The objective of the course is to develop fundamental skills in the quantitative developer role. The course is designed by practitioners from quantitative finance with experience in model development for derivative pricing and systematic trading. The primary coding languages of the course are Python and C++. As it is essential in finance to work with time series data we introduce database KDB and the language q, which are the leading solutions for storing the timeseries.
The objective of the course is to develop fundamental skills in the quantitative developer role. The course is designed by practitioners from quantitative finance with experience in model development for derivative pricing and systematic trading. The primary coding languages of the course are Python and C++. As it is essential in finance to work with time series data we introduce database KDB and the language q, which are the leading solutions for storing the timeseries.
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Global Course Fee:
₹ 5,20,000 (£ 4,995)
Exclusive Discounted Wright Offer:
₹ 2,50,000 ₹ 5,20,000 (£ 4,995)
50% OFF
Time Commitment:
2-3 Hours Live Lectures Weekly | 22 Weeks
Start Date:
17th October - 10th April 2025
Evaluation:
Final Exam
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Banks, hedge funds and financial technology companies (fintechs) employ thousands of quantitative software development experts with salaries averaging $124,762 per year (approximately £100,000 or €115,000) as reported by Glassdoor, with salaries for senior practitioners and managers extending into seven and eight figures. Not only are these jobs financially lucrative, they are intellectually challenging and stimulating, and highly regarded socially. Employers include Tower Research Capital, Citadel, Bloomberg L.P., and all the major bulge bracket investment banks.
This course has been designed to empower individuals who work in or are seeking a career in quantitative finance. Throughout our unique QDC programme, candidates work with hands-on assignments to experience first-hand practical challenges in model development for derivative pricing and systematic trading. The QDC is a career-enhancing professional certificate that can be taken worldwide. Throughout this course sample test questions from quant interviews will be provided.
QDC candidates come from some of the world’s most prestigious financial institutions including: Nomura International Plc, JP Morgan, Deloitte, Credit Suisse, Jefferies, Point 72, Nationwide, Deutsche Bank…
The QDC is a graduate-level professional certificate, internationally renowned and a solid demonstration of individual commitment to career development.
Practitioner Oriented
The QDC delivers learning of practical value, developed and taught by highly experienced practitioners.
Expert teaching and support
The QDC Faculty is an acclaimed team of instructors combining respected academics and renowned practitioners in the field of quantitative finance. The Faculty provides mentoring and support during the course and all members are accessible by email or via the online QDC Forum.
Prior to the start of the QDC students are given access to our world class quantitative finance online resource, in preparation for the certificate and to enhance your future learning. This resource offers over 300 hours of the latest research and cutting edge techniques.
QDC Learning Resource:
The CPD Certification Service was established in 1996 as the independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies. The CPD Certification Service provides recognised independent CPD accreditation compatible with global CPD principles.
The objective of the course is to develop and enhance fundamental skills within the role of quantitative developer.
In this module, we’ll introduce the Python programming language from the basics. We’ll introduce some of the key libraries for data science such as NumPy and Pandas, as well as Matplotlib and Plotly for visualisations. Later, we’ll discuss how to download market data into Python from sources including Bloomberg and Quandl. We’ll go through many use cases for Python in finance, including developing trading strategies, calculating volatility.
Data science would not exist without the databases. In finance the data usually comes in the form of time series. The favourite of many trading houses and high-frequency trading firms, kdb+/q, is a leader among solutions for storing time series data. In this module we shall go from foundations to fluency in kdb+/q and demonstrate how this module interacts with Python and the pandas library.
The objective of the module is to teach students fundamentals of C++. The module does not assume any previous knowledge of C++. After completing of the module, the students will be able to code simple applications in C++ understand the reasons for the errors and understand the concepts of C++ language. The course introduces the student to the Standard Library in C++ where the algorithms and data structures are implemented.
The objective of the module is to teach students fundamentals of any programming language: data structures and algorithms. After completion of the module the students will know the main data structures, algorithms and will be able to understand what happens “under the hood”. The students will be able to assess the complexity of different algorithms and pick the most efficient one. The students will learn what are the pros and cons of using a particular data structure. Even though the module is implemented in C++ it does not focuses on specific features of C++ rather the generic features that are relevant for any other programming language.
