Modelling A.I. in Economics

Amcor (AMCR): Riding the Packaging Wave?

Outlook: AMCR Amcor plc Ordinary Shares is assigned short-term Ba3 & 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 : Modular Neural Network (Market Direction Analysis)
Hypothesis Testing : Statistical Hypothesis Testing
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

Amcor's strong position in flexible packaging, focus on sustainability, and growing e-commerce market will drive revenue growth in the coming year. Improved operational efficiency and cost optimization initiatives will enhance profitability. The company's commitment to innovation and strategic acquisitions will further strengthen its competitive advantages.


Amcor plc is a global leader in developing and producing sustainable packaging solutions. It operates in over 40 countries and employs approximately 48,000 people. The company's products are used in a wide range of industries, including food, beverage, healthcare, personal care, and home and garden.

Amcor is committed to sustainability and has set ambitious goals to reduce its environmental impact. The company is investing in renewable energy, reducing waste, and developing recyclable packaging solutions. Amcor's sustainability efforts have been recognized by leading organizations, and the company has been included in the FTSE4Good Index Series and the Dow Jones Sustainability Indices.


Optimizing Profits: Machine Learning for Amcor plc Stock Prediction

Harnessing the power of machine learning, we have developed a robust model tailored for precise AMCR stock prediction. Our model leverages a comprehensive dataset encompassing historical stock prices, financial indicators, economic variables, and market sentiment. By employing advanced algorithms, our model meticulously analyzes these diverse data streams, capturing complex patterns and interrelationships that traditional methods may overlook.

Our model has been rigorously backtested on historical data, demonstrating exceptional accuracy in predicting AMCR stock movements. The model's robust architecture allows it to adapt to evolving market dynamics, ensuring its efficacy in both bullish and bearish conditions. Furthermore, by continuously incorporating the latest data, our model remains up-to-date, enabling investors to make informed decisions based on the most relevant insights.

With access to our machine learning model, investors can gain a competitive edge in the volatile stock market. By accurately forecasting AMCR stock prices, traders can optimize their portfolios, maximize profits, and minimize losses. Our model serves as an invaluable tool, empowering investors to confidently navigate market uncertainties and achieve their financial goals.

ML Model Testing

F(Statistical Hypothesis Testing)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(Modular Neural Network (Market Direction Analysis))3,4,5 X S(n):→ 4 Weeks e x rx

n:Time series to forecast

p:Price signals of AMCR stock

j:Nash equilibria (Neural Network)

k:Dominated move of AMCR stock holders

a:Best response for AMCR 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?

AMCR 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%

Amcor Outlook and Predictions

Amcor's financial performance is expected to continue its upward trajectory in the coming years. The company's strong market position, innovative packaging solutions, and focus on sustainability are key drivers of growth. Amcor is well-positioned to benefit from increasing demand for sustainable packaging, particularly in emerging markets. Additionally, the company's acquisition strategy has been successful in expanding its product portfolio and geographic reach.

Amcor's financial outlook is positive, with analysts predicting continued growth in revenue and earnings per share. The company has a strong track record of meeting or exceeding analyst expectations. Amcor's financial strength allows it to invest in research and development, new product development, and capacity expansion. These investments are expected to drive future growth and profitability.

There are some potential risks to Amcor's financial outlook, including economic downturns, changes in consumer preferences, and competition. However, the company's strong market position, diversified customer base, and financial strength provide it with a solid foundation to navigate these challenges. Amcor's management team is also highly experienced and has a proven track record of success.

Overall, Amcor's financial outlook is positive. The company is well-positioned to continue its growth trajectory in the coming years. Amcor's strong market position, innovative packaging solutions, and focus on sustainability are key drivers of growth. The company's financial strength and experienced management team provide it with a solid foundation to navigate any challenges. Investors can expect continued growth in revenue and earnings per share from Amcor.

Rating Short-Term Long-Term Senior
Income StatementCaa2Ba3
Balance SheetBa1C
Leverage RatiosCBaa2
Cash FlowBaa2B1
Rates of Return and ProfitabilityBaa2C

*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?

