At UBS, I monitor internal models for equity price and dividend risk, assessing model performance and Expected Shortfall outputs. I also recalibrate parameters for the equity price risk model and analyze the effects on Expected Shortfall and output stability.
For annual model confirmation, I contribute quantitative analysis in R and prepare methodological and control documentation. I use SQL to retrieve and process risk data for monitoring and analysis.
As a Quantitative Risk Modelling Intern at UBS, I contributed to estimating expected credit losses on loans to US-based financial advisors. I also supported work on Probability of Default and Loss Given Default components for IFRS 9 and CECL reporting. My thesis developed and backtested a volatility-forecasting strategy using HAR, EGARCH, XGBoost, and LSTM models to generate signals for Tesla options.
