Modelling A.I. in Economics

GOOS Stock Forecast: A Sell For The Next 16 Weeks (Forecast)

Outlook: Canada Goose Holdings Inc. Subordinate Voting Shares is assigned short-term B2 & long-term Baa2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Modular Neural Network (DNN Layer)
Hypothesis Testing : Chi-Square
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.


Summary

Canada Goose Holdings Inc. Subordinate Voting Shares prediction model is evaluated with Modular Neural Network (DNN Layer) and Chi-Square1,2,3,4 and it is concluded that the GOOS stock is predictable in the short/long term. In a modular neural network (MNN), a DNN layer is a type of module that is used to learn complex relationships between input and output data. DNN layers are made up of a series of artificial neurons, which are connected to each other by weighted edges. The weights of the edges are adjusted during training to minimize the error between the network's predictions and the desired output. DNN layers are used in a variety of MNN applications, including natural language processing, speech recognition, and machine translation. In natural language processing, DNN layers are used to extract features from text data, such as the sentiment of a sentence or the topic of a conversation. In speech recognition, DNN layers are used to convert audio data into text data. In machine translation, DNN layers are used to translate text from one language to another.5 According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Sell

Graph 19

Key Points

  1. Modular Neural Network (DNN Layer) for GOOS stock price prediction process.
  2. Chi-Square
  3. How do you pick a stock?
  4. What are buy sell or hold recommendations?
  5. Can we predict stock market using machine learning?

GOOS Stock Price Forecast

We consider Canada Goose Holdings Inc. Subordinate Voting Shares Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of GOOS 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


Sample Set: Neural Network
Stock/Index: GOOS Canada Goose Holdings Inc. Subordinate Voting Shares
Time series to forecast: 16 Weeks

According to price forecasts, the dominant strategy among neural network is: Sell


F(Chi-Square)6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (DNN Layer)) X S(n):→ 16 Weeks i = 1 n r i

n:Time series to forecast

p:Price signals of GOOS stock

j:Nash equilibria (Neural Network)

k:Dominated move of GOOS stock holders

a:Best response for GOOS target price


In a modular neural network (MNN), a DNN layer is a type of module that is used to learn complex relationships between input and output data. DNN layers are made up of a series of artificial neurons, which are connected to each other by weighted edges. The weights of the edges are adjusted during training to minimize the error between the network's predictions and the desired output. DNN layers are used in a variety of MNN applications, including natural language processing, speech recognition, and machine translation. In natural language processing, DNN layers are used to extract features from text data, such as the sentiment of a sentence or the topic of a conversation. In speech recognition, DNN layers are used to convert audio data into text data. In machine translation, DNN layers are used to translate text from one language to another.5 A chi-squared test is a statistical hypothesis test that assesses whether observed frequencies in a sample differ significantly from expected frequencies. It is one of the most widely used statistical tests in the social sciences and in many areas of observational research. The chi-squared test is a non-parametric test, meaning that it does not assume that the data is normally distributed. This makes it a versatile tool that can be used to analyze a wide variety of data. There are two main types of chi-squared tests: the chi-squared goodness of fit test and the chi-squared test of independence.6,7

 

For further technical information as per how our model work we invite you to visit the article below: 

How do PredictiveAI algorithms actually work?

GOOS Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Modular Neural Network (DNN Layer) based GOOS Stock Prediction Model

  1. For the purposes of the transition provisions in paragraphs 7.2.1, 7.2.3–7.2.28 and 7.3.2, the date of initial application is the date when an entity first applies those requirements of this Standard and must be the beginning of a reporting period after the issue of this Standard. Depending on the entity's chosen approach to applying IFRS 9, the transition can involve one or more than one date of initial application for different requirements.
  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. An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.
  4. In some circumstances, the renegotiation or modification of the contractual cash flows of a financial asset can lead to the derecognition of the existing financial asset in accordance with this Standard. When the modification of a financial asset results in the derecognition of the existing financial asset and the subsequent recognition of the modified financial asset, the modified asset is considered a 'new' financial asset for the purposes of this Standard.

*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.

GOOS Canada Goose Holdings Inc. Subordinate Voting Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B2Baa2
Income StatementCBaa2
Balance SheetCaa2C
Leverage RatiosCBaa2
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityBaa2Baa2

*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?

References

  1. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
  2. Chernozhukov V, Escanciano JC, Ichimura H, Newey WK. 2016b. Locally robust semiparametric estimation. arXiv:1608.00033 [math.ST]
  3. Chipman HA, George EI, McCulloch RE. 2010. Bart: Bayesian additive regression trees. Ann. Appl. Stat. 4:266–98
  4. D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
  5. Scott SL. 2010. A modern Bayesian look at the multi-armed bandit. Appl. Stoch. Models Bus. Ind. 26:639–58
  6. M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.
  7. Arjovsky M, Bottou L. 2017. Towards principled methods for training generative adversarial networks. arXiv:1701.04862 [stat.ML]
Frequently Asked QuestionsQ: Is GOOS stock expected to rise?
A: GOOS stock prediction model is evaluated with Modular Neural Network (DNN Layer) and Chi-Square and it is concluded that dominant strategy for GOOS stock is Sell
Q: Is GOOS stock a buy or sell?
A: The dominant strategy among neural network is to Sell GOOS Stock.
Q: Is Canada Goose Holdings Inc. Subordinate Voting Shares stock a good investment?
A: The consensus rating for Canada Goose Holdings Inc. Subordinate Voting Shares is Sell and is assigned short-term B2 & long-term Baa2 estimated rating.
Q: What is the consensus rating of GOOS stock?
A: The consensus rating for GOOS is Sell.
Q: What is the forecast for GOOS stock?
A: GOOS target price forecast: Sell

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