shithead548

shithead548's Stars

• h5bp/html5-boilerplate

  A professional front-end template for building fast, robust, and adaptable web apps or sites.

  Language:JavaScript56.7k2.5k1.3k12.3k

• uikit/uikit

  A lightweight and modular front-end framework for developing fast and powerful web interfaces

  Language:HTML18.4k6464.3k2.3k

• microsoft/dotnet

  This repo is the official home of .NET on GitHub. It's a great starting point to find many .NET OSS projects from Microsoft and the community, including many that are part of the .NET Foundation.

  Language:HTML14.5k1.3k6742.2k

• ruanyf/jstutorial

  Javascript tutorial book

  Language:CSS5.4k4211411.3k

• sofish/pen

  enjoy live editing (+markdown)

  Language:JavaScript4.8k139119411

• Azure/azure-sdk-for-python

  This repository is for active development of the Azure SDK for Python. For consumers of the SDK we recommend visiting our public developer docs at https://learn.microsoft.com/python/azure/ or our versioned developer docs at https://azure.github.io/azure-sdk-for-python.

  Language:Python4.7k47310.5k2.9k

• yhat/ggpy

  ggplot port for python

  Language:Python3.7k125467573

• fibjs/fibjs

  JavaScript on Fiber (built on Chrome's V8 JavaScript engine)

  Language:C++3.1k171277300

• mpld3/mpld3

  An interactive data visualization tool which brings matplotlib graphics to the browser using D3.

  Language:Jupyter Notebook2.4k82359361

• kevinlawler/kona

  Open-source implementation of the K programming language

  Language:C1.4k59561140

• enewhuis/liquibook

  Modern C++ order matching engine

  Language:C++1.2k12624388

• ematvey/pybacktest

  Vectorized backtesting framework in Python / pandas, designed to make your backtesting easier — compact, simple and fast

  Language:Python8057124242

• twitter/BreakoutDetection

  Breakout Detection via Robust E-Statistics

  Language:C++75516225180

• panpanpandas/ultrafinance

  Python project for real-time financial data collection, analyzing && backtesting trading strategies

  Language:Python425752150

• danielktaylor/PyLimitBook

  Python implementation of fast limit-order book.

  Language:Python30818570

• Kitware/tangelo

  A simple, quick, powerful web framework

  Language:JavaScript1852743635

• jordanbaucke/Limit-Order-Book

  Various implementations of limit order books (matching engines)

  Language:Objective-C11718055

• svenkreiss/databench

  Data analysis tool.

  Language:Python846613

• prystupa/scala-cucumber-matching-engine

  This repo backs a series of posts that walk through developing an equity exchange prototype using Scala and test driving the development with Cucumber

  Language:Scala5813021

• harpone/PyArb

  Statistical arbitrage simulation, modeling and backtesting with Python.

  Language:HTML5712025

• nipunbatra/mpld3-flask

  Language:CSS428114

• crtr0/votr-part1

  Part 1 of building an SMS voting app using Node.js

  Language:JavaScript376214

• sduprey/optimal_transaction_execution

  This entry contains two topics The first item is entirely based on the following paper: http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2011-056.pdf It contains 2 MATLAB demonstrating script : DATA_preprocessing.m & VAR_modeling_script.m DATA_preprocessing.m uses the LOBSTER framework (https://lobster.wiwi.hu-berlin.de/) to preprocess high frequency data from the NASDAQ Total View ITCH (csv files) allowing us to reconstruct exactly at each time the order book up to ten depths. Just look at the published script ! VAR_modeling_script.m contains the modeling of the whole order book as VEC/VAR process. It uses the great VAR/VEC Joahnsen cointegration framework. After calibrating your VAR model, you then assess the impact of an order using shock scenario (sensitivity analysis) to the VAR process. We deal with 3 scenarii : normal limit order, aggressive limit order & normal market order). Play section by section the script (to open up figures which contain a lot of graphs). It contains a power point to help you present this complex topic. The second item is entirely based on the following paper : http://www.courant.nyu.edu/~almgren/papers/optliq.pdf It contains a mupad document : symbolic_demo.mn I did struggle to get something nice with the symbolic toolbox. I was not able to drive a continuous workflow and had to recode some equations myself. I nevertheless managed to get a closed form solution for the simplified linear cost model. It contains a MATLAB demonstrating script : working_script.m For more sophisticated cost model, there is no more closed form and we there highlighted MATLAB numerical optimization abilities (fmincon). It contains an Optimization Apps you can install. Just launch the optimization with the default parameters. And then switch the slider between volatility risk and liquidation costs to see the trading strategies evolve on the efficient frontier. It contains a power point to help you present this complex topic.

  Language:Matlab345018

• beshrkayali/rtsat

  Flask + Gevent-socketio + Smoothie charts + Twitter's Streaming API = Realtime Tweets Sentiment Analysis Tool

  Language:JavaScript31609

• bigdata-trading/algo-trading-strategies

  Big Data course project (EPFL) - Trading strategies based on order book

  Language:Java307016

• alibaba-archive/pen

  enjoy live editing (+markdown)

  Language:JavaScript162302

• eneiand/OrderMatchingEngine

  A multithreaded order matching engine. The threading strategy can be changed at runtime on a per Instrument basis to one of synchronous, thread pool or dedicated number of threads.

  Language:C#15605

• AutomatedTrading/r-strategies

  Trading strategies implemented in R

  Language:R52

• Dlotan/py-editor

  Collaborative Python online IDE

  Language:JavaScript2100

• oci-labs/quickfix

  QuickFIX C++ Fix Engine Library

  Language:C++22101