All Projects → JerBouma → Algorithmictrading

JerBouma / Algorithmictrading

Licence: mit
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.

Programming Languages

python
139335 projects - #7 most used programming language

Projects that are alternatives of or similar to Algorithmictrading

Research
Notebooks based on financial machine learning.
Stars: ✭ 714 (+354.78%)
Mutual labels:  jupyter-notebook, finance, algorithmic-trading
Mixture model trading public
Stars: ✭ 166 (+5.73%)
Mutual labels:  jupyter-notebook, finance, algorithmic-trading
Pyportfolioopt
Financial portfolio optimisation in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity
Stars: ✭ 2,502 (+1493.63%)
Mutual labels:  jupyter-notebook, finance, algorithmic-trading
Alphalens
Performance analysis of predictive (alpha) stock factors
Stars: ✭ 2,130 (+1256.69%)
Mutual labels:  jupyter-notebook, finance, algorithmic-trading
Fetching Financial Data
Fetching financial data for technical & fundamental analysis and algorithmic trading from a variety of python packages and sources.
Stars: ✭ 137 (-12.74%)
Mutual labels:  jupyter-notebook, algorithmic-trading
Financial Machine Learning
A curated list of practical financial machine learning tools and applications.
Stars: ✭ 2,172 (+1283.44%)
Mutual labels:  finance, algorithmic-trading
Python For Data Science
A blog for data analytics using data science technologies
Stars: ✭ 139 (-11.46%)
Mutual labels:  jupyter-notebook, finance
Data Science Portfolio
A Portfolio of my Data Science Projects
Stars: ✭ 149 (-5.1%)
Mutual labels:  jupyter-notebook, finance
Tradingstrategies
Algorithmic trading strategies
Stars: ✭ 120 (-23.57%)
Mutual labels:  finance, arbitrage
Finrl Library
FinRL: Financial Reinforcement Learning Framework. Please star. 🔥
Stars: ✭ 3,037 (+1834.39%)
Mutual labels:  jupyter-notebook, finance
Simfin Tutorials
Tutorials for SimFin - Simple financial data for Python
Stars: ✭ 150 (-4.46%)
Mutual labels:  jupyter-notebook, finance
Roq Api
API for algorithmic and high-frequency trading
Stars: ✭ 132 (-15.92%)
Mutual labels:  algorithmic-trading, arbitrage
Turingtrader
The Open-Source Backtesting Engine/ Market Simulator by Bertram Solutions.
Stars: ✭ 132 (-15.92%)
Mutual labels:  finance, algorithmic-trading
Ipytracer
📊 Algorithm Visualizer for IPython/Jupyter Notebook
Stars: ✭ 138 (-12.1%)
Mutual labels:  algorithm, jupyter-notebook
Codetective
a tool to determine the crypto/encoding algorithm used according to traces from its representation
Stars: ✭ 121 (-22.93%)
Mutual labels:  analysis, algorithm
Data structures and algorithms in python
📖 Worked Solutions of "Data Structures & Algorithms in Python", written by Michael T. Goodrich, Roberto Tamassia and Michael H. Goldwasser. ✏️
Stars: ✭ 147 (-6.37%)
Mutual labels:  algorithm, jupyter-notebook
Datagene
DataGene - Identify How Similar TS Datasets Are to One Another (by @firmai)
Stars: ✭ 156 (-0.64%)
Mutual labels:  jupyter-notebook, finance
Pastas
🍝 Pastas is an open-source Python framework for the analysis of hydrological time series.
Stars: ✭ 155 (-1.27%)
Mutual labels:  analysis, jupyter-notebook
Gobacktest
event-driven backtesting framework written in golang
Stars: ✭ 113 (-28.03%)
Mutual labels:  finance, algorithmic-trading
Analyzing neural time series
python implementations of Analyzing Neural Time Series Textbook
Stars: ✭ 117 (-25.48%)
Mutual labels:  analysis, jupyter-notebook

Algorithmic Trading

This repository contains three ways to obtain arbitrage:

  • Dual Listing Arbitrage
  • Options Arbitrage
  • Statistical Arbitrage

These are projects in collaboration with Optiver and have been peer-reviewed by staff members of Optiver. Therefore, much of the analysis are correct and give an indication how these methods work.

Please note that these methods can only be effective when written in C++ as speed is of utmost performance. Next to that it requires a lightning fast connection (talking in nanoseconds) which is not feasible for the retail investor. Any profits made by using these strategies is therefore by pure chance.

I suggest using my FinanceDatabase to do fundamental analysis and base your investment decisions on that since it has proven to be profitable.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].