High frequency AI based algorithmic trading module.

Overview

Flow

Flow is a high frequency algorithmic trading module that uses machine learning to self regulate and self optimize for maximum return.

The current approach uses a stack of financial indicators which is consumed by a Q-learning algorithm which determines an Agent's action at a given step in the stream of financial quotes.

Flow uses an idea called Scopes which is essentially a sampling of the time series quotes to discover trends along any sort of time interval. At every moment, the Supervisor ensures there is at least one Agent per scope looking for an opportunity to make a profitable trade.

Currently trades CAD/USD from quotes taken from January 2016. A fork that actually ties into a trading platform practice account has also been developed - this fork actually makes a profit before accounting for spread.

Installation

  1. Clone the project:

    $ git clone https://github.com/yazanobeidi/flow.git && cd flow

  2. Pip-install dependencies. For example using a virtualenv:

    $ virtualenv env && source env/bin/activate && pip install -r requirements.txt

Usage

  1. To live stream transactions, open a second terminal window and:

    $ tail -f -n 40 logs/bankroll.log

  2. Now to run Flow, back to the first tab:

    $ python python/executive.py

  3. The simulation should begin to run.

Contributing

  1. Fork it
  2. Create your feature branch: git checkout -b my-new-feature
  3. Commit your changes: git commit -am 'Add some feature'
  4. Push to the branch: git push origin my-new-feature
  5. Submit a pull request

Authors

Yazan Obeidi

Matthew Robichaud

Contributors

Micheal Broughton

Copyright

2016, Yazan Obeidi

🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrai

Hugging Face 77.4k Jan 05, 2023
DrNAS: Dirichlet Neural Architecture Search

This paper proposes a novel differentiable architecture search method by formulating it into a distribution learning problem. We treat the continuously relaxed architecture mixing weight as random va

Xiangning Chen 37 Jan 03, 2023
Computational Pathology Toolbox developed by TIA Centre, University of Warwick.

TIA Toolbox Computational Pathology Toolbox developed at the TIA Centre Getting Started All Users This package is for those interested in digital path

Tissue Image Analytics (TIA) Centre 156 Jan 08, 2023
Ganilla - Official Pytorch implementation of GANILLA

GANILLA We provide PyTorch implementation for: GANILLA: Generative Adversarial Networks for Image to Illustration Translation. Paper Arxiv Updates (Fe

Samet Hi 462 Dec 05, 2022
PyTorch reimplementation of Diffusion Models

PyTorch pretrained Diffusion Models A PyTorch reimplementation of Denoising Diffusion Probabilistic Models with checkpoints converted from the author'

Patrick Esser 265 Jan 01, 2023
[TIP 2021] SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction

SADRNet Paper link: SADRNet: Self-Aligned Dual Face Regression Networks for Robust 3D Dense Face Alignment and Reconstruction Requirements python

Multimedia Computing Group, Nanjing University 99 Dec 30, 2022
Implementation of ECCV20 paper: the devil is in classification: a simple framework for long-tail object detection and instance segmentation

Implementation of our ECCV 2020 paper The Devil is in Classification: A Simple Framework for Long-tail Instance Segmentation This repo contains code o

twang 98 Sep 17, 2022
Deep Multi-Magnification Network for multi-class tissue segmentation of whole slide images

Deep Multi-Magnification Network This repository provides training and inference codes for Deep Multi-Magnification Network published here. Deep Multi

Computational Pathology 12 Aug 06, 2022
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)

SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an

Benedek Rozemberczki 202 Dec 27, 2022
A hybrid framework (neural mass model + ML) for SC-to-FC prediction

The current workflow simulates brain functional connectivity (FC) from structural connectivity (SC) with a neural mass model. Gradient descent is applied to optimize the parameters in the neural mass

Yilin Liu 1 Jan 26, 2022
A general framework for inferring CNNs efficiently. Reduce the inference latency of MobileNet-V3 by 1.3x on an iPhone XS Max without sacrificing accuracy.

GFNet-Pytorch (NeurIPS 2020) This repo contains the official code and pre-trained models for the glance and focus network (GFNet). Glance and Focus: a

Rainforest Wang 169 Oct 28, 2022
Controlling the MicriSpotAI robot from scratch

Project-MicroSpot-AI Controlling the MicriSpotAI robot from scratch Colaborators Alexander Dennis Components from MicroSpot The MicriSpotAI has the fo

Dennis Núñez-Fernández 5 Oct 20, 2022
LBBA-boosted WSOD

LBBA-boosted WSOD Summary Our code is based on ruotianluo/pytorch-faster-rcnn and WSCDN Sincerely thanks for your resources. Newer version of our code

Martin Dong 20 Sep 19, 2022
Libraries, tools and tasks created and used at DeepMind Robotics.

dm_robotics: Libraries, tools, and tasks created and used for Robotics research at DeepMind. Package overview Package Summary Transformations Rigid bo

DeepMind 273 Jan 06, 2023
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Directed Graph Contrastive Learning Paper | Poster | Supplementary The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this

Tong Zekun 28 Jan 08, 2023
Vision-and-Language Navigation in Continuous Environments using Habitat

Vision-and-Language Navigation in Continuous Environments (VLN-CE) Project Website — VLN-CE Challenge — RxR-Habitat Challenge Official implementations

Jacob Krantz 132 Jan 02, 2023
A PoC Corporation Relationship Knowledge Graph System on top of Nebula Graph.

Corp-Rel is a PoC of Corpartion Relationship Knowledge Graph System. It's built on top of the Open Source Graph Database: Nebula Graph with a dataset

Wey Gu 20 Dec 11, 2022
a minimal terminal with python 😎😉

Meterm a terminal with python 😎 How to use Clone Project: $ git clone https://github.com/motahharm/meterm.git Run: in Terminal: meterm.exe Or pip ins

Motahhar.Mokfi 5 Jan 28, 2022
Decision Transformer: A brand new Offline RL Pattern

DecisionTransformer_StepbyStep Intro Decision Transformer: A brand new Offline RL Pattern. 这是关于NeurIPS 2021 热门论文Decision Transformer的复现。 👍 原文地址: Deci

Irving 14 Nov 22, 2022