Time-series momentum for momentum investing strategy

Overview

Time-series-momentum


Time-series momentum strategy. You can use the data_analysis.py file to find out the best trigger and window for a given asset and/or the plot_strategy.py file to plot and compare the strategy with a given asset.


Disclaimer:

Before using any strategy, do your own research. Losses are part of trading.

This project does not constitute any offer, recommendation or solicitation to any person to enter into any transaction or adopt any hedging, trading or investment strategy, nor does it constitute any prediction of likely future movement in rates or prices or any representation that any such future movements will not exceed those shown in any illustration.

This project is not an investment advice. I accept no liability and will not be liable for any loss or damage arising directly or indirectly (including special, incidental or consequential loss or damage) from your use of this project, howsoever arising, and including any loss, damage or expense arising from, but not limited to, any defect, error, imperfection, fault, mistake or inaccuracy with this project.

Owner
Victor Caldeira
Victor Caldeira
Examples and code for the Practical Machine Learning workshop series

Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D

CompatibL 21 Jun 25, 2022
Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining

**Tutorials, examples, collections, and everything else that falls into the categories: pattern classification, machine learning, and data mining.** S

Sebastian Raschka 4k Dec 30, 2022
Practical Time-Series Analysis, published by Packt

Practical Time-Series Analysis This is the code repository for Practical Time-Series Analysis, published by Packt. It contains all the supporting proj

Packt 325 Dec 23, 2022
Scikit-Learn useful pre-defined Pipelines Hub

Scikit-Pipes Scikit-Learn useful pre-defined Pipelines Hub Usage: Install scikit-pipes It's advised to install sklearn-genetic using a virtual env, in

Rodrigo Arenas 1 Apr 26, 2022
Anomaly Detection and Correlation library

luminol Overview Luminol is a light weight python library for time series data analysis. The two major functionalities it supports are anomaly detecti

LinkedIn 1.1k Jan 01, 2023
Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models

Highly interpretable, sklearn-compatible classifier based on decision rules This is a scikit-learn compatible wrapper for the Bayesian Rule List class

Tamas Madl 482 Nov 19, 2022
LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRerank, Seq2Slate.

LibRerank LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRer

126 Dec 28, 2022
ETNA – time series forecasting framework

ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an

Tinkoff.AI 675 Jan 08, 2023
customer churn prediction prevention in telecom industry using machine learning and survival analysis

Telco Customer Churn Prediction - Plotly Dash Application Description This dash application allows you to predict telco customer churn using machine l

Benaissa Mohamed Fayçal 3 Nov 20, 2021
Crunchdao - Python API for the Crunchdao machine learning tournament

Python API for the Crunchdao machine learning tournament Interact with the Crunc

3 Jan 19, 2022
This is the code repository for LRM Stochastic watershed model.

LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit

1 Feb 14, 2022
A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search

A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search

Nicholas Monath 31 Nov 03, 2022
Time series changepoint detection

changepy Changepoint detection in time series in pure python Install pip install changepy Examples from changepy import pelt from cha

Rui Gil 92 Nov 08, 2022
A repository to work on Machine Learning course. Select an algorithm to classify writer's gender, of Hebrew texts.

MachineLearning A repository to work on Machine Learning course. Select an algorithm to classify writer's gender, of Hebrew texts. Tested algorithms:

Haim Adrian 1 Feb 01, 2022
NumPy-based implementation of a multilayer perceptron (MLP)

My own NumPy-based implementation of a multilayer perceptron (MLP). Several of its components can be tuned and played with, such as layer depth and size, hidden and output layer activation functions,

1 Feb 10, 2022
Avocado hass time series vs predict price

AVOCADO HASS TIME SERIES VÀ PREDICT PRICE Trước khi vào Heroku muốn giao diện đẹp mọi người chuyển giúp mình theo hình bên dưới https://avocado-hass.h

hieulmsc 3 Dec 18, 2021
Machine Learning Study 혼자 해보기

Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil

Teddy Lee 1.7k Jan 01, 2023
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.

Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi

BentoML 4.4k Jan 04, 2023
GRaNDPapA: Generator of Rad Names from Decent Paper Acronyms

Generator of Rad Names from Decent Paper Acronyms

264 Nov 08, 2022
Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft contributing libraries, tools, recipes, sample codes and workshop contents for machine learning & deep learning.

Microsoft 366 Jan 03, 2023