Dominant Strategy : SellBuy
Time series to forecast n: 04 Apr 2023 for (n+16 weeks)
Methodology : Transfer Learning (ML)
Abstract
ATAI Life Sciences N.V. Common Shares prediction model is evaluated with Transfer Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the ATAI stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: SellBuyKey Points
- Is now good time to invest?
- What is the best way to predict stock prices?
- Is Target price a good indicator?
ATAI Target Price Prediction Modeling Methodology
We consider ATAI Life Sciences N.V. Common Shares Decision Process with Transfer Learning (ML) where A is the set of discrete actions of ATAI 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= X R(Transfer Learning (ML)) X S(n):→ (n+16 weeks)
n:Time series to forecast
p:Price signals of ATAI 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?
ATAI Stock Forecast (Buy or Sell) for (n+16 weeks)
Sample Set: Neural NetworkStock/Index: ATAI ATAI Life Sciences N.V. Common Shares
Time series to forecast n: 04 Apr 2023 for (n+16 weeks)
According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: SellBuy
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 ATAI Life Sciences N.V. Common Shares
- 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.
- Fluctuation around a constant hedge ratio (and hence the related hedge ineffectiveness) cannot be reduced by adjusting the hedge ratio in response to each particular outcome. Hence, in such circumstances, the change in the extent of offset is a matter of measuring and recognising hedge ineffectiveness but does not require rebalancing.
- The business model may be to hold assets to collect contractual cash flows even if the entity sells financial assets when there is an increase in the assets' credit risk. To determine whether there has been an increase in the assets' credit risk, the entity considers reasonable and supportable information, including forward looking information. Irrespective of their frequency and value, sales due to an increase in the assets' credit risk are not inconsistent with a business model whose objective is to hold financial assets to collect contractual cash flows because the credit quality of financial assets is relevant to the entity's ability to collect contractual cash flows. Credit risk management activities that are aimed at minimising potential credit losses due to credit deterioration are integral to such a business model. Selling a financial asset because it no longer meets the credit criteria specified in the entity's documented investment policy is an example of a sale that has occurred due to an increase in credit risk. However, in the absence of such a policy, the entity may demonstrate in other ways that the sale occurred due to an increase in credit risk.
- IFRS 15, issued in May 2014, amended paragraphs 3.1.1, 4.2.1, 5.1.1, 5.2.1, 5.7.6, B3.2.13, B5.7.1, C5 and C42 and deleted paragraph C16 and its related heading. Paragraphs 5.1.3 and 5.7.1A, and a definition to Appendix A, were added. An entity shall apply those amendments when it applies IFRS 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
ATAI Life Sciences N.V. Common Shares is assigned short-term Ba1 & long-term Ba1 estimated rating. ATAI Life Sciences N.V. Common Shares prediction model is evaluated with Transfer Learning (ML) and Wilcoxon Sign-Rank Test1,2,3,4 and it is concluded that the ATAI stock is predictable in the short/long term. According to price forecasts for (n+16 weeks) period, the dominant strategy among neural network is: SellBuy
ATAI ATAI Life Sciences N.V. Common Shares Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Baa2 | Ba2 |
Balance Sheet | Baa2 | B1 |
Leverage Ratios | C | Baa2 |
Cash Flow | C | Ba3 |
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

References
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- Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79
- H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
- M. Sobel. The variance of discounted Markov decision processes. Applied Probability, pages 794–802, 1982
- Bottomley, P. R. Fildes (1998), "The role of prices in models of innovation diffusion," Journal of Forecasting, 17, 539–555.
- Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
- Bera, A. M. L. Higgins (1997), "ARCH and bilinearity as competing models for nonlinear dependence," Journal of Business Economic Statistics, 15, 43–50.
Frequently Asked Questions
Q: What is the prediction methodology for ATAI stock?A: ATAI stock prediction methodology: We evaluate the prediction models Transfer Learning (ML) and Wilcoxon Sign-Rank Test
Q: Is ATAI stock a buy or sell?
A: The dominant strategy among neural network is to SellBuy ATAI Stock.
Q: Is ATAI Life Sciences N.V. Common Shares stock a good investment?
A: The consensus rating for ATAI Life Sciences N.V. Common Shares is SellBuy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of ATAI stock?
A: The consensus rating for ATAI is SellBuy.
Q: What is the prediction period for ATAI stock?
A: The prediction period for ATAI is (n+16 weeks)
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