Stanley Wong

I am currently a postgraduate student, studying Masters of science in Quantitative Finance that is expected to graduate in July 2023. I am experienced in client relationship management as well as client portfolio management from my previous role in OCBC Bank in personal wealth management banking for a tenure of four years. Prior to that, I honed my negotiation, analytical and problem-solving skills from my experience in Private Equity for about a year.

Before my full-time studies for my master's degree, I was a Fintech Analyst contracted under a 6-month SG United Traineeship program at DBS Bank where I was responsible for identifying key threats and opportunities in the market relating to any latest fintech developments and monitored the development of innovation projects within the bank. 

Prior to that, I was a wealth management personal banker at OCBC Bank where I managed close to about S$5 million worth of clientele books and was involved in client portfolio structuring and advised on portfolio risk management using suitable hedging instruments. My work at both institutions allowed me to hone my analytical and problem-solving skills as well as portfolio management and client relationship management skillsets, which are crucial in the finance industry.

Prior to my tenure in OCBC Bank, my experience as an Investment Analyst at Golden Equator Capital has provided me with experience in the private equity and private debt alternative investment space, which has exposed me to deal analysis, deal-making, and contract negotiation work.

I am currently pursuing my studies in MSc. Quantitative Finance in Singapore Management University. My expected graduation is on July 2023.

In my time at Singapore Management University, I have gained practical experience in applying quantitative finance techniques to real-world scenarios. Specifically, I have undertaken relevant project work to this role, such as using cubic spline interpolator to build an Arbitrage-Free local volatility surface for derivative option pricing. Another project I have done was reconstructing our version of an All-Weather Portfolio using Machine Learning NLP Technique by analyzing historical Fed speeches to make predictions on economic regimes that will affect our portfolio of index returns. In addition to that, I have also performed cross-sectional stock analysis using PCA, VaR, and ARIMA to improve performance.

Through my coursework, I have gained technical expertise in Python Programming, R Studio, Excel, and Machine Learning methodologies.