Dominant Strategy : Buy
Time series to forecast n: 18 May 2023 for (n+6 month)
Methodology : Reinforcement Machine Learning (ML)
Abstract
Skydeck Acquisition Corp. Warrants prediction model is evaluated with Reinforcement Machine Learning (ML) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the SKYAW stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: BuyKey Points
- Game Theory
- Is Target price a good indicator?
- What is a prediction confidence?
SKYAW Target Price Prediction Modeling Methodology
We consider Skydeck Acquisition Corp. Warrants Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of SKYAW 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 Rank-Sum Test)5,6,7= X R(Reinforcement Machine Learning (ML)) X S(n):→ (n+6 month)
n:Time series to forecast
p:Price signals of SKYAW 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?
SKYAW Stock Forecast (Buy or Sell) for (n+6 month)
Sample Set: Neural NetworkStock/Index: SKYAW Skydeck Acquisition Corp. Warrants
Time series to forecast n: 18 May 2023 for (n+6 month)
According to price forecasts for (n+6 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 Skydeck Acquisition Corp. Warrants
- If, at the date of initial application, it is impracticable (as defined in IAS 8) for an entity to assess whether the fair value of a prepayment feature was insignificant in accordance with paragraph B4.1.12(c) on the basis of the facts and circumstances that existed at the initial recognition of the financial asset, an entity shall assess the contractual cash flow characteristics of that financial asset on the basis of the facts and circumstances that existed at the initial recognition of the financial asset without taking into account the exception for prepayment features in paragraph B4.1.12. (See also paragraph 42S of IFRS 7.)
- For floating-rate financial assets and floating-rate financial liabilities, periodic re-estimation of cash flows to reflect the movements in the market rates of interest alters the effective interest rate. If a floating-rate financial asset or a floating-rate financial liability is recognised initially at an amount equal to the principal receivable or payable on maturity, re-estimating the future interest payments normally has no significant effect on the carrying amount of the asset or the liability.
- 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.
- The assessment of whether lifetime expected credit losses should be recognised is based on significant increases in the likelihood or risk of a default occurring since initial recognition (irrespective of whether a financial instrument has been repriced to reflect an increase in credit risk) instead of on evidence of a financial asset being credit-impaired at the reporting date or an actual default occurring. Generally, there will be a significant increase in credit risk before a financial asset becomes credit-impaired or an actual default occurs.
*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
Skydeck Acquisition Corp. Warrants is assigned short-term Ba1 & long-term Ba1 estimated rating. Skydeck Acquisition Corp. Warrants prediction model is evaluated with Reinforcement Machine Learning (ML) and Wilcoxon Rank-Sum Test1,2,3,4 and it is concluded that the SKYAW stock is predictable in the short/long term. According to price forecasts for (n+6 month) period, the dominant strategy among neural network is: Buy
SKYAW Skydeck Acquisition Corp. Warrants Financial Analysis*
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook* | Ba1 | Ba1 |
Income Statement | Ba3 | B3 |
Balance Sheet | Ba3 | Ba1 |
Leverage Ratios | B3 | Baa2 |
Cash Flow | Ba3 | Ba3 |
Rates of Return and Profitability | Caa2 | 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.
- K. Tumer and D. Wolpert. A survey of collectives. In K. Tumer and D. Wolpert, editors, Collectives and the Design of Complex Systems, pages 1–42. Springer, 2004.
- Gentzkow M, Kelly BT, Taddy M. 2017. Text as data. NBER Work. Pap. 23276
- K. Boda, J. Filar, Y. Lin, and L. Spanjers. Stochastic target hitting time and the problem of early retirement. Automatic Control, IEEE Transactions on, 49(3):409–419, 2004
- Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
- Challen, D. W. A. J. Hagger (1983), Macroeconomic Systems: Construction, Validation and Applications. New York: St. Martin's Press.
- Kallus N. 2017. Balanced policy evaluation and learning. arXiv:1705.07384 [stat.ML]
Frequently Asked Questions
Q: What is the prediction methodology for SKYAW stock?A: SKYAW stock prediction methodology: We evaluate the prediction models Reinforcement Machine Learning (ML) and Wilcoxon Rank-Sum Test
Q: Is SKYAW stock a buy or sell?
A: The dominant strategy among neural network is to Buy SKYAW Stock.
Q: Is Skydeck Acquisition Corp. Warrants stock a good investment?
A: The consensus rating for Skydeck Acquisition Corp. Warrants is Buy and is assigned short-term Ba1 & long-term Ba1 estimated rating.
Q: What is the consensus rating of SKYAW stock?
A: The consensus rating for SKYAW is Buy.
Q: What is the prediction period for SKYAW stock?
A: The prediction period for SKYAW is (n+6 month)