Modelling A.I. in Economics

DDR DICKER DATA LIMITED

Outlook: DICKER DATA LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Hold
Time series to forecast n: 07 Feb 2023 for (n+16 weeks)
Methodology : Deductive Inference (ML)

Abstract

DICKER DATA LIMITED prediction model is evaluated with Deductive Inference (ML) and Polynomial Regression1,2,3,4 and it is concluded that the DDR 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. Trading Signals
  2. Should I buy stocks now or wait amid such uncertainty?
  3. What is a prediction confidence?

DDR Target Price Prediction Modeling Methodology

We consider DICKER DATA LIMITED Decision Process with Deductive Inference (ML) where A is the set of discrete actions of DDR 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(Polynomial 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(Deductive Inference (ML)) X S(n):→ (n+16 weeks) R = r 1 r 2 r 3

n:Time series to forecast

p:Price signals of DDR 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?

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

Sample Set: Neural Network
Stock/Index: DDR DICKER DATA LIMITED
Time series to forecast n: 07 Feb 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 DICKER DATA LIMITED

  1. Historical information is an important anchor or base from which to measure expected credit losses. However, an entity shall adjust historical data, such as credit loss experience, on the basis of current observable data to reflect the effects of the current conditions and its forecasts of future conditions that did not affect the period on which the historical data is based, and to remove the effects of the conditions in the historical period that are not relevant to the future contractual cash flows. In some cases, the best reasonable and supportable information could be the unadjusted historical information, depending on the nature of the historical information and when it was calculated, compared to circumstances at the reporting date and the characteristics of the financial instrument being considered. Estimates of changes in expected credit losses should reflect, and be directionally consistent with, changes in related observable data from period to period
  2. There are two types of components of nominal amounts that can be designated as the hedged item in a hedging relationship: a component that is a proportion of an entire item or a layer component. The type of component changes the accounting outcome. An entity shall designate the component for accounting purposes consistently with its risk management objective.
  3. Compared to a business model whose objective is to hold financial assets to collect contractual cash flows, this business model will typically involve greater frequency and value of sales. This is because selling financial assets is integral to achieving the business model's objective instead of being only incidental to it. However, there is no threshold for the frequency or value of sales that must occur in this business model because both collecting contractual cash flows and selling financial assets are integral to achieving its objective.
  4. As noted in paragraph B4.3.1, when an entity becomes a party to a hybrid contract with a host that is not an asset within the scope of this Standard and with one or more embedded derivatives, paragraph 4.3.3 requires the entity to identify any such embedded derivative, assess whether it is required to be separated from the host contract and, for those that are required to be separated, measure the derivatives at fair value at initial recognition and subsequently. These requirements can be more complex, or result in less reliable measures, than measuring the entire instrument at fair value through profit or loss. For that reason this Standard permits the entire hybrid contract to be designated as at fair value through profit or loss.

*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

DICKER DATA LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. DICKER DATA LIMITED prediction model is evaluated with Deductive Inference (ML) and Polynomial Regression1,2,3,4 and it is concluded that the DDR 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

DDR DICKER DATA LIMITED Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*Ba1Ba1
Income StatementBaa2Caa2
Balance SheetCBaa2
Leverage RatiosBa3Ba1
Cash FlowCBa1
Rates of Return and ProfitabilityCBaa2

*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: 89 out of 100 with 540 signals.

References

  1. R. Rockafellar and S. Uryasev. Optimization of conditional value-at-risk. Journal of Risk, 2:21–42, 2000.
  2. S. Devlin, L. Yliniemi, D. Kudenko, and K. Tumer. Potential-based difference rewards for multiagent reinforcement learning. In Proceedings of the Thirteenth International Joint Conference on Autonomous Agents and Multiagent Systems, May 2014
  3. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Is TPL a Buy?. AC Investment Research Journal, 101(3).
  4. E. Altman, K. Avrachenkov, and R. N ́u ̃nez-Queija. Perturbation analysis for denumerable Markov chains with application to queueing models. Advances in Applied Probability, pages 839–853, 2004
  5. V. Borkar. A sensitivity formula for the risk-sensitive cost and the actor-critic algorithm. Systems & Control Letters, 44:339–346, 2001
  6. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
  7. D. S. Bernstein, S. Zilberstein, and N. Immerman. The complexity of decentralized control of Markov Decision Processes. In UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30 - July 3, 2000, pages 32–37, 2000.
Frequently Asked QuestionsQ: What is the prediction methodology for DDR stock?
A: DDR stock prediction methodology: We evaluate the prediction models Deductive Inference (ML) and Polynomial Regression
Q: Is DDR stock a buy or sell?
A: The dominant strategy among neural network is to Hold DDR Stock.
Q: Is DICKER DATA LIMITED stock a good investment?
A: The consensus rating for DICKER DATA LIMITED is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of DDR stock?
A: The consensus rating for DDR is Hold.
Q: What is the prediction period for DDR stock?
A: The prediction period for DDR is (n+16 weeks)



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