Zifeng Cheng Email & Phone Number

Malden, Ma, Us

美国 马萨诸塞州 波士顿

Shenzhen, China

Utilized R to clean and analyze data, covering the Federal Reserve risk index, Japan’s YCC monetary policy and China’s LPR and SLF rates, and employed linear regression and multifactor models for index forecastingCleaned bond market and macroeconomic data using Python and Excel and created data visualization dashboards Produced global risk tracking weekly reports, analyzing EPU Index, China’s macro leverage ratio, etc. and wrote currency policy and liquidity weekly reports, covering central bank operations and government debt financingResearched the impact of bilateral currency swaps, local currency settlement and bilateral trade on domestic currency liquidity, summarizing commonly-used settlement models and supporting the department’s macro-liquidity analysis Investigated China’s RMB exchange rate policy and its evolution over the past 30 years, considering the impact of the international environment and domestic policies, providing support to currency exchange rate and liquidity research

Shenzhen, China

Used SQL to extract risk indicators for the REITs market from Wind, cleaned data using Python, utilized linear regression models to predict trends in the market, and used internal BI tools to create data dashboards Conducted daily macro analysis of ETFs and REITs-related industries and hot events, visualizing findings and providing insights on industry performance and risk factors based on a multifactor model to support investment strategy adjustmentGathered recent financial data on REITs and ETFs industries from Wind and analyzed the performance of REITs and ETFs markets based on factors such as trading volume, monthly index changes, and capital flowsUtilized Python packages, like Seaborn, for visualized analysis of market trends and wrote industry analysis reports to provide data-driven support for the investment department

Shenzhen, China

Conducted fundamental research on corporate bonds and stocks of listed firms within portfolios based on internal databases and Wind, and integrated daily risk indicators to analyze the development trends and offer daily risk alertsUsed Python to extract and analyze bonds and stocks data and financial statements of relevant firms to evaluate their performance and create data dashboards, offering insights on macro conditions to support the audit departmentGathered data on financial derivatives, convertible bonds, and the bill market and assisted traders in producing PowerPoint presentations for bill market transactionsCollected information on companies in the primary market and executed 100+ primary bond subscription transactionsConducted daily market review, logical analysis, and interpretation of the secondary bond market, employed the Heng Seng system for trading, and utilized the repo spreads between interbank and exchange to achieve funds arbitrage Assisted traders in bond transactions on various platforms, like Qeubee and Ideal

Master Of Science, Quantitative Finance

Education record

学士, 商务管理