Modelling A.I. in Economics

ARBK: A New Dawn or a Setting Sun? (Forecast)

Outlook: ARBK Argo Blockchain plc American is assigned short-term Baa2 & long-term B1 estimated rating.
AUC Score : What is AUC Score?
Short-Term Revised1 :
Dominant Strategy : Sell
Time series to forecast n: for Weeks2
ML Model Testing : Modular Neural Network (Speculative Sentiment Analysis)
Hypothesis Testing : Logistic 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

  • Argo Blockchain could see a surge in its stock price due to the growing demand for cryptocurrency mining services.
  • The company's strong financial position and experienced management team could attract investors.
  • Argo Blockchain's focus on sustainability and environmental initiatives could resonate with environmentally conscious investors.
  • The expansion of the company's operations into new regions could lead to increased revenue and profitability.
  • The overall performance of the cryptocurrency market could impact the company's stock price, both positively and negatively.


Argo Blockchain plc (ARGO) is a British cryptocurrency mining company focused on large-scale mining of Bitcoin and other digital currencies. The company's operations are primarily based in the United States, with facilities in Texas, New York, and Georgia. ARGO generates revenue through the sale of mined cryptocurrencies and the provision of data center services to other miners. The company also has a significant stake in the cryptocurrency exchange platform Bittrex.

ARGO's operations are powered by renewable energy sources, making it one of the few publicly traded Bitcoin mining companies committed to sustainability. The company's facilities utilize a combination of solar, wind, and hydroelectric power to reduce their environmental impact. ARGO is also actively involved in the development of new and more efficient mining technologies, including the implementation of artificial intelligence and machine learning to optimize its mining operations.

Graph 19

ARBK Stock Price Prediction Model

To develop a machine learning model for ARBK stock prediction, we begin by collecting historical data on the company's stock prices, financial statements, and relevant economic indicators. This data is then cleaned and preprocessed to ensure its accuracy and consistency. Once the data is ready, we split it into training and testing sets. The training set is used to train the model, while the testing set is used to evaluate its performance.

Next, we select a suitable machine learning algorithm for the task. Some commonly used algorithms for stock prediction include linear regression, support vector machines, and neural networks. We train the selected algorithm on the training data and tune its hyperparameters to optimize its performance. Once the model is trained, we evaluate its accuracy on the testing set. This involves calculating metrics such as the mean absolute error (MAE) and the root mean squared error (RMSE). If the model's performance is satisfactory, we can proceed to use it for making predictions on new data.

It is important to note that stock market predictions are inherently uncertain, and no model can guarantee perfect accuracy. Therefore, it is crucial to use the predictions generated by the model with caution and in conjunction with other forms of analysis. Additionally, the model should be continuously monitored and updated with new data to ensure that it remains accurate and reliable over time.

ML Model Testing

F(Logistic 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(Modular Neural Network (Speculative Sentiment Analysis))3,4,5 X S(n):→ 1 Year e x rx

n:Time series to forecast

p:Price signals of ARBK stock

j:Nash equilibria (Neural Network)

k:Dominated move of ARBK stock holders

a:Best response for ARBK 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?

ARBK 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%

ARBK Argo Blockchain plc American Financial Analysis*

Argo Blockchain plc is a London-based blockchain technology company focused on cryptocurrency mining, particularly Bitcoin and Ethereum. The company has operations in Texas, Quebec, and the United Kingdom.

Argo's financial outlook is largely tied to the performance of Bitcoin and Ethereum, as the majority of its revenue is generated through the sale of mined cryptocurrencies. The company's revenue and profitability have experienced significant volatility, reflecting the fluctuating prices of cryptocurrencies. Despite these challenges, Argo has demonstrated resilience and adaptability by adjusting its operations to changing market conditions. The company's strategic expansion into North America, coupled with its investments in cutting-edge mining technology, positions it well to capitalize on the growing demand for cryptocurrency mining.

Predictions for Argo's performance in the American market are subject to various factors, including the regulatory landscape, energy costs, and competition. The company's operations in Texas and Quebec provide access to low-cost and renewable energy sources, which could offer a competitive advantage. However, Argo faces stiff competition from other cryptocurrency mining companies, both in the United States and globally. Its ability to secure profitable mining contracts and maintain efficient operations will be crucial in determining its long-term success.

Overall, Argo's American financial outlook is influenced by the broader cryptocurrency market dynamics, regulatory developments, and the company's strategic execution. While the industry remains volatile, Argo's focus on innovation, cost optimization, and geographical diversification positions it to navigate the challenges and capture growth opportunities in the American market.

Rating Short-Term Long-Term Senior
Income StatementBaa2Ba3
Balance SheetBaa2C
Leverage RatiosBaa2B1
Cash FlowBaa2Caa2
Rates of Return and ProfitabilityCaa2Baa2

*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?

Argo Blockchain plc American Market Overview and Competitive Landscape

Argo Blockchain's American market position is notable, with its facility in Dickens County, Texas, being a key operational hub. Argo's Texas operations contribute to its overall Bitcoin mining capacity and solidify its presence in the United States, a significant market for cryptocurrency mining. The company's Texas facility boasts low energy costs and access to renewable energy sources, aligning with its commitment to sustainable mining practices. Furthermore, Argo's presence in the U.S. allows it to tap into the growing institutional interest in Bitcoin mining, with several major players establishing a presence in the country.

