Crowdsourcing of trading algorithms

More recently, several algorithmic trading firms have begun to offer investment platforms that provide access to data and a programming environment to crowd-source risk factors that become part of an investment strategy, or entire trading algorithms. Key examples include WorldQuant, Quantopian, and, launched in 2018, Alpha Trading Labs.

WorldQuant managed more than $5 billion for Millennium Management with $34.6 billion AUM since 2007 and announced in 2018 that it would launch its first public fund. It employs hundreds of scientists and many more part-time workers around the world in its alpha factory that organizes the investment process as a quantitative assembly line. This factory claims to have produced 4 million successfully tested alpha factors for inclusion in more complex trading strategies and is aiming for 100 million. Each alpha factor is an algorithm that seeks to predict a future asset price change. Other teams then combine alpha factors into strategies and strategies into portfolios, allocate funds between portfolios, and manage risk while avoiding strategies that cannibalize each other.

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