Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study | Video and Text Based |
Course Overview
Algorithmic trading has been used for a long time, the rise of artificial intelligence and machine learning has accelerated the advancement of algorithmic trading. With the help of various algorithms, machine learning and artificial intelligence recognise the profitable pattern and make a trade at high frequency. The Oxford Algorithmic Trading Programme online course introduces the rules that drive hedge funds and algorithmic trading strategies.
The Oxford Algorithmic Trading Programme syllabus provides a grounded introduction to behavioural finance and financial theory. The course teaches to evaluate the algorithm training models by which artificial intelligence recognises trade patterns. The course covers various factors which affect the market and creates exploitable patterns.
The Oxford Algorithmic Trading Programme training focuses on investment and trading space. The course discusses the key issues faced by algorithmic traders and the future of Artificial intelligence and machine learning algorithmic trading. The course teaches about various experimental models of algorithmic trading.
The Highlights
- Case-study based learning
- Split fee option available
- Course assessments and projects
- 6 weeks duration
- Online Learning
- University of Oxford offering
- Course provider Getsmarter
- Downloadable resources
- 6 modules
- 7-10 hours learning/week
- Shareable certificate
Programme Offerings
- assessments
- Certification
- quizzes
- Offline resources
- insights
- Case Studies
- Projects
- online learning
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Said Business School, Oxford |
Fee type | Fee amount in INR |
Algorithmic Trading Programme fees | Rs. 210,811 |
The Algorithmic Trading Programme fees are Rs. 210,811 Getsmarter offers a split option of payment in which learners can pay the fee in 2 instalments of Rs. 87,390.00 per month. A 3% admin fee will be charged as an admin fee for split payments.
Eligibility Criteria
Certification Qualifying Details
To get qualified for the Oxford Algorithmic Trading Programme certification, learners will have to complete the series of practical assessments along with all the modules included in the online course. Learners will have to meet all the requirements written in the coursebook for certification.
What you will learn
After completing the Oxford Algorithmic Trading Programme online training, candidates will gain knowledge of algorithmic training models. Candidates will learn about 4 key rules of algorithmic training strategies. Learning will gain knowledge of emerging technologies like machine learning, artificial intelligence.
Who it is for
- Traders, financial professionals, and investors who want to gain knowledge of Algorithmic trading and understand algo-trading strategy can join this course.
- Business leaders who want to take advantage of algorithmic trading in their companies can join the Oxford Algorithmic Trading Programme course for beginners.
- Technology and IT professionals who want to know about the strategies behind algorithmic training models can enroll in this course.
- New hires and MBA graduates who want to learn about automatic trading techniques.
Admission Details
To get admission to the Oxford Algorithmic Trading Programme online training by the University of Oxford, follow the steps written below:
Step 1. Go through the official link to open the course webpage.
Step 2. Click the ‘Register Now’ button on the course page to start the registration
Step 3. Provide required details to create a profile on the Getsmarter
Step 4. Provide billing address and choose the method of payment
Step 5. Pay the fee either by bank transfer or with a debit/credit card and begin your class
The Syllabus
- Review the fundamental principles of the efficient frontier
- Define the efficient market hypothesis and other concepts related to classic finance theory
- Discuss how behavioral biases impact the market
- Discuss how stock market trends are identified in practice
- Define terminology associated with stock market trends
- Identify rules or principles that can be used to build and evaluate an algorithmic trading model
- Identify the characteristics of hedge funds and their history
- Review the principles of systematic trading within hedge funds
- Identify which types of investors tend to invest in hedge funds
- Identify the difference between large systematic trading organisations and smaller players
- Discuss the factors that contribute to the success or failure of large systematic trading organisations
- Interpret the historical and current opportunities and challenges of the systematic trading industry
- Review appropriate measures of model performance, including their advantages and disadvantages
- Identify the characteristics of out-of-sample testing and backtesting as methods of statistical verification
- Discuss how the Sharpe ratio is used to measure a model’s validity
- Interpret the risks associated with algorithmic trading at the management and programming levels
- Identify the origins of trading rules and the importance of futures in algorithmic trading
- Identify the role of APIs and other programming considerations in the modelling of algorithmic trading strategies
- Articulate the benefits and challenges of cross-disciplinary collaboration in financial modelling
- Review important considerations for selecting appropriate in-sample data
- Review the process of building and optimising a simple trend model
- Articulate useful techniques for testing whether a trend model is functional or viable
- Reflect on the applications of an algorithmic trading model to a live environment or real-world market circumstance
- Test whether a trend model can be applied to a different set of data
- Test the functionality and viability of a trend model, given changes in the underlying data
- Discuss the different avenues for growth that can help to further develop or improve an algorithm model
- Discuss the opportunities and challenges faced by different participants in the algorithm-trading ecosystem
- Evaluate whether or not a fund is worth investing in based on the four rules for fund evaluation
- Investigate the strengths and weaknesses of a systematic fund in order to analyze how it is likely to perform
- Investigate the opportunities and challenges of utilising robot-advisers and algorithmic technology for systematic trading
- Review the current state of the digital finance technology industry
- Review the ways in which AI and machine learning are utilized for algorithmic trading
- Formulate a view on future trends in algorithmic trading and the relationship between these trends and new technologies
- Assess the real value and impact of AI and machine learning on the algorithmic trading industry
Instructors
Said Business School, Oxford Frequently Asked Questions (FAQ's)
Around 70-80 percent of the whole trading is algorithm-based.
Algorithmic trading helps traders with more strategic testing, design and execution of a trade.
Start learning algorithmic trading with the Oxford Algorithmic Trading Programme for beginners.
The Oxford Algorithmic Trading Programme online course by the University of Oxford is the best online course to learn algorithmic trading.
Yes, Algorithmic trading is profitable. it reduces risks and identifies profitable patterns with trained algorithms.