AUC Score :
Short-term Tactic1 :
Dominant Strategy :
Time series to forecast n:
ML Model Testing : Inductive Learning (ML)
Hypothesis Testing : Pearson Correlation
Surveillance : Major exchange and OTC
1Short-term revised.
2Time series is updated based on short-term trends.
Key Points
This exclusive content is only available to premium users.About EBC
This exclusive content is only available to premium users.
ML Model Testing
n:Time series to forecast
p:Price signals of EBC stock
j:Nash equilibria (Neural Network)
k:Dominated move of EBC stock holders
a:Best response for EBC 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?
EBC 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 | Ba3 |
| Income Statement | Baa2 | B3 |
| Balance Sheet | Baa2 | B1 |
| Leverage Ratios | B2 | B3 |
| Cash Flow | B2 | Baa2 |
| Rates of Return and Profitability | C | Ba1 |
*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
- Bamler R, Mandt S. 2017. Dynamic word embeddings via skip-gram filtering. In Proceedings of the 34th Inter- national Conference on Machine Learning, pp. 380–89. La Jolla, CA: Int. Mach. Learn. Soc.
- Rosenbaum PR, Rubin DB. 1983. The central role of the propensity score in observational studies for causal effects. Biometrika 70:41–55
- G. Shani, R. Brafman, and D. Heckerman. An MDP-based recommender system. In Proceedings of the Eigh- teenth conference on Uncertainty in artificial intelligence, pages 453–460. Morgan Kaufmann Publishers Inc., 2002
- Hastie T, Tibshirani R, Friedman J. 2009. The Elements of Statistical Learning. Berlin: Springer
- J. Hu and M. P. Wellman. Nash q-learning for general-sum stochastic games. Journal of Machine Learning Research, 4:1039–1069, 2003.
- Cheung, Y. M.D. Chinn (1997), "Further investigation of the uncertain unit root in GNP," Journal of Business and Economic Statistics, 15, 68–73.
- D. Bertsekas. Min common/max crossing duality: A geometric view of conjugacy in convex optimization. Lab. for Information and Decision Systems, MIT, Tech. Rep. Report LIDS-P-2796, 2009