Built a 200k-edge market knowledge graph to filter false dip-buy signals
I’ve been experimenting with a graph-based approach to a classic trading problem: why most dip-buying strategies can’t tell the difference between a temporary overreaction and a genuine structural collapse. Most systems treat a −5% move the same regardless of context. My hypothesis was that where a company sits in the market’s structure matters more than the price move itself. The engineering idea I built a knowledge graph of the U.S. public markets with ~207k edges across ~21 relationship types, organized into four layers: Operational: supply-chain relationships (SUPPLIES_TO, PRODUCES)…
Built a 200k-edge market knowledge graph to filter false dip-buy signals launched on December 29, 2025 with 5 votes, #2,550 of 11,628 launches that month and more than 75% of that year's launches.
What it does
In the maker’s words, at launch
I’ve been experimenting with a graph-based approach to a classic trading problem: why most dip-buying strategies can’t tell the difference between a temporary overreaction and a genuine structural collapse. Most systems treat a −5% move the same regardless of context. My hypothesis was that where a company sits in…
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