Thursday 15th June, 8:30 PM IST | 8:00 AM PST | 11:00 AM EST
Introduction to Machine Learning
Everyone is talking about Machine learning these days. This exciting webinar on Machine Learning will take you through the basics of machine learning, it will cover the cool features of the Quantiacs toolkit, and illustrate how to create and test machine learning strategies using Quantiacs.
An Overview of Machine Learning
The Machine Learning Process
Various Features of Quantiacs toolkit
Applying Machine Learning to Futures Data Using Quantiacs
QuantInsti will be hosting one-of-a-kind webinar with three leading experts from across the globe. Register for the webinar to learn to trade fundamentals profitably, understand the challenges surrounding High-frequency data analysis, discover the opportunities and gotchas in Futures trading, and view a live demonstration of a step-by-step tutorial on one of the most popular trading strategies, the Pairs trading strategy!
Don’t miss out on this opportunity to learn from the market practitioners themselves
Asset returns based on low frequency prices (e.g. end-of-day quotes) are still dominating modern portfolio analysis. To make portfolio metrics more relevant intraday and improve the precision of estimates, new data frequency needs to be explored.
In this presentation we demonstrate how using high frequency market data for portfolio risk management and optimization could improve the classic variance-bias trade-off and bring new insights to strategy backtesting.
Since high frequency prices require special handling, we discuss key components of an automatic model pipeline for microstructure noise, price jumps, outliers, fat tails and long-memory.
We conclude our presentation with an introduction to high frequency portfolio optimization built on top of intraday portfolio metrics. Examples will be shown in Python. (more…)
No worries, because Quantinsti’s back with the webinar that eased the lives of thousands of attendees. This time, it is only getting bigger as Interactive Brokers themselves are hosting an insightful session on Implement Algo Trading coded in Python using Interactive Brokers API.
Many quant traders and researchers prefer Python algorithmic trading these days over other programming languages as Python help them build their own data connectors, execution mechanisms, backtesting engines, risk and order management system, Walk forward and Optimization testing modules.
For Individuals new to algorithmic trading, Python code is easily readable and understandable. Python is easier to write and evaluate Algo trading structures because of its functional programming approach.