mvind

mvind's Stars

• kernc/backtesting.py

  :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python.

  Language:Python5.4k1204991.1k

• letianzj/QuantResearch

  Quantitative analysis, strategies and backtests

  Language:Jupyter Notebook1.9k644416

• philipperemy/keras-tcn

  Keras Temporal Convolutional Network.

  Language:Python1.9k48171455

• hfawaz/dl-4-tsc

  Deep Learning for Time Series Classification

  Language:Python1.5k4847569

• nuxt/hackernews

  HackerNews clone built with Nuxt.

  Language:Vue1.3k2340262

• dwcoder/QuantitativePrimer

  An Interview Primer for Quantitative Finance

  Language:TeX1.2k386158

• alpacahq/example-hftish

  Example Order Book Imbalance Algorithm

  Language:Python752366235

• Mcompetitions/M5-methods

  Data, Benchmarks, and methods submitted to the M5 forecasting competition

  Language:Jupyter Notebook5774713232

• martellaj/chrome-extension-react-typescript-boilerplate

  🔨 A boilerplate project to quickly build a Chrome extension using TypeScript and React (built using webpack).

  Language:JavaScript5127692

• nimashahbazi/optiver-trading-close

  Language:Jupyter Notebook39910092

• okeeffed/cheat-sheets

  Language:PHP363151229

• lucidrains/q-transformer

  Implementation of Q-Transformer, Scalable Offline Reinforcement Learning via Autoregressive Q-Functions, out of Google Deepmind

  Language:Python33261019

• davecliff/BristolStockExchange

  BSE is a simple minimal simulation of a limit order book financial exchange

  Language:Jupyter Notebook297276131

• jkirkby3/PROJ_Option_Pricing_Matlab

  Quant Option Pricing - Exotic/Vanilla: Barrier, Asian, European, American, Parisian, Lookback, Cliquet, Variance Swap, Swing, Forward Starting, Step, Fader

  Language:MATLAB1715265

• greatwhiz/tft_tf2

  Temporal Fusion Transformers for Tensorflow 2.x

  Language:Python15431482

• atavakol/action-branching-agents

  (AAAI 2018) Action Branching Architectures for Deep Reinforcement Learning

  Language:Python10910823

• jerryxyx/TreasuryFutureTrading

  A statistical arbitrage strategy on treasury futures using mean-reversion property and meanwhile insensitive to the yield change

  Language:Jupyter Notebook719035

• tianchen101/MQRNN

  Multi-Quantile Recurrent Neural Network for Quantile Regression

  Language:Jupyter Notebook651219

• crunchdao/adialab-notebooks

  Language:Jupyter Notebook484119

• HFTrader/hbthreads

  A simple coroutine-based reactor library

  Language:C++486147

• mkhushi/MQL5-Python-Backtesting

  MQL5 based backtesting using python

  Language:Python474021

• WhatAShot/ExcelFormer

  The pioneering neural network surpassing extremely-tuned XGboost and Catboost on varied tabular datasets.

  Language:Python45567

• Joaopeuko/metatrader5EasyT

  This project is part of a bigger one. I want to make Algo Trading Easy for you! You can find examples and more information in the documentation. easyT, easyTo trade, easyTo use!

  Language:Python31206

• kingychiu/target-permutation-importances

  A Python Package that computes Target Permutation Importances (Null Importances) of a machine learning model.

  Language:Python14200

• Xin-Jing/Dynamic-Hedging-using-LSTM

  A new and more effective method for dynamic hedging

  Language:Python13502

• bearloga/MLPUGS

  An R package for Multi-Label Prediction Using Gibbs Sampling (and Classifier Chains)

  Language:R11443

• juliansester/nga

  Robust deep hedging and Non-linear generalized affine processes

  Language:Jupyter Notebook11103

• keelm/XDCC

  Extreme Dynamic Classifier Chains - XGBoost for Multi-label Classification

  Language:Cuda6322

• acoache/RL-ElicitableDynamicRisk

  Implementation of a risk-aware RL algorithm with conditionally elicitable dynamic risk

  Language:Jupyter Notebook41

• BGTCapital/AlgorithmicTrading

  This repository contains three ways to obtain arbitrage which are Dual Listing, Options and Statistical Arbitrage. These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver.

  Language:Jupyter Notebook2000