AC Investment Research

DDT Dillard's Capital Trust I Research Report

Outlook: Dillard's Capital Trust I is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Buy
Time series to forecast n: 08 Jan 2023 for (n+3 month)
Methodology : Modular Neural Network (Social Media Sentiment Analysis)

Abstract

Dillard's Capital Trust I prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Logistic Regression1,2,3,4 and it is concluded that the DDT 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. How do you decide buy or sell a stock?
  2. Is it better to buy and sell or hold?
  3. What is prediction model?

DDT Target Price Prediction Modeling Methodology

We consider Dillard's Capital Trust I Decision Process with Modular Neural Network (Social Media Sentiment Analysis) where A is the set of discrete actions of DDT 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= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Modular Neural Network (Social Media Sentiment Analysis)) X S(n):→ (n+3 month) R = 1 0 0 0 1 0 0 0 1

n:Time series to forecast

p:Price signals of DDT 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?

DDT Stock Forecast (Buy or Sell) for (n+3 month)

Sample Set: Neural Network
Stock/Index: DDT Dillard's Capital Trust I
Time series to forecast n: 08 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 Dillard's Capital Trust I

  1. This Standard does not specify a method for assessing whether a hedging relationship meets the hedge effectiveness requirements. However, an entity shall use a method that captures the relevant characteristics of the hedging relationship including the sources of hedge ineffectiveness. Depending on those factors, the method can be a qualitative or a quantitative assessment.
  2. The fact that a derivative is in or out of the money when it is designated as a hedging instrument does not in itself mean that a qualitative assessment is inappropriate. It depends on the circumstances whether hedge ineffectiveness arising from that fact could have a magnitude that a qualitative assessment would not adequately capture.
  3. 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.
  4. When determining whether the recognition of lifetime expected credit losses is required, an entity shall consider reasonable and supportable information that is available without undue cost or effort and that may affect the credit risk on a financial instrument in accordance with paragraph 5.5.17(c). An entity need not undertake an exhaustive search for information when determining whether credit risk has increased significantly since initial recognition.

*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

Dillard's Capital Trust I is assigned short-term Ba1 & long-term Ba1 estimated rating. Dillard's Capital Trust I prediction model is evaluated with Modular Neural Network (Social Media Sentiment Analysis) and Logistic Regression1,2,3,4 and it is concluded that the DDT 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

DDT Dillard's Capital Trust I Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementB3C
Balance SheetBaa2Caa2
Leverage RatiosBaa2C
Cash FlowCCaa2
Rates of Return and ProfitabilityCB1

*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: 76 out of 100 with 594 signals.

References

  1. Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
  2. Athey S. 2019. The impact of machine learning on economics. In The Economics of Artificial Intelligence: An Agenda, ed. AK Agrawal, J Gans, A Goldfarb. Chicago: Univ. Chicago Press. In press
  3. S. Bhatnagar and K. Lakshmanan. An online actor-critic algorithm with function approximation for con- strained Markov decision processes. Journal of Optimization Theory and Applications, 153(3):688–708, 2012.
  4. Dudik M, Erhan D, Langford J, Li L. 2014. Doubly robust policy evaluation and optimization. Stat. Sci. 29:485–511
  5. Barrett, C. B. (1997), "Heteroscedastic price forecasting for food security management in developing countries," Oxford Development Studies, 25, 225–236.
  6. V. Konda and J. Tsitsiklis. Actor-Critic algorithms. In Proceedings of Advances in Neural Information Processing Systems 12, pages 1008–1014, 2000
  7. Schapire RE, Freund Y. 2012. Boosting: Foundations and Algorithms. Cambridge, MA: MIT Press
Frequently Asked QuestionsQ: What is the prediction methodology for DDT stock?
A: DDT stock prediction methodology: We evaluate the prediction models Modular Neural Network (Social Media Sentiment Analysis) and Logistic Regression
Q: Is DDT stock a buy or sell?
A: The dominant strategy among neural network is to Buy DDT Stock.
Q: Is Dillard's Capital Trust I stock a good investment?
A: The consensus rating for Dillard's Capital Trust I is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of DDT stock?
A: The consensus rating for DDT is Buy.
Q: What is the prediction period for DDT stock?
A: The prediction period for DDT is (n+3 month)

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