Quantiacs

toolbox

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

strategy-ml-crypto-long-short

This example shows how to use supervised learning for writing a trading system on stocks.

documentation

This repository contains the documentation for the current Quantiacs project. Check it out at: https://quantiacs.com/documentation/en/

strategy-blank

A basic template for creating trading systems from scratch.

strategy-cryptofutures-ml-ridge-with-futures

This template uses supervised learning for taking trading decisions. The example uses multiple features and is based on Ridge regression.

strategy-first-crypto-daily-long

This template shows how to make a submission to the Nasdaq-100 contest and contains some useful code snippets.

strategy-futures-commodity

This template uses external commodity International Monetary Fund data for creating an algorithm for futures contracts.

strategy-futures-currency

This template uses International Monetary Fund currency data and shows an algorithm for futures contracts.

strategy-futures-trend-following

This template contains a trend-following strategy for futures contracts.

strategy-ml-backtester

This template shows how the implemented backtester allows for a walking retraining of your model.

strategy-ml-predict-BTC-use-IMF

This template shows how to use International Monetary Fund Data for predicting the price of Bitcoin futures contracts.

strategy-futures-bls

This template uses data from the Bureau of Labor Statistics for trading futures contracts.

strategy-ml-nn

This example shows how to use neural networks for writing a trading system on stocks.

Stateful-Long-Short-strategy

Long-Short strategy with tehnical indicators and take profit, stop loss and days counter exits

strategy-cryptofutures-ml-ridge

This template uses supervised learning for taking trading decisions. The example runs on stocks and is based on Ridge regression.

strategy-futures-optimization-each-asset

This template shows how to perform optimization of indicator parameters for each asset.

strategy-futures-ta-global-optimizer

This template shows how to use the Quantiacs global optimizer to study parametric dependence of the results and control optimal parameters.

strategy-futures-trending-custom-args

This template contains an improved trend-following strategy for futures contracts.

strategy-ml-voting-crypto

This template uses voting for combining classifiers and it shows how to use the backtester with retraining option.

strategy-ml_lstm_multiple_features

This example shows how to use neural networks for writing a trading system on stocks.

strategy-ml_lstm_state

This example shows how to use neural networks for writing a trading system on stocks using state

strategy-predict-NASDAQ100-use-atr-lwma

Predicting stocks using technical indicators (atr, lwma)

strategy-predict-NASDAQ100-use-SPX

Predicting stocks using the SPX index

strategy-predict-NASDAQ100-use-trix-ema

Predicting stocks using technical indicators (trix, ema)

strategy-q18-nasdaq100-quick-start

strategy-q20-nasdaq100-fundamental-data-quick-start

This example showcases a trading strategy based on fundamental data on the Quantiacs platform. The strategy uses Nasdaq 100 index data and focuses on liquid stocks.

strategy-q20-nasdaq100-quick-start

This guide introduces you to a Dual Simple Moving Average Crossover strategy implemented on the Quantiacs platform. The strategy uses Nasdaq 100 index data and focuses on liquid stocks.

strategy-stateful_long_short_with_exits

strategy-stateful_strategy_optimization