EPAT Faculty > Jay Parmar
Jay Parmar
Quantitative Researcher, iRage
About the Faculty
Jay Parmar is a Quantitative Researcher at iRage Capital and plays an integral role in developing content for QuantInsti’s quant finance courses. With several years of experience in the BFSI (Banking, Financial Services, and Insurance) sector, Jay has worked extensively on quantitative research and trading strategies. He is also the co-author of Python Basics: With Illustrations from the Financial Markets, a guide for applying Python programming to trading.
Jay holds a Bachelor’s degree in Computer Science and has a strong interest in applying machine learning models to various aspects of trading. He actively mentors participants in the EPAT program and is committed to helping learners understand the practical implementation of quantitative finance concepts.
Jay’s hands-on experience with quantitative research and his ability to integrate machine learning into trading make him a valuable resource for those seeking practical knowledge in the field.
EPAT Teaching
Jay’s session covers the complete strategy lifecycle, from using IB Trader Workstation (TWS) and its API for trading operations to cloud computing and REST APIs for data and order management. He also covers machine learning models like Decision Trees and Neural Networks, gaining hands-on experience in implementing these concepts in Python to enhance trading strategies.
Webinars Conducted
Common Mistakes Made by Algo Traders
2024
Free Online Workshop: Learn Algo Trading Basics in 3 Days
2021
[Algo Trading Webinar] Stock Data Analysis: Excel Vs Python
2021
