Search Results for "algorithmic trading software" - Page 4
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Showing 175 open source projects for "algorithmic trading software"
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1
Blankly
Easily build, backtest and deploy your algo in just a few lines
Blankly is a live trading engine, backtest runner and development framework wrapped into one powerful open-source package. Models can be instantly backtested, paper traded, sandbox tested and run live by simply changing a single line. We built blankly for every type of quant including training & running ML models in the same environment, cross-exchange/cross-symbol arbitrage, and even long/short positions on stocks (all with built-in WebSockets). Blankly is the first framework to enable... -
2
Node Binance Trader NBT
Cryptocurrency trading strategy & portfolio management development
By default the trader tries to trade with margin, so you need to have at least 0.001 BTC in your spot as well as your margin account. Also, to cover trading fees, you'll need a small amount of BNB in both your spot and margin wallets. While the Bitcoin vs. Altcoins website itself is closed source, the automated trading bot called Node Binance Trader (NBT) is open source. It connects to your Binance account via the Binance API and executes the trades on your behalf. Choose any unique name you... -
3
go-algorithms
Algorithms and data structures for golang
go-algorithms is an open-source educational repository that provides implementations of common algorithms and data structures written in the Go programming language. The project is designed primarily as a learning resource to help developers understand how fundamental computer science concepts can be implemented idiomatically in Go. It includes a wide range of classic sorting, searching, and numerical algorithms alongside basic collection structures such as stacks, queues, linked lists, and... -
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Machine Learning Financial Laboratory
MlFinLab helps portfolio managers and traders
MlFinLab is a comprehensive Python library designed to support the development of machine learning strategies in quantitative finance and algorithmic trading. The project provides a large collection of tools that implement techniques from academic research on financial machine learning. It covers the full lifecycle of developing data-driven trading strategies, including data preprocessing, feature engineering, labeling techniques, model training, and performance evaluation. ... -
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5
Kelp
Kelp is a free and open-source trading bot for the Stellar DEX
...The modular design allows you to easily create new trading strategies, exchange integrations, and assets to give you full control over the bot. Whenever you trade on Stellar, you are trading with volatile assets, in volatile markets, and you risk losing money. Kelp is experimental software that contains bugs. Use Kelp at your own risk. There is no guarantee you'll make a profit from using our bots or strategies. -
6
Peatio
Open-source crypto currency exchange software
...Our mission is to build an open-source crypto exchange software with a high-performance trading engine and incomparable security. We are moving toward dev/ops best practices of running an enterprise-grade exchange. We provide webinar or on-site training for installing, configuring, and administering the best practices of Peatio. -
7
ML for Trading
Code for machine learning for algorithmic trading, 2nd edition
On over 800 pages, this revised and expanded 2nd edition demonstrates how ML can add value to algorithmic trading through a broad range of applications. Organized in four parts and 24 chapters, it covers the end-to-end workflow from data sourcing and model development to strategy backtesting and evaluation. Covers key aspects of data sourcing, financial feature engineering, and portfolio management. The design and evaluation of long-short strategies based on a broad range of ML algorithms, how to extract tradeable signals from financial text data like SEC filings, earnings call transcripts or financial news. ... -
8
SoundHelix
Versatile algorithmic random music generation software written in Java
SoundHelix is a free versatile Java framework for algorithmic random music composition. SoundHelix can generate random songs, play them (for example, on any number of MIDI devices or MIDI-capable software synthesizers) and is highly customizable using XML configuration. SoundHelix also allows writing the generated music as MIDI files. SoundHelix produces music that is actually enjoyable to listen to. -
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Differentiable Neural Computer
A TensorFlow implementation of the Differentiable Neural Computer
The Differentiable Neural Computer (DNC), developed by Google DeepMind, is a neural network architecture augmented with dynamic external memory, enabling it to learn algorithms and solve complex reasoning tasks. Published in Nature in 2016 under the paper “Hybrid computing using a neural network with dynamic external memory,” the DNC combines the pattern recognition power of neural networks with a memory module that can be written to and read from in a differentiable way. This allows the... -
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Zipline
Zipline, a Pythonic algorithmic trading library
Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backtesting and live-trading engine powering Quantopian -- a free, community-centered, hosted platform for building and executing trading strategies. Quantopian also offers a fully managed service for professionals that includes Zipline, Alphalens, Pyfolio, FactSet data, and more. -
11
Eiten
Statistical and Algorithmic Investing Strategies for Everyone
Eiten is an open-source Python project focused on providing statistical and algorithmic trading strategies powered by data analysis and machine learning techniques. It is designed to make quantitative investing more accessible by offering ready-to-use strategies that analyze market behavior, detect patterns, and generate actionable insights. The project includes tools for evaluating stock performance, identifying trends, and applying algorithmic models to financial data, enabling users to experiment with different investment approaches. ... -
12
TradingVue.js
Hackable charting lib for traders. You can draw literally anything
TradingVue.js was a hackable charting lib for traders. You could draw literally ANYTHING on top of candlestick charts. If you create trading software, this lib is probably for you. If you like to make custom indicators and think out of the box, this lib is most likely for you. And if you miss the usability of TradingView.com in other open-source libraries and can't stand it, you are definitely in the right place! The process of adding a new indicator is simple, first you define your own data format (should be timestamped though) and display settings. ... -
13
surpriver
Find big moving stocks before they move using machine learning
...The project is intended as a research tool for quantitative finance experiments and algorithmic trading strategy development. -
14
AlphaPy
Python AutoML for Trading Systems and Sports Betting
AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow.... -
15
gradslam
gradslam is an open source differentiable dense SLAM library
gradslam is an open-source framework providing differentiable building blocks for simultaneous localization and mapping (SLAM) systems. We enable the usage of dense SLAM subsystems from the comfort of PyTorch. The question of “representation” is central in the context of dense simultaneous localization and mapping (SLAM). Newer learning-based approaches have the potential to leverage data or task performance to directly inform the choice of representation. However, learning representations... -
16
EliteQuant
A list of online resources for quantitative modeling, trading, etc.
