AUC Score :
Short-term Tactic1 :
Dominant Strategy :
Time series to forecast n:
ML Model Testing : Modular Neural Network (News Feed Sentiment Analysis)
Hypothesis Testing : Multiple Regression
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 OMXS30 Index
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ML Model Testing
n:Time series to forecast
p:Price signals of OMXS30 index
j:Nash equilibria (Neural Network)
k:Dominated move of OMXS30 index holders
a:Best response for OMXS30 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?
OMXS30 Index Forecast 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 | B3 | B3 |
| Income Statement | Caa2 | B2 |
| Balance Sheet | Baa2 | B2 |
| Leverage Ratios | B2 | C |
| Cash Flow | C | C |
| Rates of Return and Profitability | C | B3 |
*An aggregate rating for an index summarizes the overall sentiment towards the companies it includes. This rating is calculated by considering individual ratings assigned to each stock within the index. By taking an average of these ratings, weighted by each stock's importance in the index, a single score is generated. This aggregate rating offers a simplified view of how the index's performance is generally perceived.
How does neural network examine financial reports and understand financial state of the company?
References
- Bai J, Ng S. 2002. Determining the number of factors in approximate factor models. Econometrica 70:191–221
- Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Google's Stock Price Set to Soar in the Next 3 Months. AC Investment Research Journal, 220(44).
- Chernozhukov V, Chetverikov D, Demirer M, Duflo E, Hansen C, et al. 2018a. Double/debiased machine learning for treatment and structural parameters. Econom. J. 21:C1–68
- P. Milgrom and I. Segal. Envelope theorems for arbitrary choice sets. Econometrica, 70(2):583–601, 2002
- Hoerl AE, Kennard RW. 1970. Ridge regression: biased estimation for nonorthogonal problems. Technometrics 12:55–67
- Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Google's Stock Price Set to Soar in the Next 3 Months. AC Investment Research Journal, 220(44).
- Bell RM, Koren Y. 2007. Lessons from the Netflix prize challenge. ACM SIGKDD Explor. Newsl. 9:75–79