This 3-day online workshop will introduce you to systematic and quant trading, discuss various strategy paradigms, teach how to formulate a strategy and showcase the backtesting of a sample strategy on multiple assets using both visual coding and the Python console.
For those of you who are looking for a complete algo trading course, QuantInsti's EPAT programme is the best choice for you. It comes with an endless list of benefits, get in touch with a course counsellor to know more today.
This workshop has ended. Access the complete workshop recordings and presentations below.
Day 1: The big picture
- A brief introduction to systematic and quant trading.
- Understand its reach and spread in the current trading landscape.
- Learn the benefits of quant trading.
- You will learn about the process of converting a trading idea from conception, to taking it live in an algorithmic trading setup.
- Compare and contrast the traditional and quantitative trading styles.
This guide to learning algo trading provides an overview of systematic and quantitative trading, highlighting its growing significance in modern markets. It explains how to transform a trading idea into a functional algorithmic setup and contrasts traditional trading approaches with quantitative methods for a comprehensive understanding.
Complete recording of Day 1:
Presentation Slides from Day 1:
Day 2: The finer details: Working with data, formulating and backtesting a trading strategy
- Discuss various strategy paradigms.
- Learn about the strategy workflow.
- Take a short detour about data we can use.
- Explore data sources.
- Formulate a strategy and backtest it.
Complete recording of Day 2:
Presentation Slides from Day 2:
Day 3: Test driving a trading strategy (on a backtesting platform)
- Extend the ideas discussed in the last session to learn about backtesting in a platform environment.
- Gain a basic understanding of the Blueshift platform and its features(including visual coding). Power your trading strategy with an innovative Algorithmic Trading Platform.
- Showcase the backtesting of a sample strategy on multiple assets using both visual coding and the Python console.
- Q&A session about the domain.
Complete recording of Day 3:
Presentation Slides from Day 3:
Who Should Attend?
- Discretionary/manual traders (ex. professional traders, part-time traders) who are looking to upskill and get better returns.
- Technology professionals, who want to leverage their technical skills to invest wisely in the financial markets.
- Students and other enthusiasts who wish to make a career in quantitative finance.
About the Speakers
Ashutosh Dave (Senior Associate, Content & Research at QuantInsti)
Ashutosh has more than a decade of experience in the area of financial derivatives trading and quant finance. Apart from contributing to the overall content development at QuantInsti, he teaches Python in our flagship programme EPAT.
He has worked as a derivatives trader specializing in trading interest rates and commodities with a proprietary trading firm in London for several years before joining QuantInsti. His key areas of interest include applying advanced data science and machine learning techniques to financial data.
Ashutosh holds a Masters in Statistics with distinction from the London School of Economics (LSE) and is a Certified FRM (GARP). He is the co-author of the book, “A rough-and-ready guide to algorithmic trading (2020)”.
Jay Parmar (Associate, Content & Research at QuantInsti)
Jay works as an Associate, Content & Research at QuantInsti and comes with several years of experience in the BFSI industry. He is actively engaged in content development for quant finance courses and mentors EPAT participants across the globe.
He is the co-author of the book, “Python Basics: With illustrations from the financial markets (2019)” and “A rough-and-ready guide to algorithmic trading (2020)”. He is passionate about algo trading and programming and enjoys developing automated trading systems. He holds a Bachelors’ in Computer Science and the EPAT Certificate. His research interests are in applying machine learning models to various facets of trading.
For those starting with automated trading for beginners, his work shows how learning programming and trading concepts can lead to building effective trading systems. It’s a great example of how to get started in this field.
Vivek Krishnamoorthy (Head of Content & Research at QuantInsti)
Vivek teaches participants data analysis, building quant strategies and time series analysis using Python. He has over 15 years of experience across India, Singapore and Canada in industry, academia and research.
He is the co-author of the books, “Python Basics: With illustrations from the financial markets (2019)” and “A rough-and-ready guide to algorithmic trading (2020)” He has a Bachelors' in Electronics & Telecom Engineering from VESIT (Mumbai University), and an MBA from NTU Singapore.
This event was conducted from:
May 20 to 22, 2021
9:30 AM ET | 7:00 PM IST | 9:30 PM SGT
