Algorithmic and quantitative trading: fundamental principles workshop
View AgendaKey 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
Customised Solutions
Does your team require a tailored learning solution on this or any other topic?
Working with the portfolio of expert tutors and Risk.net’s editorial team, we can develop and deliver a customised learning to make the most impact for your team, from initial assessment to final review.
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
Agenda
Sessions:
- 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
Pre-reading materials
The Risk.net resources below have been selected to enhance your learning experience:
- AI expert warns of algo-based market manipulation
Read article | Risk.net - How AI can give banks an edge in bond trading
Read article | Risk.net - Slicing algos blamed for market impact on dark venues
Read article | Risk.net
A Risk.net subscription will provide you access to these articles. Alternatively, register for free to read two news articles a month.
Expand your learning
Events
The premier meeting place for the risk community. Providing clarity and guidance on the fast-changing regulatory landscape of capital, credit and market risk, liquidity and derivates use.
Journals
Risk Journals deliver academically rigorous, practitioner-focused content and resources for the rapidly evolving discipline of financial risk management.
Books
Risk Books are authored by leading professionals and academics. With over 150 books spanning 1,000s of chapters, our publications team is committed to connecting readers with these world class experts.
Glossary
Regularly updated by our team analysts, journalists and producers, our glossary demystifies the terminology and acronyms used in risk management, risk transfer, policy, technology and innovation.