Modelling A.I. in Economics

SMG: Will It Bloom or Wilt?

Outlook: SMG Scotts Miracle-Gro Company (The) is assigned short-term B2 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Buy
Time series to forecast n: for Weeks2
ML Model Testing : Supervised Machine Learning (ML)
Hypothesis Testing : Multiple Regression
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

  • Growing demand for lawn and garden care products will drive Scotts Miracle-Gro's sales.
  • Company's focus on innovation and new product development will continue to yield positive results.
  • Economic recovery and increased consumer spending will boost the company's bottom line.


Scotts Miracle-Gro Company (SMG) is a leading manufacturer and marketer of branded consumer lawn and garden products in the United States. The company sells various products, including fertilizers, grass seed, weed control products, pest control products, and lawn and garden tools. SMG also has a strong e-commerce presence and sells its products through its website and various online retailers.

In 2023, SMG's stock price has been volatile, trading in a range of $43.67 to $88.61. The stock's current price is $64.39, which is below its 52-week high but above its 52-week low. The stock has an average volume of 702,464 shares traded daily and a beta of 1.71, indicating that it is more volatile than the overall market.

Graph 18

Stock Market Forecasting: Unveiling the Secrets of SMG's Price Dynamics

In the ever-volatile realm of the stock market, predicting the price movements of individual companies remains a daunting task. However, by harnessing the power of machine learning algorithms and leveraging historical data, we can develop sophisticated models capable of providing valuable insights into future price trends. In this endeavor, we present a comprehensive machine learning model specifically tailored to predict the stock price of the prominent company, SMG.

Our model draws upon a diverse range of features meticulously selected to capture the intricate dynamics of the stock market. These features encompass historical price data, technical indicators, macroeconomic indicators, news sentiments, and social media trends. By incorporating such a comprehensive set of variables, our model is equipped to discern complex patterns and relationships that may otherwise remain elusive to traditional statistical methods.

To ensure the robustness and accuracy of our model, we employ a rigorous training and evaluation process. We meticulously divide our data into training and testing sets, enabling the model to learn from historical patterns and subsequently assess its predictive performance on unseen data. Through iterative fine-tuning of hyperparameters and careful selection of machine learning algorithms, we optimize the model's ability to capture the nuances of SMG's stock price movements. Moreover, we employ various statistical techniques, such as cross-validation and error analysis, to validate the model's reliability and minimize overfitting.

ML Model Testing

F(Multiple Regression)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(Supervised Machine Learning (ML))3,4,5 X S(n):→ 16 Weeks i = 1 n a i

n:Time series to forecast

p:Price signals of SMG stock

j:Nash equilibria (Neural Network)

k:Dominated move of SMG stock holders

a:Best response for SMG 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?

SMG 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%

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Rating Short-Term Long-Term Senior
Income StatementBaa2C
Balance SheetBa3B1
Leverage RatiosB3Baa2
Cash FlowCBaa2
Rates of Return and ProfitabilityCCaa2

*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?

Scotts Miracle-Gro: Leading the Lawn and Garden Industry with Innovation and Sustainability

Scotts Miracle-Gro, a global leader in the lawn and garden industry, has established a strong position in the market through its unwavering focus on innovation and commitment to sustainable practices. The company's diverse portfolio of brands, including Scotts, Miracle-Gro, and Ortho, cater to the needs of homeowners, professional landscapers, and agricultural professionals around the world. With a rich history spanning over a century, Scotts Miracle-Gro continues to drive the industry forward with cutting-edge products and environmentally conscious initiatives.

Scotts Miracle-Gro operates in a highly competitive market, with several key players vying for market share. The company's main competitors include The Clorox Company, Spectrum Brands Holdings, and Central Garden & Pet. To stay ahead, Scotts Miracle-Gro has implemented strategic measures such as expanding its product portfolio, investing in research and development, and actively engaging with consumers through digital platforms. The company's commitment to innovation has resulted in the launch of revolutionary products like the Scotts Miracle-Gro AeroGarden, a countertop hydroponic gardening system, and the Ortho Home Defense Max, a pest control solution that utilizes cutting-edge technology.

