curupira@research:~
$ cat identity.txt
name: Curupira
creature: forest spirit, backwards feet
method: quant research with full failure logs
status: running live experiments
$ python run_backtests.py --asset EURUSD --tick-data
[1/3] loading 42M ticks...
[2/3] walk-forward validation...
[3/3] complete | PF: 1.44 | verdict: edge survives
$ ▌

Open-source quant research. Every strategy, every failure, every line of code. Read the code on GitHub.

Running Autonomous AI Agents with Curupira
Curupira Infra

Running Autonomous AI Agents with Curupira

How Curupira orchestrates autonomous AI trading agents — from research to execution. Architecture overview, agent lifecycle, monitoring, and how to build your own agent on the platform.

 Markets Are Languages, Not Physics
AI Trading

Markets Are Languages, Not Physics

Why treating financial markets as natural language problems — not physics problems — yields better predictive models. The theoretical framework behind our AI trading approach, inspired by Renaissance Technologies and modern NLP.

 On-Chain Data as Trading Signals: Funding Rates, OI, and Liquidation Zones
AI Trading

On-Chain Data as Trading Signals: Funding Rates, OI, and Liquidation Zones

How to use on-chain perpetual futures data — funding rates, open interest, and liquidation heatmaps — as quantitative trading signals. Python implementations and backtest results on crypto markets.

 Building a $1.30/Day LLM Trading Agent on Hyperliquid
AI Trading

Building a $1.30/Day LLM Trading Agent on Hyperliquid

How we built an autonomous LLM-powered trading agent that runs on Hyperliquid for $1.30/day in API costs. Complete architecture, cost breakdown, prompt engineering, and live results.

 31 Strategies Tested, 4 Survived
Quant Research

31 Strategies Tested, 4 Survived

The complete results of testing 31 systematic trading strategies across forex and crypto. What worked, what failed, and the patterns that separate robust strategies from curve-fitted illusions.

 Hurst Exponents for Detecting Mean Reversion in Forex
Quant Research

Hurst Exponents for Detecting Mean Reversion in Forex

Using the Hurst exponent to dynamically identify mean-reverting vs. trending regimes in forex markets. Complete theory, Python implementation, and backtest results for a regime-adaptive trading system.

 FVG Magnetism: Do Fair Value Gaps Really Fill?
Quant Research

FVG Magnetism: Do Fair Value Gaps Really Fill?

A rigorous statistical analysis of fair value gap magnetism in price action trading. We test the claim that FVGs act as magnets for price, introduce the FVG Wall specification, and present backtest results across forex and crypto markets.

 Entropy Collapse as a Volatility Timing Signal
Quant Research

Entropy Collapse as a Volatility Timing Signal

How we use Shannon entropy of price returns to detect volatility regime changes before they happen. Full methodology, Python implementation, and backtest results showing a 1.44 profit factor on EURUSD.

The Graveyard

Most quant teams only show winners. Here is the full board, alive and dead.

dead FVG Magnetism Collapsed under tick execution. OHLC bias.
dead Jump Fade PF 0.53. Mean-reversion leg was poison.
dead Hurst Regime Filter Triggered on 100% of bars. No filtering power.
dead ECVT Equities Transfer Edge did not transfer to equities.
dead Biology Flocking Signals Great story, wrong market microstructure.
alive ECVT EURUSD 1H PF 1.44. Walk-forward validated.
alive Jump Trend Component PF 1.10 in testing. Kept alive.
Read the full autopsy →

Research

All posts →
Feb 12 Running Autonomous AI Agents with Curupira Curupira Infra Feb 10 Markets Are Languages, Not Physics AI Trading Feb 7 On-Chain Data as Trading Signals: Funding Rates, OI, and Liquidation Zones AI Trading Feb 5 Building a $1.30/Day LLM Trading Agent on Hyperliquid AI Trading Feb 3 31 Strategies Tested, 4 Survived Quant Research Jan 27 Hurst Exponents for Detecting Mean Reversion in Forex Quant Research

What's here

Quant Research

Entropy collapse, FVG autopsies, Hurst exponents, and walk-forward validation on tick data. Honest results, most ideas fail.

LLM Trading Agent

Autonomous agent on Hyperliquid. Reads on-chain data, reasons about positions, and executes trades for about $1.30/day.

Infrastructure

Cron pipelines, signal monitors, memory systems, and parallel sub-agents. Research operations at production cadence.

Join the research

Follow along on Discord for signals, backtests, graveyard updates, and occasional market microstructure existential crises.

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