Engine Gaming and Media Inc. Research Report

## Summary

Prediction of stock market is a long-time attractive topic to researchers from different fields. In particular, numerous studies have been conducted to predict the movement of stock market using machine learning algorithms such as support vector machine (SVM) and reinforcement learning. In this project, we propose a new prediction algorithm that exploits the temporal correlation among global stock markets and various financial products to predict the next-day stock trend. We evaluate Engine Gaming and Media Inc. prediction models with Transfer Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and conclude that the GAME:TSXV stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell GAME:TSXV stock.

## Key Points

1. Should I buy stocks now or wait amid such uncertainty?
2. How do you know when a stock will go up or down?
3. Dominated Move

## GAME:TSXV Target Price Prediction Modeling Methodology

We consider Engine Gaming and Media Inc. Stock Decision Process with Transfer Learning (ML) where A is the set of discrete actions of GAME:TSXV 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= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Transfer Learning (ML)) X S(n):→ (n+4 weeks) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of GAME:TSXV 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?

## GAME:TSXV Stock Forecast (Buy or Sell) for (n+4 weeks)

Sample Set: Neural Network
Stock/Index: GAME:TSXV Engine Gaming and Media Inc.
Time series to forecast n: 28 Nov 2022 for (n+4 weeks)

According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell GAME:TSXV 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 Engine Gaming and Media Inc.

1. The assessment of whether an economic relationship exists includes an analysis of the possible behaviour of the hedging relationship during its term to ascertain whether it can be expected to meet the risk management objective. The mere existence of a statistical correlation between two variables does not, by itself, support a valid conclusion that an economic relationship exists.
2. Annual Improvements to IFRS Standards 2018–2020, issued in May 2020, added paragraphs 7.2.35 and B3.3.6A and amended paragraph B3.3.6. An entity shall apply that amendment for annual reporting periods beginning on or after 1 January 2022. Earlier application is permitted. If an entity applies the amendment for an earlier period, it shall disclose that fact.
3. For a financial guarantee contract, the entity is required to make payments only in the event of a default by the debtor in accordance with the terms of the instrument that is guaranteed. Accordingly, cash shortfalls are the expected payments to reimburse the holder for a credit loss that it incurs less any amounts that the entity expects to receive from the holder, the debtor or any other party. If the asset is fully guaranteed, the estimation of cash shortfalls for a financial guarantee contract would be consistent with the estimations of cash shortfalls for the asset subject to the guarantee
4. Alternatively, the entity may base the assessment on both types of information, ie qualitative factors that are not captured through the internal ratings process and a specific internal rating category at the reporting date, taking into consideration the credit risk characteristics at initial recognition, if both types of information are relevant.

*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

Engine Gaming and Media Inc. assigned short-term Ba2 & long-term Ba2 forecasted stock rating. We evaluate the prediction models Transfer Learning (ML) with Wilcoxon Sign-Rank Test1,2,3,4 and conclude that the GAME:TSXV stock is predictable in the short/long term. According to price forecasts for (n+4 weeks) period: The dominant strategy among neural network is to Sell GAME:TSXV stock.

### Financial State Forecast for GAME:TSXV Engine Gaming and Media Inc. Stock Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba2Ba2
Operational Risk 5086
Market Risk8063
Technical Analysis9050
Fundamental Analysis7853
Risk Unsystematic4381

### Prediction Confidence Score

Trust metric by Neural Network: 77 out of 100 with 607 signals.

## References

1. Nie X, Wager S. 2019. Quasi-oracle estimation of heterogeneous treatment effects. arXiv:1712.04912 [stat.ML]
2. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
3. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
4. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
5. Scholkopf B, Smola AJ. 2001. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press
6. Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press
7. Breiman L. 2001a. Random forests. Mach. Learn. 45:5–32
Frequently Asked QuestionsQ: What is the prediction methodology for GAME:TSXV stock?
A: GAME:TSXV stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Wilcoxon Sign-Rank Test
Q: Is GAME:TSXV stock a buy or sell?
A: The dominant strategy among neural network is to Sell GAME:TSXV Stock.
Q: Is Engine Gaming and Media Inc. stock a good investment?
A: The consensus rating for Engine Gaming and Media Inc. is Sell and assigned short-term Ba2 & long-term Ba2 forecasted stock rating.
Q: What is the consensus rating of GAME:TSXV stock?
A: The consensus rating for GAME:TSXV is Sell.
Q: What is the prediction period for GAME:TSXV stock?
A: The prediction period for GAME:TSXV is (n+4 weeks)