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Tags: Trading bot

1.hummingbot / hummingbot

Open source software that helps you create and deploy high-frequency crypto trading bots

arbitrage
crypto
trading
python
algotrading
hft
+13 more

Python APACHE-2.021K total5.1K forks

+1,711 stars

from 19,230 · score 7.45

2.QuantConnect / Lean

Lean Algorithmic Trading Engine by QuantConnect (Python, C#)

c-sharp
algorithmic-trading-engine
quantconnect
lean-engine
finance
algorithm
+9 more

C#APACHE-2.022K total5.4K forks

+1,415 stars

from 20,974 · score 7.26

Translatedstock. Get stock data, calculate stock indicators, chip distribution, identify stock patterns, comprehensive stock selection, stock selection strategies, stock verification and backtesting, automatic stock trading, supports PC and mobile devices.

stock
stocks
backtest
backtesting
quantitative
quantitative-finance
+6 more

Python APACHE-2.015K total3.1K forks

+1,365 stars

from 13,609 · score 7.22

4.tensortrade-org / tensortrade

An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.

Python APACHE-2.07.3K total1.3K forks

+676 stars

from 6,581 · score 6.52

5.AI4Finance-Foundation / FinRL-Trading

FinRL-X: An AI-Native Modular Infrastructure for Quantitative Trading

deep-reinforcement-learning
stock-trading
a2c-algorithm
ppo
ddpg
ensemble-strategy
+8 more

Python APACHE-2.03.9K total1.1K forks

+384 stars

from 3,520 · score 5.95

6.YichengYang-Ethan / oracle3-prediction-market-agent

Oracle3: open-source trading engine and MCP server for prediction markets. Finds fee-adjusted no-arbitrage violations across related event contracts and trades them live on Kalshi, Polymarket and Solana, or on paper, under pre-trade risk limits. 13 MCP tools, JSON CLI, agent skills, 600+ tests.

algorithmic-trading
kalshi
polymarket
python
quantitative-finance
trading-bot
+14 more

Python APACHE-2.0565 total67 forks

+329 stars

from 236 · score 5.80

7.ValueCell-ai / valuecell

ValueCell is a community-driven, multi-agent platform for financial applications.

agentic-ai
agents
ai
assitant
crypto
equity
+6 more

Python APACHE-2.011K total1.8K forks

+155 stars

from 10,886 · score 5.05

8.alexanderwanyoike / the0

Open Source Algorithmic Trading Engine

algorithmic-trading
quantitative-finance
bots
docker
kubernetes
quant
+4 more

TypeScript APACHE-2.0434 total62 forks

+113 stars

from 321 · score 4.74

9.scrtlabs / catalystArchived

An Algorithmic Trading Library for Crypto-Assets in Python

cryptocurrency
trading
algorithmic-trading
cryptocurrencies

Python APACHE-2.02.6K total703 forks

+2 stars

from 2,556 · score 1.10

Order: Attention Score

Most net stars gained in the window first. The score only puts this gain on a log scale, so the order is the order of the gain.

How the ranking works

Ranked by stars gained in the window. The score is the natural log of one plus that gain, so a repository's rank is exactly its star gain's rank.

score = log1p(net stars gained in the trailing T complete UTC days)

A repository is ranked only when its Star History covers every day of the window and its latest Observation is not missing.

The longest window is 180 days. Star History from the Repository Host goes back at most 180 days before the first daily record that AwesomeRepos made for the repository. A longer window needs more of these daily records first. A repository younger than the window does not rank in it.

The filters select from the same eligible repositories. A repository matches the topics when it has any of them. Total stars is the count now. Last push and creation on the Repository Host count back from the start of today (UTC). The counts beside the languages, licenses, and topics include all ranked repositories in the window. A Tag holds the repositories that have it. See Tags.

A new repository enters the index when it gains stars faster than the published admission threshold, whatever its size. A repository stays in the index after it enters. Thus an archived repository can still rank.

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