Silvia Trading Systems is a project founded by Antonio de Jesús Campos Rodríguez that explores how artificial intelligence and machine learning can be applied to financial markets. The main goal is to build a solid set of trading systems, predictive models, and quantitative strategies that help people make better investment decisions.
We believe that trading should be transparent and realistic. That’s why we share both successful and unsuccessful trades, along with the reasons behind each case, such as market shocks, unexpected news, or earnings surprises. Trading always carries risk and uncertainty, and understanding that is part of becoming a better investor.
Our approach is based on the idea that there isn’t a single perfect model, but an ecosystem of methods that together offer a clearer view of the market. This includes technical, fundamental, quantitative, macroeconomic, and natural language models, among others, applied across stocks, options, crypto, fixed income, and other instruments. Every system we build is part of a continuous learning process, where we keep refining and improving models to reduce error and adapt to changing conditions.
We also look to collaborate with individuals, researchers, and organizations who share an interest in applying AI and data science to finance, whether you’re developing your own model, want to use our tools, or simply want to exchange ideas.