**Outlook:**Black Stone Minerals L.P. Common units representing limited partner interests assigned short-term Ba1 & long-term Ba1 forecasted stock rating.

**Dominant Strategy :**Buy

**Time series to forecast n: 19 Dec 2022**for (n+16 weeks)

**Methodology :**Multi-Task Learning (ML)

## Abstract

Fuzzy rough theory can describe real-world situations in a mathematically effective and interpretable way, while evolutionary neural networks can be utilized to solve complex problems. Combining them with these complementary capabilities may lead to evolutionary fuzzy rough neural network with the interpretability and prediction capability. In this article, we propose modifications to the existing models of fuzzy rough neural network and then develop a powerful evolutionary framework for fuzzy rough neural networks by inheriting the merits of both the aforementioned systems.(Anand, C., 2021. Comparison of stock price prediction models using pre-trained neural networks. Journal of Ubiquitous Computing and Communication Technologies (UCCT), 3(02), pp.122-134.)** We evaluate Black Stone Minerals L.P. Common units representing limited partner interests prediction models with Multi-Task Learning (ML) and Logistic Regression ^{1,2,3,4} and conclude that the BSM stock is predictable in the short/long term. **

**According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy**

## Key Points

- Dominated Move
- Trading Signals
- Operational Risk

## BSM Target Price Prediction Modeling Methodology

We consider Black Stone Minerals L.P. Common units representing limited partner interests Decision Process with Multi-Task Learning (ML) where A is the set of discrete actions of BSM 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(Logistic Regression)

^{5,6,7}= $\begin{array}{cccc}{p}_{\mathrm{a}1}& {p}_{\mathrm{a}2}& \dots & {p}_{1n}\\ & \vdots \\ {p}_{j1}& {p}_{j2}& \dots & {p}_{jn}\\ & \vdots \\ {p}_{k1}& {p}_{k2}& \dots & {p}_{kn}\\ & \vdots \\ {p}_{n1}& {p}_{n2}& \dots & {p}_{nn}\end{array}$ X R(Multi-Task Learning (ML)) X S(n):→ (n+16 weeks) $\sum _{i=1}^{n}\left({r}_{i}\right)$

n:Time series to forecast

p:Price signals of BSM 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?

## BSM Stock Forecast (Buy or Sell) for (n+16 weeks)

**Sample Set:**Neural Network

**Stock/Index:**BSM Black Stone Minerals L.P. Common units representing limited partner interests

**Time series to forecast n: 19 Dec 2022**for (n+16 weeks)

**According to price forecasts for (n+16 weeks) 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%**

## Adjusted IFRS* Prediction Methods for Black Stone Minerals L.P. Common units representing limited partner interests

- If the group of items does not have any offsetting risk positions (for example, a group of foreign currency expenses that affect different line items in the statement of profit or loss and other comprehensive income that are hedged for foreign currency risk) then the reclassified hedging instrument gains or losses shall be apportioned to the line items affected by the hedged items. This apportionment shall be done on a systematic and rational basis and shall not result in the grossing up of the net gains or losses arising from a single hedging instrument.
- In almost every lending transaction the creditor's instrument is ranked relative to the instruments of the debtor's other creditors. An instrument that is subordinated to other instruments may have contractual cash flows that are payments of principal and interest on the principal amount outstanding if the debtor's non-payment is a breach of contract and the holder has a contractual right to unpaid amounts of principal and interest on the principal amount outstanding even in the event of the debtor's bankruptcy. For example, a trade receivable that ranks its creditor as a general creditor would qualify as having payments of principal and interest on the principal amount outstanding. This is the case even if the debtor issued loans that are collateralised, which in the event of bankruptcy would give that loan holder priority over the claims of the general creditor in respect of the collateral but does not affect the contractual right of the general creditor to unpaid principal and other amounts due.
- An embedded prepayment option in an interest-only or principal-only strip is closely related to the host contract provided the host contract (i) initially resulted from separating the right to receive contractual cash flows of a financial instrument that, in and of itself, did not contain an embedded derivative, and (ii) does not contain any terms not present in the original host debt contract.
- The change in the value of the hedged item determined using a hypothetical derivative may also be used for the purpose of assessing whether a hedging relationship meets the hedge effectiveness requirements.

*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

Black Stone Minerals L.P. Common units representing limited partner interests assigned short-term Ba1 & long-term Ba1 forecasted stock rating.** We evaluate the prediction models Multi-Task Learning (ML) with Logistic Regression ^{1,2,3,4} and conclude that the BSM stock is predictable in the short/long term.**

**According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Buy**

### BSM Black Stone Minerals L.P. Common units representing limited partner interests Financial Analysis*

Rating | Short-Term | Long-Term Senior |
---|---|---|

Outlook* | Ba1 | Ba1 |

Operational Risk | B2 | C |

Market Risk | Ba3 | B3 |

Technical Analysis | C | Baa2 |

Fundamental Analysis | Baa2 | Ba2 |

Risk Unsystematic | Ba1 | 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?

### Prediction Confidence Score

## References

- Dimakopoulou M, Athey S, Imbens G. 2017. Estimation considerations in contextual bandits. arXiv:1711.07077 [stat.ML]
- Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
- Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
- 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
- A. Tamar, D. Di Castro, and S. Mannor. Policy gradients with variance related risk criteria. In Proceedings of the Twenty-Ninth International Conference on Machine Learning, pages 387–396, 2012.
- F. A. Oliehoek, M. T. J. Spaan, and N. A. Vlassis. Optimal and approximate q-value functions for decentralized pomdps. J. Artif. Intell. Res. (JAIR), 32:289–353, 2008
- Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]

## Frequently Asked Questions

Q: What is the prediction methodology for BSM stock?A: BSM stock prediction methodology: We evaluate the prediction models Multi-Task Learning (ML) and Logistic Regression

Q: Is BSM stock a buy or sell?

A: The dominant strategy among neural network is to Buy BSM Stock.

Q: Is Black Stone Minerals L.P. Common units representing limited partner interests stock a good investment?

A: The consensus rating for Black Stone Minerals L.P. Common units representing limited partner interests is Buy and assigned short-term Ba1 & long-term Ba1 forecasted stock rating.

Q: What is the consensus rating of BSM stock?

A: The consensus rating for BSM is Buy.

Q: What is the prediction period for BSM stock?

A: The prediction period for BSM is (n+16 weeks)