The construction of trading platform constitutes a multidisciplinary craft and science. The developer needs to be aware of the hardware, whether or not it is his or her speciality, at least for the sake of having mechanical sympathy. Special disciplines in programming have arisen that are favoured by high- and medium-frequency trading platform developers: low-latency programming and functional reactive programming. We will cover these specialised disciplines in this module.
Candidates will sit a formal examination on a computer. The exam is taken online by students globally.
Examination Preparation Week: Thursday 27th March 2025
Examination Date: Thursday 10th April 2025
Marking Classifications
Students achieving an overall mark of 70% or higher will be awarded the Certificate with Distinction. The total mark is calculated as equally weighted marks for module tests and final exam.
Distinction: 70-100%; US equivalent: A/A+
Merit 60-69%; US equivalent: B+/A
Pass 50-59%; US equivalent: B-/B
Our faculty is hand picked to offer you the best learning experience.
Systematic Trading, JPMorgan Chase & Co
Ivan Zhdankin is a quantitative researcher with experience in diverse areas of quantitative finance, including risk modelling, XVA, and electronic trading across asset classes, including commodity futures and G10 and emerging market currencies. Ivan was consulting various banks in quantitative modeling and has recently joined JP Morgan as a quantitative analyst. He has become one of the first researchers to generate convincing results in electronic alpha with neural nets. He has a solid mathematical background from New Economic School and Moscow State University, where he studied under the celebrated Albert Shiryaev, one of the developers of modern probability theory.
Turnleaf Analytics / Cuemacro / Visiting Lecturer at QMUL
Saeed has a decade of experience creating and successfully running systematic trading models at Lehman Brothers and Nomura. He is the founder of Cuemacro, Cuemacro is a company focused on understanding macro markets from a quantitative perspective. He is the author of ‘Trading Thalesians – What the ancient world can teach us about trading today’ (Palgrave Macmillan), and graduated with a first class honours master’s degree from Imperial College in Mathematics& Computer Science.
CEO, Thalesians, Visiting Professor, Imperial College
Dr. Paul Bilokon is CEO and Founder of Thalesians Ltd and an expert in electronic and algorithmic trading across multiple asset classes, having helped build such businesses at Deutsche Bank and Citigroup. Before focussing on electronic trading, Paul worked on derivatives and has served in quantitative roles at Nomura, Lehman Brothers, and Morgan Stanley. Paul has been educated at Christ Church College, Oxford, and Imperial College. Apart from mathematical and computational finance, his academic interests include machine learning and mathematical logic.
The faculty advise that the course is self-sufficient and there are no prerequisite reading requirements. Additional readings on top of the course, for a more advanced level, will be presented during the course.
However, if you would like to prepare for the course by reading some materials, the faculty recommends the following sources:
The QDC is a practitioner-orientated professional certificate that will enhance the short-term and long-term career prospects of anyone seeking a career or working in quantitative finance
Next start date is Thursday 17th October 2024.
The examined part of the course takes place over 6 months, with the examination and project taking place at the end of the course.
This course has been designed to empower individuals who work in or are seeking a career in quantitative finance
At any stage during the QDC you may defer your education until the next cohort (one deferral is permitted). The QDC cohorts run twice per annum: April & October.
The course will take place globally online with weekly lectures on Thursday taking approximately 2 hours at 10:30 pm.
Thursday 10th April 2025
The live streaming will be available on Cisco Webex, you will be sent weekly login access details.
You will have one chance to retake the final examination.
All the lectures are filmed and recordings are available for you on the QDC Student Portal for the duration of the course.
Yes the QDC offers flexible payment options where candidates can pay for the course by instalments.
Option 1: Pay in full
Option 2: Full course: Pay 50% on registration and 50% in week 12
It is possible for students to defer completion of the QDC to the next cohort at no extra charge.
The current pricing of ₹ 2,50,000 is at a 52% discount compared to global fees of ₹ 5,20,000 (£ 4,995). As this is a negotiated & heavily discounted price specifically for the Wright community, there are no further discounts or early bird offers.
However, we do offer volume discounts, so if 2 or more people from your institution wish to take the course please contact us and we will be happy to discuss the pricing.
In addition to this, if you are interested in taking multiple courses from the following list, then we can offer you specific discounts:
You will receive a mail with further instructions and a payment link within 24 hours.
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