I'm dev-belly, a Data Science & Big Data Technology student at Central University of Finance and Economics. I build tools for credit risk, financial data and quantitative research.
把金融问题拆成能运行、能检验、能追溯的系统。最近在做：决策时点的数据、跨期信贷评估，以及组合尾部风险。
01 · CreditVintage — A credit score is only useful if its data and evaluation hold up.
训练、校准、测试分期隔离；标签等待完整表现期；同时展示原始与校准后的结果。新增 PITBridge 联合案例，从预测追到特征值、源记录、修订版本和可用时间。
Source · Risk report · Source → prediction · Score monitor
02 · PITBridge — Reconstruct what a decision could actually know.
同时考虑事件、发布、入库时间与历史修订；构造决策时点快照和 7/30 天滚动特征。每个聚合值都有源记录成员，SQLite 结果与独立 Python 实现逐项核对。
Source · Snapshot counterexample · Rolling features · Walkthrough
03 · StressAtlas — A tail estimate should come with its uncertainty.
用借款人层面的相关违约路径比较基准与压力情景；计算离散尾部 ES 和行业贡献；再用 300 次成对重采样检查 20,000 条路径下的估计精度。
Source · Stress report · Tail precision · Walkthrough
Public financial examples use synthetic data. They demonstrate the code and methodology; they do not establish live investment performance or real borrower risk.
| Shipped | Inspect the work |
|---|---|
| 2026-10 · Sources meet the model | CreditVintage × PITBridge: checked feature contracts, original event records, end-to-end replay and a browser explorer. |
| 2026-10 · Revision-safe cash-flow windows | PITBridge rolling features: select eligible revisions before aggregation; preserve every contributing record. |
| 2026-10 · Precision of portfolio tails | StressAtlas paired bootstrap: resample complete simulation paths together; recompute absolute and incremental VaR/ES. |
| Project | The engineering question |
|---|---|
| AlphaForge | Do factor signals survive walk-forward validation, portfolio constraints and costs? Computed run ↗ |
| TradeForge | Can C++ execution events agree with an independent Python reference? 60-second tour ↗ |
| AuditLens | Can an anomaly become an explainable review item? Workpapers ↗ |
| ControlTrace | Can an IT control finding be traced to the original evidence? Case study ↗ |
| LedgerX | Can trading fills, accounting and portfolio marks reconcile exactly? Valuation example ↗ |
Experiments & earlier work
| Experiment | What it explores |
|---|---|
| Investor Network GNN | Graph ablations and three-seed saved predictions. |
| High-dimensional Causal Allocation Lab | Simulated causal estimation and robust allocation; interactive example. |
| Interval Financial Risk | A retained negative result: distributional features reduced AUC in this synthetic experiment. |
| FactorLab | A-share factor evaluation and purged validation; 中文文档. |
| WeCom Agent Platform | Document retrieval and query workflows. |
| Personal AI Chat | Local chat plus a separately configured private model connection. |
Earlier builds: Digital Craftsman · Ranxin · Goose Leg Auntie.
Project evidence · Portfolio review · Design references · Profile CI
Financial questions. Runnable code. Evidence you can inspect.