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SioliBros is also member of SIAT,
the Italian Society of Technical Analysis



SioliBros is an innovative Italian technology and research working group with a legacy dating back to 2001.

Founded by two brothers, our deep-rooted passion for computing was passed down to us by our father and has driven our professional evolution for over 25 years.
We have built our reputation on the belief that direct, hands-on experience is the most effective path to achieving excellence. Throughout our history, we have managed complex hardware networks for major training centers and developed high-level software solutions, including bespoke e-commerce platforms and web applications.
For several years, we served as IT instructors across the city of Milan. We continue to provide high-level teaching to this day, though since 2020 we have relocated our primary operations to Castiglione della Pescaia (Grosseto).

Professional Profile and Research
Our evolution into financial technology began in 2017, when we became members of SIAT (Italian Technical Analysis Society). This partnership has significantly enriched our expertise and allowed us to transition our technical background into the financial sector.
Following the emergence of generative AI models in November 2022, we immediately identified the transformative potential of AI-driven financial trading. Since then, our research has focused on bridging the gap between advanced quantitative analysis and artificial intelligence.

Quantitative Strategy & Technical Advisory
Our current practice is rooted in Technical Analysis, deciphering financial instrument performance by synthesizing market-generated data—including price action, volume, volatility, open interest, and market sentiment.
Given the multifaceted nature of the field, we focus on the optimization and validation of technical indicators. We leverage these metrics to assess the risk/reward profile of specific instruments across multiple timeframes.
Our methodology is built upon:
  • Proprietary Algorithmic Systems: A sophisticated framework executing multi-factor analysis by integrating various technical indicators simultaneously.
  • Custom Indicator Development: We engineer bespoke technical indicators tailored to the unique liquidity and volatility profiles of specific market environments.
  • Historical Data Analysis: Strategies underpinned by extensive backtesting across diverse historical datasets to ensure statistical robustness.
Key Milestones and Publications
  • SIAT Workshop & University of Perugia (2025): We were invited as keynote speakers to present our research paper, "Developing Customized Indicators for Individual Markets," which received high acclaim for its innovative approach to market-specific optimization.
  • SIAT Academy Lerici (2026): We will be presenting our latest research, "Practical Applications of AI in Trading." This work demonstrates a rigorous scientific methodology—developed and validated through ChatGPT, Gemini, and Claude—designed to consistently outperform the MSCI World Index.
Our Specializations
  • Paolo Sioli is a professional software developer with 30 years of experience across multiple programming languages. He is an expert in databases and statistics, and specializes in the development of complex custom data analysis systems.
  • Luca Sioli is a systems engineer with 30 years of experience. He supports his brother in the co-development of innovative local and remote computing systems, constantly seeking more effective and efficient computational solutions.
Contact us for further information.

 
SioliBros | Castiglione della Pescaia, 58043 Grosseto (Italy) | info@siolibros.net | VAT IT10653560960 - IT10673200969

The reports and analysis services provided by this website must not be understood as operating advice in any way for direct investment or as a solicitation to public savings deposits.
The results presented - real or simulated - do not constitute any guarantee regarding hypothetical future performances.
Siolibros assumes no responsibility for any direct or indirect damage in connection with investment decisions taken by the customer.