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 Reversion Strategies in Python by Dr. Ernest P. Chan
- 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