DNA DONACO INTERNATIONAL LIMITED

Outlook: DONACO INTERNATIONAL LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating.
Dominant Strategy : Wait until speculative trend diminishes
Time series to forecast n: 13 Apr 2023 for (n+16 weeks)
Methodology : Modular Neural Network (DNN Layer)

Abstract

DONACO INTERNATIONAL LIMITED prediction model is evaluated with Modular Neural Network (DNN Layer) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the DNA stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

Key Points

1. Game Theory
2. Can statistics predict the future?
3. Which neural network is best for prediction?

DNA Target Price Prediction Modeling Methodology

We consider DONACO INTERNATIONAL LIMITED Decision Process with Modular Neural Network (DNN Layer) where A is the set of discrete actions of DNA 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(Wilcoxon Sign-Rank Test)^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 DNA 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?

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

Sample Set: Neural Network
Stock/Index: DNA DONACO INTERNATIONAL LIMITED
Time series to forecast n: 13 Apr 2023 for (n+16 weeks)

According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

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 DONACO INTERNATIONAL LIMITED

1. Financial assets that are held within a business model whose objective is to hold assets in order to collect contractual cash flows are managed to realise cash flows by collecting contractual payments over the life of the instrument. That is, the entity manages the assets held within the portfolio to collect those particular contractual cash flows (instead of managing the overall return on the portfolio by both holding and selling assets). In determining whether cash flows are going to be realised by collecting the financial assets' contractual cash flows, it is necessary to consider the frequency, value and timing of sales in prior periods, the reasons for those sales and expectations about future sales activity. However sales in themselves do not determine the business model and therefore cannot be considered in isolation. Instead, information about past sales and expectations about future sales provide evidence related to how the entity's stated objective for managing the financial assets is achieved and, specifically, how cash flows are realised. An entity must consider information about past sales within the context of the reasons for those sales and the conditions that existed at that time as compared to current conditions.
2. If a financial instrument is designated in accordance with paragraph 6.7.1 as measured at fair value through profit or loss after its initial recognition, or was previously not recognised, the difference at the time of designation between the carrying amount, if any, and the fair value shall immediately be recognised in profit or loss. For financial assets measured at fair value through other comprehensive income in accordance with paragraph 4.1.2A, the cumulative gain or loss previously recognised in other comprehensive income shall immediately be reclassified from equity to profit or loss as a reclassification adjustment.
3. For the purposes of measuring expected credit losses, the estimate of expected cash shortfalls shall reflect the cash flows expected from collateral and other credit enhancements that are part of the contractual terms and are not recognised separately by the entity. The estimate of expected cash shortfalls on a collateralised financial instrument reflects the amount and timing of cash flows that are expected from foreclosure on the collateral less the costs of obtaining and selling the collateral, irrespective of whether foreclosure is probable (ie the estimate of expected cash flows considers the probability of a foreclosure and the cash flows that would result from it). Consequently, any cash flows that are expected from the realisation of the collateral beyond the contractual maturity of the contract should be included in this analysis. Any collateral obtained as a result of foreclosure is not recognised as an asset that is separate from the collateralised financial instrument unless it meets the relevant recognition criteria for an asset in this or other Standards.
4. 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

*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

DONACO INTERNATIONAL LIMITED is assigned short-term Ba1 & long-term Ba1 estimated rating. DONACO INTERNATIONAL LIMITED prediction model is evaluated with Modular Neural Network (DNN Layer) and Wilcoxon Sign-Rank Test^1,2,3,4 and it is concluded that the DNA stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: Wait until speculative trend diminishes

DNA DONACO INTERNATIONAL LIMITED Financial Analysis*

Rating	Short-Term	Long-Term Senior
Outlook*	Ba1	Ba1
Income Statement	B3	Caa2
Balance Sheet	Caa2	B3
Leverage Ratios	Baa2	Caa2
Cash Flow	Caa2	Ba3
Rates of Return and Profitability	B3	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: 89 out of 100 with 521 signals.

References

1. Cortes C, Vapnik V. 1995. Support-vector networks. Mach. Learn. 20:273–97
2. Miller A. 2002. Subset Selection in Regression. New York: CRC Press
3. Alpaydin E. 2009. Introduction to Machine Learning. Cambridge, MA: MIT Press
4. Athey S, Imbens GW. 2017a. The econometrics of randomized experiments. In Handbook of Economic Field Experiments, Vol. 1, ed. E Duflo, A Banerjee, pp. 73–140. Amsterdam: Elsevier
5. V. Borkar and R. Jain. Risk-constrained Markov decision processes. IEEE Transaction on Automatic Control, 2014
6. Mullainathan S, Spiess J. 2017. Machine learning: an applied econometric approach. J. Econ. Perspect. 31:87–106
7. Çetinkaya, A., Zhang, Y.Z., Hao, Y.M. and Ma, X.Y., Can stock prices be predicted?(SMI Index Stock Forecast). AC Investment Research Journal, 101(3).

Frequently Asked Questions

Q: What is the prediction methodology for DNA stock?
A: DNA stock prediction methodology: We evaluate the prediction models Modular Neural Network (DNN Layer) and Wilcoxon Sign-Rank Test
Q: Is DNA stock a buy or sell?
A: The dominant strategy among neural network is to Wait until speculative trend diminishes DNA Stock.
Q: Is DONACO INTERNATIONAL LIMITED stock a good investment?
A: The consensus rating for DONACO INTERNATIONAL LIMITED is Wait until speculative trend diminishes and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of DNA stock?
A: The consensus rating for DNA is Wait until speculative trend diminishes.
Q: What is the prediction period for DNA stock?
A: The prediction period for DNA is (n+16 weeks)

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