Algorithmic and quantitative trading: fundamental principles workshop

  • Quant and model risk
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Key reasons to attend

  • Generate ideas, develop strategies and identify opportunities
  • Learn about the existing key components in a trading platform
  • Gain a basic overview of the Python programming language


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About the course

Gain a robust understanding of the diverse components, strategies and challenges of algorithmic and quantitative trading. 

This highly informative learning event will provide participants with the best practices for building a trend-following strategy and for aligning the foundations of Python with quantitative trading strategies. Participants will explore the efficient ways that risk management frameworks, such as automated compliance, are being implemented in algorithmic and quantitative trading processes. 

Key sessions will delve into the principles of algorithmic trading strategies, such as statistical arbitrage, market timing strategies and a case study on high-frequency trading. Practical examples will offer insight into the day-to-day of algorithmic and quantitative traders’ responsibilities.

Learning objectives

  • Evaluate the effectiveness of strategies with backtesting processes
  • Navigate the diverse quantitative models and methods
  • Develop trend-following, execution and market timing strategies
  • Integrate machine learning models into algorithmic trading practices
  • Analyse technical indicators used in quantitative trading
  • Align compliance with algorithmic and quantitative 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


November 13, 2024

In-person. Location: Sydney, Australia


  • Algorithmic trading
  • Deep diving into algorithmic trading
  • Risk management frameworks for algorithmic and quantitative trading
  • Quantitative models and methods
  • Quantitative trading
  • Deep diving into quantitative trading
  • Mapping it all together


  • Ben Watson, Chief executive, Maroon Analytics Australia

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Ben Watson

Chief executive

Maroon Analytics Australia

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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

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November 13, 2024

In-person, Sydney, Australia



Early-bird Price

Ends October 11
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