tianli

Tian Li is a professional with a strong background in quantitative skills, market risk understanding, and experience in buy/sell side and exchange. With proficiency in Python for data analysis and risk/trading modeling, Tian is currently a Derivative Risk Analyst at FORIS Limited (CRYPTO.COM), where they have implemented margin model parameter calibration and VaR back-testing under smart cross margin structure for spot instruments and perpetual contracts.

Tian has also designed, documented, and performed new instruments listing process, periodic risk parameters review, and regular risk parameters monitoring with interactions on flask UI. They have collaborated with data engineers to define data requirements, design table schema, and provide sample scripts to help set up regular airflow jobs.

Prior to this, Tian was a Quant Analyst at Alpha Sherpa Capital Limited, where they analyzed and back-tested a trader's trading strategy to optimize on position sizing, stop-loss limit, holding period, timing for partially close, and big loss controlling. They also built trading signal schema as standard codes and factorized related information from disordered data and performed data cleaning, descriptive analysis, and visualization on past P&L.

Tian's expertise also extends to risk consulting, having worked at Ernst & Young Advisory Service Limited as a Risk Consultant. They reviewed relevant risk policies and procedures for five major banks to assess compliance with HKMA's Supervisory Policy Manual (SPM) requirements.

Tian is a Certified FRM and holds a Master of Science in Quantitative Finance from Fordham University, as well as a Bachelor of Science in Actuarial Science and Statistics from Purdue University. They have a passion for trading, macroeconomics, crypto market, and blockchain technology applications like Defi and NFTs.