Themes
Cyber Risk
Stochastic multi-group SIR models coupled with granular firm growth to measure the impact of cyber epidemics on firms and insurance portfolios, and major–minor mean-field games in which firms choose their cybersecurity investment against a strategic ransomware group.
\[\frac{\mathrm{d}I_{k,t}}{\mathrm{d}t}=-\gamma_{k,t}I_{k,t}+Y_t\sum_{j=k}^{K}jS_{j,t}\,b_{jk,t}\]Infected firms of size k (Scandinavian Actuarial Journal, 2026)
\[J_d(H_0,z)=\mathbb{E}^{\mathbb{Q}}\Big[U_d\Big(L^\star_T-L_T-\int_0^T\big(c_1Az_t+\tfrac{c_2}{2}(Az_t)^2+A\pi_t\big)\,\mathrm{d}t\Big)\Big]\]Defender’s objective in the major–minor mean-field game (ongoing work)
Climate Transition Risk
How a carbon price and global warming propagate to firm values, collateral, credit losses and bank equity, from closed-form credit models to agent-based economies with cascading failures.
\[\mathrm{LGD}^n_t=(1-\gamma)\,\mathbb{E}\Big[\Big(1-(1-k)\,e^{-ra}\frac{C^n_{t+a}}{\mathrm{EAD}^n_t}\Big)^{+}\,\Big|\,V^n_t\lt D^n_t,\,\mathcal{G}_t\Big]\]Loss given default with stochastic collateral (Quantitative Finance, 2025)
\[\pi^i_t=e^{-\gamma(T_t-T_0)}\nu^i_tK^i_t-(\omega^i_t+r^i_t)K^i_t-\tfrac{\chi}{2}\tfrac{(I^i_t)^2}{\bar K_{t-1}}-\big(y^i_tK^i_t-E^{i,\mathrm{target}}_t\big)\delta_t\]Firm profit under physical and transition risk (agent-based model, 2026)
Market Microstructure
Price formation and liquidity in limit order books, market making and optimal execution, and statistical and learning-based trading strategies.
\[r_t=S_t-q_t\,\gamma\,\sigma^2\,(T-t)\]Reservation price of an inventory-averse market maker
\[\lambda^{\pm}(\delta)=A\,e^{-k\,\delta}\]Execution intensity of a quote at distance δ
Ongoing work
- Real estate pricing under transition risk: a real option approachClimate Transition Risk
- A major–minor MFG with common jumps and impulse control for optimal cybersecurity investmentCyber Risk
Applied projects
- Trading algorithms on stocks and cryptocurrencies. Statistical-arbitrage strategies implemented in Python and deployed through the Interactive Brokers and Binance APIs.
- Deep and reinforcement learning for option pricing and hedging. Estimating Black–Scholes option values and hedging strategies with modern learning methods.
- Economic conditions and stock-market performance. Regression analyses linking the S&P 500 to inflation, unemployment and interest rates.
- Machine learning on DAX and EURO STOXX futures. Statistical inference and learning-based trading strategies.