Chin Huang
About Chin Huang
Chin Huang serves as the Head of Marketing at Quantitative Brokers, where he has worked since 2023. He holds a Bachelor of Business Administration from National Taiwan University and a Master's degree in Integrated Marketing Communication from Emerson College, and has extensive experience in marketing and research related to financial markets.
Work at Quantitative Brokers
Chin Huang currently serves as the Head of Marketing at Quantitative Brokers, a position he has held since 2023. In this role, he oversees marketing strategies and initiatives aimed at enhancing the company's market presence. Prior to this, he worked as a Marketing Specialist at the same firm from 2020 to 2023, where he contributed to various marketing projects and campaigns. His experience at Quantitative Brokers has allowed him to develop a deep understanding of the financial technology landscape.
Education and Expertise
Chin Huang has a diverse educational background. He earned a Bachelor of Business Administration in Financial Accounting from National Taiwan University, completing his studies from 2011 to 2015. He furthered his education with a Master of Arts in Integrated Marketing Communication from Emerson College, which he attended from 2017 to 2019. Additionally, he participated in a Summer Program in International Business at the University of California, Berkeley, from 2013 for 11 months. His academic training equips him with a strong foundation in both marketing and finance.
Background
Chin Huang began his professional career as a Staff Auditor at Deloitte in Taiwan, where he worked for eight months from 2015 to 2016. He then transitioned to marketing roles, starting with a Digital Marketing Internship at East Coast Realty in 2019, followed by a Marketing and Sales Internship at Viewpoint Creative in the Greater Boston Area for two months in 2018. His varied experiences in both auditing and marketing have shaped his approach to his current role.
Research and Publications
Chin Huang has engaged in extensive research related to market microstructure and liquidity. He has explored the use of reinforcement learning for trade execution and has written about the liquidity of futures and the impact of market events. His publications include discussions on the microstructure changes in various futures markets, the impact of AI on cash treasury trading, and insights on liquidity during market crises. His analytical work also covers the effects of block trades on futures markets and changes in quote size.