Dominant Strategy : Sell
Time series to forecast n: 24 Dec 2022 for (n+8 weeks)
Methodology : Modular Neural Network (News Feed Sentiment Analysis)
Abstract
The stock market is very volatile and non-stationary and generates huge volumes of data in every second. In this article, the existing machine learning algorithms are analyzed for stock market forecasting and also a new pattern-finding algorithm for forecasting stock trend is developed. Three approaches can be used to solve the problem: fundamental analysis, technical analysis, and the machine learning. Experimental analysis done in this article shows that the machine learning could be useful for investors to make profitable decisions.(Song, Y., 2018. Stock trend prediction: Based on machine learning methods (Doctoral dissertation, UCLA).) We evaluate Canopy Growth Corporation Common Shares prediction models with Modular Neural Network (News Feed Sentiment Analysis) and Sign Test1,2,3,4 and conclude that the CGC stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell
Key Points
- Short/Long Term Stocks
- What is neural prediction?
- Which neural network is best for prediction?
CGC Target Price Prediction Modeling Methodology
We consider Canopy Growth Corporation Common Shares Decision Process with Modular Neural Network (News Feed Sentiment Analysis) where A is the set of discrete actions of CGC 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(Sign Test)5,6,7= X R(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ (n+8 weeks)
n:Time series to forecast
p:Price signals of CGC 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?
CGC Stock Forecast (Buy or Sell) for (n+8 weeks)
Sample Set: Neural NetworkStock/Index: CGC Canopy Growth Corporation Common Shares
Time series to forecast n: 24 Dec 2022 for (n+8 weeks)
According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell
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 Canopy Growth Corporation Common Shares
- 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.
- For the purpose of determining whether a forecast transaction (or a component thereof) is highly probable as required by paragraph 6.3.3, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.
- The rebuttable presumption in paragraph 5.5.11 is not an absolute indicator that lifetime expected credit losses should be recognised, but is presumed to be the latest point at which lifetime expected credit losses should be recognised even when using forward-looking information (including macroeconomic factors on a portfolio level).
- Conversely, if the critical terms of the hedging instrument and the hedged item are not closely aligned, there is an increased level of uncertainty about the extent of offset. Consequently, the hedge effectiveness during the term of the hedging relationship is more difficult to predict. In such a situation it might only be possible for an entity to conclude on the basis of a quantitative assessment that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6). In some situations a quantitative assessment might also be needed to assess whether the hedge ratio used for designating the hedging relationship meets the hedge effectiveness requirements (see paragraphs B6.4.9–B6.4.11). An entity can use the same or different methods for those two different purposes.
*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
Canopy Growth Corporation Common Shares assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) with Sign Test1,2,3,4 and conclude that the CGC stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Sell
CGC Canopy Growth Corporation Common Shares Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Caa2 | Baa2 |
Balance Sheet | Baa2 | B3 |
Leverage Ratios | Caa2 | C |
Cash Flow | B2 | B3 |
Rates of Return and Profitability | B1 | B1 |
*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
References
- Belsley, D. A. (1988), "Modelling and forecast reliability," International Journal of Forecasting, 4, 427–447.
- Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
- Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
- S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014
- M. Babes, E. M. de Cote, and M. L. Littman. Social reward shaping in the prisoner's dilemma. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3, pages 1389–1392, 2008.
- Abadie A, Diamond A, Hainmueller J. 2015. Comparative politics and the synthetic control method. Am. J. Political Sci. 59:495–510
- J. Spall. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37(3):332–341, 1992.
Frequently Asked Questions
Q: What is the prediction methodology for CGC stock?A: CGC stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Sign Test
Q: Is CGC stock a buy or sell?
A: The dominant strategy among neural network is to Sell CGC Stock.
Q: Is Canopy Growth Corporation Common Shares stock a good investment?
A: The consensus rating for Canopy Growth Corporation Common Shares is Sell and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of CGC stock?
A: The consensus rating for CGC is Sell.
Q: What is the prediction period for CGC stock?
A: The prediction period for CGC is (n+8 weeks)