TradeClaw

Inspiration

In March 2026, Iran closed the Strait of Hormuz. Brent crude surged past $100/barrel. Markets were moving every second. We started the hackathon trading manually — watching prices, reading headlines, clicking buy. And we couldn’t keep up. By the time you read a headline, process it, and place an order, the opportunity is gone. We were leaving money on the table or, worse, reacting too slow and taking losses. So we asked: what if we never had to click a button again?

What It Does

TradeClaw is a dual-bot autonomous trading system for Brent crude oil perpetual futures on Liquid DEX. Two bots work in tandem — one reads the charts, one reads the world. The Quant watches Brent crude price every 15 seconds, calculates a moving average crossover, and auto-executes trades when the price crosses above or below. It takes profit automatically at 10%. Tonight it locked in a 10.6% gain on a single trade — completely autonomous. The Analyst scrapes Google News, Reddit, and Twitter/X every 60 seconds for oil-related headlines and feeds them to Anthropic’s Claude. Claude decides: is this genuinely new, or already priced in? When the NYT headline “Iran Defies Trump’s Threats Over Strait of Hormuz Blockade” came in, Claude scored it 2/10 and said hold. Not new information. Exactly the right call.

How We Built It

Python for the core bot logic, event loops, and position management. Liquid DEX API for on-chain perpetual futures at 20x leverage. Anthropic Claude (Sonnet) for real-time geopolitical news analysis. Google News RSS across 13 query channels for headline ingestion. Reddit JSON API pulling from r/worldnews, r/energy, r/oil, r/geopolitics, and r/commodities for sentiment. Twitter/X search for early social media signals. The Quant runs a 15-second price polling loop computing a simple moving average crossover — price crosses above the MA, buy; below, sell; auto-TP at 10%. The Analyst runs a parallel 60-second loop aggregating headlines from three sources, deduplicating them, and sending them to Claude with full market context: current price, position status, account balance, and price trend. Claude is prompted with the current geopolitical baseline — Iran war, Hormuz closure, $100+ oil are all priced in — and only flags genuinely unprecedented developments like a ceasefire, a new country entering the war, or a nuclear threat. Trades use graduated position sizing: severity 7 deploys 25% of available capital, severity 10 goes all in.

Challenges We Ran Into

Calibrating Claude’s severity threshold so it doesn’t over-trade on noise was the hardest part. The Iran war generates hundreds of headlines per hour, but 99% are already priced in. Managing $100 at 20x leverage without getting liquidated required surgical position sizing — a 5% adverse move wipes the account. Rate limiting across three news sources without missing breaking stories meant staggering queries and deduplicating aggressively. The Liquid SDK had limited documentation, so we reverse-engineered the API from example code and trial-and-error during live market hours. And honestly, the hardest part was trusting the system and not manually overriding the bots.

Accomplishments

60% win rate. Average win of about $9. Average loss of about $3. Best single trade: 10.6% gain. That’s a 3:1 reward-to-risk ratio at 20x leverage — meaning even when we’re wrong, we’re wrong small. Two fully autonomous bots running live on Liquid DEX during the hackathon, trading Brent crude perpetual futures in real-time against a live wartime market. That’s how real hedge fund quant desks operate, except this runs on a laptop and we built it in a weekend.

What We Learned

LLMs are shockingly good at filtering noise from signal in news — Claude correctly held through dozens of recycled war headlines without flinching. The crypto oil market moves faster than traditional markets, so speed matters more than depth of analysis. Combining technical signals (the Quant) with fundamental signals (the Analyst) produces better results than either alone. And position sizing matters more than being right — our 3:1 reward-to-risk ratio means we can be wrong 40% of the time and still make money.

What’s Next for TradeClaw

Adding more asset classes beyond Brent crude — WTI, natural gas, gold. Building a live dashboard so you can watch both bots’ decisions in real time. Integrating WebSocket feeds from Liquid for sub-second price updates instead of polling. Adding a third bot — the Arbitrageur — to exploit price discrepancies between crypto oil markets and traditional futures. And expanding the news sources to include Bloomberg Terminal alerts, government press releases, and satellite imagery of oil tanker traffic through the Strait of Hormuz.

Built With

• liquid
• liquidapi
• liquidsdk
• python