Algorithmic and quantitative trading: best practices workshop
View AgendaKey reasons to attend
- Learn about the existing key components in a trading platform
- Gain an overview of the Python programming language for trading uses
- Use backtesting to analyse trading scenarios
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About the course
Gain valuable insights into the diverse components, strategies and challenges of algorithmic and quantitative trading.
This highly informative learning event will equip participants with best practices for effectively aligning the foundations of Python with quantitative trading strategies through practical examples. Participants will learn how to build a trade simulator to analyse model and strategy risk, while interactive sessions will delve into the key principles of algorithmic trading strategies, including statistical arbitrage and market timing.
Alongside peers and the expert tutor, participants will explore high-frequency trading in a detailed case study, and will participate in a practical demonstration on parameter-tuning techniques to optimise performance.
Pricing options*:
- Early-bird rate: save up to $800 per person by booking in advance
- 3-for-2 rate: save over $3,000 by booking a group of three attendees
- Subscriber reward: save 30% off the standard rate if you are a Risk.net subscriber
- Season tickets: save up to 60% - request price breakdown
*T&Cs apply
Learning objectives
- Develop trend-following, execution and market timing strategies
- Integrate machine learning models into algorithmic trading practices
- Align compliance with algorithmic and quantitative trading
- Evaluate the effectiveness of strategies with backtesting processes
- Analyse technical indicators used in quantitative trading
- Explore the relationship between quantitative and traditional trading
Who should attend
Relevant departments may include but are not limited to:
- Trading
- Risk management
- Machine learning
- Model risk
- Artificial intelligence
- Compliance
- Regulation
- Technology
- Algorithmic trading
- Quantitative trading
Agenda
This workshop is part of Risk Live Australia which will take place one day before the conference in Sydney. Click here to learn more about the workshop and conference rates.
August 6, 2025
In-person. Location: Sydney, Australia
Venue: Cliftons Sydney, L13, 60 Margaret St, Sydney NSW 2000
Sessions:
- Algorithmic trading
- Deep diving into algorithmic trading: part I
- Deep diving into algorithmic trading: part II
- Risk management frameworks for algorithmic and quantitative trading
- Quantitative and technical trading framework
- Quantitative modelling
- Class demonstration
- Summary
Tutor:
- Ben Watson, chief executive, Maroon Analytics Australia
Tutors
![](/sites/default/files/styles/people_image_250x250/public/2024-02/Ben%20Watson%20-%20PP.jpg.webp?itok=iAkd5JqR)
Ben Watson
Chief executive
Maroon Analytics Australia
Ben Watson is the chief executive of Maroon Analytics Australia, a quantitative analytics consultancy that helps banks and financial institutions with all aspect of their quant requirements. Maroon has been helping it clients with some of the more complex issues that they face today, such as OIS discounting, XVA pricing, risk management, initial margin modelling, market and credit risk management and portfolio modelling. Ben has successfully been running Maroon Analytics consulting business for the past 11 years.
Ben has recently developed a full featured analytical risk management system called Quantics. This system is currently being rolled out to a wholesale fund manager that is being used to manage the credit and market risk, provide full profit and loss attribution along with powerful analytic tools that perform risk and relative value modelling of instruments and portfolios. Ben is expanding Quantic’s capabilities by incorporating machine learning algorithms for analytical tasks such as factor analysis, relative value analysis, risk management and algo trading.
Ben came to the Maroon business with 17 years working for investment banks as a quantitative analyst. Up to 2012 he was the APAC regional head of the quant function for RBS, and before that he was the local head of quantitative analytics at ABN AMRO Australia. Working directly with traders he has a long track record of building real time pricing and risk management systems. He has built credit, bond, swaps, FWD FX, swaptions, inflation bonds and swaps, MBS, CDS pricing and trading systems for the front office. While at ABN Amro, Ben also ran a successful quantitative trading book based on relative value trading strategies in interest rate swaps and futures.
Pre-reading materials
The Risk.net resources below have been selected to enhance your learning experience:
- Can algos collude? Quants are finding out
- Neil Chriss sets out to codify the game theory of trading
- AI expert warns of algo-based market manipulation
A Risk.net subscription will provide you access to these articles. Alternatively, register for free to read two news articles a month.