EliteQuant is a curated directory of online resources for quantitative finance: trading, portfolio management, quantitative modeling, data sources, libraries, platforms, and communities. It is not a software library per se, but a “list of things” - i.e., an aggregator of open source projects, blogs, tools etc., intended to help practitioners find useful resources. It is licensed under Apache-2.0, and maintained by volunteers. -
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Quantitative-Notebooks
Educational notebooks on quantitative finance, algorithmic trading
Quantitative-Notebooks is a curated set of Jupyter notebooks focused on quantitative finance, algorithmic investing, and data-driven portfolio analysis. While each individual notebook is aimed at practical finance workflows, the overall repository helps practitioners and learners use Python, pandas, and numerical libraries to build, test, and evaluate financial strategies using historical market data. The notebooks typically showcase how to perform backtesting, factor analysis, risk... -
18
PandoraTrader
C++ Trade Platform for quant developer
...We hope that the strategy designer will design excellent strategies to give the trading software enough wisdom to be able to ride the wind and waves in the floating market, hanging sails across the sea. Position pending orders and other information are maintained locally, and strategies can be obtained simultaneously, simplifying logic. -
19
node-csgo
A node-steam plugin for Counter-Strike: Global Offensive
Node-CSGO is a Node.js library that allows interaction with Counter-Strike: Global Offensive (CS:GO) game servers and Steam APIs. It enables developers to retrieve game data, manage inventories, and automate in-game operations. -
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Strategems
Quantitative systematic trading strategy development and backtesting
Strategems is a Julia package aimed at simplifying and streamlining the process of developing, testing, and optimizing algorithmic/systematic trading strategies. This package is inspired in large part by the quantstrat1,2 package in R, adopting a similar general structure to the building blocks that make up a strategy. Given the highly iterative nature of event-driven trading strategy development, Julia's high-performance design (particularly in the context of loops) and straightforward syntax would seem to make it a natural fit as a language for systematic strategy research and development. ... -
21
exchange-core java
Ultra-fast matching engine written in Java based on LMAX Disruptor
Exchange-core is an open source market exchange core based on LMAX Disruptor, Eclipse Collections (ex. Goldman Sachs GS Collections), Real Logic Agrona, OpenHFT Chronicle-Wire, LZ4 Java, and Adaptive Radix Trees. HFT optimized. Priority is a limit-order-move operation mean latency (currently ~0.5µs). Cancel operation takes ~0.7µs, placing new order ~1.0µs. Pipelined multi-core processing (based on LMAX Disruptor): each CPU core is responsible for certain processing stage, user accounts... -
22
MADDPG
Code for the MADDPG algorithm from a paper
MADDPG (Multi-Agent Deep Deterministic Policy Gradient) is the official code release from OpenAI’s paper Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments. The repository implements a multi-agent reinforcement learning algorithm that extends DDPG to scenarios where multiple agents interact in shared environments. Each agent has its own policy, but training uses centralized critics conditioned on the observations and actions of all agents, enabling learning in... -
23
AIAlpha
Use unsupervised and supervised learning to predict stocks
AIAlpha is a machine learning project focused on building predictive models for financial markets and algorithmic trading strategies. The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. -
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Bitcoin Exchange Script
cryptocurrency exchange software for trading hundreds of digital asset
Bitcoin and altcoin software for buying and selling of cryptocurrency with support for local currencies. -
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Coach
Enables easy experimentation with state of the art algorithms
Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments...
