Behind the Numbers

We're financial professionals who believe education changes everything. From market volatility to portfolio optimization, we teach the skills that matter in 2025's evolving landscape.

How We Started

Back in 2019, I was sitting in yet another corporate training session about "cutting-edge" financial modeling. The presenter was clicking through slides full of theoretical concepts that had little connection to real market conditions.

That's when Fletcher and I decided something had to change. We'd both spent years working with actual portfolio data, dealing with real client concerns, and watching how traditional education missed the mark completely.

We started zelquinavora because we wanted to teach financial analysis the way it actually works - messy data, market uncertainty, and all.

What began as weekend workshops for colleagues has grown into comprehensive programs that prepare students for the financial realities they'll face. We focus on practical application because that's what creates confident analysts.

Financial analysis workspace with charts and data

Meet Your Instructors

We're practitioners first, educators second. Both of us still work with live financial data and real client portfolios because that's what keeps our teaching relevant.

Fletcher Eriksen

Director of Financial Education

Fletcher spent eight years at ANZ working on institutional portfolio analysis before joining us. He specializes in risk modeling and has this uncanny ability to explain complex derivatives in ways that actually make sense. His students often say he makes the most intimidating concepts feel manageable.

Dmitri Kowalski

Senior Financial Analyst

Dmitri brings a unique perspective from his background in quantitative research at Macquarie. He's passionate about alternative data sources and behavioral finance patterns. When he's not teaching, he's usually diving deep into market microstructure research or mentoring junior analysts.

What We Actually Teach

Our programs go beyond textbook theory. We work with real datasets, current market conditions, and the kind of messy situations you'll encounter in professional practice.

Advanced financial modeling techniques demonstration

Advanced Modeling Techniques

We cover Monte Carlo simulations, stress testing, and scenario analysis using Python and R. Students work with actual ASX data and learn to handle the inconsistencies and gaps that exist in real datasets.

Risk Management Frameworks

Our risk modules focus on practical implementation of VaR models, credit risk assessment, and operational risk frameworks. We spend significant time on model validation and backtesting procedures.

Alternative Data Analysis

Students learn to incorporate satellite data, social sentiment, and economic indicators into traditional models. This includes working with APIs, data cleaning, and feature engineering for financial applications.

Our Teaching Philosophy

We believe the best way to learn financial analysis is by doing it. Every concept gets paired with hands-on application, and every model gets tested against real market conditions. Our students graduate knowing not just what to do, but why it works and when it doesn't.

Real Data First

We start every module with actual market data, not cleaned academic datasets. Students learn to identify and handle the inconsistencies they'll face in practice.

Build Then Break

After students build their models, we stress test them against historical crisis periods and unusual market conditions. This teaches resilience and adaptability.

Peer Review Process

Students present their work to classmates and receive feedback, mimicking the collaborative environment they'll encounter in professional settings.

Students collaborating on financial analysis projects

Ready to Learn with Us?

Our next comprehensive program begins in September 2025. We limit class sizes to ensure every student gets individual attention and meaningful feedback on their work.

Get Program Details