SCRM Stock Price Prediction

Outlook: Screaming Eagle Acquisition Corp. Class A Ordinary Shares is assigned short-term B2 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
Methodology : Reinforcement Machine Learning (ML)
Hypothesis Testing : Multiple Regression
Surveillance : Major exchange and OTC

1The accuracy of the model is being monitored on a regular basis.(15-minute period)

2Time series is updated based on short-term trends.


Summary

Screaming Eagle Acquisition Corp. Class A Ordinary Shares prediction model is evaluated with Reinforcement Machine Learning (ML) and Multiple Regression1,2,3,4 and it is concluded that the SCRM stock is predictable in the short/long term. Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.5 According to price forecasts for 4 Weeks period, the dominant strategy among neural network is: Sell

Graph 32

Key Points

  1. Reinforcement Machine Learning (ML) for SCRM stock price prediction process.
  2. Multiple Regression
  3. Prediction Modeling
  4. What are main components of Markov decision process?
  5. How do you know when a stock will go up or down?

SCRM Stock Price Forecast

We consider Screaming Eagle Acquisition Corp. Class A Ordinary Shares Decision Process with Reinforcement Machine Learning (ML) where A is the set of discrete actions of SCRM 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


Sample Set: Neural Network
Stock/Index: SCRM Screaming Eagle Acquisition Corp. Class A Ordinary Shares
Time series to forecast: 4 Weeks

According to price forecasts, the dominant strategy among neural network is: Sell


F(Multiple Regression)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(Reinforcement Machine Learning (ML)) X S(n):→ 4 Weeks r s rs

n:Time series to forecast

p:Price signals of SCRM stock

j:Nash equilibria (Neural Network)

k:Dominated move of SCRM stock holders

a:Best response for SCRM target price


Reinforcement machine learning (RL) is a type of machine learning where an agent learns to take actions in an environment in order to maximize a reward. The agent does this by trial and error, and is able to learn from its mistakes. RL is a powerful tool that can be used for a variety of tasks, including game playing, robotics, and finance.5 Multiple regression is a statistical method that analyzes the relationship between a dependent variable and multiple independent variables. The dependent variable is the variable that is being predicted, and the independent variables are the variables that are used to predict the dependent variable. Multiple regression is a more complex statistical method than simple linear regression, which only analyzes the relationship between a dependent variable and one independent variable. Multiple regression can be used to analyze more complex relationships between variables, and it can also be used to control for confounding variables. A confounding variable is a variable that is correlated with both the dependent variable and one or more of the independent variables. Confounding variables can distort the relationship between the dependent variable and the independent variables. Multiple regression can be used to control for confounding variables by including them in the model.6,7

 

For further technical information as per how our model work we invite you to visit the article below: 

How do Predictive A.I. algorithms actually work?

SCRM Stock Forecast (Buy or Sell) Strategic Interaction Table

Strategic Interaction Table Legend:

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%

Financial Data Adjustments for Reinforcement Machine Learning (ML) based SCRM Stock Prediction Model

  1. 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
  2. In some jurisdictions, the government or a regulatory authority sets interest rates. For example, such government regulation of interest rates may be part of a broad macroeconomic policy or it may be introduced to encourage entities to invest in a particular sector of the economy. In some of these cases, the objective of the time value of money element is not to provide consideration for only the passage of time. However, despite paragraphs B4.1.9A–B4.1.9D, a regulated interest rate shall be considered a proxy for the time value of money element for the purpose of applying the condition in paragraphs 4.1.2(b) and 4.1.2A(b) if that regulated interest rate provides consideration that is broadly consistent with the passage of time and does not provide exposure to risks or volatility in the contractual cash flows that are inconsistent with a basic lending arrangement.
  3. When defining default for the purposes of determining the risk of a default occurring, an entity shall apply a default definition that is consistent with the definition used for internal credit risk management purposes for the relevant financial instrument and consider qualitative indicators (for example, financial covenants) when appropriate. However, there is a rebuttable presumption that default does not occur later than when a financial asset is 90 days past due unless an entity has reasonable and supportable information to demonstrate that a more lagging default criterion is more appropriate. The definition of default used for these purposes shall be applied consistently to all financial instruments unless information becomes available that demonstrates that another default definition is more appropriate for a particular financial instrument.
  4. Unless paragraph 6.8.8 applies, for a hedge of a non-contractually specified benchmark component of interest rate risk, an entity shall apply the requirement in paragraphs 6.3.7(a) and B6.3.8—that the risk component shall be separately identifiable—only at the inception of the hedging relationship.

*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.

SCRM Screaming Eagle Acquisition Corp. Class A Ordinary Shares Financial Analysis*

Rating Short-Term Long-Term Senior
Outlook*B2B1
Income StatementBa1Caa2
Balance SheetBaa2Caa2
Leverage RatiosCaa2Ba3
Cash FlowCBa1
Rates of Return and ProfitabilityCaa2B1

*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?

References

  1. P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
  2. Abadir, K. M., K. Hadri E. Tzavalis (1999), "The influence of VAR dimensions on estimator biases," Econometrica, 67, 163–181.
  3. H. Kushner and G. Yin. Stochastic approximation algorithms and applications. Springer, 1997.
  4. Chernozhukov V, Demirer M, Duflo E, Fernandez-Val I. 2018b. Generic machine learning inference on heteroge- nous treatment effects in randomized experiments. NBER Work. Pap. 24678
  5. 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.
  6. Athey S, Wager S. 2017. Efficient policy learning. arXiv:1702.02896 [math.ST]
  7. Li L, Chu W, Langford J, Moon T, Wang X. 2012. An unbiased offline evaluation of contextual bandit algo- rithms with generalized linear models. In Proceedings of 4th ACM International Conference on Web Search and Data Mining, pp. 297–306. New York: ACM
Frequently Asked QuestionsQ: Is SCRM stock expected to rise?
A: SCRM stock prediction model is evaluated with Reinforcement Machine Learning (ML) and Multiple Regression and it is concluded that dominant strategy for SCRM stock is Sell
Q: Is SCRM stock a buy or sell?
A: The dominant strategy among neural network is to Sell SCRM Stock.
Q: Is Screaming Eagle Acquisition Corp. Class A Ordinary Shares stock a good investment?
A: The consensus rating for Screaming Eagle Acquisition Corp. Class A Ordinary Shares is Sell and is assigned short-term B2 & long-term B1 estimated rating.
Q: What is the consensus rating of SCRM stock?
A: The consensus rating for SCRM is Sell.
Q: What is the forecast for SCRM stock?
A: SCRM target price forecast: Sell

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