Algorithmic trading is becoming more accessible with cheaper computational resources and increasingly widespread knowledge of computer programming. Anyone that has a desire to automate their trading strategies can now do so at a marginal cost. This article focuses on a variety of tools that are continuously making the process to write, optimize and automate your trading strategy fairly easy. More particularly, the focus will be on two tools — Blueshift by QuantInsti and the Alpaca API for stock trading that is commission free. Prior to exploring these tools, a little background will prove to be beneficial in understanding the potential of these tools.

The Problem

Quantopian has become one of the most popular algorithmic trading tools used for learning and practicing algorithms. The platform enables users to write and backtest their algorithms using a variety of APIs. The main API, on which the whole platform is built, is a popular trading pythonic package called Zipline. They initially made live trading available by scheduling trades through the Robinhood API, which has since been terminated. Users are able to fine tune their algorithms and once they have maximized profits, users can enter their algorithms into competitions and seek sponsorship for funds. For those who are writing algorithms solely for the purpose of obtaining sponsors and funds, this is an excellent platform; however, for those that are wanting to optimize their algorithms for live trading and automation of such algorithms, this is not the ideal tool for writing and backtesting your algorithms. The reason being that all strategies written in Quantopian must be transitioned to conform with whatever trading API used to live trade. This process can be time consuming and inconvenient. However, the backtest environment created by Quantopian is incredibly useful and makes all the difference when trying to optimize your algorithm.

The Alpaca API has been developed to cater to algorithmic traders and makes live trading as well as paper trading incredibly easy. However, their API does not have any backtesting modules, so that leaves users to find other backtesting libraries or to write their own. So, ideally you would want a platform that allows users to backtest their algos and then have the capability to make their algo go live using the Alpaca API. This is where Blueshift by QuantInist enters the picture.

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