AUC Score :
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n:
Methodology : Modular Neural Network (Emotional Trigger/Responses Analysis)
Hypothesis Testing : Spearman Correlation
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
Global Net Lease Inc. 7.375% Series E Cumulative Redeemable Perpetual Preferred Stock prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation1,2,3,4 and it is concluded that the GNL^E stock is predictable in the short/long term. A modular neural network (MNN) is a type of artificial neural network that can be used for emotional trigger/responses analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of emotional trigger/responses analysis, MNNs can be used to identify the emotional triggers that cause people to experience certain emotions, and to identify the responses that people typically exhibit when they experience those emotions. This information can then be used to develop more effective emotional support systems, to improve the accuracy of artificial intelligence systems, and to create more engaging and immersive entertainment experiences.5 According to price forecasts for 8 Weeks period, the dominant strategy among neural network is: Buy
Key Points
- Modular Neural Network (Emotional Trigger/Responses Analysis) for GNL^E stock price prediction process.
- Spearman Correlation
- Reaction Function
- Buy, Sell and Hold Signals
- Short/Long Term Stocks
GNL^E Stock Price Forecast
We consider Global Net Lease Inc. 7.375% Series E Cumulative Redeemable Perpetual Preferred Stock Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of GNL^E 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: GNL^E Global Net Lease Inc. 7.375% Series E Cumulative Redeemable Perpetual Preferred Stock
Time series to forecast: 8 Weeks
According to price forecasts, the dominant strategy among neural network is: Buy
n:Time series to forecast
p:Price signals of GNL^E stock
j:Nash equilibria (Neural Network)
k:Dominated move of GNL^E stock holders
a:Best response for GNL^E target price
A modular neural network (MNN) is a type of artificial neural network that can be used for emotional trigger/responses analysis. MNNs are made up of multiple smaller neural networks, called modules. Each module is responsible for learning a specific task, such as identifying sentiment in text or identifying patterns in data. The modules are then combined to form a single neural network that can perform multiple tasks. In the context of emotional trigger/responses analysis, MNNs can be used to identify the emotional triggers that cause people to experience certain emotions, and to identify the responses that people typically exhibit when they experience those emotions. This information can then be used to develop more effective emotional support systems, to improve the accuracy of artificial intelligence systems, and to create more engaging and immersive entertainment experiences.5 Spearman correlation is a nonparametric measure of the strength and direction of association between two variables. It is a rank-based correlation, which means that it does not assume that the data is normally distributed. Spearman correlation is calculated by first ranking the data for each variable, and then calculating the Pearson correlation between the ranks.6,7
For further technical information as per how our model work we invite you to visit the article below:
GNL^E 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 (Emotional Trigger/Responses Analysis) based GNL^E Stock Prediction Model
- However, depending on the nature of the financial instruments and the credit risk information available for particular groups of financial instruments, an entity may not be able to identify significant changes in credit risk for individual financial instruments before the financial instrument becomes past due. This may be the case for financial instruments such as retail loans for which there is little or no updated credit risk information that is routinely obtained and monitored on an individual instrument until a customer breaches the contractual terms. If changes in the credit risk for individual financial instruments are not captured before they become past due, a loss allowance based only on credit information at an individual financial instrument level would not faithfully represent the changes in credit risk since initial recognition.
- For example, Entity A, whose functional currency is its local currency, has a firm commitment to pay FC150,000 for advertising expenses in nine months' time and a firm commitment to sell finished goods for FC150,000 in 15 months' time. Entity A enters into a foreign currency derivative that settles in nine months' time under which it receives FC100 and pays CU70. Entity A has no other exposures to FC. Entity A does not manage foreign currency risk on a net basis. Hence, Entity A cannot apply hedge accounting for a hedging relationship between the foreign currency derivative and a net position of FC100 (consisting of FC150,000 of the firm purchase commitment—ie advertising services—and FC149,900 (of the FC150,000) of the firm sale commitment) for a nine-month period.
- 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.
- When measuring hedge ineffectiveness, an entity shall consider the time value of money. Consequently, the entity determines the value of the hedged item on a present value basis and therefore the change in the value of the hedged item also includes the effect of the time value of money.
*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.
GNL^E Global Net Lease Inc. 7.375% Series E Cumulative Redeemable Perpetual Preferred Stock Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | B2 | B2 |
Income Statement | Ba1 | Caa2 |
Balance Sheet | C | Caa2 |
Leverage Ratios | B2 | B2 |
Cash Flow | B3 | Baa2 |
Rates of Return and Profitability | Baa2 | C |
*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
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- White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
- Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
- Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20
- Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, et al. 2008. Top 10 algorithms in data mining. Knowl. Inform. Syst. 14:1–37
- Hartigan JA, Wong MA. 1979. Algorithm as 136: a k-means clustering algorithm. J. R. Stat. Soc. Ser. C 28:100–8
- Z. Wang, T. Schaul, M. Hessel, H. van Hasselt, M. Lanctot, and N. de Freitas. Dueling network architectures for deep reinforcement learning. In Proceedings of the International Conference on Machine Learning (ICML), pages 1995–2003, 2016.
Frequently Asked Questions
Q: Is GNL^E stock expected to rise?A: GNL^E stock prediction model is evaluated with Modular Neural Network (Emotional Trigger/Responses Analysis) and Spearman Correlation and it is concluded that dominant strategy for GNL^E stock is Buy
Q: Is GNL^E stock a buy or sell?
A: The dominant strategy among neural network is to Buy GNL^E Stock.
Q: Is Global Net Lease Inc. 7.375% Series E Cumulative Redeemable Perpetual Preferred Stock stock a good investment?
A: The consensus rating for Global Net Lease Inc. 7.375% Series E Cumulative Redeemable Perpetual Preferred Stock is Buy and is assigned short-term B2 & long-term B2 estimated rating.
Q: What is the consensus rating of GNL^E stock?
A: The consensus rating for GNL^E is Buy.
Q: What is the forecast for GNL^E stock?
A: GNL^E target price forecast: Buy