Theoretical
Adv. Stochastic Calculus
- Malliavin Calculus & Greeks
- Lévy Processes & Jumps
- Girsanov & Measure Change
- Stochastic Volatility (Heston)
Financial Econometrics
- State-Space Models (Kalman)
- Cointegration & VECM
- GARCH & Realized Volatility
- GMM & MLE Inference
Computational Methods
- PDE Solvers (ADI, Crank-Nicolson)
- Quasi-Monte Carlo (Sobol)
- FFT Pricing (Carr-Madan)
- Calibration & Regularization
Convex Optimization
- Conic Programming (SOCP/SDP)
- Interior-Point Methods
- Robust Optimization
- Dynamic Programming (HJB)
Quant Asset Pricing
- Term Structure (HJM, LMM)
- Credit Risk Models (Merton/CDS)
- Market Microstructure (Hawkes)
- Exotics & Incomplete Markets
Applied
Machine Learning
- Deep Learning (Transformers, CNN)
- Ensemble (LightGBM, XGBoost)
- Elastic Net Regularization
- Reinforcement Learning (RL)
NLP for Finance
- Sentiment & Topic Modeling (BERT)
- Knowledge Graphs & NER
- 10-K/Q & Earnings Calls Analysis
- Audio Emotion Analysis
Algorithmic Trading
- Stat Arb & Mean Reversion
- Order Flow & Bid-Ask Spreads
- Signals (RSI, Amihud, Lottery)
- Backtesting & Slippage Models
Statistical Methods
- Survival Analysis (Kaplan-Meier)
- Cox Proportional Hazards
- Geopolitical Risk Indexing
- Causal Inference & Event Studies
Computational Stack
- C++, Python, R, SQL
- AWS Spark & Data Pipelines
- Bloomberg, LSEG, WRDS
- Tableau & Shiny Dashboards