April 2017 Edition

How to use Mixture Models to Predict Market Bottoms 


Register for the webinar to learn how Mixture Models work and explore its application to predict an asset’s return distribution and identify outlier returns that are likely to mean revert. The webinar will cover designing the research experiment, defining and evaluating the strategy and further areas to explore on the topic.

Learn the basics of XGBoost, a winning model for many kaggle competitions. The post includes a sample of XGBoost stock forecasting model using the “xgboost” package in R programming. Learn how to train the data, make predictions on test data, evaluate model performance, and to plot the XGBoost trees.

What's new @Quantra


Trading Using Options Sentiment Indicators

This self-paced course teaches you to build trading strategies in Python to trade futures using options as sentiment indicators through videos and guided hands-on coding. Indicators like Volatility Index, Put/Call ratio, and Arms Index are covered in detail. Get certification from QuantInsti and lifetime access to the course.

Featured Alumnus


Mr. Indradeap Chatterjee


Mr Indradeap Chatterjee has been successfully placed by QuantInsti’s placement cell with PRB Securities as a Trading Strategist in Kolkata, India. Indradeap has a Bachelor of Commerce degree with Honors from St. Xavier’s College, Kolkata and has cleared all three levels of the CFA program.                                                         

Latest on QuantInsti's #AlgoBlog

R Package for IB

Architecture of IBrokers Package  

This post explains the architecture of IBrokers R implementation in Interactive Brokers which allows executing orders in the IB Trader Workstation (TWS). Learn the various key functions from the package, real-time data model structure, Callback argument, and a sample strategy in R.

Machine Learning for Quants and Traders

Overview of Machine Learning in Trading

This post highlights the growing importance of machine learning in trading across markets for quants and traders and its wide adoption by firms worldwide. Know various ML resources, ML competitions, firms using ML strategies and the future of machine learning in trading.

Setting-Up an Algo Trading Desk

Aspire to set-up your own Algo Trading Desk! Read this unique blog that for setting up an algorithmic trading desk. It covers capital requirement, infrastructure set-up, access to market, algorithmic trading platforms, trading paradigms, team creation and more!