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Achievement: Pull Shark

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Achievement: Pull Shark

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sefaav/README.md

Sefa Avci

Computer Science student at EPFL focused on quantitative research, machine learning, and statistics.

Featured work

  • QuantLab — Reproducible quantitative research and backtesting platform with walk-forward validation, robustness testing, realistic transaction costs, and automated research reporting.

  • Quant Research Notebooks — Reproducible empirical research in quantitative finance. The first study tests whether ADF stationarity filtering improves pairs-trading performance out of sample across 92 ETF pairs and 34 walk-forward folds.

Interests

Quantitative Research · Statistical Learning · Systematic Investing · Time Series Analysis · Portfolio Construction · Machine Learning

Portfolio · LinkedIn

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  1. quant-research-notebooks quant-research-notebooks Public

    Reproducible empirical research notes built on QuantLab, starting with a walk-forward study of ADF stationarity filtering in pairs trading.

    Jupyter Notebook

  2. QuantLab QuantLab Public

    Reproducible quantitative research and backtesting platform with walk-forward validation, robustness testing, realistic costs, and automated research reporting.

    Python

  3. website website Public

    Personal portfolio — projects in quantitative research, machine learning, and computer science.

    HTML