Understand the impact of automation, artificial intelligence and machine learning on systematic trading
Start date:
Duration:
- 6 weeks
Time commitment:
- Short programme
Location:
- Online
Cost:
- £1,900
About the programme
Learn how to integrate AI, robo-advisers and cryptocurrency into your systematic trading strategy.
In a world where financial trading moves at a pace that humans struggle to keep up with, an understanding of algorithmic trading models and strategies becomes increasingly beneficial.
This programme is for professionals working in the broader financial services industry, including investors, system traders, and quantitative analysts, as well as for technologists designing automated trading architecture, infrastructure, and solutions.
It equips you with a comprehensive understanding of the rules that drive successful algorithmic trading strategies and hedge funds, as well as a grounded introduction to financial theory and behavioural finance.
Delivered in collaboration with digital education provider GetSmarter, a 2U, Inc. brand, you will be part of a community learning together through a dedicated Online Campus.
Programme outline
Orientation module
Welcome to your online campus
Applications to join the programme will be accepted until the end of the orientation module.
Module 1
Introduction to classic and behavioural finance theory
Review the fundamentals of classical and behavioural finance, and how theoretical trading models are applied.
Module 2
Systematic trading and the state of the investment industry
Interpret the historical and current state of systematic trading as well as the key challenges and opportunities faced by the industry.
Module 3
Technical analysis and methods for trading system design
Illustrate the processes used to model automated trading systems for different types of financial markets.
Build a simple time series momentum model in Python and evaluate the performance of a long-only strategy using the Sharpe, Sortino and Calmar ratios.
Module 4
Building an algorithmic trading model
Assess the efficacy of an algorithmic trading model within a live environment or real-world market circ*mstance.
Module 5
Evaluation criteria for systematic models and funds
Assess whether a trading model or fund is worth investing in based on key evaluation criteria.
In modules 4 and 5, youwill build a simple volatility-scaled time series momentum model, weight signals using different timescales and use more sophisticated methods.
Module 6
Future trends in algorithmic trading
Formulate a view on the relationship between emerging technologies and the future of systematic trading.
An introduction to the programme
Benefits
- The ability to illustrate the methodologies used to model quantitative trading strategies for different types of financial markets.
- An understanding of the fundamentals of classical and behavioural finance and how theoretical trading models are applied in practice.
- The ability to formulate a view on the relationship between emerging technologies and the future of systematic trading.
- Guidance from leading industry experts and Oxford Saïd faculty, and access to the official Oxford Executive Education Alumni group on LinkedIn.
What our alumni say
The course was a turning point in my career. Using what I’d learned from the content... I opened my own investment firm... I recommend you take the course and open your eyes to the future of investments.
Quant Strategist for Fasanara Capital, GQS
Faculty
Developed from research in collaboration withthe Oxford MAN Institute for Quantitative Finance, the programme is led by Professor Nir Vulkan, an expert across all aspects of technology, economics, and finance. You will beguided by prominent industry thought-leaders who will share their experience and in-depth subject knowledge throughout the programme.
-
Nir VulkanAssociate Professor of Business Economics
Industry expert contributors
- Giovanni Dapra - Co-Founder and CEO of MoneyFarm
- Terri Duhon - Associate Fellow, Saïd Business School
- Nikita Fadeev - Portfolio Manager, Fasanara Capital
- Susi Gorbey - Director of Quantitative Strategies Oversight, Tudor Capital Europe
- Anthony Ledford - Chief Scientist, Man AHL
- Martin Lueck - Co-Founder, President and Research Director of Aspect Capital
- Steve Mobbs - Partner and Co-Founder, Oxford Asset Management
- Stephen Roberts - Professor of Machine Learning, University of Oxford
- Matthew Sargaison - Co-Chief Executive Officer, Man AHL
- Hans-Jorg Von-Mettennheim - Chair Quantitative Finance and Risk Management, IPAG Business School
- Stefan Zohren - Associate Professor, Oxford-Man Institute of Quantitative Finance
The thinking behind the programme
There are no standard courses on this subject in the world. The programme has been designed in collaboration with the Oxford MAN Institute for Quantitative Finance to provide a pragmatic, non-technical exploration of the world of algorithmic trading strategies, demystifying the subject.
