Skip to content
#

algorithmic-trading

Here are 461 public repositories matching this topic...

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies.

  • Updated Sep 18, 2021
  • Python
quant-trading

Python quantitative trading strategies including VIX Calculator, Pattern Recognition, Commodity Trading Advisor, Monte Carlo, Options Straddle, London Breakout, Heikin-Ashi, Pair Trading, RSI, Bollinger Bands, Parabolic SAR, Dual Thrust, Awesome, MACD

  • Updated Aug 30, 2021
  • Python
Superalgos
WenceslaoGrillo
WenceslaoGrillo commented May 29, 2020

Some suggestions to make it easier to run the backend without the front end. Some of these suggestions might be *ix only:

  • a command line parameter to indicate that the back end should start with everything that is pending without waiting for a front end to be available in the browser.
  • some instruction to make it work as a daemon (Linux) or service (Windows) to gain independence from the te
backtesting.py
moodoid
moodoid commented Nov 10, 2020

I have set the reference price for the cash PnL at the spread between two securities (I am backtesting a mean reversion strategy). However, in the html output of the plot I am getting the PnL in terms of the differnce in the spread as a function of the entry price of the spread when the trade was initiated. Instead, I want to get the PnL based off of the prices of the sum of the two securities (VI

Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. >150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/

  • Updated Sep 5, 2020
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the algorithmic-trading topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the algorithmic-trading topic, visit your repo's landing page and select "manage topics."

Learn more