This post covers the basics of XGBoost machine learning model, along with a sample of XGBoost stock forecasting model using the “xgboost” package in R programming....

This post explains the architecture of IBrokers R implementation in Interactive Brokers API which allows executing orders in the IB Trader Workstation (TWS)....

Trend-following strategy based on the indicators like MACD, SuperTrend, and ADX coded in Python, which is a part of EPAT™ coursework at QuantInsti®....

Complete RecordingCheck out the complete recording of the webinar here: About the eventQuantInsti will be...

Trading using R on Interactive Brokers The session would be covering Installing R-studio IDE Reference sheet for the IBroker Package....

Implied Volatility: From Theory to Practice Volatility is a cornerstone concept in options trading, and...

This webinar offers a unique chance for attendees to interact with a team of Quants & HFT developers on a one-to-one level and ask career-related queries you might have....

This project work explains the implementation of a Pairs Trading strategy using Kalman Filter in Executive Programme in Algorithmic Trading (EPAT™) Course....

Short recap of what happened during 2016 at QuantInsti, which is one of Asia’s pioneer Algorithmic Trading Research and Training Institute...

In this post we defined market impact cost, factors driving it, and learned why the cost assume significance for portfolio managers....