Quant Studio
AI-augmented quant finance consulting
research & techology
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Who I Work With
Four types of traders.
One common problem.
$1M–$50M AUM. Lean teams building systematic infrastructure. You've got strategies in backtest that haven't been stress-tested against live conditions.
- Overfitting in strategy selection
- No out-of-sample validation framework
- Backtest Sharpe vs live Sharpe diverging
- Risk decomposition missing
Discretionary or systematic. Trading BTC, ETH, alts — dealing with regime shifts, volatility clustering, and exchange-specific execution gaps.
- Backtest ignores funding rates & slippage
- Strategy breaks during regime shift
- High drawdown relative to returns
- No ML-based signal enhancement
Speed-first teams running equity, futures, or crypto. You need fast turnarounds, actionable findings, and zero fluff in the output.
- Execution gaps eating strategy edge
- High-turnover models degrading live
- No systematic risk governance
- ML models overfitting to noise
Quant-grade oversight without a full-time hire. Risk modeling, portfolio stress-testing, and AI-integrated monitoring on a fractional basis.
- No in-house quant capability
- Allocation decisions not statistically grounded
- Risk models outdated or absent
- Vendor tools lack customization
Services
Structured engagements, measurable outcomes.
Every engagement is scoped, deliverable-based, and focused on statistical robustness. Maximum 3 active clients at any time.A fast, high-impact quantitative assessment of your trading approach. I identify structural weaknesses, measure statistical robustness, and deliver a concrete optimization roadmap. Works across equities, crypto, futures, and multi-asset portfolios.
- Statistical evaluation (Sharpe, Sortino, MDD, volatility)
- Overfitting risk & curve-fitting detection
- Risk decomposition by factor and regime
- Crypto: slippage, funding rate & execution gap analysis
- ML feature enhancement suggestions
- 60-minute strategy review call
- Structured PDF report + action plan
- NDA-ready · ACH / SWIFT / USDC
Full implementation of dianostic findings. I redesign or rebuild the components of your system producing statistical drag — from feature engineering to risk architecture. Includes code delivery and performance validation framework. Crypto variant includes exchange-specific execution modeling.
- All Tier 1 deliverables included
- Feature engineering improvements
- ML model integration (XGBoost, LSTM, ensemble)
- WFO backtest validation framework
- Risk module redesign
- Code refactoring & delivery (Python)
- Performance monitoring setup
- NDA-ready · ACH / SWIFT / USDC
Fractional quant advisor for funds needing ongoing statistical oversight without a full-time hire. Monthly reviews, continuous AI research integration, and real-time regime monitoring structured around your existing operations.
- Monthly system performance review
- Performance diagnostics report
- AI / ML research integration
- Strategy refinement recommendations
- Market regime monitoring & alerts
- Priority async availability
- NDA-ready · ACH / SWIFT / USDC
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About
Claudio Catalani
Built on discipline, validated in markets.
I believe trading should be systematic, measurable, and statistically validated. Markets reward structure, not optimism. My work focuses on helping traders transform fragile strategies into robust quantitative systems that survive regime shifts and capital scaling. Before quantitative finance, I served as a Deck and Weapons Officer in the Argentine Navy — where precision, resilience, and methodical execution under pressure weren't optional. That operational foundation shapes every engagement.
Quant Stack
Technical Stack
Selected Credentials
Fintech & Quantitative Finance
Oxford: Algorithmic Trading Programme
MIT 15.455x: Mathematical Methods for Quantitative Finance
MIT 15.415.1x: Theory of Modern Finance I
MIT 15.415.2x: Theory of Modern Finance II
MIT 6.86x: Machine Learning with Python
MIT 6.431x: Probability - The Science of Data and Uncertainty
BAI003x: Reinforcement Learning
ETFM2016x: Electronic Trading in Financial Markets
CS198.1x: Bitcoin and Cryptocurrencies
Computer Science
Anthropic Academy: Al Fluency Framework & Foundations
6.00.1x: Introduction to CS and Programming (Python)
6.00.2x: Computational Thinking and Data Science
ALGS200x: Algorithmic Design and Techniques
ALGS201x: Data Structures Fundamentals
ALGS202x: Graph Algorithms
ALGS203x: Algorithms for NP-complete Problems
NET04x: Advanced Algorithmics and Graph Theory
CSE 330: Operating Systems
Contact
Start with an assessment call.
If you're serious about strengthening your trading system, book a 30-minute discovery call. We'll review your current strategy structure, risk profile, and objectives — no obligation, no sales pitch. Works for all segments: quant funds, crypto traders, prop desks, family offices.
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