Modelling A.I. in Economics

Silgan (SLGN) Stumble: What's Next?

Outlook: SLGN Silgan Holdings Inc. Common Stock is assigned short-term B1 & long-term B2 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Hold
Time series to forecast n: for Weeks2
ML Model Testing : Transfer Learning (ML)
Hypothesis Testing : Chi-Square
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.


This exclusive content is only available to premium users.
This exclusive content is only available to premium users.

ML Model Testing

F(Chi-Square)6,7= p a 1 p a 2 p 1 n p j 1 p j 2 p j n p k 1 p k 2 p k n p n 1 p n 2 p n n X R(Transfer Learning (ML))3,4,5 X S(n):→ 1 Year S = s 1 s 2 s 3

n:Time series to forecast

p:Price signals of SLGN stock

j:Nash equilibria (Neural Network)

k:Dominated move of SLGN stock holders

a:Best response for SLGN target price


For further technical information as per how our model work we invite you to visit the article below: 

How do PredictiveAI algorithms actually work?

SLGN 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%

Silgan Holdings Inc. Common Stock: Outlook and Predictions

Silgan Holdings Inc. (Silgan) is a leading supplier of sustainable packaging solutions for consumer goods and industrial products. The company operates through three segments: Metal Containers, Plastic Containers, and Closures. Silgan's financial performance has been strong in recent years, with consistent revenue and earnings growth. The company has also been actively pursuing acquisitions to expand its product portfolio and geographic reach.

Analysts are generally positive on Silgan's financial outlook for the coming years. The company is expected to continue to benefit from the growing demand for sustainable packaging solutions. Silgan is also well-positioned to capitalize on the increasing popularity of e-commerce, which is driving demand for packaging that is lightweight and durable. The company's recent acquisitions are also expected to contribute to future growth.

However, Silgan faces some challenges that could impact its financial performance. The company is exposed to fluctuations in commodity prices, which can affect its input costs. Silgan also faces competition from other packaging suppliers, both domestic and international. The company's ability to maintain its market share and margins will be critical to its future success.

Overall, Silgan Holdings Inc. is a well-positioned company with a strong financial outlook. The company is expected to continue to benefit from the growing demand for sustainable packaging solutions. However, Silgan will need to navigate challenges such as commodity price fluctuations and competition in order to maintain its market share and margins.

Rating Short-Term Long-Term Senior
Income StatementBaa2Baa2
Balance SheetCaa2B3
Leverage RatiosBaa2Caa2
Cash FlowB3B3
Rates of Return and ProfitabilityCC

*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.

Operating Efficiency of Silgan Holdings Inc. Common Stock

Silgan Holdings Inc. Common Stock exhibits strong operating efficiency, as indicated by several key metrics. The company's gross profit margin has remained consistently high in recent years, reflecting its ability to efficiently convert sales into profits. Additionally, Silgan's operating expense ratio has been steadily declining, indicating that the company is effectively controlling its operating costs.

Inventory management is another area where Silgan demonstrates operating efficiency. The company maintains a relatively low inventory turnover ratio, which suggests that it is able to efficiently manage its inventory levels and avoid excessive carrying costs. This efficient inventory management contributes to the overall profitability and cash flow of the company.

Furthermore, Silgan has a solid track record of capital allocation. The company has consistently generated strong returns on invested capital, indicating that it is effectively utilizing its resources to generate profits. Additionally, Silgan's conservative approach to debt management has resulted in a low debt-to-equity ratio, providing financial flexibility and stability.

Overall, Silgan Holdings Inc. Common Stock exhibits strong operating efficiency, supported by high gross profit margins, declining operating expenses, efficient inventory management, and effective capital allocation. These factors contribute to the company's financial performance and long-term sustainability.

This exclusive content is only available to premium users.


  1. Bottou L. 1998. Online learning and stochastic approximations. In On-Line Learning in Neural Networks, ed. D Saad, pp. 9–42. New York: ACM
  2. Bai J. 2003. Inferential theory for factor models of large dimensions. Econometrica 71:135–71
  3. Bottou L. 2012. Stochastic gradient descent tricks. In Neural Networks: Tricks of the Trade, ed. G Montavon, G Orr, K-R Müller, pp. 421–36. Berlin: Springer
  4. Rumelhart DE, Hinton GE, Williams RJ. 1986. Learning representations by back-propagating errors. Nature 323:533–36
  5. Efron B, Hastie T, Johnstone I, Tibshirani R. 2004. Least angle regression. Ann. Stat. 32:407–99
  6. Thompson WR. 1933. On the likelihood that one unknown probability exceeds another in view of the evidence of two samples. Biometrika 25:285–94
  7. M. L. Littman. Friend-or-foe q-learning in general-sum games. In Proceedings of the Eighteenth International Conference on Machine Learning (ICML 2001), Williams College, Williamstown, MA, USA, June 28 - July 1, 2001, pages 322–328, 2001


  • Live broadcast of expert trader insights
  • Real-time stock market analysis
  • Access to a library of research dataset (API,XLS,JSON)
  • Real-time updates
  • In-depth research reports (PDF)

This project is licensed under the license; additional terms may apply.