Dominant Strategy : Hold
Time series to forecast n: 23 Mar 2023 for (n+8 weeks)
Methodology : Transfer Learning (ML)
Abstract
JD SPORTS FASHION PLC prediction model is evaluated with Transfer Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the LON:JD. stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: HoldKey Points
- How do you know when a stock will go up or down?
- Decision Making
- Can neural networks predict stock market?
LON:JD. Target Price Prediction Modeling Methodology
We consider JD SPORTS FASHION PLC Decision Process with Transfer Learning (ML) where A is the set of discrete actions of LON:JD. 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= X R(Transfer Learning (ML)) X S(n):→ (n+8 weeks)
n:Time series to forecast
p:Price signals of LON:JD. 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?
LON:JD. Stock Forecast (Buy or Sell) for (n+8 weeks)
Sample Set: Neural NetworkStock/Index: LON:JD. JD SPORTS FASHION PLC
Time series to forecast n: 23 Mar 2023 for (n+8 weeks)
According to price forecasts for (n+8 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 JD SPORTS FASHION PLC
- If such a mismatch would be created or enlarged, the entity is required to present all changes in fair value (including the effects of changes in the credit risk of the liability) in profit or loss. If such a mismatch would not be created or enlarged, the entity is required to present the effects of changes in the liability's credit risk in other comprehensive income.
- An entity's documentation of the hedging relationship includes how it will assess the hedge effectiveness requirements, including the method or methods used. The documentation of the hedging relationship shall be updated for any changes to the methods (see paragraph B6.4.17).
- Paragraph 5.5.4 requires that lifetime expected credit losses are recognised on all financial instruments for which there has been significant increases in credit risk since initial recognition. In order to meet this objective, if an entity is not able to group financial instruments for which the credit risk is considered to have increased significantly since initial recognition based on shared credit risk characteristics, the entity should recognise lifetime expected credit losses on a portion of the financial assets for which credit risk is deemed to have increased significantly. The aggregation of financial instruments to assess whether there are changes in credit risk on a collective basis may change over time as new information becomes available on groups of, or individual, financial instruments.
- If an entity measures a hybrid contract at fair value in accordance with paragraphs 4.1.2A, 4.1.4 or 4.1.5 but the fair value of the hybrid contract had not been measured in comparative reporting periods, the fair value of the hybrid contract in the comparative reporting periods shall be the sum of the fair values of the components (ie the non-derivative host and the embedded derivative) at the end of each comparative reporting period if the entity restates prior periods (see paragraph 7.2.15).
*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
JD SPORTS FASHION PLC is assigned short-term Ba1 & long-term Ba1 estimated rating. JD SPORTS FASHION PLC prediction model is evaluated with Transfer Learning (ML) and Chi-Square1,2,3,4 and it is concluded that the LON:JD. stock is predictable in the short/long term. According to price forecasts for (n+8 weeks) period, the dominant strategy among neural network is: Hold
LON:JD. JD SPORTS FASHION PLC Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | Caa2 |
Balance Sheet | B2 | C |
Leverage Ratios | Caa2 | C |
Cash Flow | C | Baa2 |
Rates of Return and Profitability | B3 | 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
References
- M. Puterman. Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, New York, 1994.
- D. White. Mean, variance, and probabilistic criteria in finite Markov decision processes: A review. Journal of Optimization Theory and Applications, 56(1):1–29, 1988.
- M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994
- Christou, C., P. A. V. B. Swamy G. S. Tavlas (1996), "Modelling optimal strategies for the allocation of wealth in multicurrency investments," International Journal of Forecasting, 12, 483–493.
- F. A. Oliehoek, M. T. J. Spaan, and N. A. Vlassis. Optimal and approximate q-value functions for decentralized pomdps. J. Artif. Intell. Res. (JAIR), 32:289–353, 2008
- Barkan O. 2016. Bayesian neural word embedding. arXiv:1603.06571 [math.ST]
- Imai K, Ratkovic M. 2013. Estimating treatment effect heterogeneity in randomized program evaluation. Ann. Appl. Stat. 7:443–70
Frequently Asked Questions
Q: What is the prediction methodology for LON:JD. stock?A: LON:JD. stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Chi-Square
Q: Is LON:JD. stock a buy or sell?
A: The dominant strategy among neural network is to Hold LON:JD. Stock.
Q: Is JD SPORTS FASHION PLC stock a good investment?
A: The consensus rating for JD SPORTS FASHION PLC is Hold and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of LON:JD. stock?
A: The consensus rating for LON:JD. is Hold.
Q: What is the prediction period for LON:JD. stock?
A: The prediction period for LON:JD. is (n+8 weeks)
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