Yuexuan (Yolanda) Wu graduated from UCLA in 2025 with a double major in Mathematics/Economics and Statistics and Data Science. At UCLA, she developed a strong foundation in applied mathematics, econometrics, and statistical modeling, which she applied in research studying microfinance diffusion through network theory. Her passion for solving real-world problems led her to internships in quantitative finance, where she gained hands-on experience with machine learning, alpha signal construction, and systematic strategy design. At Shepherd Ventures, Yolanda co-led the machine learning team, applying various machine learning models to improve stock selection and portfolio performance. At High Hope Wisdom Capital, she engineered alpha factors, developed backtesting frameworks, and optimized market timing strategies based on price-volume dynamics. Through the MSCF program, she aims to further deepen her expertise in quantitative methods and global financial markets. She is excited to start a career in quantitative research, quantitative trading, or portfolio management, where she can apply data-driven models and machine learning to support high-impact investment decisions.
