Quantiacs

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This is the current Quantiacs toolbox which includes the backtester for developing and testing trading algorithms. This library is designed for both beginners and seasoned traders, enabling the development and testing of trading algorithms. Quantiacs hosts a variety of quant competitions, catering to different asset classes and investment styles:. Since , Quantiacs has hosted numerous quantitative trading contests, allocating over 38 million USD to winning algorithms in futures markets. Since , the platform has expanded to include contests for predicting futures, cryptocurrencies, and stocks. The Quantiacs library QNT is optimized for local strategy development.

Quantiacs

This is the current Quantiacs toolbox which includes the backtester for developing and testing trading algorithms. Python 45 This repository contains the documentation for the current Quantiacs project. Stylus 2 1. This template shows how to make a submission to the Nasdaq contest and contains some useful code snippets. Jupyter Notebook 1 1. This template shows how the implemented backtester allows for a walking retraining of your model. Jupyter Notebook 1. This example shows how to use supervised learning for writing a trading system on stocks. Jupyter Notebook 4. This example showcases a trading strategy based on fundamental data on the Quantiacs platform. The strategy uses Nasdaq index data and focuses on liquid stocks. Predicting stocks using technical indicators atr, lwma. Predicting stocks using technical indicators trix, ema. Predicting stocks using the SPX index.

Topics python data-science trading. December

Quantiacs is a crowd-sourced quant platform hosting algorithmic trading contests and a marketplace serving investors and quants. Quantiacs was founded in The company has grown from a base of users of 6, quants in April [2] to over 10, quants in January The company invests some of its own money in the competition winners and aims to become a marketplace for automated trading systems. The performance of the algorithms can be controlled on the Quantiacs website as their charts are publicly displayed. The company focuses on quantitative strategies with long term performance horizons, highly scalable and with multiple years of backtested data.

This is the current Quantiacs toolbox which includes the backtester for developing and testing trading algorithms. Python 45 This repository contains the documentation for the current Quantiacs project. Stylus 2 1. This template shows how to make a submission to the Nasdaq contest and contains some useful code snippets. Jupyter Notebook 1 1. This template shows how the implemented backtester allows for a walking retraining of your model. Jupyter Notebook 1. This example shows how to use supervised learning for writing a trading system on stocks.

Quantiacs

Quick Start. Working with Data. User Guide. Api Reference. Quantiacs hosts quantitative trading contests since and has allocated more than 30M USD to winning algorithms on futures markets. We are expanding the universe of assets you can use and adding new tools. Participate to our competitions and take one of the top spots. Open the strategy development tab ;. Create a strategy from scratch or clone one of the provided templates; after cloning you will be able to edit your strategy. Submit strategies and monitor their live performance in your private area.

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Top languages Jupyter Notebook Python Stylus. This example showcases a trading strategy based on fundamental data on the Quantiacs platform. Go to the head of this page and follow the instructions for conda. Run all cells to test your strategy in the Jupyter Notebook. Dismiss alert. Single Command Setup. United States. You switched accounts on another tab or window. Predicting stocks using the SPX index. The Economic Times. Updating the pip environment. Last updated Name Stars. Quantiacs is a crowd-sourced quant platform hosting algorithmic trading contests and a marketplace serving investors and quants.

This is the current Quantiacs toolbox which includes the backtester for developing and testing trading algorithms.

Contributors 4. This example demonstrates a basic long-short trading strategy based on the crossing of two simple moving averages SMAs with lookback periods of 20 and trading days. Request a Preqin Pro demo for full access to all profiles and underlying data. This organization has no public members. Natural Resources. Private Debt. Showing 1 of 1 hedge funds managed by Quantiacs Request a Demo to see more. Real Estate. Unlock exclusive data on future plans, company financials, fundraising history, track records, and more. Hidden categories: Orphaned articles from December All orphaned articles. About This is the current Quantiacs toolbox which includes the backtester for developing and testing trading algorithms. Quantiacs hosts a variety of quant competitions, catering to different asset classes and investment styles:. There are 2 options:.