Built while learning

Projects

Guides, references, and tools I build for myself while learning commodity trading — published here in case they help someone else climbing the same curve.

Reference guides

The Commodity Derivatives Playbook 期货与衍生品实战手册

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A bilingual (中文 / English) first-principles playbook of how physical commodity traders actually use futures and derivatives — hedging, cash & carry arbitrage, basis trading, options, swaps, and the position book and risk organisation behind it all. Every concept is built from the same worked example (1,000 t of coking coal) with full scenario analysis, and a running answer to the question that confuses everyone: where does the physical cargo actually move?

Bilingual · 10 chapters · worked numbers throughout

Interactive tools

Tanzania Resource Atlas 坦桑尼亚资源交互地图

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A three-layer interactive map of Tanzania built from public sources: administrative regions and their capitals (2022 census population), the mineral picture — deposits, artisanal mining districts and the greenstone, Karagwe–Ankole, Mozambique Belt, carbonatite, Karoo and coastal host belts — and the wider natural-resource base beyond metals (livestock, fisheries, forestry, cash crops, protected areas). Ports, rail, roads and power stay on top of every layer. Every figure carries its year and source; where the sources disagree, both are shown rather than reconciled.

Leaflet · 3 layers · 30 regions · sourced & dated throughout

Live dashboards

China Futures Positioning Dashboard 期货会员持仓监控

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Tracks who is long and short across the Dalian, Shanghai and Guangzhou futures exchanges: each broker's long, short and net positions, with daily and 7-day changes and new or exiting names flagged. Refreshed automatically every trading day. It also includes the iron ore cash & carry calculator I built on a ferrous trading desk: buy port spot, deliver against the DCE contract, with every step of the margin shown.

Python · Streamlit · daily refresh · Chinese interface

Commodity OS

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A research system for copper, aluminium, nickel and crude. Macro data is collected on a schedule into a database that keeps every figure as it was first published, so a backtest never uses numbers that were not yet public. The dashboard shows the macro picture and the release calendar; commodity fundamentals and news are being added.

Python · Postgres · Streamlit · access on request