TFPM:TSX Triple Flag Precious Metals Corp.

Triple Flag Precious Metals Corp. Research Report

Summary

Accurate prediction of stock price movements is highly challenging and significant topic for investors. Investors need to understand that stock price data is the most essential information which is highly volatile, non-linear, and non-parametric and are affected by many uncertainties and interrelated economic and political factors across the globe. Artificial Neural Networks (ANN) have been found to be an efficient tool in modeling stock prices and quite a large number of studies have been done on it. We evaluate Triple Flag Precious Metals Corp. prediction models with Modular Neural Network (Market Direction Analysis) and Wilcoxon Rank-Sum Test^1,2,3,4 and conclude that the TFPM:TSX 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 TFPM:TSX stock.

Key Points

1. Can neural networks predict stock market?
2. Why do we need predictive models?
3. How do you know when a stock will go up or down?

TFPM:TSX Target Price Prediction Modeling Methodology

We consider Triple Flag Precious Metals Corp. Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of TFPM:TSX 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 Rank-Sum Test)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ (n+1 year) $\begin{array}{l}\int e^x\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of TFPM:TSX 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?

TFPM:TSX Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: TFPM:TSX Triple Flag Precious Metals Corp.
Time series to forecast n: 04 Dec 2022 for (n+1 year)

According to price forecasts for (n+1 year) period: The dominant strategy among neural network is to Sell TFPM:TSX 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 Triple Flag Precious Metals Corp.

1. If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.
2. Paragraph 4.1.1(a) requires an entity to classify financial assets on the basis of the entity's business model for managing the financial assets, unless paragraph 4.1.5 applies. An entity assesses whether its financial assets meet the condition in paragraph 4.1.2(a) or the condition in paragraph 4.1.2A(a) on the basis of the business model as determined by the entity's key management personnel (as defined in IAS 24 Related Party Disclosures).
3. For the purpose of applying paragraphs B4.1.11(b) and B4.1.12(b), irrespective of the event or circumstance that causes the early termination of the contract, a party may pay or receive reasonable compensation for that early termination. For example, a party may pay or receive reasonable compensation when it chooses to terminate the contract early (or otherwise causes the early termination to occur).
4. If there are changes in circumstances that affect hedge effectiveness, an entity may have to change the method for assessing whether a hedging relationship meets the hedge effectiveness requirements in order to ensure that the relevant characteristics of the hedging relationship, including the sources of hedge ineffectiveness, are still captured.

*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

Triple Flag Precious Metals Corp. assigned short-term B2 & long-term B2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Direction Analysis) with Wilcoxon Rank-Sum Test^1,2,3,4 and conclude that the TFPM:TSX 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 TFPM:TSX stock.

Financial State Forecast for TFPM:TSX Triple Flag Precious Metals Corp. Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B2
Operational Risk	60	40
Market Risk	70	83
Technical Analysis	39	38
Fundamental Analysis	70	51
Risk Unsystematic	38	52

Prediction Confidence Score

Trust metric by Neural Network: 92 out of 100 with 691 signals.

References

1. Breiman L, Friedman J, Stone CJ, Olshen RA. 1984. Classification and Regression Trees. Boca Raton, FL: CRC Press
2. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
3. G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
4. Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
5. Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
6. Kitagawa T, Tetenov A. 2015. Who should be treated? Empirical welfare maximization methods for treatment choice. Tech. Rep., Cent. Microdata Methods Pract., Inst. Fiscal Stud., London
7. Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276

Frequently Asked Questions

Q: What is the prediction methodology for TFPM:TSX stock?
A: TFPM:TSX stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Wilcoxon Rank-Sum Test
Q: Is TFPM:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Sell TFPM:TSX Stock.
Q: Is Triple Flag Precious Metals Corp. stock a good investment?
A: The consensus rating for Triple Flag Precious Metals Corp. is Sell and assigned short-term B2 & long-term B2 forecasted stock rating.
Q: What is the consensus rating of TFPM:TSX stock?
A: The consensus rating for TFPM:TSX is Sell.
Q: What is the prediction period for TFPM:TSX stock?
A: The prediction period for TFPM:TSX is (n+1 year)

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