CIGI:TSX Stock: A Spark That Could Fizzle

Outlook: Colliers International Group Inc. is assigned short-term B1 & long-term Ba2 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 (CNN Layer)
Hypothesis Testing : Beta
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

Colliers International Group Inc. prediction model is evaluated with Modular Neural Network (CNN Layer) and Beta^1,2,3,4 and it is concluded that the CIGI:TSX stock is predictable in the short/long term. CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell

Key Points

1. Reaction Function
2. What are the most successful trading algorithms?
3. Is Target price a good indicator?

CIGI:TSX Target Price Prediction Modeling Methodology

We consider Colliers International Group Inc. Decision Process with Modular Neural Network (CNN Layer) where A is the set of discrete actions of CIGI: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(Beta)^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 (CNN Layer)) X S(n):→ 8 Weeks $\sum _{i=1}^n\left(a_i\right)$

n:Time series to forecast

p:Price signals of CIGI:TSX stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

Modular Neural Network (CNN Layer)

CNN layers are a powerful tool for extracting features from images. They are able to learn to detect patterns in images that are not easily detected by humans. This makes them well-suited for a variety of MNN applications.

Beta

In statistics, beta (β) is a measure of the strength of the relationship between two variables. It is calculated as the slope of the line of best fit in a regression analysis. Beta can range from -1 to 1, with a value of 0 indicating no relationship between the two variables. A positive beta indicates that as one variable increases, the other variable also increases. A negative beta indicates that as one variable increases, the other variable decreases. For example, a study might find that there is a positive relationship between height and weight. This means that taller people tend to weigh more. The beta coefficient for this relationship would be positive.

 

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?

CIGI:TSX Stock Forecast (Buy or Sell)

Sample Set: Neural Network
Stock/Index: CIGI:TSX Colliers International Group Inc.
Time series to forecast: 8 Weeks

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

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 (CNN Layer) based CIGI:TSX Stock Prediction Model

1. A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.
2. The definition of a derivative refers to non-financial variables that are not specific to a party to the contract. These include an index of earthquake losses in a particular region and an index of temperatures in a particular city. Non-financial variables specific to a party to the contract include the occurrence or non-occurrence of a fire that damages or destroys an asset of a party to the contract. A change in the fair value of a non-financial asset is specific to the owner if the fair value reflects not only changes in market prices for such assets (a financial variable) but also the condition of the specific non-financial asset held (a non-financial variable). For example, if a guarantee of the residual value of a specific car exposes the guarantor to the risk of changes in the car's physical condition, the change in that residual value is specific to the owner of the car.
3. If, in applying paragraph 7.2.44, an entity reinstates a discontinued hedging relationship, the entity shall read references in paragraphs 6.9.11 and 6.9.12 to the date the alternative benchmark rate is designated as a noncontractually specified risk component for the first time as referring to the date of initial application of these amendments (ie the 24-month period for that alternative benchmark rate designated as a non-contractually specified risk component begins from the date of initial application of these amendments).
4. The credit risk on a financial instrument is considered low for the purposes of paragraph 5.5.10, if the financial instrument has a low risk of default, the borrower has a strong capacity to meet its contractual cash flow obligations in the near term and adverse changes in economic and business conditions in the longer term may, but will not necessarily, reduce the ability of the borrower to fulfil its contractual cash flow obligations. Financial instruments are not considered to have low credit risk when they are regarded as having a low risk of loss simply because of the value of collateral and the financial instrument without that collateral would not be considered low credit risk. Financial instruments are also not considered to have low credit risk simply because they have a lower risk of default than the entity's other financial instruments or relative to the credit risk of the jurisdiction within which an entity operates.

*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.

CIGI:TSX Colliers International Group Inc. Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B1	Ba2
Income Statement	Caa2	Baa2
Balance Sheet	Baa2	B1
Leverage Ratios	B1	Baa2
Cash Flow	Caa2	Caa2
Rates of Return and Profitability	Baa2	Baa2

*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?

Conclusions

Colliers International Group Inc. is assigned short-term B1 & long-term Ba2 estimated rating. Colliers International Group Inc. prediction model is evaluated with Modular Neural Network (CNN Layer) and Beta^1,2,3,4 and it is concluded that the CIGI:TSX stock is predictable in the short/long term. According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Sell

Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 876 signals.

References

1. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. S&P 500: Is the Bull Market Ready to Run Out of Steam?. AC Investment Research Journal, 220(44).
2. Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
3. Wager S, Athey S. 2017. Estimation and inference of heterogeneous treatment effects using random forests. J. Am. Stat. Assoc. 113:1228–42
4. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Can Neural Networks Predict Stock Market?. AC Investment Research Journal, 220(44).
5. Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.
6. Y. Le Tallec. Robust, risk-sensitive, and data-driven control of Markov decision processes. PhD thesis, Massachusetts Institute of Technology, 2007.
7. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press

Frequently Asked Questions

Q: What is the prediction methodology for CIGI:TSX stock?
A: CIGI:TSX stock prediction methodology: We evaluate the prediction models Modular Neural Network (CNN Layer) and Beta
Q: Is CIGI:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Sell CIGI:TSX Stock.
Q: Is Colliers International Group Inc. stock a good investment?
A: The consensus rating for Colliers International Group Inc. is Sell and is assigned short-term B1 & long-term Ba2 estimated rating.
Q: What is the consensus rating of CIGI:TSX stock?
A: The consensus rating for CIGI:TSX is Sell.
Q: What is the prediction period for CIGI:TSX stock?
A: The prediction period for CIGI:TSX is 8 Weeks