DKL Delek Logistics Partners L.P. Common Units representing Limited Partner Interests

Outlook: Delek Logistics Partners L.P. Common Units representing Limited Partner Interests is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 19 Jan 2023 for (n+16 weeks)
Methodology : Modular Neural Network (DNN Layer)

Abstract

Delek Logistics Partners L.P. Common Units representing Limited Partner Interests prediction model is evaluated with Modular Neural Network (DNN Layer) and Chi-Square^1,2,3,4 and it is concluded that the DKL stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold

Key Points

1. How can neural networks improve predictions?
2. Can machine learning predict?
3. What is statistical models in machine learning?

DKL Target Price Prediction Modeling Methodology

We consider Delek Logistics Partners L.P. Common Units representing Limited Partner Interests Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of DKL 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 (DNN Layer)) X S(n):→ (n+16 weeks) $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of DKL 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?

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

Sample Set: Neural Network
Stock/Index: DKL Delek Logistics Partners L.P. Common Units representing Limited Partner Interests
Time series to forecast n: 19 Jan 2023 for (n+16 weeks)

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

IFRS Reconciliation Adjustments for Delek Logistics Partners L.P. Common Units representing Limited Partner Interests

1. If a variable-rate financial liability bears interest of (for example) three-month LIBOR minus 20 basis points (with a floor at zero basis points), an entity can designate as the hedged item the change in the cash flows of that entire liability (ie three-month LIBOR minus 20 basis points—including the floor) that is attributable to changes in LIBOR. Hence, as long as the three-month LIBOR forward curve for the remaining life of that liability does not fall below 20 basis points, the hedged item has the same cash flow variability as a liability that bears interest at three-month LIBOR with a zero or positive spread. However, if the three-month LIBOR forward curve for the remaining life of that liability (or a part of it) falls below 20 basis points, the hedged item has a lower cash flow variability than a liability that bears interest at threemonth LIBOR with a zero or positive spread.
2. The definition of a derivative in this Standard includes contracts that are settled gross by delivery of the underlying item (eg a forward contract to purchase a fixed rate debt instrument). An entity may have a contract to buy or sell a non-financial item that can be settled net in cash or another financial instrument or by exchanging financial instruments (eg a contract to buy or sell a commodity at a fixed price at a future date). Such a contract is within the scope of this Standard unless it was entered into and continues to be held for the purpose of delivery of a non-financial item in accordance with the entity's expected purchase, sale or usage requirements. However, this Standard applies to such contracts for an entity's expected purchase, sale or usage requirements if the entity makes a designation in accordance with paragraph 2.5 (see paragraphs 2.4–2.7).
3. When applying the effective interest method, an entity generally amortises any fees, points paid or received, transaction costs and other premiums or discounts that are included in the calculation of the effective interest rate over the expected life of the financial instrument. However, a shorter period is used if this is the period to which the fees, points paid or received, transaction costs, premiums or discounts relate. This will be the case when the variable to which the fees, points paid or received, transaction costs, premiums or discounts relate is repriced to market rates before the expected maturity of the financial instrument. In such a case, the appropriate amortisation period is the period to the next such repricing date. For example, if a premium or discount on a floating-rate financial instrument reflects the interest that has accrued on that financial instrument since the interest was last paid, or changes in the market rates since the floating interest rate was reset to the market rates, it will be amortised to the next date when the floating interest is reset to market rates. This is because the premium or discount relates to the period to the next interest reset date because, at that date, the variable to which the premium or discount relates (ie interest rates) is reset to the market rates. If, however, the premium or discount results from a change in the credit spread over the floating rate specified in the financial instrument, or other variables that are not reset to the market rates, it is amortised over the expected life of the financial instrument.
4. Rebalancing does not apply if the risk management objective for a hedging relationship has changed. Instead, hedge accounting for that hedging relationship shall be discontinued (despite that an entity might designate a new hedging relationship that involves the hedging instrument or hedged item of the previous hedging relationship as described in paragraph B6.5.28).

*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

Delek Logistics Partners L.P. Common Units representing Limited Partner Interests is assigned short-term Ba1 & long-term Ba1 estimated rating. Delek Logistics Partners L.P. Common Units representing Limited Partner Interests prediction model is evaluated with Modular Neural Network (DNN Layer) and Chi-Square^1,2,3,4 and it is concluded that the DKL stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Hold

DKL Delek Logistics Partners L.P. Common Units representing Limited Partner Interests Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B3	C
Balance Sheet	Caa2	Caa2
Leverage Ratios	Baa2	Baa2
Cash Flow	Caa2	Caa2
Rates of Return and Profitability	Baa2	Baa2

*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: 75 out of 100 with 741 signals.

References

1. Morris CN. 1983. Parametric empirical Bayes inference: theory and applications. J. Am. Stat. Assoc. 78:47–55
2. C. Wu and Y. Lin. Minimizing risk models in Markov decision processes with policies depending on target values. Journal of Mathematical Analysis and Applications, 231(1):47–67, 1999
3. Mikolov T, Chen K, Corrado GS, Dean J. 2013a. Efficient estimation of word representations in vector space. arXiv:1301.3781 [cs.CL]
4. Vilnis L, McCallum A. 2015. Word representations via Gaussian embedding. arXiv:1412.6623 [cs.CL]
5. R. Sutton and A. Barto. Introduction to reinforcement learning. MIT Press, 1998
6. J. Filar, L. Kallenberg, and H. Lee. Variance-penalized Markov decision processes. Mathematics of Opera- tions Research, 14(1):147–161, 1989
7. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36

Frequently Asked Questions

Q: What is the prediction methodology for DKL stock?
A: DKL stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Chi-Square
Q: Is DKL stock a buy or sell?
A: The dominant strategy among neural network is to Hold DKL Stock.
Q: Is Delek Logistics Partners L.P. Common Units representing Limited Partner Interests stock a good investment?
A: The consensus rating for Delek Logistics Partners L.P. Common Units representing Limited Partner Interests is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of DKL stock?
A: The consensus rating for DKL is Hold.
Q: What is the prediction period for DKL stock?
A: The prediction period for DKL is (n+16 weeks)

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