Outlook: NB GLOBAL CORPORATE INCOME TRUST is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 23 Mar 2023 for (n+1 year)
Methodology : Reinforcement Machine Learning (ML)

## Abstract

NB GLOBAL CORPORATE INCOME TRUST prediction model is evaluated with Reinforcement Machine Learning (ML) and Independent T-Test1,2,3,4 and it is concluded that the NBI stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

## Key Points

2. Can we predict stock market using machine learning?
3. What is prediction in deep learning?

## NBI Target Price Prediction Modeling Methodology

We consider NB GLOBAL CORPORATE INCOME TRUST Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of NBI 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(Independent T-Test)5,6,7= $\begin{array}{cccc}{p}_{a1}& {p}_{a2}& \dots & {p}_{1n}\\ & ⋮\\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & ⋮\\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & ⋮\\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Reinforcement Machine Learning (ML)) X S(n):→ (n+1 year) $\begin{array}{l}\int {r}^{s}\mathrm{rs}\end{array}$

n:Time series to forecast

p:Price signals of NBI stock

j:Nash equilibria (Neural Network)

k:Dominated move

a:Best response for target price

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?

## NBI Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: NBI NB GLOBAL CORPORATE INCOME TRUST
Time series to forecast n: 23 Mar 2023 for (n+1 year)

According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

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%

## IFRS Reconciliation Adjustments for NB GLOBAL CORPORATE INCOME TRUST

1. If a component of the cash flows of a financial or a non-financial item is designated as the hedged item, that component must be less than or equal to the total cash flows of the entire item. However, all of the cash flows of the entire item may be designated as the hedged item and hedged for only one particular risk (for example, only for those changes that are attributable to changes in LIBOR or a benchmark commodity price).
2. Interest Rate Benchmark Reform—Phase 2, which amended IFRS 9, IAS 39, IFRS 7, IFRS 4 and IFRS 16, issued in August 2020, added paragraphs 5.4.5–5.4.9, 6.8.13, Section 6.9 and paragraphs 7.2.43–7.2.46. An entity shall apply these amendments for annual periods beginning on or after 1 January 2021. Earlier application is permitted. If an entity applies these amendments for an earlier period, it shall disclose that fact.
3. When a group of items that constitute a net position is designated as a hedged item, an entity shall designate the overall group of items that includes the items that can make up the net position. An entity is not permitted to designate a non-specific abstract amount of a net position. For example, an entity has a group of firm sale commitments in nine months' time for FC100 and a group of firm purchase commitments in 18 months' time for FC120. The entity cannot designate an abstract amount of a net position up to FC20. Instead, it must designate a gross amount of purchases and a gross amount of sales that together give rise to the hedged net position. An entity shall designate gross positions that give rise to the net position so that the entity is able to comply with the requirements for the accounting for qualifying hedging relationships.
4. At the date of initial application, an entity shall determine whether the treatment in paragraph 5.7.7 would create or enlarge an accounting mismatch in profit or loss on the basis of the facts and circumstances that exist at the date of initial application. This Standard shall be applied retrospectively on the basis of that determination.

*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.

## Conclusions

NB GLOBAL CORPORATE INCOME TRUST is assigned short-term Ba1 & long-term Ba1 estimated rating. NB GLOBAL CORPORATE INCOME TRUST prediction model is evaluated with Reinforcement Machine Learning (ML) and Independent T-Test1,2,3,4 and it is concluded that the NBI stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Buy

### NBI NB GLOBAL CORPORATE INCOME TRUST Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementCaa2Baa2
Balance SheetCBaa2
Leverage RatiosCC
Cash FlowBa3Ba1
Rates of Return and ProfitabilityBaa2C

*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?

### Prediction Confidence Score

Trust metric by Neural Network: 78 out of 100 with 536 signals.

## References

1. R. Williams. Simple statistical gradient-following algorithms for connectionist reinforcement learning. Ma- chine learning, 8(3-4):229–256, 1992
2. Keane MP. 2013. Panel data discrete choice models of consumer demand. In The Oxford Handbook of Panel Data, ed. BH Baltagi, pp. 54–102. Oxford, UK: Oxford Univ. Press
3. M. Colby, T. Duchow-Pressley, J. J. Chung, and K. Tumer. Local approximation of difference evaluation functions. In Proceedings of the Fifteenth International Joint Conference on Autonomous Agents and Multiagent Systems, Singapore, May 2016
4. Alexander, J. C. Jr. (1995), "Refining the degree of earnings surprise: A comparison of statistical and analysts' forecasts," Financial Review, 30, 469–506.
5. M. Ono, M. Pavone, Y. Kuwata, and J. Balaram. Chance-constrained dynamic programming with application to risk-aware robotic space exploration. Autonomous Robots, 39(4):555–571, 2015
6. Angrist JD, Pischke JS. 2008. Mostly Harmless Econometrics: An Empiricist's Companion. Princeton, NJ: Princeton Univ. Press
7. Breiman L. 1996. Bagging predictors. Mach. Learn. 24:123–40
Frequently Asked QuestionsQ: What is the prediction methodology for NBI stock?
A: NBI stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Independent T-Test
Q: Is NBI stock a buy or sell?
A: The dominant strategy among neural network is to Buy NBI Stock.
Q: Is NB GLOBAL CORPORATE INCOME TRUST stock a good investment?
A: The consensus rating for NB GLOBAL CORPORATE INCOME TRUST is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of NBI stock?
A: The consensus rating for NBI is Buy.
Q: What is the prediction period for NBI stock?
A: The prediction period for NBI is (n+1 year)

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