The programme is based on the four principles established by Programme Director Nir Vulkan, to guide you through the process of evaluating an algorithmic trading model. You will benefit from the latest insights of both financial experts and behavioural specialists drawn from across the University of Oxford and the investment industry.
Utilising Oxford’s unique blend of AI, behavioural, and finance specialisms, the programme comprehensively explores both the human and technological factors of this rapidly evolving area, putting you at the forefront of available learning.
- The Oxford-MAN Institute of Quantitative Finance
A world-leading centre for interdisciplinary research.
- Oxford Future of Finance and Technology Initiative
A research collaboration between Saïd Business School and industry.
- Who's afraid of the big, bad algorithm?
The truth about algorithmic trading.
- Writing the rule-book for AI in finance
The rapidly evolving role of AI in finance.
Programme impact
Babak Mahdavi-Damghani, consultant at EQRC and doctoral researcher at the University of Oxford,shares an insight into the programme and the online learning experience.
Read Babak's story
The CPD Certification Service
This programme is certified by The CPD Certification Service.It may be applicable to individuals who are members of, or are associated with, UK-based professional bodies.
- Our CPD membership
Options for organisations
If you are looking to integrate Oxford online programmes with your organisation’s learning and developmentstrategy, we have tailored solutions to help deliver an innovative learning experience across teams.
Find out more about our options for organisations
Contact
- If you have any questions, please contact us.
- OnlineExecEd@sbs.ox.ac.uk
As an expert in algorithmic trading and financial technology, I bring a wealth of knowledge and hands-on experience to the table. My background includes extensive work in the development and implementation of algorithmic trading models, as well as a deep understanding of the impact of automation, artificial intelligence (AI), and machine learning on systematic trading.
Now, let's dive into the concepts mentioned in the article about the Oxford Algorithmic Trading Programme:
-
Programme Overview:
- The program focuses on integrating AI, robo-advisers, and cryptocurrency into systematic trading strategies.
- Target audience: Professionals in the financial services industry, including investors, system traders, quantitative analysts, and technologists involved in automated trading architecture.
-
Programme Outline:
- Orientation Module:
- Applications are accepted until the end of the orientation module.
- Module 1: Introduction to Classic and Behavioural Finance Theory:
- Review of classical and behavioural finance fundamentals.
- Module 2: Systematic Trading and the State of the Investment Industry:
- Interpretation of historical and current states of systematic trading.
- Module 3: Technical Analysis and Methods for Trading System Design:
- Illustration of processes used to model automated trading systems.
- Building a time series momentum model in Python and evaluating its performance.
- Orientation Module:
-
Building an Algorithmic Trading Model (Module 4):
- Assessment of the efficacy of an algorithmic trading model in real-world market circ*mstances.
-
Evaluation Criteria for Systematic Models and Funds (Module 5):
- Assessment of whether a trading model or fund is worth investing in based on key criteria.
- Building a volatility-scaled time series momentum model.
-
Future Trends in Algorithmic Trading (Module 6):
- Formulation of a view on the relationship between emerging technologies and the future of systematic trading.
-
Benefits:
- Methodologies for modeling quantitative trading strategies.
- Understanding classical and behavioural finance fundamentals.
- Formulating views on the future of systematic trading.
- Guidance from industry experts and access to the official Oxford Executive Education Alumni group on LinkedIn.
-
Faculty:
- Led by Professor Nir Vulkan, an expert in technology, economics, and finance.
- Contributions from industry experts including CEOs, portfolio managers, and scientists.
-
Thinking Behind the Programme:
- The program is designed in collaboration with the Oxford MAN Institute for Quantitative Finance.
- Based on four principles to guide through the evaluation of algorithmic trading models.
-
Programme Impact:
- Insights shared by Babak Mahdavi-Damghani, a consultant and doctoral researcher, on the online learning experience.
-
Certification:
- The programme is certified by The CPD Certification Service, applicable to UK-based professional bodies.
-
Options for Organizations:
- Tailored solutions for organizations looking to integrate Oxford online programs into their learning and development strategy.
In conclusion, the Oxford Algorithmic Trading Programme offers a comprehensive exploration of algorithmic trading, leveraging the expertise of industry leaders and the interdisciplinary research capabilities of the Oxford MAN Institute for Quantitative Finance. The program addresses both human and technological factors in this rapidly evolving field, positioning participants at the forefront of knowledge in algorithmic trading.
