IGD Stock: A High-Growth Company with a Bright Future

Outlook: Voya Global Equity Dividend and Premium Opportunity Fund is assigned short-term B1 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Buy
Time series to forecast n: for Weeks²
Methodology : Multi-Instance Learning (ML)
Hypothesis Testing : Wilcoxon Sign-Rank 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.

Summary

Voya Global Equity Dividend and Premium Opportunity Fund prediction model is evaluated with Multi-Instance Learning (ML) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the IGD stock is predictable in the short/long term. Multi-instance learning (MIL) is a machine learning (ML) problem where a dataset consists of multiple instances, and each instance is associated with a single label. The goal of MIL is to learn a model that can predict the label of a new instance based on the labels of the instances that it is similar to. MIL is a challenging problem because the instances in a dataset are not labeled individually. This means that the model cannot simply learn a mapping from the features of an instance to its label. Instead, the model must learn a way to combine the features of multiple instances to predict the label of a new instance.⁵ According to price forecasts for 1 Year period, the dominant strategy among neural network is: Buy

Key Points

1. Multi-Instance Learning (ML) for IGD stock price prediction process.
2. Wilcoxon Sign-Rank Test
3. Probability Distribution
4. What is neural prediction?
5. What is prediction in deep learning?

IGD Stock Price Forecast

We consider Voya Global Equity Dividend and Premium Opportunity Fund Decision Process with Multi-Instance Learning (ML) where A is the set of discrete actions of IGD 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: IGD Voya Global Equity Dividend and Premium Opportunity Fund
Time series to forecast: 1 Year

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

F(Wilcoxon Sign-Rank Test)^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(Multi-Instance Learning (ML)) X S(n):→ 1 Year $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of IGD stock

j:Nash equilibria (Neural Network)

k:Dominated move of IGD stock holders

a:Best response for IGD target price

Multi-instance learning (MIL) is a machine learning (ML) problem where a dataset consists of multiple instances, and each instance is associated with a single label. The goal of MIL is to learn a model that can predict the label of a new instance based on the labels of the instances that it is similar to. MIL is a challenging problem because the instances in a dataset are not labeled individually. This means that the model cannot simply learn a mapping from the features of an instance to its label. Instead, the model must learn a way to combine the features of multiple instances to predict the label of a new instance.⁵ The Wilcoxon rank-sum test, also known as the Mann-Whitney U test, is a non-parametric test that is used to compare the medians of two independent samples. It is a rank-based test, which means that it does not assume that the data is normally distributed. The Wilcoxon rank-sum test is calculated by first ranking the data from both samples, and then finding the sum of the ranks for one of the samples. The Wilcoxon rank-sum test statistic is then calculated by subtracting the sum of the ranks for one sample from the sum of the ranks for the other sample. The p-value for the Wilcoxon rank-sum test is calculated using a table of critical values. The p-value is the probability of obtaining a test statistic at least as extreme as the one observed, assuming that the null hypothesis is true.^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?

IGD 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 Multi-Instance Learning (ML) based IGD Stock Prediction Model

1. The underlying pool must contain one or more instruments that have contractual cash flows that are solely payments of principal and interest on the principal amount outstanding
2. At the date of initial application, an entity shall use reasonable and supportable information that is available without undue cost or effort to determine the credit risk at the date that a financial instrument was initially recognised (or for loan commitments and financial guarantee contracts at the date that the entity became a party to the irrevocable commitment in accordance with paragraph 5.5.6) and compare that to the credit risk at the date of initial application of this Standard.
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. If changes are made in addition to those changes required by interest rate benchmark reform to the financial asset or financial liability designated in a hedging relationship (as described in paragraphs 5.4.6–5.4.8) or to the designation of the hedging relationship (as required by paragraph 6.9.1), an entity shall first apply the applicable requirements in this Standard to determine if those additional changes result in the discontinuation of hedge accounting. If the additional changes do not result in the discontinuation of hedge accounting, an entity shall amend the formal designation of the hedging relationship as specified in paragraph 6.9.1.

*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.

IGD Voya Global Equity Dividend and Premium Opportunity Fund Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	B1	B2
Income Statement	B3	C
Balance Sheet	Caa2	B2
Leverage Ratios	Caa2	C
Cash Flow	Baa2	Caa2
Rates of Return and Profitability	Ba1	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?

References

1. Thomas P, Brunskill E. 2016. Data-efficient off-policy policy evaluation for reinforcement learning. In Pro- ceedings of the International Conference on Machine Learning, pp. 2139–48. La Jolla, CA: Int. Mach. Learn. Soc.
2. Tibshirani R, Hastie T. 1987. Local likelihood estimation. J. Am. Stat. Assoc. 82:559–67
3. S. Bhatnagar. An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes. Systems & Control Letters, 59(12):760–766, 2010
4. White H. 1992. Artificial Neural Networks: Approximation and Learning Theory. Oxford, UK: Blackwell
5. Dimakopoulou M, Zhou Z, Athey S, Imbens G. 2018. Balanced linear contextual bandits. arXiv:1812.06227 [cs.LG]
6. Abadie A, Cattaneo MD. 2018. Econometric methods for program evaluation. Annu. Rev. Econ. 10:465–503
7. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010

Frequently Asked Questions

Q: Is IGD stock expected to rise?
A: IGD stock prediction model is evaluated with Multi-Instance Learning (ML) and Wilcoxon Sign-Rank Test and it is concluded that dominant strategy for IGD stock is Buy
Q: Is IGD stock a buy or sell?
A: The dominant strategy among neural network is to Buy IGD Stock.
Q: Is Voya Global Equity Dividend and Premium Opportunity Fund stock a good investment?
A: The consensus rating for Voya Global Equity Dividend and Premium Opportunity Fund is Buy and is assigned short-term B1 & long-term B2 estimated rating.
Q: What is the consensus rating of IGD stock?
A: The consensus rating for IGD is Buy.
Q: What is the forecast for IGD stock?
A: IGD target price forecast: Buy