Outlook: GoldMining Inc. Common Shares is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 17 May 2023 for (n+8 weeks)
Methodology : Deductive Inference (ML)

## Abstract

GoldMining Inc. Common Shares prediction model is evaluated with Deductive Inference (ML) and Linear Regression1,2,3,4 and it is concluded that the GLDG stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

## Key Points

1. Which neural network is best for prediction?
2. Is now good time to invest?
3. What are buy sell or hold recommendations?

## GLDG Target Price Prediction Modeling Methodology

We consider GoldMining Inc. Common Shares Decision Process with Deductive Inference (ML) where A is the set of discrete actions of GLDG 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(Linear Regression)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(Deductive Inference (ML)) X S(n):→ (n+8 weeks) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of GLDG 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?

## GLDG Stock Forecast (Buy or Sell) for (n+8 weeks)

Sample Set: Neural Network
Stock/Index: GLDG GoldMining Inc. Common Shares
Time series to forecast n: 17 May 2023 for (n+8 weeks)

According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

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%

## IFRS Reconciliation Adjustments for GoldMining Inc. Common Shares

1. For example, an entity may use this condition to designate financial liabilities as at fair value through profit or loss if it meets the principle in paragraph 4.2.2(b) and the entity has financial assets and financial liabilities that share one or more risks and those risks are managed and evaluated on a fair value basis in accordance with a documented policy of asset and liability management. An example could be an entity that has issued 'structured products' containing multiple embedded derivatives and manages the resulting risks on a fair value basis using a mix of derivative and non-derivative financial instruments
2. Expected credit losses reflect an entity's own expectations of credit losses. However, when considering all reasonable and supportable information that is available without undue cost or effort in estimating expected credit losses, an entity should also consider observable market information about the credit risk of the particular financial instrument or similar financial instruments.
3. For the purpose of this Standard, reasonable and supportable information is that which is reasonably available at the reporting date without undue cost or effort, including information about past events, current conditions and forecasts of future economic conditions. Information that is available for financial reporting purposes is considered to be available without undue cost or effort.
4. If a financial instrument is designated in accordance with paragraph 6.7.1 as measured at fair value through profit or loss after its initial recognition, or was previously not recognised, the difference at the time of designation between the carrying amount, if any, and the fair value shall immediately be recognised in profit or loss. For financial assets measured at fair value through other comprehensive income in accordance with paragraph 4.1.2A, the cumulative gain or loss previously recognised in other comprehensive income shall immediately be reclassified from equity to profit or loss as a reclassification adjustment.

*International Financial Reporting Standards (IFRS) adjustment process involves reviewing the company's financial statements and identifying any differences between the company's current accounting practices and the requirements of the IFRS. If there are any such differences, neural network makes adjustments to financial statements to bring them into compliance with the IFRS.

## Conclusions

GoldMining Inc. Common Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. GoldMining Inc. Common Shares prediction model is evaluated with Deductive Inference (ML) and Linear Regression1,2,3,4 and it is concluded that the GLDG stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold

### GLDG GoldMining Inc. Common Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB1Baa2
Balance SheetBaa2Ba3
Leverage RatiosB3C
Cash FlowCBaa2
Rates of Return and ProfitabilityCaa2Baa2

*Financial analysis is the process of evaluating a company's financial performance and position by neural network. It involves reviewing the company's financial statements, including the balance sheet, income statement, and cash flow statement, as well as other financial reports and documents.
How does neural network examine financial reports and understand financial state of the company?

### Prediction Confidence Score

Trust metric by Neural Network: 91 out of 100 with 672 signals.

## References

1. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
2. S. Bhatnagar. An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes. Systems & Control Letters, 59(12):760–766, 2010
3. Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
4. Farrell MH, Liang T, Misra S. 2018. Deep neural networks for estimation and inference: application to causal effects and other semiparametric estimands. arXiv:1809.09953 [econ.EM]
5. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
6. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
7. C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999
Frequently Asked QuestionsQ: What is the prediction methodology for GLDG stock?
A: GLDG stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Linear Regression
Q: Is GLDG stock a buy or sell?
A: The dominant strategy among neural network is to Hold GLDG Stock.
Q: Is GoldMining Inc. Common Shares stock a good investment?
A: The consensus rating for GoldMining Inc. Common Shares is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of GLDG stock?
A: The consensus rating for GLDG is Hold.
Q: What is the prediction period for GLDG stock?
A: The prediction period for GLDG is (n+8 weeks)