Outlook: Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest assigned short-term Ba3 & long-term Ba2 forecasted stock rating.
Dominant Strategy : Hold
Time series to forecast n: 10 Dec 2022 for (n+1 year)
Methodology : Modular Neural Network (Emotional Trigger/Responses Analysis)

## Abstract

Predicting the future price of financial assets has always been an important research topic in the field of quantitative finance. This paper attempts to use the latest artificial intelligence technologies to design and implement a framework for financial asset price prediction.(Verma, J.P., Tanwar, S., Garg, S., Gandhi, I. and Bachani, N.H., 2019. Evaluation of pattern based customized approach for stock market trend prediction with big data and machine learning techniques. International Journal of Business Analytics (IJBAN), 6(3), pp.1-15.) We evaluate Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest prediction models with Modular Neural Network (Emotional Trigger/Responses Analysis) and Beta1,2,3,4 and conclude that the BSL stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

## Key Points

1. What are buy sell or hold recommendations?
2. What is the use of Markov decision process?
3. Stock Rating

## BSL Target Price Prediction Modeling Methodology

We consider Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest Decision Process with Modular Neural Network (Emotional Trigger/Responses Analysis) where A is the set of discrete actions of BSL 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(Beta)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(Modular Neural Network (Emotional Trigger/Responses Analysis)) X S(n):→ (n+1 year) $\begin{array}{l}\int {e}^{x}\mathrm{rx}\end{array}$

n:Time series to forecast

p:Price signals of BSL 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?

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

Sample Set: Neural Network
Stock/Index: BSL Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest
Time series to forecast n: 10 Dec 2022 for (n+1 year)

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

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 Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest

1. For the purpose of determining whether a forecast transaction (or a component thereof) is highly probable as required by paragraph 6.3.3, an entity shall assume that the interest rate benchmark on which the hedged cash flows (contractually or non-contractually specified) are based is not altered as a result of interest rate benchmark reform.
2. For hedges other than hedges of foreign currency risk, when an entity designates a non-derivative financial asset or a non-derivative financial liability measured at fair value through profit or loss as a hedging instrument, it may only designate the non-derivative financial instrument in its entirety or a proportion of it.
3. For the purposes of the transition provisions in paragraphs 7.2.1, 7.2.3–7.2.28 and 7.3.2, the date of initial application is the date when an entity first applies those requirements of this Standard and must be the beginning of a reporting period after the issue of this Standard. Depending on the entity's chosen approach to applying IFRS 9, the transition can involve one or more than one date of initial application for different requirements.
4. IFRS 16, issued in January 2016, amended paragraphs 2.1, 5.5.15, B4.3.8, B5.5.34 and B5.5.46. An entity shall apply those amendments when it applies IFRS 16.

*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

Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest assigned short-term Ba3 & long-term Ba2 forecasted stock rating. We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) with Beta1,2,3,4 and conclude that the BSL stock is predictable in the short/long term. According to price forecasts for (n+1 year) period, the dominant strategy among neural network is: Hold

### Financial State Forecast for BSL Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest Options & Futures

Rating Short-Term Long-Term Senior
Outlook*Ba3Ba2
Operational Risk 3556
Market Risk8270
Technical Analysis7182
Fundamental Analysis8566
Risk Unsystematic6459

### Prediction Confidence Score

Trust metric by Neural Network: 88 out of 100 with 627 signals.

## References

1. Pennington J, Socher R, Manning CD. 2014. GloVe: global vectors for word representation. In Proceedings of the 2014 Conference on Empirical Methods on Natural Language Processing, pp. 1532–43. New York: Assoc. Comput. Linguist.
2. Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
3. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
4. Bessler, D. A. T. Covey (1991), "Cointegration: Some results on U.S. cattle prices," Journal of Futures Markets, 11, 461–474.
5. Zou H, Hastie T. 2005. Regularization and variable selection via the elastic net. J. R. Stat. Soc. B 67:301–20
6. D. Bertsekas and J. Tsitsiklis. Neuro-dynamic programming. Athena Scientific, 1996.
7. Li L, Chen S, Kleban J, Gupta A. 2014. Counterfactual estimation and optimization of click metrics for search engines: a case study. In Proceedings of the 24th International Conference on the World Wide Web, pp. 929–34. New York: ACM
Frequently Asked QuestionsQ: What is the prediction methodology for BSL stock?
A: BSL stock prediction methodology: We evaluate the prediction models Modular Neural Network (Emotional Trigger/Responses Analysis) and Beta
Q: Is BSL stock a buy or sell?
A: The dominant strategy among neural network is to Hold BSL Stock.
Q: Is Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest stock a good investment?
A: The consensus rating for Blackstone Senior Floating Rate Term Fund Common Shares of Beneficial Interest is Hold and assigned short-term Ba3 & long-term Ba2 forecasted stock rating.
Q: What is the consensus rating of BSL stock?
A: The consensus rating for BSL is Hold.
Q: What is the prediction period for BSL stock?
A: The prediction period for BSL is (n+1 year)