Jianglin Feng
Applied Mathematics & Statistics | Stony Brook University
- Role
- Quantitative Research Intern at 国元证券股份有限公司
- Location
- Stony Brook, NY, US
- LinkedIn followers
- 500 followers
About Jianglin Feng
I am an international student double majoring in Applied Mathematics and Business Management. I am open to any networking or internship opportunities. Please feel free to connect with me and I can also be reached through email at f••••••••@gmail.com.
Experience
Quantitative Research Intern
Jun 2025 — Present · Hefei, CN
Analyzed the linkage between margin-financing balances and China A-share constituents’ indexes. Constructed two categories of base factors—one for margin-financing exposure and one for large/small order money flows—and combined them into composite signals. One composite factor achieved an average IC of –0.060 (IR –0.842), while another reached an IC mean of 0.057 (IR 0.803)- Examined the relationship between the 5-day candlestick upper-shadow ratio, 20-day uptrend momentum, and 20-day volume amplification factors across China’s Sci-Tech Innovation Board and micro-cap A-share stocks. Leveraged these insights to refine the composite “pullback-warning” factor, which achieved an average IC of 0.07 and an IR of 0.51- Designed a multi-layer LSTM model incorporating residual connections, batch normalization, and dropout regularization to integrate 89 alpha factors into a unified stock predictive signal. Employed overlapping 30-day lookback windows to forecast 10-day forward returns using a rolling validation approach with 2-year training periods and 1-year out-of-sample testing- Developed an optimized Random Forest model to merge 94 alpha factors into a single predictive signal for stock return forecasting. Preprocessed factors through industry and market-cap neutralization, cross-sectional z-score normalization, and missing-value imputation to ensure training stability. Applied strict chronological data splitting with 70/30 train-test ratio and temporal validation, achieving robust out-of-sample performance (IC mean = 0.101, IR = 1.107) for portfolio management applications.
Education
Stony Brook University
Bachelor's degree, Applied Mathematics & Statistics
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