- Advanced Predictive Modeling: Developed robust models for forecasting USD/JPY and USD/CNH exchange rates using ARIMA, ARIMA-GARCH, ARIMAX, and advanced machine learning algorithms (e.g., LSTM, Gradient Boosting). Integrated exogenous factors such as macroeconomic indicators and sentiment analysis to enhance predictive accuracy.- Rigorous Model Validation: Conducted extensive back-testing with cross-validation techniques and statistical metrics to evaluate and select the optimal forecasting models, ensuring precision and reliability.- In-Depth Forecasting & Analysis: Generated detailed exchange rate forecasts with uncertainty quantification, producing comprehensive reports that analyzed trends, identified market opportunities, and mitigated risks.- Client Reporting & Insights: Delivered tailored investment insights by translating complex quantitative findings into actionable strategies. Used visualization tools (e.g., Matplotlib, Power BI) to present data clearly, enhancing client understanding and decision-making.

- Analyzed and adjusted monthly Abbott customer account reports, evaluating the effects of implemented price increases on key metrics- Applied Python and statistical expertise to establish optimal pricing structures for various tiers of Abbott products, enhancing revenue potential- Leveraged Python proficiency to efficiently manage, update, and renew prices within extensive datasets comprising over 300,000 records- Utilized Python to systematically track price fluctuations across APAC countries, conducting in-depth analyses to quantify the resultant impact on revenue

- Replicated AlphaNet, a quantitative trading model based on Convolutional Neural Networks (CNNs) originally proposed and developed by Huatai Securites- Trained the model with downloaded datasets containing stock data metrics such as variance, z-score, covariance, and more for 100 stocks over the past 30 days from open sources online- Employed the model to forecast the returns of these stocks over the subsequent 10-day period, with the aim of achieving a 5% - 10% rate of return

I organized tutorial sessions for ARSC 2022.