With technological advancements, big data can be easily generated and collected in many applications. Embedded in these big data are useful information and knowledge that can be discovered by machine learning and data mining models, techniques or algorithms.** We evaluate GameStop prediction models with Modular Neural Network (News Feed Sentiment Analysis) and Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the GME 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 Hold GME stock.**

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

*Keywords:*## Key Points

- Understanding Buy, Sell, and Hold Ratings
- Is Target price a good indicator?
- Why do we need predictive models?

## GME Target Price Prediction Modeling Methodology

Prediction of stock prices has been an important area of research for a long time. While supporters of the efficient market hypothesis believe that it is impossible to predict stock prices accurately, there are formal propositions demonstrating that accurate modeling and designing of appropriate variables may lead to models using which stock prices and stock price movement patterns can be very accurately predicted. We consider GameStop Stock Decision Process with Wilcoxon Sign-Rank Test where A is the set of discrete actions of GME 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(Wilcoxon Sign-Rank Test)

^{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(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ (n+1 year) $\overrightarrow{S}=\left({s}_{1},{s}_{2},{s}_{3}\right)$

n:Time series to forecast

p:Price signals of GME 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?

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

**Sample Set:**Neural Network

**Stock/Index:**GME GameStop

**Time series to forecast n: 03 Nov 2022**for (n+1 year)

**According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Hold GME 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%**

## Adjusted IFRS* Prediction Methods for GameStop

- For purchased or originated credit-impaired financial assets, expected credit losses shall be discounted using the credit-adjusted effective interest rate determined at initial recognition.
- If a financial instrument that was previously recognised as a financial asset is measured at fair value through profit or loss and its fair value decreases below zero, it is a financial liability measured in accordance with paragraph 4.2.1. However, hybrid contracts with hosts that are assets within the scope of this Standard are always measured in accordance with paragraph 4.3.2.
- However, the fact that a financial asset is non-recourse does not in itself necessarily preclude the financial asset from meeting the condition in paragraphs 4.1.2(b) and 4.1.2A(b). In such situations, the creditor is required to assess ('look through to') the particular underlying assets or cash flows to determine whether the contractual cash flows of the financial asset being classified are payments of principal and interest on the principal amount outstanding. If the terms of the financial asset give rise to any other cash flows or limit the cash flows in a manner inconsistent with payments representing principal and interest, the financial asset does not meet the condition in paragraphs 4.1.2(b) and 4.1.2A(b). Whether the underlying assets are financial assets or non-financial assets does not in itself affect this assessment.
- A contractually specified inflation risk component of the cash flows of a recognised inflation-linked bond (assuming that there is no requirement to account for an embedded derivative separately) is separately identifiable and reliably measurable, as long as other cash flows of the instrument are not affected by the inflation risk component.

*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

GameStop assigned short-term B3 & long-term B1 forecasted stock rating.** We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with Wilcoxon Sign-Rank Test ^{1,2,3,4} and conclude that the GME 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 Hold GME stock.**

### Financial State Forecast for GME GameStop Stock Options & Futures

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | B3 | B1 |

Operational Risk | 37 | 80 |

Market Risk | 62 | 35 |

Technical Analysis | 36 | 35 |

Fundamental Analysis | 70 | 78 |

Risk Unsystematic | 41 | 57 |

### Prediction Confidence Score

## References

- A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.
- Hirano K, Porter JR. 2009. Asymptotics for statistical treatment rules. Econometrica 77:1683–701
- Greene WH. 2000. Econometric Analysis. Upper Saddle River, N J: Prentice Hall. 4th ed.
- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
- J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
- J. Spall. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37(3):332–341, 1992.
- Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.

## Frequently Asked Questions

Q: What is the prediction methodology for GME stock?A: GME stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Wilcoxon Sign-Rank Test

Q: Is GME stock a buy or sell?

A: The dominant strategy among neural network is to Hold GME Stock.

Q: Is GameStop stock a good investment?

A: The consensus rating for GameStop is Hold and assigned short-term B3 & long-term B1 forecasted stock rating.

Q: What is the consensus rating of GME stock?

A: The consensus rating for GME is Hold.

Q: What is the prediction period for GME stock?

A: The prediction period for GME is (n+1 year)