TR/CC CRB Nickel Index Forecast

Outlook: TR/CC CRB Nickel index is assigned short-term Caa2 & long-term B1 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 (Market News Sentiment Analysis)
Hypothesis Testing : Polynomial Regression
Surveillance : Major exchange and OTC

¹Short-term revised.

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

Key Points

The TR/CC CRB Nickel index faces a near-term forecast of moderate price appreciation driven by robust industrial demand, particularly from the electric vehicle and stainless steel sectors, and expectations of tightening global supply due to ongoing geopolitical tensions impacting key producing regions. However, a significant risk to this optimistic outlook is the potential for a sudden downturn in global economic growth, which could curb manufacturing activity and subsequently reduce nickel consumption. Furthermore, there is a risk of increased production from less established or secondary sources as prices rise, which could introduce new supply dynamics and dampen the upward price momentum.

About TR/CC CRB Nickel Index

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ML Model Testing

F(Polynomial Regression)^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 (Market News Sentiment Analysis))^3,4,5 X S(n):→ 3 Month $\sum _{i=1}^n\left(r_i\right)$

n:Time series to forecast

p:Price signals of TR/CC CRB Nickel index

j:Nash equilibria (Neural Network)

k:Dominated move of TR/CC CRB Nickel index holders

a:Best response for TR/CC CRB Nickel 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 Nickel 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	Caa2	B1
Income Statement	C	Caa2
Balance Sheet	C	Baa2
Leverage Ratios	B3	Baa2
Cash Flow	Baa2	Caa2
Rates of Return and Profitability	C	Caa2

*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.
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References

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3. Imbens GW, Rubin DB. 2015. Causal Inference in Statistics, Social, and Biomedical Sciences. Cambridge, UK: Cambridge Univ. Press
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5. Meinshausen N. 2007. Relaxed lasso. Comput. Stat. Data Anal. 52:374–93
6. Krizhevsky A, Sutskever I, Hinton GE. 2012. Imagenet classification with deep convolutional neural networks. In Advances in Neural Information Processing Systems, Vol. 25, ed. Z Ghahramani, M Welling, C Cortes, ND Lawrence, KQ Weinberger, pp. 1097–105. San Diego, CA: Neural Inf. Process. Syst. Found.
7. Jorgenson, D.W., Weitzman, M.L., ZXhang, Y.X., Haxo, Y.M. and Mat, Y.X., 2023. Apple's Stock Price: How News Affects Volatility. AC Investment Research Journal, 220(44).