Introduction to Quant Research
A quant strategy is a systematic strategy, driven by data and the model, which is programmed to generate investment decisions.
The main pillar within quant research is the scientific method.
Big Data Management 4 - Using the Datalake in Zipline
In this article, we will create a solution to use any type of data within a zipline pipeline. We will create an algorithm that queries the datalake, performs the appropriate transformations, and subsequently ingests the data into zipline within the so-called bundle.
Big Data Management 3 - Building a Datalake on the Nasdaq with ArcticDB.
In this article, we will explore the creation of an algorithm to manage financial data in our datalake, using ArcticDB as the backend and the End Of Day Historical (EODH) data provider.
Big Data Management. 2 - First Lines of Code
In the previous article, we introduced NoSQL databases and their advantages, use cases, and relevant justifications.
Big Data Management. 1 - Introduction to Big Data for Trading with ArcticDB
This article explains the characteristics and qualities of a datalake, while also explaining an execution plan for its creation based on Python and ArcticDB.
The Working Environment - 1
In this new article, we cover how to create a professional environment for algorithmic quant trading. To do so, we use a stack of technologies that make deployment easier, allowing us to focus on pure research rather than infrastructure.
