Learn Algorithmic Trading From QuantInsti
QuantInsti™ (QI) is one of Asia’s pioneer Algorithmic Trading Research and Training Institute, focused on preparing financial market professionals for the contemporary field of Algorithmic and High Frequency Trading. Headquartered in Mumbai with a subsidiary in Singapore, QI was founded by iRageCapital and a team of Quantitative and High Frequency Traders and domain experts dedicated to providing practical knowledge to professionals interested in Algorithmic Trading.
Executive Programme in Algorithmic Trading (EPATTM)
EPATTM is tailor-made algorithmic trading course for individuals working in, or intending to move into the buy or sell-side of business focusing on derivatives, quantitative trading, electronic market-making or trading related technology and risk management.
The program is built around a fully examined core of three modules:
- Statistics & Econometrics
- Algorithmic & Quantitative Trading
- Financial Computing & Technology
The course covers all aspects of the theory and practice of quantitative tools, products and methods.
The course is a result of QuantInsti Faculty’s several years of experience in trading in financial markets and domain expertise. Its comprehensive, interactive and collaborative learning environment makes it highly-preferred among the beginners as well as seasoned traders.
Start Learning Algo Trading
Dr. Ernest P. Chan
Ernie is the author of “Quantitative Trading: How to Build Your Own Algorithmic Trading Business” and “Algorithmic Trading: Winning Strategies and Their Rationale”.
Dr. Gautam Mitra
Internationally renowned research scientist in the field of Operational Research in general and computational optimisation and modelling in particular.
Global Training Programmes & Workshops
Short & Self-Study Courses
Quantra™ is QuantInsti™’s e-learning portal which offers a unique learning experience through highly interactive short-term courses focused on Algorithmic and Quantitative Trading. Quantra is already benefiting users from over 60 countries and is setting its mark in this domain.
Mean Revision Strategies
- Course by Ernest P. Chan, 4.5 hours of course content covering four different mean reversion strategies
- Also covers different statistical techniques to detect stationarity and cointegration of a portfolio of instruments
- Code and implement all four strategies in Python along with downloadable code
Trading with Machine Learning: Classification and SVM
- 4 hours of content covering Classification predictive models (Binary and Multi-class classification in detail)
- Also covers Support vector machine classifier and different hyper-parameters used for algorithm optimization
- Code a trading strategy using predictions made by SVM algorithm
Statistical Arbitrage Trading
- 4 hours of content covering concepts like z-score, stationarity of time series, co-integration, pair trading and related risks in detail
- Build pairs trading strategy in Excel and code it using Python with lots of guided hands-on coding
- Certification from QuantInsti & MCX