Economics PhD | Crypto Volatility · Quant Risk
PhD in Economics from University of Bath, specialising in time-series econometrics and financial market microstructure. My research applies volatility modelling and regime-switching methods to crypto markets — directly transferable to systematic trading and risk management.
📍 UK (PSW eligible) | Open to London / Remote
| Repo | Description |
|---|---|
| bitcoin-var-determinants | VAR for Bitcoin price determinants — Granger causality, IRF & historical decomposition |
| bitcoin-inflation-mfvar | Mixed-frequency VAR linking daily Bitcoin returns to monthly CPI across US, Korea & Japan |
| bitcoin-regime-switching | Markov-switching VAR with EM estimation & bootstrap IRFs for regime detection |
Originally developed across Stata, EViews, and R — redesigned and unified in Python.
Quantitative Methods: GARCH / EGARCH / DCC · VAR / SVAR / Markov-switching · VaR · Monte Carlo simulation
Python Stack: pandas · numpy · scipy · statsmodels · matplotlib
🎓 PhD Economics — University of Bath (2021–2025, thesis submitted)
📚 MSc Applied Economics — University of Bath (Banking & Financial Markets)


