Artificial Intelligence (or AI) is already playing a role and it is changing the markets in many ways. In this blog post, the author shares his views on the repercussions of this transformation. What you'll learn: Covered Call, Protective Put, Iron Condor, Bull Call, Bear Put

Learn basics to advanced concepts in machine learning and its implementation in financial markets. Includes deep learning, tensor flows, installation guides, downloadable strategy codes along with real-market data.

The most challenging part of trading is to decide when to exit a position. This EPAT Project could help you predict when to exit a BUY/ SELL position ie. in predicting SL/TP signal without human intervention, by using Machine Learning. This article is the final project submitted by the authors as a part of their coursework in the Executive Programme in Algorithmic Trading (EPAT) at QuantInsti . Do check our Projects page and have a look at what our students are building. Sunanda Balla is a senior data scientist building algorithmic trading models using machine learning.

Machine learning is increasing in popularity and is a buzzword in the quantitative finance community. After all, it is a branch of artificial intelligence where algorithms and mathematical models are used to progressively improve performance on a specific task. Today we will be covering the basic framework of coding out a machine learning algorithm on FXCM's CFD index, SPX500. This article is based on the free course Introduction to Machine Learning by QuantInsti. The machine learning algorithm in this article will learn from basic open and close data.

I work at QuantInsti, a leading global institute which imparts training in Algorithmic trading. As a quantitative writer and a trader, my world mostly revolves around volatile markets, trending stocks, programming trading strategies, scouting for alphas, and writing on topics that give an insight into the automated trading world. Naturally, as a part of my daily readings, I am accustomed to words that generally form part of a financial markets glossary. However, in the past few weeks & months, I found myself reading more and more on the surging layoffs, impact of automation, the rise of robots and the threat to our future. The list of such articles on the net seemed endless.

'Looks can be deceiving,' a wise person once said. The phrase holds true for Algorithmic Trading Strategies. The term Algorithmic trading strategies might sound very fancy or too complicated. However, the concept is very simple to understand, once the basics are clear. In this article, I will be telling you about algorithmic trading strategies with some interesting examples. If you look at it from the outside, an algorithm is just a set of instructions or rules. These set of rules are then used on a stock exchange to automate the execution of orders without human intervention. This concept is called Algorithmic Trading.