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FlorentYigbe/README.md

Hi, I'm Florent !

Business Mathematics student at the University of Mannheim focused on developing skills in quantitative finance through hands-on projects. I built Quantitative-Portfolio-Optimizer, a python-based multi-asset portfolio optimization engine spanning equities, fixed income, and commodities, an European call option pricing model via Monte Carlo simulations validated against Black-Scholes and VaR-CVaR-Simulator, a risk simulation tool for portfolio tail-risk analysis.

Open to summer internships in:

  • Structuring
  • Trading
  • Traditional Asset Management
  • Fundamental and Quantitative Asset Management

⚡ Fun fact: I'm just as passionate about literature as I'm about quantitative finance !

📫 Reach me: yigbekofi@gmail.com | LinkedIn


🛠️ Tech Stack

Python Jupyter Pandas NumPy Spicy Matplotlib Seaborn

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  1. Quantitative-Portfolio-Optimizer Quantitative-Portfolio-Optimizer Public

    A quantitative portfolio optimizer built in Python, applied to a diversified universe of 29 global assets spanning European equities, international equities, fixed income, and alternative assets.

    Jupyter Notebook 1

  2. VaR-CVaR-Simulator VaR-CVaR-Simulator Public

    Monte Carlo simulation estimating a portfolio's Value at Risk and Conditional Value at Risk at 95% confidence.

    Python 1

  3. European-Call-Option-Pricing European-Call-Option-Pricing Public

    Prices an European call option using Monte Carlo simulation, validated against the Black-Scholes closed-form formula.

    Python 1

  4. Pi-Estimator Pi-Estimator Public

    Estimates the value of π using Monte Carlo simulation and random point sampling in a unit circle.

    Python