Skip to content
#

algorithmic-trading

Here are 483 public repositories matching this topic...

freqtrade
MNThomson
MNThomson commented Nov 30, 2021

Describe the enhancement

In the docs, I'm not seeing any /api/v1/healthcheck endpoint or whatnot (heartbeat specific, not referencing ping). Potentially returning the time of last heartbeat and any errors (if present).

This would be highly useful for monitoring and ensuring nothing crazy is going wrong. This would make monitoring from another server much easier and with some simple sc

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. An increasing number of SOTA Quant research works/papers are released in Qlib.

  • Updated Jan 4, 2022
  • Python
quant-trading

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

  • Updated Nov 10, 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
zillionare
zillionare commented Apr 30, 2021

this is how Buy & Hold Return is calculated:

        c = data.Close.values
        s.loc['Buy & Hold Return [%]'] = (c[-1] - c[0]) / c[0] * 100  # long-only return

so it's calced use day one and the day last.

Expected Behavior

Buy & Hold Return is used for compare with strategy gain. Therefore, I guess they should started at same time, since the strategy get enough data to w

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