TR/CC CRB ex Energy ER Index Forecast

Outlook: TR/CC CRB ex Energy ER index is assigned short-term B1 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-term Tactic¹ :
Dominant Strategy :
Time series to forecast n: for Weeks²
ML Model Testing : Modular Neural Network (Financial Sentiment Analysis)
Hypothesis Testing : Beta
Surveillance : Major exchange and OTC

¹Short-term revised.

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

Key Points

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About TR/CC CRB ex Energy ER Index

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ML Model Testing

F(Beta)^6,7= $\begin{array}{cccc}{p}_{\mathrm{a}1}& p_{\mathrm{a}2}& \dots & p_{1n}\\ & ⋮\\ p_{j1}& p_{j2}& \dots & p_{jn}\\ & ⋮\\ p_{k1}& p_{k2}& \dots & p_{kn}\\ & ⋮\\ p_{n1}& p_{n2}& \dots & p_{nn}\end{array}$ X R(Modular Neural Network (Financial Sentiment Analysis))^3,4,5 X S(n):→ 1 Year $\overrightarrow{S}=\left(s_1,s_2,s_3\right)$

n:Time series to forecast

p:Price signals of TR/CC CRB ex Energy ER index

j:Nash equilibria (Neural Network)

k:Dominated move of TR/CC CRB ex Energy ER index holders

a:Best response for TR/CC CRB ex Energy ER 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?

TR/CC CRB ex Energy ER 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%

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Rating	Short-Term	Long-Term Senior
Outlook	B1	B2
Income Statement	Ba3	B3
Balance Sheet	B3	Caa2
Leverage Ratios	Baa2	B1
Cash Flow	B3	B2
Rates of Return and Profitability	C	B2

*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

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