To me, quantitative finance is not only about finding signals, but also about understanding which signals can survive noise, risk, and changing market conditions. I am interested in quantitative research, especially systematic investment strategies. My mathematics and economics background has trained me to approach financial problems with both theoretical rigor and empirical discipline. It also helps me analyze noisy market behavior and translate empirical patterns into disciplined investment decisions. During my quantitative research internship, I implemented portfolio optimization models, tested multifactor stock-selection signals, and built backtests that incorporated hedging and risk constraints. Beyond traditional quant research, my experience in analyzing blockchain transaction data gave me exposure to a different perspective on market structure. While working with decentralized Web3 transaction data, I used Python and SQL to clean high-dimensional financial data. I also learned how difficult it can be to build reliable models for identifying abnormal transaction patterns.Outside of finance, poker has sharpened my interest in probability and decision-making under uncertainty. Please feel free to connect if my background aligns with your team鈥檚 work in quantitative research, systematic strategies, or portfolio analytics. 听
