Oxford Algorithmic Trading Programme | Saïd Business School (2024)

Oxford Algorithmic Trading Programme | Saïd Business School (1)
Oxford Algorithmic Trading Programme | Saïd Business School (2)

Understand the impact of automation, artificial intelligence and machine learning on systematic trading

Start dates:

Duration:

  • 6 weeks

Time commitment:

  • Short programme

Location:

  • Online

Cost:

  • £1,995

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

Oxford Algorithmic Trading Programme | Saïd Business School (3)

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
  • Membership of the official Oxford Saïd elumni community
  • Access to the official Oxford Executive Education Elumni 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.

  • Oxford Algorithmic Trading Programme | Saïd Business School (4)
    Nir Vulkan

    Associate 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.

  • Oxford Algorithmic Trading Programme | Saïd Business School (5)
    The Oxford-MAN Institute of Quantitative Finance

    A world-leading centre for interdisciplinary research.

  • Oxford Algorithmic Trading Programme | Saïd Business School (6)
    Oxford Future of Finance and Technology Initiative

    A research collaboration between Saïd Business School and industry.

  • Oxford Algorithmic Trading Programme | Saïd Business School (7)
    Who's afraid of the big, bad algorithm?

    The truth about algorithmic trading.

  • Oxford Algorithmic Trading Programme | Saïd Business School (8)
    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.

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
Oxford Algorithmic Trading Programme | Saïd Business School (2024)

FAQs

Is the Oxford algorithmic trading programme worth it? ›

Future trends in algorithmic trading

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.

Is the Oxford AI course worth it? ›

In conclusion the Oxford AI Programme is a worthwhile investment for managers and business leaders who wish to gain a comprehensive understanding of AI's history, function, potential and ethical issues. It also provides you with skills and tools to be able to consider and manage AI in your organisation.

Is Python better than R for algo-trading? ›

In general, Python is more commonly used in algo trading due to its versatility and ease of use, as well as its extensive community and library support. However, some traders may prefer R for its advanced statistical analysis capabilities and built-in functions.

Is it worth learning algorithmic trading? ›

Nevertheless, algorithmic trading helps you carry out multiple trade orders simultaneously and also the algorithm can enter and exit the market according to your conditions at a great speed which increases the probability of better returns. The speed at which algorithms can trade can not be matched by any human.

Can you make a living with algorithmic trading? ›

Is algo trading profitable? The answer is both yes and no. If you use the system correctly, implement the right backtesting, validation, and risk management methods, it can be profitable. However, many people don't get this entirely right and end up losing money, leading some investors to claim that it does not work.

How much do algorithmic traders make? ›

The estimated total pay for a Algorithmic Trader is $176,180 per year, with an average salary of $128,027 per year. These numbers represent the median, which is the midpoint of the ranges from our proprietary Total Pay Estimate model and based on salaries collected from our users.

Who is the most successful algo trader? ›

He built mathematical models to beat the market. He is none other than Jim Simons. Even back in the 1980's when computers were not much popular, he was able to develop his own algorithms that can make tremendous returns. From 1988 to till date, not even a single year Renaissance Tech generated negative returns.

Is algo trading always profitable? ›

Algorithmic trading is beneficial for most individuals, but not always. An algo trading method involves costly and complex technology. Complex strategies might take a long to implement.

Has anyone made money from algorithmic trading? ›

Most experienced algorithmic traders use stringent research methods to ensure that their strategy works and they are able to create a sturdy trading system. So, algorithmic traders make money by studying the markets, finding the trading edges, doing searches, and gathering trading ideas.

What is the success rate of algo trading? ›

The success rate of algo trading is 97% All the work will be done by the program once you set the desired trade parameters.

How hard is algo trading? ›

(But that would involve paying interest, so it's a bit more complicated) So, algo trading is at the same time difficult and easy, it is difficult because you have to learn programming, mathematics, and finance, but it is easy because it is about going into a position and then getting out of a position.

Which is the best software for algorithmic trading? ›

Algorithmic trading can be used in various markets, including stocks, futures, options, and IPOs.
  • Zerodha Streak.
  • Upstox Algo Lab.
  • Tradetron.
  • AlgoTraders.
  • TradeSanta.
  • Robo Trader.
  • NinjaTrader.
  • Algobulls.
Jan 5, 2024

Which course is best in algo trading? ›

In summary, here are 10 of our most popular algorithmic trading courses
  • Machine Learning for Trading: Google Cloud.
  • Trading Algorithms: Indian School of Business.
  • Trading Strategies in Emerging Markets: Indian School of Business.
  • Advanced Trading Algorithms: Indian School of Business.
  • Machine Learning: DeepLearning.AI.

Which platform is better for algorithmic trading? ›

StrategyQuant is a powerful platform for developing and backtesting trading strategies. It offers a wide range of tools and features, including genetic algorithms, optimization, and portfolio analysis. StrategyQuant is suitable for both beginner and advanced traders looking to launch low-frequency trading bots.

Which programming language is best for trading algorithms? ›

Let's explore some of the best programming languages for algorithmic trading systems:
  • Python. Python has emerged as a popular choice among developers for building algorithmic trading systems. ...
  • Java. ...
  • C++ ...
  • R. ...
  • MATLAB.
Feb 13, 2024

Top Articles
Latest Posts
Article information

Author: Pres. Carey Rath

Last Updated:

Views: 6246

Rating: 4 / 5 (61 voted)

Reviews: 92% of readers found this page helpful

Author information

Name: Pres. Carey Rath

Birthday: 1997-03-06

Address: 14955 Ledner Trail, East Rodrickfort, NE 85127-8369

Phone: +18682428114917

Job: National Technology Representative

Hobby: Sand art, Drama, Web surfing, Cycling, Brazilian jiu-jitsu, Leather crafting, Creative writing

Introduction: My name is Pres. Carey Rath, I am a faithful, funny, vast, joyous, lively, brave, glamorous person who loves writing and wants to share my knowledge and understanding with you.