BIP.UN:TSX Stock: A Cautionary Tale

Outlook: Brookfield Infrastructure Partners L.P. is assigned short-term Ba3 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised¹ :
Dominant Strategy : Hold
Time series to forecast n: for Weeks²
Methodology : Modular Neural Network (News Feed Sentiment Analysis)
Hypothesis Testing : Chi-Square
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

Brookfield Infrastructure Partners L.P. prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Chi-Square^1,2,3,4 and it is concluded that the BIP.UN:TSX 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 news feed sentiment 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 news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Hold

Key Points

1. Can machine learning predict?
2. Short/Long Term Stocks
3. Why do we need predictive models?

BIP.UN:TSX Target Price Prediction Modeling Methodology

We consider Brookfield Infrastructure Partners L.P. Decision Process with Modular Neural Network (News Feed Sentiment Analysis) 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(Chi-Square)^5,6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (News Feed Sentiment Analysis)) X S(n):→ 1 Year $\begin{array}{l}\int r^s\mathrm{rs}\end{array}$

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

Modular Neural Network (News Feed Sentiment Analysis)

A modular neural network (MNN) is a type of artificial neural network that can be used for news feed sentiment 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 news feed sentiment analysis, MNNs can be used to identify the sentiment of news articles, social media posts, and other forms of online content. This information can then be used to filter out irrelevant or unwanted content, to identify trends in public opinion, and to target users with relevant advertising.

Chi-Square

A chi-squared test is a statistical hypothesis test that assesses whether observed frequencies in a sample differ significantly from expected frequencies. It is one of the most widely used statistical tests in the social sciences and in many areas of observational research. The chi-squared test is a non-parametric test, meaning that it does not assume that the data is normally distributed. This makes it a versatile tool that can be used to analyze a wide variety of data. There are two main types of chi-squared tests: the chi-squared goodness of fit test and the chi-squared test of independence.

 

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)

Sample Set: Neural Network
Stock/Index: BIP.UN:TSX Brookfield Infrastructure Partners L.P.
Time series to forecast: 1 Year

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

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 (News Feed Sentiment Analysis) based BIP.UN:TSX Stock Prediction Model

1. 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).
2. If an entity previously accounted at cost (in accordance with IAS 39), for an investment in an equity instrument that does not have a quoted price in an active market for an identical instrument (ie a Level 1 input) (or for a derivative asset that is linked to and must be settled by delivery of such an equity instrument) it shall measure that instrument at fair value at the date of initial application. Any difference between the previous carrying amount and the fair value shall be recognised in the opening retained earnings (or other component of equity, as appropriate) of the reporting period that includes the date of initial application.
3. Paragraphs 6.9.7–6.9.13 provide exceptions to the requirements specified in those paragraphs only. An entity shall apply all other hedge accounting requirements in this Standard, including the qualifying criteria in paragraph 6.4.1, to hedging relationships that were directly affected by interest rate benchmark reform.
4. If an entity prepares interim financial reports in accordance with IAS 34 Interim Financial Reporting the entity need not apply the requirements in this Standard to interim periods prior to the date of initial application if it is impracticable (as defined in IAS 8).

*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.

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

Rating	Short-Term	Long-Term Senior
Outlook*	Ba3	B1
Income Statement	Caa2	B1
Balance Sheet	Baa2	Baa2
Leverage Ratios	C	B2
Cash Flow	Baa2	B3
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?

Conclusions

Brookfield Infrastructure Partners L.P. is assigned short-term Ba3 & long-term B1 estimated rating. Brookfield Infrastructure Partners L.P. prediction model is evaluated with Modular Neural Network (News Feed Sentiment Analysis) and Chi-Square^1,2,3,4 and it is concluded that the BIP.UN:TSX stock is predictable in the short/long term. According to price forecasts for 1 Year period, the dominant strategy among neural network is: Hold

Prediction Confidence Score

Trust metric by Neural Network: 75 out of 100 with 642 signals.

References

1. Friedman JH. 2002. Stochastic gradient boosting. Comput. Stat. Data Anal. 38:367–78
2. Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press
3. G. Konidaris, S. Osentoski, and P. Thomas. Value function approximation in reinforcement learning using the Fourier basis. In AAAI, 2011
4. R. Howard and J. Matheson. Risk sensitive Markov decision processes. Management Science, 18(7):356– 369, 1972
5. Athey S. 2017. Beyond prediction: using big data for policy problems. Science 355:483–85
6. Van der Vaart AW. 2000. Asymptotic Statistics. Cambridge, UK: Cambridge Univ. Press
7. Mnih A, Hinton GE. 2007. Three new graphical models for statistical language modelling. In International Conference on Machine Learning, pp. 641–48. La Jolla, CA: Int. Mach. Learn. Soc.

Frequently Asked Questions

Q: What is the prediction methodology for BIP.UN:TSX stock?
A: BIP.UN:TSX stock prediction methodology: We evaluate the prediction models Modular Neural Network (News Feed Sentiment Analysis) and Chi-Square
Q: Is BIP.UN:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Hold 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 Hold and is assigned short-term Ba3 & long-term B1 estimated rating.
Q: What is the consensus rating of BIP.UN:TSX stock?
A: The consensus rating for BIP.UN:TSX is Hold.
Q: What is the prediction period for BIP.UN:TSX stock?
A: The prediction period for BIP.UN:TSX is 1 Year

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