Data Science for Finance: Quantitative Trading Strategies by Nick Firoozye

Online Course Running Time: 13 Hours 

Goals: This course is for those who wish to

Professionals - Understand the mechanics of standard implementations of the single asset and portfolio based risk-premia trading strategies, the basis for CTAs and Quant funds, Equities Quant funds, position taking by e-traders/market-makers and a standard set of strategies in HFT. Recognize pros and cons of various approaches to designing strategies and the common pitfalls encountered by algorithmic traders. Be able to devise new and improved algorithmic strategies.

Algorithmic Traders - Recognize the reasons commonly-used strategies work, the basis for why they should, and when they don't. Understand the statistical properties of strategies and discern the mathematically-proven from the empirical.  Acquire and improve methods to prevent overfitting.

Academics/students - Gain familiarity with the broad area of algorithmic trading strategies. Master the underlying theory and mechanics behind the most common strategies. Acquire the understanding of principals and the context necessary for new academic research into the large number of open questions in the area.

Published date

Monday, 4 June, 2018