Marco Corpa Criado

Quantitative Finance & Data Science

Math & Stats graduate building systematic strategies at the intersection of statistics, machine learning, and financial markets.

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About Me

I'm a Mathematics & Statistics graduate from Universidad Complutense de Madrid, currently completing a Master's in Quantitative Finance (MIAX). I'm ambitious, driven by a genuine hunger to keep learning, and I thrive when tackling complex, unfamiliar problems — whether that means building a regularization model from scratch or designing a portfolio optimization algorithm. I combine strong analytical rigour with a collaborative mindset, and I'm currently working toward CFA Level I (November 2026) as I pursue a long-term career as a Quantitative Portfolio Manager.

Languages

Spanish — NativeEnglish — Advanced

Education

B.Sc. in Mathematics & Statistics

Universidad Complutense de Madrid (UCM)

2021 – 2025

Rigorous training in probability, statistical inference, stochastic processes, and mathematical optimization.

MIAX — Master's in Quantitative Finance

In Progress

Instituto BME

2025 – Present

Advanced quantitative methods applied to derivatives pricing, portfolio management, algorithmic trading, and financial risk.

CFA Level I Candidate

In Progress

CFA Institute

Exam: November 2026

Skills

Programming Languages

PythonRSQL

Python Libraries & Frameworks

pandasNumPypolarsscikit-learnXGBooststatsmodelsmatplotlibseaborn

Quantitative Finance

Portfolio OptimizationFactor ModelsRisk ManagementDerivativesBacktestingAlgorithmic TradingTime Series Analysis

Mathematics & Statistics

Regression & RegularizationStochastic ProcessesStatistical InferenceLinear AlgebraOptimization

Tools

GitGitHubLaTeXExcelJupyter

Projects

LASSO Regularization — Undergraduate Thesis

Final degree dissertation implementing LASSO (Least Absolute Shrinkage and Selection Operator) for variable selection and regularization. Applied to real datasets to study sparsity, bias-variance tradeoff, and predictive performance vs. OLS.

Pythonscikit-learnNumPyLaTeX

View on GitHub

Housing Price Forecasting with ARIMA/SARIMA

Time series analysis and forecasting of residential property prices using ARIMA and SARIMA models. Focused on seasonality decomposition, stationarity testing (ADF), and model selection via AIC/BIC.

Pythonstatsmodelspandasmatplotlib

View on GitHub

Markowitz Portfolio Optimization

Implementation of Modern Portfolio Theory to construct the efficient frontier, identify the minimum-variance portfolio and the tangency portfolio. Includes Sharpe ratio maximization under different constraint regimes.

PythonNumPypandasmatplotlib

View on GitHub

Algorithmic Trading & Backtesting

Design and backtesting of systematic investment strategies. Includes signal generation, transaction cost modeling, and performance evaluation through metrics such as Sharpe ratio, max drawdown, and CAGR.

Pythonpandasbacktesting

View on GitHub

Machine Learning Preprocessing Pipeline

End-to-end preprocessing and feature engineering pipeline for structured financial and tabular data. Covers missing data imputation, encoding, scaling, outlier detection, and feature selection.

Pythonpandaspolarsscikit-learnXGBoost

View on GitHub

Experience

Personal Algorithmic Trading Research

Ongoing

2024 — Present

Independently developing and testing systematic investment algorithms applied to my own portfolio — covering signal generation, position sizing, and performance evaluation. This is an ongoing research and learning exercise focused on building practical intuition for systematic strategies.

Open to Opportunities

Actively seeking my first professional role in quantitative finance, risk, or data-driven investment research. Open to collaborations, internships, and junior quant roles.

Want to know more?

Download my full CV or get in touch directly.

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Get in Touch

Feel free to reach out for opportunities or collaborations.

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