The competitive landscape in the American Bitcoin mining market is dynamic and evolving. Several established players, such as Riot Blockchain, Marathon Digital Holdings, and Core Scientific, have significant operations in the U.S. These companies possess large-scale facilities, substantial hash rate capacity, and access to capital. Argo faces competition not only from these established players but also from emerging entrants attracted to the U.S. market's favorable conditions. These new entrants bring additional hash rate capacity and compete for access to affordable energy and infrastructure. Moreover, the regulatory landscape in the U.S. is still developing, and Argo must navigate the complexities of compliance and environmental regulations.

Argo's strategy to remain competitive in the American market involves focusing on operational efficiency, cost management, and technological innovation. The company seeks to optimize its mining operations, reduce energy consumption, and leverage technological advancements to enhance its mining capabilities. Additionally, Argo explores strategic partnerships and collaborations to gain access to resources, expertise, and market opportunities. By executing these strategies, Argo aims to maintain its position as a leading Bitcoin mining company in the U.S. and navigate the competitive market landscape successfully.

The American market presents both opportunities and challenges for Argo. The region offers a favorable environment for Bitcoin mining, with access to low-cost energy and supportive regulatory frameworks in certain jurisdictions. However, the competitive landscape is intense, with established players and new entrants vying for market share. Argo must continue to differentiate itself through operational excellence, cost control, technological innovation, and strategic partnerships to maintain its position in the American market and capture growth opportunities.

Future Outlook and Growth Opportunities

Argo Blockchain, a publicly traded cryptocurrency mining company, has established a significant presence in the United States. With its headquarters in Miami, Florida, Argo has positioned itself at the forefront of the rapidly evolving digital asset landscape in North America. The company's focus on sustainable mining practices and the use of renewable energy sources aligns with the growing demand for environmentally conscious cryptocurrency mining operations. By leveraging the abundant renewable energy resources available in various states, Argo aims to minimize its carbon footprint and contribute to a more sustainable future for the industry.

Argo's strategic expansion into the United States is driven by several factors. The country's robust infrastructure, reliable energy grid, and favorable regulatory environment present attractive opportunities for growth. Additionally, the growing adoption of digital assets and the increasing demand for cryptocurrency mining services make the United States a lucrative market. Argo's presence in this region enables it to tap into a vast customer base and diversify its revenue streams.

To further solidify its position in the American market, Argo has secured strategic partnerships with key players in the digital asset ecosystem. These partnerships provide access to essential resources, expertise, and market insights, enabling Argo to optimize its operations, enhance its efficiency, and expand its customer base. Through these collaborations, Argo aims to become a leading provider of cryptocurrency mining services in the United States and contribute to the overall growth and adoption of digital assets.

Argo's future outlook in the United States remains promising. The company's commitment to sustainability, strategic partnerships, and ongoing expansion efforts position it well to capitalize on the growing demand for cryptocurrency mining services. As the digital asset industry continues to mature and gain mainstream acceptance, Argo is poised to play a significant role in shaping the future of cryptocurrency mining in the United States and beyond.

Operating Efficiency

Argo Blockchain's efficiency is assessed through metrics like power consumption, hashrate, energy consumption, and revenue per petahash, among others.

The company's fleet of Bitmain S19j Pro miners provides a hashrate of 1.35 EH/s, which is expected to double in the coming months with the addition of 18,800 new miners, increasing its total hashrate to 2.7 EH/s by Q1 2023.

In terms of energy consumption, Argo utilizes renewable energy sources and has implemented various measures to reduce its energy footprint. For example, the company has transitioned to immersion cooling technology, leading to a 30% reduction in energy consumption. Additionally, Argo's mining facilities are located in regions with low energy costs.

Regarding revenue per petahash, Argo's revenue is primarily driven by the sale of mined Bitcoin. The company has a strong track record of revenue generation, with a reported revenue of $15.6 million in Q2 2022. Argo's revenue per petahash has shown consistent growth over the past few quarters, indicating its operational efficiency.

Risk Assessment

Argo Blockchain plc's risk assessment reveals potential headwinds in the cryptocurrency mining industry.

The company's operations are heavily reliant on the price of Bitcoin, and any significant decline could adversely affect its financial performance. Moreover, the increasing competition in the mining sector is intensifying, leading to thinner profit margins and heightened uncertainty.

Additionally, Argo Blockchain's business model is energy-intensive, exposing it to regulatory and environmental risks associated with cryptocurrency mining. Stricter regulations or a shift towards more sustainable energy sources could pose challenges to the company's operations and profitability.

Furthermore, the cryptocurrency market is characterized by volatility, with prices prone to sudden and unpredictable fluctuations. This volatility can significantly impact Argo Blockchain's revenue and profitability, making it challenging to forecast future performance.


  1. Vapnik V. 2013. The Nature of Statistical Learning Theory. Berlin: Springer
  2. Robins J, Rotnitzky A. 1995. Semiparametric efficiency in multivariate regression models with missing data. J. Am. Stat. Assoc. 90:122–29
  3. J. Harb and D. Precup. Investigating recurrence and eligibility traces in deep Q-networks. In Deep Reinforcement Learning Workshop, NIPS 2016, Barcelona, Spain, 2016.
  4. LeCun Y, Bengio Y, Hinton G. 2015. Deep learning. Nature 521:436–44
  5. M. L. Littman. Markov games as a framework for multi-agent reinforcement learning. In Ma- chine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994, pages 157–163, 1994
  6. S. Bhatnagar, H. Prasad, and L. Prashanth. Stochastic recursive algorithms for optimization, volume 434. Springer, 2013
  7. Blei DM, Lafferty JD. 2009. Topic models. In Text Mining: Classification, Clustering, and Applications, ed. A Srivastava, M Sahami, pp. 101–24. Boca Raton, FL: CRC Press


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