A Python-based development platform for automated trading systems - from backtesting to optimisation to livetrading.

Overview

AutoTrader Logo

AutoTrader

Latest version Total downloads Monthly downloads Build Status Documentation Status

AutoTrader is Python-based platform intended to help in the development, optimisation and deployment of automated trading systems. From simple indicator-based strategies, to complex non-directional hedging strategies, AutoTrader can do it all. If you prefer a more hands-on approach to trading, AutoTrader can also assist you by notifying you of price behaviour, ensuring you never miss a signal again. A basic level of experience with Python is recommended for using AutoTrader, but the docs aim to make using it as easy as possible with detailed tutorials and documentation.

Features

Installation

AutoTrader can be installed using pip:

pip install autotrader

Updating

AutoTrader can be updated by appending the --upgrade flag to the install command:

pip install autotrader --upgrade

Documentation

AutoTrader is very well documented in-code and on Read the Docs. There is also a detailed walthrough, covering everything from strategy concept to livetrading.

Example Strategies

Example strategies can be found in the demo repository. You can also request your own strategy to be built here.

Backtest Demo

The chart below is produced by a backtest of the MACD trend strategy documented in the tutorials (and available in the demo repository). Entry signals are defined by MACD crossovers, with exit targets defined by a 1.5 risk-to-reward ratio. Stop-losses are automatically placed using the custom swing detection indicator, and position sizes are dynamically calculated based on risk percentages defined in the strategy configuration.

Running this strategy with AutoTrader in backtest mode will produce the following interactive chart.

MACD-backtest-demo

Note that stop loss and take profit levels are shown for each trade taken. This allows you to see how effective your exit strategy is - are you being stopped out too early by placing your stop losses too tight? Are you missing out on otherwise profitable trades becuase your take profits are too far away? AutoTrader helps you visualise your strategy and answer these questions.

Legal

License

AutoTrader is licensed under the GNU General Public License v3.0.

Disclaimer

This platform is currently under heavy development and should not be considered stable for livetrading until version 1.0.0 is released.

Never risk money you cannot afford to lose. Always test your strategies on a paper trading account before taking it live.

Transformer based SAR image despeckling

Transformer based SAR image despeckling Using the code: The code is stable while using Python 3.6.13, CUDA =10.1 Clone this repository: git clone htt

27 Nov 13, 2022
Collection of NLP model explanations and accompanying analysis tools

Thermostat is a large collection of NLP model explanations and accompanying analysis tools. Combines explainability methods from the captum library wi

126 Nov 22, 2022
[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning | 斗地主AI

[ICML 2021] DouZero: Mastering DouDizhu with Self-Play Deep Reinforcement Learning DouZero is a reinforcement learning framework for DouDizhu (斗地主), t

Kwai Inc. 3.1k Jan 04, 2023
Official implementation of NPMs: Neural Parametric Models for 3D Deformable Shapes - ICCV 2021

NPMs: Neural Parametric Models Project Page | Paper | ArXiv | Video NPMs: Neural Parametric Models for 3D Deformable Shapes Pablo Palafox, Aljaz Bozic

PabloPalafox 109 Nov 22, 2022
Package for working with hypernetworks in PyTorch.

Package for working with hypernetworks in PyTorch.

Christian Henning 71 Jan 05, 2023
Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis

Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesis Website | ICCV paper | arXiv | Twitter This repository contains the official i

Ajay Jain 73 Dec 27, 2022
Mmdetection3d Noted - MMDetection3D is an open source object detection toolbox based on PyTorch

MMDetection3D is an open source object detection toolbox based on PyTorch

Jiangjingwen 13 Jan 06, 2023
Anomaly Localization in Model Gradients Under Backdoor Attacks Against Federated Learning

Federated_Learning This repo provides a federated learning framework that allows to carry out backdoor attacks under varying conditions. This is a ker

Arçelik ARGE Açık Kaynak Yazılım Organizasyonu 0 Nov 30, 2021
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Intelligent Robotics and Machine Vision Lab 4 Jul 19, 2022
Discord Multi Tool that focuses on design and easy usage

Multi-Tool-v1.0 Discord Multi Tool that focuses on design and easy usage Delete webhook Block all friends Spam webhook Modify webhook Webhook info Tok

Lodi#0001 24 May 23, 2022
This repository contains all the code and materials distributed in the 2021 Q-Programming Summer of Qode.

Q-Programming Summer of Qode This repository contains all the code and materials distributed in the Q-Programming Summer of Qode. If you want to creat

Sammarth Kumar 11 Jun 11, 2021
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver

Shape As Points (SAP) Paper | Project Page | Short Video (6 min) | Long Video (12 min) This repository contains the implementation of the paper: Shape

394 Dec 30, 2022
Semi-Supervised Learning, Object Detection, ICCV2021

End-to-End Semi-Supervised Object Detection with Soft Teacher By Mengde Xu*, Zheng Zhang*, Han Hu, Jianfeng Wang, Lijuan Wang, Fangyun Wei, Xiang Bai,

Microsoft 789 Dec 27, 2022
A list of multi-task learning papers and projects.

This page contains a list of papers on multi-task learning for computer vision. Please create a pull request if you wish to add anything. If you are interested, consider reading our recent survey pap

svandenh 297 Dec 17, 2022
Contrastive Loss Gradient Attack (CLGA)

Contrastive Loss Gradient Attack (CLGA) Official implementation of Unsupervised Graph Poisoning Attack via Contrastive Loss Back-propagation, WWW22 Bu

12 Dec 23, 2022
Code for the paper: Sketch Your Own GAN

Sketch Your Own GAN Project | Paper | Youtube | Slides Our method takes in one or a few hand-drawn sketches and customizes an off-the-shelf GAN to mat

677 Dec 28, 2022
Neural Cellular Automata + CLIP

🧠 Text-2-Cellular Automata Using Neural Cellular Automata + OpenAI CLIP (Work in progress) Examples Text Prompt: Cthulu is watching cthulu_is_watchin

Mainak Deb 21 Dec 19, 2022
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)

PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.

PyG 16.5k Jan 08, 2023
Computer-Vision-Paper-Reviews - Computer Vision Paper Reviews with Key Summary along Papers & Codes

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio

Jonathan Choi 2 Mar 17, 2022
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning

TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig

Yixuan Su 79 Nov 04, 2022