Chenxi Yu

Operational Risk & RCSA

• Conducted interactive sessions on Risk Control Self-Assessment (RCSA) that helped students analyze key risk indicators (KRIs), assess risks, and implement appropriate control measures to enhance governance.
• Encouraged group learning on operational risk failures by examining specific case studies, such as technology failures, process breakdowns, and human error incidents. This collaboration allowed students to brainstorm strategies to minimize these risks, culminating in team presentations of their proposed solutions.

Market Risk

• Lectured on Value at Risk (VaR) models: Historical Simulation, Monte Carlo Simulation, and Parametric (Variance-Covariance) VaR; students were equipped to apply these models and interpret Basel III requirements.
• Conducted projects with teams related to market risk modeling using Python and Excel, where students performed portfolio risk assessments, stress testing, and scenario analysis to quantify exposure to interest rate changes, credit spread fluctuations, and equity price volatility.

• Extracted and examined trading data based on equities, commodities, and derivatives to study price volatility, turnover rates, and position changes of CTA and alpha funds, to find arbitrage strategies and enhance investment strategies, leading to portfolio efficiency and risk-adjusted return improvement.

• Researched macro trends, assessing global recovery, U.S. inflation expectations, and China’s economic restructuring to promote insights on commodity price action and asset allocation, which led to better investment performance.

• Performed due diligence on target investments by examining financial health, management background, and market positioning to inform higher-quality investment decisions, resulting in a more robust portfolio.

• Achieved higher accuracy standards in investment strategy and a 7% increase in client returns within my teams across firms through compiling financial reports on market observations, macroeconomic analysis, risk assessments, and fund behavior studies.

• Recognized and mitigated significant operational risks with optimization solutions that decreased high-risk incidents by 15% and significantly supplemented compliance efficiency. Carried out risk assessments to create control measures to enhance the security and consistency of business processes.

• Leveraged SQL to analyze transactional and market data to uncover business insights on aspects such as default, market volatility, and cyber threat risks, enabling the team to prioritize and bolster operational resilience against them by focusing on critical risk points.

• Developed credit default score models based on random forests, which improved the accuracy, speed, and quality of credit risk assessments by 30%.

• Improved cybersecurity of securities platform by refactoring the platform code base to make it less vulnerable and implementing firewalls and CAPTCHA to protect customers from cyberattacks when transacting financial transactions.