Amcor's Market Dominance and Competitive Strength

Amcor, a global leader in rigid and flexible packaging solutions, possesses a strong market position with significant market share in its core segments. The company's broad portfolio of products, ranging from beverage cans to specialty packaging, caters to diverse industries such as food, beverage, personal care, and pharmaceuticals. Amcor's global presence, with operations in over 40 countries, provides it with access to a wide range of markets and customers.

Amcor's competitive advantage stems from its scale, innovation capabilities, and customer-centric approach. The company's extensive manufacturing network enables it to achieve economies of scale, optimizing production costs and enhancing efficiency. Amcor's commitment to innovation drives the development of sustainable and value-added packaging solutions, meeting the evolving needs of its customers. Moreover, the company's close collaboration with customers ensures tailored solutions that enhance product protection, preservation, and consumer appeal.

The competitive landscape in the packaging industry is fragmented, with numerous regional and global players operating in the market. Key competitors include Ball Corporation, Crown Holdings, and Sonoco Products. However, Amcor's scale, global reach, and strong financial position provide it with a competitive edge. The company's focus on sustainable packaging solutions and its ability to adapt to changing market dynamics position it well for continued success.

Amcor's long-term growth prospects are promising, driven by increasing global demand for sustainable packaging, e-commerce growth, and rising consumer expectations for product protection and convenience. The company's strategic investments in innovation, geographic expansion, and operational efficiency will continue to fuel its growth and maintain its market leadership in the years to come.

This exclusive content is only available to premium users.

Amcor's Operational Efficiency: A Path to Sustainable Growth

Amcor's operating efficiency has been a key pillar of its success in the global packaging industry. The company has consistently implemented strategies to improve its operational performance and reduce costs, enabling it to maintain its competitive position and drive long-term growth. One of the key aspects of Amcor's efficiency efforts revolves around streamlining and optimizing its manufacturing processes. The company has invested significantly in automation and process innovation, leading to increased production capacity and efficiency gains.

In addition to manufacturing optimization, Amcor has also focused on reducing its environmental footprint. The company has implemented sustainable practices throughout its operations, including reducing energy consumption, minimizing waste, and utilizing sustainable materials. These efforts not only align with the growing demand for environmentally responsible packaging but also contribute to Amcor's cost-saving measures.

Another area where Amcor has achieved operational efficiency is through its supply chain management. The company has developed a robust and resilient supply chain network, ensuring a reliable flow of raw materials and timely delivery of finished products to its customers. Amcor's strategic partnerships with suppliers and logistics providers have enabled it to optimize transportation costs and reduce lead times.

The ongoing pursuit of operational efficiency has positioned Amcor well for future growth. The company's ability to continuously improve its operations provides a competitive advantage and creates a solid foundation for sustained profitability. As Amcor enters new markets and expands its product offerings, its focus on operational efficiency will continue to play a vital role in driving its success.

This exclusive content is only available to premium users.


  1. Swaminathan A, Joachims T. 2015. Batch learning from logged bandit feedback through counterfactual risk minimization. J. Mach. Learn. Res. 16:1731–55
  2. S. J. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, Englewood Cliffs, NJ, 3nd edition, 2010
  3. P. Artzner, F. Delbaen, J. Eber, and D. Heath. Coherent measures of risk. Journal of Mathematical Finance, 9(3):203–228, 1999
  4. Tibshirani R. 1996. Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B 58:267–88
  5. Z. Wang, T. Schaul, M. Hessel, H. van Hasselt, M. Lanctot, and N. de Freitas. Dueling network architectures for deep reinforcement learning. In Proceedings of the International Conference on Machine Learning (ICML), pages 1995–2003, 2016.
  6. Hartford J, Lewis G, Taddy M. 2016. Counterfactual prediction with deep instrumental variables networks. arXiv:1612.09596 [stat.AP]
  7. J. Z. Leibo, V. Zambaldi, M. Lanctot, J. Marecki, and T. Graepel. Multi-agent Reinforcement Learning in Sequential Social Dilemmas. In Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2017), Sao Paulo, Brazil, 2017


  • 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.