HITI High Tide Inc. Common Shares

Outlook: High Tide Inc. Common Shares assigned short-term Caa2 & long-term B3 forecasted stock rating.
Dominant Strategy : Sell
Time series to forecast n: 07 Dec 2022 for (n+3 month)
Methodology : Modular Neural Network (Market Volatility Analysis)

Abstract

The main objective of this research is to predict the market performance on day closing using different machine learning techniques. The prediction model uses different attributes as an input and predicts market as Positive & Negative. (Güreşen, E. and Kayakutlu, G., 2008, October. Forecasting stock exchange movements using artificial neural network models and hybrid models. In International Conference on Intelligent Information Processing (pp. 129-137). Springer, Boston, MA.) We evaluate High Tide Inc. Common Shares prediction models with Modular Neural Network (Market Volatility Analysis) and Pearson Correlation^1,2,3,4 and conclude that the HITI stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is: Sell

Key Points

1. Trust metric by Neural Network
2. What is the use of Markov decision process?
3. What is the use of Markov decision process?

HITI Target Price Prediction Modeling Methodology

We consider High Tide Inc. Common Shares Decision Process with Modular Neural Network (Market Volatility Analysis) where A is the set of discrete actions of HITI 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(Pearson Correlation)^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 Volatility Analysis)) X S(n):→ (n+3 month) $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of HITI 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?

HITI Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: HITI High Tide Inc. Common Shares
Time series to forecast n: 07 Dec 2022 for (n+3 month)

According to price forecasts for (n+3 month) period: The dominant strategy among neural network is to Sell HITI 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 High Tide Inc. Common Shares

1. 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.
2. If a guarantee provided by an entity to pay for default losses on a transferred asset prevents the transferred asset from being derecognised to the extent of the continuing involvement, the transferred asset at the date of the transfer is measured at the lower of (i) the carrying amount of the asset and (ii) the maximum amount of the consideration received in the transfer that the entity could be required to repay ('the guarantee amount'). The associated liability is initially measured at the guarantee amount plus the fair value of the guarantee (which is normally the consideration received for the guarantee). Subsequently, the initial fair value of the guarantee is recognised in profit or loss when (or as) the obligation is satisfied (in accordance with the principles of IFRS 15) and the carrying value of the asset is reduced by any loss allowance.
3. For the purposes of applying the requirements in paragraphs 5.7.7 and 5.7.8, an accounting mismatch is not caused solely by the measurement method that an entity uses to determine the effects of changes in a liability's credit risk. An accounting mismatch in profit or loss would arise only when the effects of changes in the liability's credit risk (as defined in IFRS 7) are expected to be offset by changes in the fair value of another financial instrument. A mismatch that arises solely as a result of the measurement method (ie because an entity does not isolate changes in a liability's credit risk from some other changes in its fair value) does not affect the determination required by paragraphs 5.7.7 and 5.7.8. For example, an entity may not isolate changes in a liability's credit risk from changes in liquidity risk. If the entity presents the combined effect of both factors in other comprehensive income, a mismatch may occur because changes in liquidity risk may be included in the fair value measurement of the entity's financial assets and the entire fair value change of those assets is presented in profit or loss. However, such a mismatch is caused by measurement imprecision, not the offsetting relationship described in paragraph B5.7.6 and, therefore, does not affect the determination required by paragraphs 5.7.7 and 5.7.8.
4. One of the defining characteristics of a derivative is that it has an initial net investment that is smaller than would be required for other types of contracts that would be expected to have a similar response to changes in market factors. An option contract meets that definition because the premium is less than the investment that would be required to obtain the underlying financial instrument to which the option is linked. A currency swap that requires an initial exchange of different currencies of equal fair values meets the definition because it has a zero initial net investment.

*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

High Tide Inc. Common Shares assigned short-term Caa2 & long-term B3 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) with Pearson Correlation^1,2,3,4 and conclude that the HITI stock is predictable in the short/long term. According to price forecasts for (n+3 month) period: The dominant strategy among neural network is: Sell

Financial State Forecast for HITI High Tide Inc. Common Shares Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	Caa2	B3
Operational Risk	66	46
Market Risk	30	56
Technical Analysis	44	68
Fundamental Analysis	41	35
Risk Unsystematic	45	32

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 831 signals.

References

1. Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
2. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
3. Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.
4. Allen, P. G. (1994), "Economic forecasting in agriculture," International Journal of Forecasting, 10, 81–135.
5. D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009
6. A. Shapiro, W. Tekaya, J. da Costa, and M. Soares. Risk neutral and risk averse stochastic dual dynamic programming method. European journal of operational research, 224(2):375–391, 2013
7. A. Tamar, Y. Glassner, and S. Mannor. Policy gradients beyond expectations: Conditional value-at-risk. In AAAI, 2015

Frequently Asked Questions

Q: What is the prediction methodology for HITI stock?
A: HITI stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Volatility Analysis) and Pearson Correlation
Q: Is HITI stock a buy or sell?
A: The dominant strategy among neural network is to Sell HITI Stock.
Q: Is High Tide Inc. Common Shares stock a good investment?
A: The consensus rating for High Tide Inc. Common Shares is Sell and assigned short-term Caa2 & long-term B3 forecasted stock rating.
Q: What is the consensus rating of HITI stock?
A: The consensus rating for HITI is Sell.
Q: What is the prediction period for HITI stock?
A: The prediction period for HITI is (n+3 month)

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