Greencity Acquisition Corporation Unit is assigned short-term Ba1 & long-term Ba1 estimated  rating.

Jorgenson, Dale W.; Weitzman, Martin L.; ZXhang, Yoshua X; Haxo, Yann M; Mat , Ying X

Outlook: Greencity Acquisition Corporation Unit is assigned short-term Ba1 & long-term Ba1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Buy
Time series to forecast n: for Weeks²
Methodology : Modular Neural Network (Market Direction Analysis)
Hypothesis Testing : Sign Test
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.

Greencity Acquisition Corporation Unit prediction model is evaluated with Modular Neural Network (Market Direction Analysis) and Sign Test^1,2,3,4 and it is concluded that the GRCYU stock is predictable in the short/long term. Modular neural networks (MNNs) are a type of artificial neural network that can be used for market direction analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements.⁵ According to price forecasts for 16 Weeks period, the dominant strategy among neural network is: Buy

Key Points

What is prediction model?
Dominated Move
How can neural networks improve predictions?

GRCYU Stock Price Forecast

We consider Greencity Acquisition Corporation Unit Decision Process with Modular Neural Network (Market Direction Analysis) where A is the set of discrete actions of GRCYU 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: GRCYU Greencity Acquisition Corporation Unit
Time series to forecast: 16 Weeks

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

F(Sign Test)^6,7=

\begin{matrix} p_{a 1} & p_{a 2} & \dots & p_{1 n} \\ ⋮ \\ p_{j 1} & p_{j 2} & \dots & p_{j n} \\ ⋮ \\ p_{k 1} & p_{k 2} & \dots & p_{k n} \\ ⋮ \\ p_{n 1} & p_{n 2} & \dots & p_{n n} \end{matrix}

X R(Modular Neural Network (Market Direction Analysis)) X S(n):→ 16 Weeks

\vec{S} = (s_{1}, s_{2}, s_{3})

n:Time series to forecast

p:Price signals of GRCYU stock

j:Nash equilibria (Neural Network)

k:Dominated move of GRCYU stock holders

a:Best response for GRCYU target price

Modular neural networks (MNNs) are a type of artificial neural network that can be used for market direction analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying patterns in data or predicting future price movements. The modules are then combined to form a single neural network that can perform multiple tasks.In the context of market direction analysis, MNNs can be used to identify patterns in market data that suggest that the market is likely to move in a particular direction. This information can then be used to make predictions about future price movements.⁵ The sign test is a non-parametric hypothesis test that is used to compare two paired samples. In a paired sample, each data point in one sample is paired with a data point in the other sample. The pairs are typically related in some way, such as before and after measurements, or measurements from the same subject under different conditions. The sign test is a non-parametric test, which means that it does not assume that the data is normally distributed. The sign test is also a dependent samples test, which means that the data points in each pair are correlated.^6,7

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?

GRCYU 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 (Market Direction Analysis) based GRCYU Stock Prediction Model

The following example describes a situation in which an accounting mismatch would be created in profit or loss if the effects of changes in the credit risk of the liability were presented in other comprehensive income. A mortgage bank provides loans to customers and funds those loans by selling bonds with matching characteristics (eg amount outstanding, repayment profile, term and currency) in the market. The contractual terms of the loan permit the mortgage customer to prepay its loan (ie satisfy its obligation to the bank) by buying the corresponding bond at fair value in the market and delivering that bond to the mortgage bank. As a result of that contractual prepayment right, if the credit quality of the bond worsens (and, thus, the fair value of the mortgage bank's liability decreases), the fair value of the mortgage bank's loan asset also decreases. The change in the fair value of the asset reflects the mortgage customer's contractual right to prepay the mortgage loan by buying the underlying bond at fair value (which, in this example, has decreased) and delivering the bond to the mortgage bank. Consequently, the effects of changes in the credit risk of the liability (the bond) will be offset in profit or loss by a corresponding change in the fair value of a financial asset (the loan). If the effects of changes in the liability's credit risk were presented in other comprehensive income there would be an accounting mismatch in profit or loss. Consequently, the mortgage bank is required to present all changes in fair value of the liability (including the effects of changes in the liability's credit risk) in profit or loss.
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.
An equity method investment cannot be a hedged item in a fair value hedge. This is because the equity method recognises in profit or loss the investor's share of the investee's profit or loss, instead of changes in the investment's fair value. For a similar reason, an investment in a consolidated subsidiary cannot be a hedged item in a fair value hedge. This is because consolidation recognises in profit or loss the subsidiary's profit or loss, instead of changes in the investment's fair value. A hedge of a net investment in a foreign operation is different because it is a hedge of the foreign currency exposure, not a fair value hedge of the change in the value of the investment.
For example, when the critical terms (such as the nominal amount, maturity and underlying) of the hedging instrument and the hedged item match or are closely aligned, it might be possible for an entity to conclude on the basis of a qualitative assessment of those critical terms that the hedging instrument and the hedged item have values that will generally move in the opposite direction because of the same risk and hence that an economic relationship exists between the hedged item and the hedging instrument (see paragraphs B6.4.4–B6.4.6).

*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.

GRCYU Greencity Acquisition Corporation Unit Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B1	Baa2
Balance Sheet	Ba2	Ba3
Leverage Ratios	B1	Baa2
Cash Flow	Baa2	Ba1
Rates of Return and Profitability	Baa2	Caa2

*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

R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
O. Bardou, N. Frikha, and G. Pag`es. Computing VaR and CVaR using stochastic approximation and adaptive unconstrained importance sampling. Monte Carlo Methods and Applications, 15(3):173–210, 2009.
M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
Holland PW. 1986. Statistics and causal inference. J. Am. Stat. Assoc. 81:945–60
M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
Bengio Y, Ducharme R, Vincent P, Janvin C. 2003. A neural probabilistic language model. J. Mach. Learn. Res. 3:1137–55
J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017

Frequently Asked Questions

Q: What is the prediction methodology for GRCYU stock?
A: GRCYU stock prediction methodology: We evaluate the prediction models Modular Neural Network (Market Direction Analysis) and Sign Test
Q: Is GRCYU stock a buy or sell?
A: The dominant strategy among neural network is to Buy GRCYU Stock.
Q: Is Greencity Acquisition Corporation Unit stock a good investment?
A: The consensus rating for Greencity Acquisition Corporation Unit is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of GRCYU stock?
A: The consensus rating for GRCYU is Buy.
Q: What is the prediction period for GRCYU stock?
A: The prediction period for GRCYU is 16 Weeks

What did you think about the prediction? (Insufficient-Outstanding)

Tell us how we can improve PredictiveAI

Greencity Acquisition Corporation Unit is assigned short-term Ba1 & long-term Ba1 estimated rating.