Mathematics · Quantitative Finance
Laurin
Rodacker
Mathematics student at Leibniz University Hannover with a focus on PDEs and quantitative finance. I build derivatives pricing engines, calibrate yield curve models, and implement vol surface interpolation from real market data — from first principles.
∂V/∂t + ½σ²S²∂²V/∂S² + rS∂V/∂S − rV = 0
dS = μS dt + √v · S dW₁
dv = κ(θ − v) dt + ξ√v dW₂
r(τ) = β₀ + β₁·(1−e^(−τ/λ))/(τ/λ)
+ β₂·((1−e^(−τ/λ))/(τ/λ) − e^(−τ/λ))
01 — About
Rigorous mathematics,
real market data
I'm a mathematics student at Leibniz University Hannover specialising in partial differential equations and numerical analysis. My coursework in PDEs and functional analysis directly informs how I approach derivatives pricing and calibration problems.
Outside lectures, I build quantitative tools from scratch — pricing engines in Python with no black-box dependencies, yield curve models calibrated on real Bundesbank data, and vol surface interpolation using the AAA algorithm on live SPX options. I also work as a teaching assistant at the Institute of Applied Mathematics, developing problem sets and running exercise sessions.
Currently finishing my BSc, targeting a Master's in Mathematical Finance.
02 — Projects
Selected
Work
Derivatives Pricing
Options Pricing Engine↗
Analytical and semi-analytical pricing for European vanilla and barrier options. Implements Black-Scholes with full Greeks, implied volatility inversion, and Heston stochastic volatility — every formula derived from first principles, no black-box libraries.
Fixed Income
Yield Curve Fitting↗
Calibration of Nelson-Siegel (1987) and Svensson (1994) yield curve models on real Bundesbank spot rate data. Pure SciPy/NumPy — no QuantLib, no sklearn. Full parameter uncertainty analysis included.
Volatility Modelling
Vol Surface Interpolation↗
Interpolation of implied volatility surfaces from real SPX options data using the AAA algorithm (Adaptive Antoulas-Anderson). Includes no-arbitrage verification via calendar spread and butterfly spread checks.
03 — Experience
Academic &
Professional
Teaching Assistant
Leibniz University Hannover · Institute of Applied Mathematics
Assisting in undergraduate analysis courses, grading assignments and correcting exams. Tutoring and grading for economics students.
Research Intern
Zuse Institute Berlin (ZIB)
Independent research on adaptive sampling strategies for AAA rational approximation of expensive black-box functions, with applications to electromagnetic transmission (Maxwell equations, JCMwave) and implied volatility surfaces (Heston, SABR).
Student Assistant
Leibniz University Hannover · Institute of Applied Mathematics
Creation of mathematical problems and competition materials for workshops and student internships.
BSc Mathematics
Leibniz University Hannover
Specialisation in partial differential equations and numerical analysis. Core coursework: Functional Analysis, Numerical Methods for PDEs, Financial Mathematics, Stochastics.
Research Intern
Leibniz University Hannover · foeXlab, Institute for Solid State Physics, Institute for Microelectronic Systems
Experimental physics and quantitative data analysis. Laboratory work with measurement systems and statistical evaluation of experimental results.
04 — Skills
Technical
Stack
Mathematics
- Partial Differential Equations
- Stochastic Calculus
- Numerical Analysis
- Functional Analysis
- Measure Theory
Programming
- Python
- MATLAB
- LaTeX
- NumPy / SciPy / Pandas
- Matplotlib / Plotly
- Git / GitHub
Quantitative Finance
- Derivatives Pricing
- Vol Surface Calibration
- Yield Curve Modelling
- Greeks & Risk Metrics
- Backtesting Frameworks
- QuantLib / Bloomberg
05 — Contact