Our aim is to help our customers perform the most realistic financial simulations possible, providing them with the ability to find new ways of extracting alpha and exploiting opportunities within the capital markets.
QuantStart's founding members have a background in equities data management and machine learning implementation within the hedge fund industry. This gives us a detailed insight into the needs of quant traders and data scientists—experience which translates directly into the quality of our data.
In a world where discretionary trading is giving way to vast capital inflows into quantitative asset managers, we believe robust financial data is the key to unlocking investment outperformance in the coming years.
QuantStart was originally founded in 2012 to provide detailed educational resources for prospective and practising quantitative analysts.
In the intervening years QuantStart has grown to publish over 200 tutorials and three highly popular textbooks on the topics of quantitative finance, mathematics, software development, algorithmic trading and machine learning.
In 2015 development commenced on the QSTrader open-source backtesting platform, which is designed to integrate fully with our robust data sources. Our internal software development team has partnered with a dedicated group of global volunteer developers to continue to push QSTrader forward.
In late 2016 QuantStart began investing heavily in financial data infrastructure, as well as partnering with leading providers, to offer comprehensive historical backtesting datasets to the quant, data science and investment community.