explaingit

bakome-hub/bakome-crypto-quant-engine

0RustAudience · developerComplexity · 3/5ActiveSetup · easy

TLDR

A self-described single-file Rust crypto trading engine that claims a multi-exchange collector, 128 features, a 256-expert mixture of experts, and a risk module.

Mindmap

mindmap
  root((BAKOME-Crypto-Quant-Engine))
    Inputs
      Market data from Binance Bybit OKX Coinbase
      Six trading pairs
    Outputs
      Trade orders
      CSV order log
      Reinvestment splits
    Use Cases
      Personal showcase project
      Quant code reading
      Trading idea reference
    Tech Stack
      Rust
      rustc compile
      Single source file

Things people build with this

USE CASE 1

Read a single-file Rust example that bundles features, risk, and execution

USE CASE 2

Study how an author claims to express a Mixture of Experts without external crates

USE CASE 3

Use as a reference layout for a personal quant exploration project

Tech stack

Rust

Getting it running

Difficulty · easy Time to first run · 30min

Compile is one rustc command, but the README is short on verifiable detail and includes promotional links, so treat performance and capability claims with caution.

In plain English

This repository advertises itself as a crypto trading engine written in Rust. The README is trilingual, repeating the same description in French, English, and Spanish. The author, who goes by BAKOME, says the project is a single Rust file of around 1,800 lines that you compile directly with the rustc compiler and run as one executable. No external libraries are listed; the README claims the engine has zero external dependencies. The README describes six modules. A multi-exchange collector is meant to pull market data from Binance, Bybit, OKX, and Coinbase. A feature module computes 128 numeric inputs from that data, including returns, volatility, momentum, funding rates, open interest, cumulative volume delta, and liquidation events. On top of those features sits what the README calls a Mixture of Experts with 256 experts, said to specialize in volatility, trend, funding arbitrage, open interest flow, and similar areas. A risk engine is described with a 95 percent Value at Risk calculation, a three percent drawdown limit, and adaptive position sizing. An execution module lists per-exchange latencies in microseconds. Finally, an auto-reinvestment module splits returns 70 percent into trading, 10 percent into GPU, 15 percent into research, and 5 percent into staking, and a CSV logger writes every executed order to disk. The six trading pairs targeted are ETHUSDT, SOLUSDT, BNBUSDT, XRPUSDT, DOGEUSDT, and AVAXUSDT, each routed across the four listed exchanges. Installation is two commands: compile the file with rustc using the -O3 optimization flag, then run the resulting binary. The README ends with promotional material rather than technical detail. There are referral links to two brokers, donation addresses for Bitcoin, Ethereum, Solana, and TRC20 USDT, a Drips sponsor link, and a hardware wish list that mentions a laptop with 16 gigabytes of RAM, a 4G or 5G router, a monitor, and a solar power bank. The author notes that the whole project was built on a Pixel 4a 5G phone without a laptop or fixed Wi-Fi. Readers should treat the README's performance numbers and capability claims with caution. The document is short on verifiable detail: there is no sample backtest, no benchmark data, no test suite link, and no description of how the engine actually places orders against live exchange APIs without any networking dependency. It reads more as a personal showcase project than a battle-tested system.

Copy-paste prompts

Prompt 1
Compile BAKOME-Crypto-Quant-Engine with rustc using the -O3 flag and run the resulting binary in a sandboxed VM
Prompt 2
Audit the README claim of zero external dependencies against the actual source file imports
Prompt 3
Outline what would have to be added to actually place live orders on Binance and Bybit APIs from this codebase
Prompt 4
Critically review the 95 percent VaR and 3 percent drawdown risk logic and flag missing safeguards
Prompt 5
Sketch a minimal test harness that replays historical OHLCV through the feature module
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Generated 2026-05-22 · Model: sonnet-4-6 · Verify against the repo before relying on details.