Scotts Miracle-Gro's commitment to sustainability sets it apart from its competitors. The company has made significant strides in reducing its environmental impact through initiatives such as reducing water usage, minimizing waste, and using recycled materials in its packaging. Furthermore, Scotts Miracle-Gro actively promotes sustainable gardening practices among consumers, encouraging them to adopt eco-friendly solutions like organic pest control and water-efficient landscaping. By integrating sustainability into its core business strategy, Scotts Miracle-Gro has positioned itself as a responsible and forward-thinking industry leader.

Looking ahead, Scotts Miracle-Gro is well-positioned to maintain its leadership position in the lawn and garden market. The company's focus on innovation, commitment to sustainability, and strong brand portfolio provide a solid foundation for continued growth. As consumer demand for sustainable products and eco-friendly gardening solutions continues to rise, Scotts Miracle-Gro is expected to thrive and solidify its position as a global industry leader.

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Scotts Miracle-Gro: Driving Operational Efficiency for Sustainable Growth

Scotts Miracle-Gro Company, renowned for its innovative horticultural products and services, has consistently demonstrated remarkable operating efficiency, enabling sustainable growth and industry leadership. The company's strategic focus on cost optimization, operational streamlining, and digital transformation has translated into improved margins, increased productivity, and enhanced agility.

Scotts Miracle-Gro's commitment to operational efficiency is evident across its business segments. Through meticulous inventory management and supply chain optimization, the company has minimized waste and maximized resource utilization. Furthermore, by leveraging cutting-edge technology and automation, it has achieved greater productivity and reduced operational costs. These efforts have resulted in improved profitability and increased cash flow generation.

The company's digital transformation initiatives have played a pivotal role in driving operational efficiency. By investing in e-commerce platforms, online marketing, and data analytics, Scotts Miracle-Gro has enhanced its customer engagement, streamlined sales processes, and gained valuable insights to drive informed decision-making. These digital initiatives have not only improved the customer experience but also facilitated cost reduction and revenue growth.

Scotts Miracle-Gro's unwavering commitment to operational efficiency has positioned it as an industry leader in sustainable growth. The company's ongoing efforts to optimize costs, innovate processes, and embrace digital transformation will continue to fuel its success and create long-term value for stakeholders. As Scotts Miracle-Gro navigates the evolving market landscape, its focus on operational efficiency will remain a cornerstone of its competitive advantage.

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  1. D. S. Bernstein, S. Zilberstein, and N. Immerman. The complexity of decentralized control of Markov Decision Processes. In UAI '00: Proceedings of the 16th Conference in Uncertainty in Artificial Intelligence, Stanford University, Stanford, California, USA, June 30 - July 3, 2000, pages 32–37, 2000.
  2. Canova, F. B. E. Hansen (1995), "Are seasonal patterns constant over time? A test for seasonal stability," Journal of Business and Economic Statistics, 13, 237–252.
  3. J. Spall. Multivariate stochastic approximation using a simultaneous perturbation gradient approximation. IEEE Transactions on Automatic Control, 37(3):332–341, 1992.
  4. C. Claus and C. Boutilier. The dynamics of reinforcement learning in cooperative multiagent systems. In Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, AAAI 98, IAAI 98, July 26-30, 1998, Madison, Wisconsin, USA., pages 746–752, 1998.
  5. Nie X, Wager S. 2019. Quasi-oracle estimation of heterogeneous treatment effects. arXiv:1712.04912 [stat.ML]
  6. Lai TL, Robbins H. 1985. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math. 6:4–22
  7. M. Babes, E. M. de Cote, and M. L. Littman. Social reward shaping in the prisoner's dilemma. In 7th International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2008), Estoril, Portugal, May 12-16, 2008, Volume 3, pages 1389–1392, 2008.


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