MRYingLEE/BackTesting-LowLaterncy MRYingLEE/BackTesting-LowLaterncy

  • This repository has been archived on 14/Jul/2021
  • Stars
    star
    9
  • Rank 1,939,727 (Top 39 %)
  • Language
    Jupyter Notebook
  • Created over 5 years ago
  • Updated over 5 years ago
Twitter logo Share LinkedIn logo Share Facebook logo Share
MRYingLEE/BackTesting-LowLaterncy
github

MRYingLEE

Reviews

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Repository Details

This is a backtesting demo in Python. Different moving average prices are used to make buy and sell decisions. A Jupyter notebook version is for serial mode. while py version is for multiprocessing. A version for GPU has been tried, but not successful.

More Repositories

1

kdb-q

A cheat sheet notebook of Q language of Kx.com. Kdb+ is the worldโ€™s fastest time-series database and q is its unique language. Most codes are modified from the samples of the book "Q for Mortals". All credits belong to Jeffry A. Borror, the author.
Jupyter Notebook
28
star
2

Stock.AI

This project tries to use AI, specifically reinforcement learning, to manage a stock portfolio. The objective is to be practical. So this is not only a demo of AI application in investment. This project is still at its early days. I will try to complete it in 1 year.
Jupyter Notebook
19
star
3

Time-series-Preprocessing-Studio-in-Jupyter

Time-series Data Preprocessing Studio in Jupyter notebook.
Jupyter Notebook
16
star
4

Trading_by_Imitation_Learning

This repo is using imitating learning to optimize portfolio. The code was derived from https://github.com/vermouth1992/drl-portfolio-management .
Jupyter Notebook
10
star
5

Stock-Price-Specific-LSTM

This is a basic LSTM application on stock (securities) market. The project uses Keras+ Tensorflow.
Python
8
star
6

MLOps-Jupyter-Templates

Some collected and improved Jupyter Notebook Templates for MLOps, mainly for Kubeflow pipelines on GCP Vertex AI platform and Tensorflow Extended pipelines.
Jupyter Notebook
4
star
7

Portfolio_GYM

This is an OPENAI gym reinforcement learning environment for investing. There are portfolio performance and risk metrics functions built in. These functions can be used to evaluate your algorithm and also in reward engineering.
Python
3
star
8

Stock-HIGH-LOW-Prediction

To predict stockโ€™s day HIGH and LOW prices based on its OPEN and historical daily price by LSTM model.
Jupyter Notebook
3
star
9

Financial-Time-Series-Lab

This is a financial time series lab in Jupyter notebook. You may treat it as a live cheat sheet.
2
star
10

Apache_Spark_in_Google_Colab

This is a Jupyter Notebook to practice Apache Spark in Google Colab, especially for the exam CCA Spark and Hadoop Developer Exam (CCA175).
Jupyter Notebook
2
star
11

Attributes-Based-Access-Control-on-BigQuery-Analytics

An Attributes Based Access Control POC solution on BigQuery for Analytics
1
star
12

DeepTime-Deep-Learning-Framework-for-Time-Series-Forecasting

This is an INTERACTIVE deep learning framework for time series forecasting. It uses Tensorflow 2+tf.karas.
Jupyter Notebook
1
star