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July 2017 Edition

Trading Using Machine Learning In Python Part-2


Catch the part two of Trading using Machine in Python. Learn how to check if the algorithm is over fitting/under fitting. The blog also explains how to predict the regime by using an unsupervised machine learning model. Also, you will learn to check the parameters used in the classification, and finally, print the output to verify the same.


Intro to Machine Learning for Trading

Quantra™ launched a course on ‘Introduction to Machine Learning for Trading’ in June and in no time, more than 2000 people signed up. The course has also received 45+ ratings having average rating of 4+.

Trading Markets Using APIs

Automated trading using APIs has gained good popularity. This post provides a brief overview of Application Programming Interfaces (APIs) in context of trading, different types and examples of some platform providers offering such APIs for trading.

Latest on QuantInsti's #AlgoBlog

An Algorithmic Trading Guide For Retail Traders

The article explains the step-by-step backtesting of the “52-Weeks High Effect in Stocks” trading strategy using R programming. The strategy paper has been sourced from the Quantpedia site where you can explore other trading strategies as well.

Dispersion Trading on NSE Stocks

How to trade using machine learning in python? This blog will explain machine learning that can help with new tool to generate more alpha with one such module. Learn how to create hyper-parameters, data splitting, making predictions and more!

QuantInsti™ last week hosted a successful webinar on “Classification of Trading Strategies” which was conducted by Radovan Vojtko, CEO and Head of Research at Quantpedia. The webinar saw a big turnout comprising of traders, quants, fund managers, students and academics. Catch the recording of the webinar in case you missed it. Watch it now! 

Trade With The Sharks: July 24th - July 28th


A full week of action with several of the industry's premiere traders & educators. Learn from battle-tested professionals with 50+ years of combined trading experience. Seats are limited, so register for free