BBU.UN:TSX Brookfield Business Partners L.P.

Brookfield Business Partners L.P. Research Report

Summary

This study aims to predict the direction of stock prices by integrating time-varying effective transfer entropy (ETE) and various machine learning algorithms. At first, we explore that the ETE based on 3 and 6 months moving windows can be regarded as the market explanatory variable by analyzing the association between the financial crises and Granger-causal relationships among the stocks. We evaluate Brookfield Business Partners L.P. prediction models with Multi-Task Learning (ML) and Factor^1,2,3,4 and conclude that the BBU.UN:TSX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold BBU.UN:TSX stock.

Key Points

1. What are the most successful trading algorithms?
2. What are the most successful trading algorithms?
3. Which neural network is best for prediction?

BBU.UN:TSX Target Price Prediction Modeling Methodology

We consider Brookfield Business Partners L.P. Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of BBU.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(Factor)^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(Multi-Task Learning (ML)) X S(n):→ (n+6 month) $\sum _{i=1}^n\left(s_i\right)$

n:Time series to forecast

p:Price signals of BBU.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?

BBU.UN:TSX Stock Forecast (Buy or Sell) for (n+6 month)

Sample Set: Neural Network
Stock/Index: BBU.UN:TSX Brookfield Business Partners L.P.
Time series to forecast n: 01 Dec 2022 for (n+6 month)

According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold BBU.UN:TSX stock.

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 (Yellow to Green): *Technical Analysis%

Adjusted IFRS* Prediction Methods for Brookfield Business Partners L.P.

1. An entity shall assess separately whether each subgroup meets the requirements in paragraph 6.6.1 to be an eligible hedged item. If any subgroup fails to meet the requirements in paragraph 6.6.1, the entity shall discontinue hedge accounting prospectively for the hedging relationship in its entirety. An entity also shall apply the requirements in paragraphs 6.5.8 and 6.5.11 to account for ineffectiveness related to the hedging relationship in its entirety.
2. A net position is eligible for hedge accounting only if an entity hedges on a net basis for risk management purposes. Whether an entity hedges in this way is a matter of fact (not merely of assertion or documentation). Hence, an entity cannot apply hedge accounting on a net basis solely to achieve a particular accounting outcome if that would not reflect its risk management approach. Net position hedging must form part of an established risk management strategy. Normally this would be approved by key management personnel as defined in IAS 24.
3. An entity shall apply the impairment requirements in Section 5.5 retrospectively in accordance with IAS 8 subject to paragraphs 7.2.15 and 7.2.18–7.2.20.
4. 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).

*International Financial Reporting Standards (IFRS) are a set of accounting rules for the financial statements of public companies that are intended to make them consistent, transparent, and easily comparable around the world.

Conclusions

Brookfield Business Partners L.P. assigned short-term B2 & long-term B1 forecasted stock rating. We evaluate the prediction models Multi-Task Learning (ML) with Factor^1,2,3,4 and conclude that the BBU.UN:TSX stock is predictable in the short/long term. According to price forecasts for (n+6 month) period: The dominant strategy among neural network is to Hold BBU.UN:TSX stock.

Financial State Forecast for BBU.UN:TSX Brookfield Business Partners L.P. Options & Futures

Rating	Short-Term	Long-Term Senior
Outlook*	B2	B1
Operational Risk	48	84
Market Risk	87	52
Technical Analysis	64	90
Fundamental Analysis	38	44
Risk Unsystematic	37	31

Prediction Confidence Score

Trust metric by Neural Network: 85 out of 100 with 698 signals.

References

1. Mikolov T, Yih W, Zweig G. 2013c. Linguistic regularities in continuous space word representations. In Pro- ceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 746–51. New York: Assoc. Comput. Linguist.
2. A. K. Agogino and K. Tumer. Analyzing and visualizing multiagent rewards in dynamic and stochastic environments. Journal of Autonomous Agents and Multi-Agent Systems, 17(2):320–338, 2008
3. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
4. Athey S, Tibshirani J, Wager S. 2016b. Generalized random forests. arXiv:1610.01271 [stat.ME]
5. Semenova V, Goldman M, Chernozhukov V, Taddy M. 2018. Orthogonal ML for demand estimation: high dimensional causal inference in dynamic panels. arXiv:1712.09988 [stat.ML]
6. R. Rockafellar and S. Uryasev. Conditional value-at-risk for general loss distributions. Journal of Banking and Finance, 26(7):1443 – 1471, 2002
7. M. Petrik and D. Subramanian. An approximate solution method for large risk-averse Markov decision processes. In Proceedings of the 28th International Conference on Uncertainty in Artificial Intelligence, 2012.

Frequently Asked Questions

Q: What is the prediction methodology for BBU.UN:TSX stock?
A: BBU.UN:TSX stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Factor
Q: Is BBU.UN:TSX stock a buy or sell?
A: The dominant strategy among neural network is to Hold BBU.UN:TSX Stock.
Q: Is Brookfield Business Partners L.P. stock a good investment?
A: The consensus rating for Brookfield Business Partners L.P. is Hold and assigned short-term B2 & long-term B1 forecasted stock rating.
Q: What is the consensus rating of BBU.UN:TSX stock?
A: The consensus rating for BBU.UN:TSX is Hold.
Q: What is the prediction period for BBU.UN:TSX stock?
A: The prediction period for BBU.UN:TSX is (n+6 month)

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