Xinyang Liu

Utilized SQL databases and crontab to manage and automate the retrieval and updating of IBKR market data, ensuring data accuracy and accessibility; Enhanced the functionality and accuracy of market scanners, enabling more effective identification of trading opportunities and faster market analysis Designed and developed the infrastructure for backtesting, including creating and implementing key indicators such as VWAP and MACD to support quantitative strategy evaluation Leveraged multithreading and multiprocessing techniques to run simultaneous backtests across a wide universe of stocks, significantly enhancing processing efficiency

• Performed equity research through different projects and better understood the investment in preferred stock and bond through the analysis and calculation on different stocks’ expected return; • Completed the initial reports through analyzing the stocks from different prospects and conducting industry research and finalized the reports into decks and presented to other teams; • Cleaned and processes the datasets collected and performed different evaluation calculation using Excel; • Conducted some translation work by translating the reports and materials into Chinese;

• Performed various data cleaning tasks including missing value imputation, outlier identification, variable normalization and standardization to get the raw data ready for further analysis • Build visualizations in Tableau to visualize the historical trend for selected stocks, conducted comparison analysis to identify the commonalities and differences regarding the fluctuation ranges and its correlation with external shocks • Fit machine learning models on training data to identify the key influencing factors in stock price, evaluated models’ out-of-sample performance based on their prediction accuracy on the test data • Leveraged Natural Language Processing techniques to examine the sentiments of stock investors’ comments and posts across social platforms and forums, extracted underlying polarities and predicted future stock price with investors’ sentiments as a key indicator of the stock market