Jiaming Lyu Email & Phone Number

New York, NY, US

Shanghai, China

• Developed ARIMA, DeepAR, and TFT models in Python to forecast Chinese Treasury Bonds and China Development Bank Bonds YTM data, attaining RMSE of 0.0104 for 1-day and 0.0416 for 5-day forecasts over 3-year period
• Enhanced securities firms’ decision-making process in trading, stress testing, and financial planning by transitioning from CNN-based models, which provided only directional predictions, to new models that predict.
• Synthesized models’ performance with detailed documentation including data leakage prevention, validation tests, and parameter stability test results; incorporated findings into a comprehensive client presentation
• Elevated model performance with automated hyperparameter tuning and model training, improving RMSE by 6.9% for 1-day and 5.3% for 5-day forecasts with 85 features including yields, yield differences, and volatilities

Rochester, New York, United States

Rochester, New York, United States

Shanghai, China

• Conducted comprehensive historical analysis utilizing financial ratio and corporate finance analysis for a company preparing for IPO
• Examined 10+ share transfers and equity transactions, including financial performance, market trends, and valuation metrics
• Contributed to proofreading and reviewing IPO application forms of 5+ companies, ensuring accuracy and compliance with regulations
• Derived insights on 3+ case inquiries, advising on the swifter options of reverse takeovers or backdoor listings versus traditional IPOs

Beijing, China

• Validated a multimillion-row dataset by collaborating with Bank of China that achieved 95% data accuracy
• Implemented 370+ Gbase SQL rules, reducing error rate from 8% to 2%, optimizing error visualization and data extraction
• Streamlined data management by automating validation, efficiently identifying and rectifying non-compliant accounts and forms

Rochester, New York, United States

Shanghai, China

• Contributed to compiling financial industry recap and collaborated on the completion of 5+ comprehensive industry analysis reports
• Developed and managed multiple hedging portfolios comprising stock index futures, specifically the CSI 300 Index and SSE 50 index
• Utilized 500+ historical data entries and strategies, involving long and short positions in stock index futures based on discount rates
• Utilized pandas for 2018-2022 historical stock prices, employing high-frequency strategies, achieving an 8.7% annualized return

Master Of Science - Ms, Financial Economics

Bachelor'S Degree, Applied Mathematics And Economics