Alternatives
Products that do what I simulated closing the Strait of Hormuz on real oil trade data does
OP here: I created this visualization tool as the byproduct of a supply chain class I taught at Columbia. The pedagogical exercise grew into a full blown visualization and paper about global oil trade. The model: The mechanics are the same as the financial network Eisenberg-Noe: Instead of banks, every country consumes oil interconnected via bilateral trading. Shocks propagate throughout the network, depleting oil reserves when bottleneck nodes (such as the Strait of Hormuz) are blocked. Insights: The interesting part is the mechanics of how the crisis unfolds: for example, France receives 0…
- 1IH
I built this because I was interested in the data. Didn't fully get it to what I wanted, but thought I'd share it nonetheless. Maybe someone has better data sources they could share! Turns out live ship tracking APIs are expensive so I manually just copied the json from https://www.marinetraffic.com/en/ais/home/centerx:57.4/cente... I'll probably have an ai agent do the same thing on some cron interval, if this gets any fanfare. To actually know if the port is open without live ship tracking I found…
Apr 2026 · ishormuzopenyet.com
- 2TC
Hello, I wanted to share with you all a interactive map of the economics and physics constraints of the AI buildout. It has macro drivers, industrial chokepoints, and where that shows up in markets. I've added 393 nodes and 562 edges to capture other supply / physics constraints as well. There's no sign up, and no pay wall, it's all free. Please let me know what you think!
Jun 2026 · atomprophet.io
- 3HC
Built this in ~4 hours with zero coding background. Tracks a few economy angles of the largest acute shipping disruption since WWII.
Mar 2026 · hormuztracker.com
- 4
- 5TT
Simulate anything on a map from a text prompt -- and conduct risk analysis against LiveUA map's global realtime data points from social media and news sources. I trained a GPT-2-size model on historical incident data used to predict things that will go wrong. As historian Benjamin Breen mentions, the leading language models are good historians, so the application will simulate historical events pretty well also. I include a Multi-Agent RL Urban Mobility model in progress displayed on the map as small white cubes representing traffic and pedestrians. Around SF, it uses real census data and…
2025 · mused.com
- 6TF
2011 · bullbear.ca
- 7
- 8MA
I built this simulator to study how simple trading agents interacting with an order book can create emergent patterns—volatility, clustering, even chaos—without any external shocks. It’s meant as both a research toy and teaching tool. You can run different strategies, adjust configs, and watch dynamics evolve. Curious to hear feedback from the HN crowd on features/dynamics you’d like to see added.
2025 · aitradingsim.com
- 9BA
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)…
Dec 2025
- 10SA
Hi HN! We are Anshuman and Karén, the co-founders of Lookback Labs and the co-designers of Soros (https://www.asksoros.com/). Soros is a compound AI system built carefully from the ground up to trace a path (multiple paths, really) from a description of a geopolitical event all the way to capital market implications. * Here's how we set it up: Given a description of a given geopolitical event (can be a couple of words; the demo literally has "US-Iran conflict" as the entire string), Soros will - (1) first analyze and perform deep research on it, running scores of searches in…
Mar 2026 · asksoros.com
- 11
- 12DC
I built an open-source system called Horaculo that analyzes coordination and divergence across financial news sources. The goal is to quantify narrative alignment, entropy shifts, and historical source reliability. Pipeline Fetch 50–100 articles (NewsAPI) Extract claims (NLP preprocessing) Generate sentence embeddings (HuggingFace) Compute cosine similarity in C++ (AVX2 + INT8 quantization) Cluster narratives Compute entropy + coordination metrics Weight results using historical source credibility Output structured JSON signals Example Output (query: “oil”) Json Copiar código { "verdict": {…
Feb 2026
- 13TI
Hey HN, For the past few years, I've been obsessed with trying to get AI to produce accurate trading signals. The main challenges I found with AI trading models are lack of consistency, context window bottlenecks, hard to backtest, and high cost. Asking ChatGPT "Should I buy Bitcoin today?" doesn't work well because the LLM doesnt have a set trading strategy to opperate from. In addition, the small context window makes it challenging to fit enough historical data into. Not to mention it gets very expensive as well. My solution is a hybrid approach. Instead of having the LLM make direct…
2025 · trend.fi
- 14QO
Hi HN, A while ago I had a mildly depressing realization. Back in 2010, I had around $60k. Like a "responsible" person, I used it as a down payment on an apartment. Recently, out of curiosity, I calculated what would have happened if I had instead put that money into NVIDIA stock. I should probably add some context. For over 10 years I've worked as a developer on trading platforms and financial infrastructure. I made a rule for myself - never trade on the market. In 2015, when Bitcoin traded about 300 usd, my brother and I were talking about whether it was a bubble. He made a bold claim that…
Feb 2026 · shouldhavebought.com
- 15IB
I built a web page that aggregates data about data center buildup, sovereign fund investments into AI and bottlenecks. The objective is to predict AI race cooldown by looking at a potential decrease of activity involving these elements. The website looks at the quarterly forms from the 5 biggest hyperscalers and adds their CapEx into the mix, calculating a composite index in the end showing how likely it is for the AI race to slow down. Enjoy!
Jul 2026 · laurentiugabriel.github.io
- 16GT
I've been working on GeoTraceroute for a while and just shipped v2.3 with submarine cable inference. A few things that might interest HN: - 320 community-contributed nodes across 50 countries, all volunteer-run - Three views: 3D globe with day/night rendering, 2D map, and a topological mode that infers submarine cable routing - The submarine cable inference is the part I find most interesting. Since cable routers don't respond to ICMP, the underwater segments are invisible to standard traceroute. The tool detects ocean crossings by geolocation delta between consecutive hops, then infers…
Apr 2026 · geotraceroute.com
- 17AN
2013 · zingfin.com
- 18GM
Mar 2026 · ryanshook.org
- 19IB
Hi HN, I'm a solo dev and for the last few months I've been building Hikaro, a tool to find statistically significant trading signals for [e.g., US equities, crypto, forex]. I built this to solve my own problem: I was tired of backtests that looked great on paper but failed in practice. Simple metrics like "win rate" can be misleading, so I wanted a way to quickly tell if a signal's performance was genuine or just noise. Hikaro ingests daily market data and runs statistical analysis on various trading signals. The goal is to surface signals with strong properties, like: Low p-value: Evidence…
Sep 2025 · hikaro.app
- 20
- 21
- 22
Interactive React components for network diagrams, fiber networks, and rack infrastructure visualization.
10d ago · react-networks-lib.rackout.net
- 23
Real‑time thermodynamic market engine not financial advice
Jul 2026 · thermomites-production.up.railway.app
- 24
Ranked by how close each launch is in meaning, then by votes. Refine with a description →