Fund investment involves certain risks. In accordance with the “Securities Investment Fund Law of the People's Republic of China”, the “Interim Measures for the Supervision and Administration of Private Investment Funds (Draft for Comments)”, and other relevant laws and regulations, please confirm that you or the institution you represent is a "Qualified Investor" before continuing to browse this material.
A "Qualified Investor" refers to an investor who meets the eligibility requirements for investing in private securities investment funds under the applicable securities and investment regulations of any country or region. This includes institutions with net asset of not less than RMB 10 million, or individuals with financial assets of not less than RMB 3 million, or an average annual income of not less than RMB 500,000 over the past three years.
Jiantao Cheng, CEO & CIO
He holds a Master’degree in Computational Mathematics and a Ph.D. in Applied Mathematics from Peking University, and has 17 years of experience in asset management.
2008-2013:
Served in the Asset Management Department of Industrial and Commercial Bank of China(ICBC) Head Office,focusing on the research and development of quantitative investment models and quantitative equity investment management. As one of the earliest core members of ICBC's independent quantitative investment team, he contributed to building the bank's proprietary quantitative investment platform and developing a series of quantitative investment models.
2013-2015:
Served as Partner and Quantitative Investment Director at a large private fund management company in Shenzhen, responsible for research and development of quantitative strategies and overall investment management.
Xiaozhou Yang, Research Director
He holds a Bachelor's degree in Applied Mathematics and Master's degree in Electronic Information Science and Technology from Peking University,as well as a Master of Finance from The University of Hong Kong.
2015:
Worked in quantitative trading at Credit Suisse, where he was responsible for developing and validating stock alpha strategies, stock arbitrage strategies, and stock index futures strategies.
2016:
Served as a quantitative analyst at Well Bright International Investment Co., Ltd. in Hong Kong, responsible for maintaining and enhancing US equity quantitative models, and developing alpha strategies for Hong Kong equities and A-shares.
Fangze Tian, Quantitative Investment Manager
He holds Bachelor's degree in Mathematics and Applied Mathematics and a Master's degree in Applied Statistics from Tsinghua University. He is also a gold medalist of the 28th China Mathematics Olympiad.
He previously worked at a large state-owned enterprise, where he was responsible for developing spot trading strategies and conducting business review analyses. He has research experience in the application of machine learning and deep learning models.
Gang Li, Quantitative Investment Manager
He is a CFA charter holder and holds a Bachelor's degree in Statistics from Renmin University of China, and a Ph.D. from the Rotman School of Management, University of Toronto.
He previously worked at a macro hedge fund in New York, where he was engaged in the research and development of quantitative investment strategies, including factor-based strategies, event-driven strategies and other systematic approches. He has extensive expertise in diversified portfolio trading models.
Guanxing Li, Quantitative Investment Manager
He holds a Bachelor's degree in Software Engineering from Sun Yat-sen University and previously served as a Research Assistant at the School of Computer Science at The University of Hong Kong.
2012-2014:
Worked in the Information Technology Department of China Merchants Bank, focusing on system research and development, with in-depth experience in system robustness and real-time performance.
2014-2015:
Served as a Research Assistant at the School of Computer Science at The University of Hong Kong, conducting research on cutting-edge technologies including machine learning and artificial intelligence.