DLNG^B Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni Research Report

Outlook: Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 14 Jan 2023 for (n+3 month)
Methodology : Transfer Learning (ML)

Abstract

Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni prediction model is evaluated with Transfer Learning (ML) and Multiple Regression^1,2,3,4 and it is concluded that the DLNG^B stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

Key Points

1. Market Risk
2. How do predictive algorithms actually work?
3. Understanding Buy, Sell, and Hold Ratings

DLNG^B Target Price Prediction Modeling Methodology

We consider Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni Decision Process with Transfer Learning (ML) where A is the set of discrete actions of DLNG^B 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= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Transfer Learning (ML)) X S(n):→ (n+3 month) $\overrightarrow{R}=\left(r_1,r_2,r_3\right)$

n:Time series to forecast

p:Price signals of DLNG^B 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?

DLNG^B Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: DLNG^B Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni
Time series to forecast n: 14 Jan 2023 for (n+3 month)

According to price forecasts for (n+3 month) 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%

IFRS Reconciliation Adjustments for Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni

1. If an entity has applied paragraph 7.2.6 then at the date of initial application the entity shall recognise any difference between the fair value of the entire hybrid contract at the date of initial application and the sum of the fair values of the components of the hybrid contract at the date of initial application in the opening retained earnings (or other component of equity, as appropriate) of the reporting period that includes the date of initial application.
2. The methods used to determine whether credit risk has increased significantly on a financial instrument since initial recognition should consider the characteristics of the financial instrument (or group of financial instruments) and the default patterns in the past for comparable financial instruments. Despite the requirement in paragraph 5.5.9, for financial instruments for which default patterns are not concentrated at a specific point during the expected life of the financial instrument, changes in the risk of a default occurring over the next 12 months may be a reasonable approximation of the changes in the lifetime risk of a default occurring. In such cases, an entity may use changes in the risk of a default occurring over the next 12 months to determine whether credit risk has increased significantly since initial recognition, unless circumstances indicate that a lifetime assessment is necessary
3. Although the objective of an entity's business model may be to hold financial assets in order to collect contractual cash flows, the entity need not hold all of those instruments until maturity. Thus an entity's business model can be to hold financial assets to collect contractual cash flows even when sales of financial assets occur or are expected to occur in the future.
4. The accounting for the time value of options in accordance with paragraph 6.5.15 applies only to the extent that the time value relates to the hedged item (aligned time value). The time value of an option relates to the hedged item if the critical terms of the option (such as the nominal amount, life and underlying) are aligned with the hedged item. Hence, if the critical terms of the option and the hedged item are not fully aligned, an entity shall determine the aligned time value, ie how much of the time value included in the premium (actual time value) relates to the hedged item (and therefore should be treated in accordance with paragraph 6.5.15). An entity determines the aligned time value using the valuation of the option that would have critical terms that perfectly match the hedged item.

*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

Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni is assigned short-term Ba1 & long-term Ba1 estimated rating. Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni prediction model is evaluated with Transfer Learning (ML) and Multiple Regression^1,2,3,4 and it is concluded that the DLNG^B stock is predictable in the short/long term. According to price forecasts for (n+3 month) period, the dominant strategy among neural network is: Buy

DLNG^B Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	Ba1	Caa2
Balance Sheet	Ba3	C
Leverage Ratios	B3	B2
Cash Flow	Ba3	Ba1
Rates of Return and Profitability	Ba1	C

*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: 84 out of 100 with 725 signals.

References

1. Chernozhukov V, Demirer M, Duflo E, Fernandez-Val I. 2018b. Generic machine learning inference on heteroge- nous treatment effects in randomized experiments. NBER Work. Pap. 24678
2. Babula, R. A. (1988), "Contemporaneous correlation and modeling Canada's imports of U.S. crops," Journal of Agricultural Economics Research, 41, 33–38.
3. 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
4. R. Sutton and A. Barto. Reinforcement Learning. The MIT Press, 1998
5. A. Y. Ng, D. Harada, and S. J. Russell. Policy invariance under reward transformations: Theory and application to reward shaping. In Proceedings of the Sixteenth International Conference on Machine Learning (ICML 1999), Bled, Slovenia, June 27 - 30, 1999, pages 278–287, 1999.
6. Dietterich TG. 2000. Ensemble methods in machine learning. In Multiple Classifier Systems: First International Workshop, Cagliari, Italy, June 21–23, pp. 1–15. Berlin: Springer
7. R. Sutton, D. McAllester, S. Singh, and Y. Mansour. Policy gradient methods for reinforcement learning with function approximation. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1057–1063, 2000

Frequently Asked Questions

Q: What is the prediction methodology for DLNG^B stock?
A: DLNG^B stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Multiple Regression
Q: Is DLNG^B stock a buy or sell?
A: The dominant strategy among neural network is to Buy DLNG^B Stock.
Q: Is Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni stock a good investment?
A: The consensus rating for Dynagas LNG Partners LP 8.75% Series B Fixed to Floating Rate Cumulative Redeemable Perpetual Preferred Units liquidation preference $25.00 per Uni is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of DLNG^B stock?
A: The consensus rating for DLNG^B is Buy.
Q: What is the prediction period for DLNG^B stock?
A: The prediction period for DLNG^B is (n+3 month)

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