AUC Score :
Short-Term Revised1 :
Dominant Strategy :
Time series to forecast n:
ML Model Testing : Transfer Learning (ML)
Hypothesis Testing : Wilcoxon Sign-Rank Test
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.
Key Points
This exclusive content is only available to premium users.About MTRO
This exclusive content is only available to premium users.ML Model Testing
n:Time series to forecast
p:Price signals of MTRO stock
j:Nash equilibria (Neural Network)
k:Dominated move of MTRO stock holders
a:Best response for MTRO target price
For further technical information as per how our model work we invite you to visit the article below:
How do KappaSignal algorithms actually work?
MTRO 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%
Rating | Short-Term | Long-Term Senior |
---|---|---|
Outlook | B1 | B2 |
Income Statement | C | B1 |
Balance Sheet | Caa2 | Caa2 |
Leverage Ratios | Baa2 | Caa2 |
Cash Flow | Baa2 | C |
Rates of Return and Profitability | B2 | 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?This exclusive content is only available to premium users.This exclusive content is only available to premium users.This exclusive content is only available to premium users.This exclusive content is only available to premium users.
References
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- Y. Chow and M. Ghavamzadeh. Algorithms for CVaR optimization in MDPs. In Advances in Neural Infor- mation Processing Systems, pages 3509–3517, 2014.