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akumuli

Time-series database

alphasim

Minimalist backtester designed to integrate with the quant workflow.

arch-linux-arm-m1

bitwarden_self_host

Automatically setup and host a Bitwarden instance on a Raspberry Pi or other Linux Server

darwinexlabs

Datasets, tools and more from Darwinex Labs - Prop Investing Arm & Quant Team @ Darwinex

dislocker

FUSE driver to read/write Windows' BitLocker-ed volumes under Linux / Mac OSX

django-docs

a simple example of document upload

dockeroandafeeder

Docker Oanda DATA Fedder

dwx-zeromq-connector

Wrapper library for algorithmic trading in Python 3, providing DMA/STP access to Darwinex liquidity via a ZeroMQ-enabled MetaTrader Bridge EA.

exchange-api-go

fecon235

Notebooks for financial economics. Keywords: Jupyter notebook pandas Federal Reserve FRED Ferbus GDP CPI PCE inflation unemployment wage income debt Case-Shiller housing asset portfolio equities SPX bonds TIPS rates currency FX euro EUR USD JPY yen XAU gold Brent WTI oil Holt-Winters time-series forecasting statistics econometrics

goanda

A Golang wrapper for OANDAs v20 API

oandafeeder

Oanda Data Feeder for marketstore

ray_custom_loss

ray_tests

research

Contains all the Jupyter Notebooks used in our research

risk-premia-app

Simple Risk Premia Strategy

slow-momentum-fast-reversion

This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (https://arxiv.org/pdf/2105.13727.pdf).

stacked-autoencoders-financial-trading

Deep Learning via Neural Network featured with Stacked Auto Encoders for Financial Trading Application in R

statelesscartpolemd

MultiDiscrete

stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

t6converter

Converter for Zorro

tmwr

Code and content for "Tidy Modeling with R"

trading-momentum-transformer

This code accompanies the the paper Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture (https://arxiv.org/pdf/2112.08534.pdf).

trajectorytracking

triplebarrier

Zorro triple barrier test case

wsae-lstm

implementation of WSAE-LSTM model as defined by Bao, Yue, Rao (2017)

zorrorandomstrategybenchmark

Repository to develop a benchmark to test a strategy against several random strategies