Outlook: Brookfield Infrastructure Partners L.P. assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Sell
Time series to forecast n: 31 Dec 2022 for (n+1 year)
Methodology : Transfer Learning (ML)

## Abstract

Stock market prediction is a major exertion in the field of finance and establishing businesses. Stock market is totally uncertain as the prices of stocks keep fluctuating on a daily basis because of numerous factors that influence it. One of the traditional ways of predicting stock prices was by using only historical data. But with time it was observed that other factors such as peoples' sentiments and other news events occurring in and around the country affect the stock market, for e.g. national elections, natural calamity etc.(Hushani, P., 2019. Using autoregressive modelling and machine learning for stock market prediction and trading. In Third International Congress on Information and Communication Technology (pp. 767-774). Springer, Singapore.) We evaluate Brookfield Infrastructure Partners L.P. prediction models with Transfer Learning (ML) and Multiple Regression1,2,3,4 and conclude that the BIP.UN:TSX stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

## Key Points

1. Which neural network is best for prediction?
2. What is the use of Markov decision process?
3. Stock Forecast Based On a Predictive Algorithm

## BIP.UN:TSX Target Price Prediction Modeling Methodology

We consider Brookfield Infrastructure Partners L.P. Decision Process with Transfer Learning (ML) where A is the set of discrete actions of BIP.UN: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(Multiple Regression)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(Transfer Learning (ML)) X S(n):→ (n+1 year) $R=\left(\begin{array}{ccc}1& 0& 0\\ 0& 1& 0\\ 0& 0& 1\end{array}\right)$

n:Time series to forecast

p:Price signals of BIP.UN:TSX 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?

## BIP.UN:TSX Stock Forecast (Buy or Sell) for (n+1 year)

Sample Set: Neural Network
Stock/Index: BIP.UN:TSX Brookfield Infrastructure Partners L.P.
Time series to forecast n: 31 Dec 2022 for (n+1 year)

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

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 Brookfield Infrastructure Partners L.P.

1. If a financial instrument that was previously recognised as a financial asset is measured at fair value through profit or loss and its fair value decreases below zero, it is a financial liability measured in accordance with paragraph 4.2.1. However, hybrid contracts with hosts that are assets within the scope of this Standard are always measured in accordance with paragraph 4.3.2.
2. Adjusting the hedge ratio by decreasing the volume of the hedged item does not affect how the changes in the fair value of the hedging instrument are measured. The measurement of the changes in the value of the hedged item related to the volume that continues to be designated also remains unaffected. However, from the date of rebalancing, the volume by which the hedged item was decreased is no longer part of the hedging relationship. For example, if an entity originally hedged a volume of 100 tonnes of a commodity at a forward price of CU80 and reduces that volume by 10 tonnes on rebalancing, the hedged item after rebalancing would be 90 tonnes hedged at CU80. The 10 tonnes of the hedged item that are no longer part of the hedging relationship would be accounted for in accordance with the requirements for the discontinuation of hedge accounting (see paragraphs 6.5.6–6.5.7 and B6.5.22–B6.5.28).
3. For loan commitments, an entity considers changes in the risk of a default occurring on the loan to which a loan commitment relates. For financial guarantee contracts, an entity considers the changes in the risk that the specified debtor will default on the contract.
4. Measurement of a financial asset or financial liability and classification of recognised changes in its value are determined by the item's classification and whether the item is part of a designated hedging relationship. Those requirements can create a measurement or recognition inconsistency (sometimes referred to as an 'accounting mismatch') when, for example, in the absence of designation as at fair value through profit or loss, a financial asset would be classified as subsequently measured at fair value through profit or loss and a liability the entity considers related would be subsequently measured at amortised cost (with changes in fair value not recognised). In such circumstances, an entity may conclude that its financial statements would provide more relevant information if both the asset and the liability were measured as at fair value through profit or loss.

*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

Brookfield Infrastructure Partners L.P. assigned short-term Ba1 & long-term Ba1 estimated rating. We evaluate the prediction models Transfer Learning (ML) with Multiple Regression1,2,3,4 and conclude that the BIP.UN:TSX stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Sell

### BIP.UN:TSX Brookfield Infrastructure Partners L.P. Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB3Caa2
Balance SheetBaa2Caa2
Leverage RatiosCaa2C
Cash FlowBaa2Baa2
Rates of Return and ProfitabilityB3C

*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: 74 out of 100 with 552 signals.

## References

1. 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
2. Ashley, R. (1988), "On the relative worth of recent macroeconomic forecasts," International Journal of Forecasting, 4, 363–376.
3. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
4. Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79
5. F. A. Oliehoek and C. Amato. A Concise Introduction to Decentralized POMDPs. SpringerBriefs in Intelligent Systems. Springer, 2016
6. Clements, M. P. D. F. Hendry (1996), "Intercept corrections and structural change," Journal of Applied Econometrics, 11, 475–494.
7. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., When to Sell and When to Hold FTNT Stock. AC Investment Research Journal, 101(3).
Frequently Asked QuestionsQ: What is the prediction methodology for BIP.UN:TSX stock?
A: BIP.UN:TSX stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Multiple Regression
Q: Is BIP.UN:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Sell BIP.UN:TSX Stock.
Q: Is Brookfield Infrastructure Partners L.P. stock a good investment?
A: The consensus rating for Brookfield Infrastructure Partners L.P. is Sell and assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of BIP.UN:TSX stock?
A: The consensus rating for BIP.UN:TSX is Sell.
Q: What is the prediction period for BIP.UN:TSX stock?
A: The prediction period for BIP.UN:TSX is (n+1 year)