Quant foundations
Probability, statistics, and time-series thinking applied to real-world market data sets, with an emphasis on robustness over cleverness.
Training for the next generation of quantitative & AI-literate investors.
ABX Capital Partners Academy is an educational initiative focused on the way markets really behave: noisy, adaptive, and shaped by data, code, and human judgment.
What the Academy focuses on
Instead of shortcuts and slogans, the Academy emphasizes core skills: statistical reasoning, systematic research, risk thinking, and practical literacy in AI tools used around modern markets.
AI in market workflows
How machine learning and language models can support research, monitoring, and documentation without replacing human responsibility.
Risk & decision-making
Frameworks for sizing, scenario analysis, and uncertainty—borrowing ideas from option theory, behavioral finance, and practical trading experience.
Built alongside active market practitioners.
The Academy draws on the same mindset that informs ABX Capital Partners Asset Management: a focus on process, documentation, and repeatable research habits rather than predictions or hype.
Case studies are grounded in historical data, public filings, and transparent assumptions. Participants are encouraged to question every step of the reasoning, including model choice, data quality, and implementation details.
Three pillars of the Academy
Every track, workshop, and project is designed around three simple pillars: clarity of thought, responsible use of tools, and respect for uncertainty.
Clarity
Making assumptions explicit, labeling speculation, and separating signal from story.
Responsibility
Understanding limits of data, models, and AI systems before making real-world decisions.
Resilience
Designing strategies, workflows, and careers that can survive error, noise, and surprise.
Curriculum, research, and mentorship in one place.
The Academy connects structured learning paths, small group mentorship, and ongoing research notes into a single learning environment.