Daniel
premium
London School of Economics and Political Science, University of London
Economics
Graduate
37About Me
Passionate professional with mathematical finance and everything utilising mathematics. I hold a CQF with Distinction, an MSc in Economics from LSE, and currently work in applied financial engineering advisory, where I benchmark and validate exotic derivatives pricing models daily — from Bermudan options and callable bonds to inflation-linked swaps and Monte Carlo simulations.
My work sits at the intersection of quantitative theory and real-world application: building independent pricing models, calibrating volatility surfaces, computing CVA/DVA adjustments, and stress-testing credit risk frameworks. I also code actively in Python, C++, and VBA, and pursue personal research in stochastic expansion methods for exotic option pricing.
In my courses, I bring this practitioner perspective directly into the classroom. If you want to understand not just the textbook formulas but how derivatives are actually priced, validated and risk-managed in industry, you’re in the right place.
My teaching style
My teaching style is detail-oriented and deeply grounded in practical illustration. I don’t gloss over the mechanics — every concept is broken down step by step, with full quantitative modelling drafts worked through in real time so you can see exactly how theory translates into a working model.
Expect spreadsheets, Python snippets, and handwritten derivations everywhere. When we cover Black-Scholes, you won’t just memorise the formula — you’ll watch me build it from the stochastic differential equation, calibrate it to market data, and stress-test where it breaks. When we price a Bermudan option, you’ll see the lattice tree sketched out node by node before we ever touch code.
I teach through examples first, abstraction second. Real trade structures, actual Bloomberg data, and industry valuation challenges form the backbone of every session. Questions are encouraged at every step — if a Greek or a curve construction feels unclear, we stop and model it together until it clicks.
If you learn best by watching ideas take shape on paper and screen rather than reading polished slides, you’ll feel at home here.
My Proudest Achievements
Achieved 4.0/4.0 in highly quantitative mathematical Year 3 course during my exchange semester in University of Glasgow.
I teach
- Accounting and Finance
- Quantitative Methods
- Maths
- Further Maths
- Statistics
- Public Speaking
- Mandarin
- Economics
- C++
- Coding
- Microsoft Office
- STATA
- SQL
- Power BI
- Python
- Programming
- Accounting
- Chartered Accounting
- Actuarial and Management Science
- Algorithmic Trading
- Chinese
- Consultancy
- Econometrics
- Cryptocurrency
- Essays
- Macroeconomics
- Machine Learning
- Mathematics
- Microeconomics
- Personal Statement
- Study Skills
- Oxbridge Application
- Finance
- Running
- Exercise and Fitness
- Piano
- Career Development
My Results and Achievements
- CQF with Mathematical Finance (83%)
- CQF with Financial Engineering Project (93%)
- Top 5% in International Economics (UG)
- 95% in Mathematical Economics (UG)
- 76% in Monetary Economics (UG)
- 83% in Intermediate Microeconomics (UG)
- GPA 4/4 in Intermediate Macroeconomics
- 81% in Econometrics and Time Series