful prediction of a stock's future price will maximize investor's gains. This paper proposes a machine learning model to predict stock market price.(Torres P, E.P., Hernández-Álvarez, M., Torres Hernández, E.A. and Yoo, S.G., 2019, February. Stock market data prediction using machine learning techniques. In International conference on information technology & systems (pp. 539-547). Springer, Cham.) We evaluate GAMES WORKSHOP GROUP PLC prediction models with Modular Neural Network (Social Media Sentiment Analysis) and Polynomial Regression1,2,3,4 and conclude that the LON:GAW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes
Key Points
- What is neural prediction?
- Is Target price a good indicator?
- What is a prediction confidence?
LON:GAW Target Price Prediction Modeling Methodology
We consider GAMES WORKSHOP GROUP PLC Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of LON:GAW 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(Polynomial Regression)5,6,7= X R(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ (n+16 weeks)
n:Time series to forecast
p:Price signals of LON:GAW stock
j:Nash equilibria (Neural Network)
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:GAW Stock Forecast (Buy or Sell) for (n+16 weeks)
Sample Set: Neural NetworkStock/Index: LON:GAW GAMES WORKSHOP GROUP PLC
Time series to forecast n: 09 Dec 2022 for (n+16 weeks)
According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes
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 (Grey to Black): *Technical Analysis%
Adjusted IFRS* Prediction Methods for GAMES WORKSHOP GROUP PLC
- Expected credit losses are a probability-weighted estimate of credit losses (ie the present value of all cash shortfalls) over the expected life of the financial instrument. A cash shortfall is the difference between the cash flows that are due to an entity in accordance with the contract and the cash flows that the entity expects to receive. Because expected credit losses consider the amount and timing of payments, a credit loss arises even if the entity expects to be paid in full but later than when contractually due.
- An entity shall amend a hedging relationship as required in paragraph 6.9.1 by the end of the reporting period during which a change required by interest rate benchmark reform is made to the hedged risk, hedged item or hedging instrument. For the avoidance of doubt, such an amendment to the formal designation of a hedging relationship constitutes neither the discontinuation of the hedging relationship nor the designation of a new hedging relationship.
- Interest Rate Benchmark Reform, which amended IFRS 9, IAS 39 and IFRS 7, issued in September 2019, added Section 6.8 and amended paragraph 7.2.26. An entity shall apply these amendments for annual periods beginning on or after 1 January 2020. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
- Historical information is an important anchor or base from which to measure expected credit losses. However, an entity shall adjust historical data, such as credit loss experience, on the basis of current observable data to reflect the effects of the current conditions and its forecasts of future conditions that did not affect the period on which the historical data is based, and to remove the effects of the conditions in the historical period that are not relevant to the future contractual cash flows. In some cases, the best reasonable and supportable information could be the unadjusted historical information, depending on the nature of the historical information and when it was calculated, compared to circumstances at the reporting date and the characteristics of the financial instrument being considered. Estimates of changes in expected credit losses should reflect, and be directionally consistent with, changes in related observable data from period to period
*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.
Conclusions
GAMES WORKSHOP GROUP PLC assigned short-term Ba3 & long-term Ba3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) with Polynomial Regression1,2,3,4 and conclude that the LON:GAW stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes
Financial State Forecast for LON:GAW GAMES WORKSHOP GROUP PLC Options & Futures
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba3 | Ba3 |
Operational Risk | 86 | 52 |
Market Risk | 61 | 88 |
Technical Analysis | 88 | 89 |
Fundamental Analysis | 52 | 52 |
Risk Unsystematic | 49 | 30 |
Prediction Confidence Score
References
- M. Benaim, J. Hofbauer, and S. Sorin. Stochastic approximations and differential inclusions, Part II: Appli- cations. Mathematics of Operations Research, 31(4):673–695, 2006
- 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.
- Bewley, R. M. Yang (1998), "On the size and power of system tests for cointegration," Review of Economics and Statistics, 80, 675–679.
- E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
- Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
- Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
- Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55
Frequently Asked Questions
Q: What is the prediction methodology for LON:GAW stock?A: LON:GAW stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Polynomial Regression
Q: Is LON:GAW stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes LON:GAW Stock.
Q: Is GAMES WORKSHOP GROUP PLC stock a good investment?
A: The consensus rating for GAMES WORKSHOP GROUP PLC is Wait until speculative trend diminishes and assigned short-term Ba3 & long-term Ba3 forecasted stock rating.
Q: What is the consensus rating of LON:GAW stock?
A: The consensus rating for LON:GAW is Wait until speculative trend diminishes.
Q: What is the prediction period for LON:GAW stock?
A: The prediction period for LON:GAW is (n+16 weeks)
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