Emiliano joined Quantiacs in late 2020 and sent to Quantiacs many suggestions which proved very useful for developing our platform. We had a short chat and we are sharing his thoughts.

Hi Emiliano, can you tell us something about yourself and your background?

I have always had a strong passion for technology and finance. I started following developments of the financial markets on a daily basis since I was 14 or 15 years old, mainly on satellite Bloomberg TV. Later I chose to study Computer Science and got my Masters Degree. In my Master thesis, I used several Machine Learning…


Quantiacs provides users with macroeconomic data from the U.S. Bureau of Labor Statistics. These data can be used on the cloud or downloaded locally for further analysis. In this article, we show how to use macroeconomic data for developing a trading algorithm.

Bureau of Labor Statistics Data

The U.S. Bureau of Labor Statistics is the principal agency for the U.S. government in the field of labor economics and statistics. It provides macroeconomic data in several interesting categories: prices, employment and unemployment, compensation and working conditions and productivity.

Photo by Vlad Busuioc on Unsplash

The macroeconomic data provided by the Bureau of Labor Statistics are used by the U.S. Congress and other…


In this article we describe the implementation of a new tool we released for the Quantiacs Python toolbox: a fast optimizer for testing the robustness of a trading system.

As Donald Knuth pointed out, “Premature optimization is the root of all evil.” This is a famous saying among software developers and it is true also in the context of trading system development.

Photo by Jefferson Santos on Unsplash

It is very tempting to write an algorithm, a simple trend-following strategy or a more refined machine-learning based system, and then to search for optimal parameters or hyperparameters which are going to maximize a given score function, normally…


The new Quantiacs platform allows quants to download financial data for free. Predictions for markets can be performed offline, downloading locally the Quantiacs backtester, or online, using our cloud for free. In this article, we describe a supervised learning example based on Ridge regression.

When we built Quantiacs we focused on a platform that allows quants to perform realistic trading simulations without getting lost in more technical details. We believe that high-quality trading systems for global financial markets can be developed by talented research scientists, software developers and students who are not part of the quant hedge fund industry.

Among…


In this article we describe the implementation of a simple quantitative strategy on Bitcoin Futures contract with Quantiacs.

This month we released a new version of the Quantiacs platform with several major improvements. In addition to providing a new open-source backtesting tool and the possibility to download for free financial data, we created a cloud environment for quants. Here it is possible to code trading algorithms in Python using Jupyter Notebook or JupyterLab and to run them directly online using our resources for free.

The competition model has also changed: the 15th edition of the Futures contest, based on 75…


Starting today you have access to a new version of the Quantiacs platform. This article summarizes the new competitions, lists the main new features and provides a simple example for getting started with the new version. The submission window for Futures systems and for Bitcoin Futures systems is open. Winners will get 4M USD in guaranteed allocations.

Quantiacs started Futures contests in 2014 and has allocated over 30M USD to top performing systems. The live evaluation phase of the current Q14 contest has started on January 1st, 2021 and will end on April 30th, 2021.

We are proud to announce…


Note: this article points to the Legacy Version of Quantiacs. Please check more recent material on the new version of Quantiacs: get started, simple bitcoin algorithm, machine learning example and optimizer.

In previous articles we have shown how to implement simple trading strategies in Quantiacs. Here we describe the implementation of an algorithm which uses machine learning methods.

The Python Quantiacs toolbox allows you to use machine learning methods for coding trading algorithms. We describe an example based on keras and use a Long Short-Term Memory (LSTM) model for time series forecasting.

All Quantiacs system files should contain a definition…


Note: this article points to the Legacy Version of Quantiacs. Please check more recent material on the new version of Quantiacs: get started, simple bitcoin algorithm, machine learning example and optimizer.

A unique feature of the Quantiacs toolbox is the use of asset exposure rather than discrete trades. In this short article we show a simple example which will help you in getting started.

Most trading backtester are event- or order-based. …


Note: this article points to the Legacy Version of Quantiacs. Please check more recent material on the new version of Quantiacs: get started, simple bitcoin algorithm, machine learning example and optimizer.

In this short note we summarize how Quantiacs contests work and which payouts are distributed to the winners.

The first Quantiacs contest was held in 2014. Since then, competitions took place on a regular basis and more than 30 M USD have been allocated to winning algorithms.

Users can take part to contests writing a trading strategy on futures and submitting it to the Quantiacs platform before a fixed…


Note: this article points to the Legacy Version of Quantiacs. Please check more recent material on the new version of Quantiacs: get started, simple bitcoin algorithm, machine learning example and optimizer.

This short tutorial describes how to run your systems over an array of different parameters. This step is important for exploring the stability of your system, and finding optimal parameters.

In a previous article, we describe how to code a simple trend-following strategy in Python using the Quantiacs toolbox. …

Quantiacs

Quantiacs is building a crowdsourced quant fund and provides quants worldwide with free data, software and computational resources.

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