Researcher course in programming
C++ for Quantitative Finance and Low-Latency Systems
Modern C++ for the code where speed matters: pricing libraries, simulation engines and trading components. Memory, ownership, templates, the standard library, testing and profiling, and exposing C++ to Python research code. It also teaches low-latency C++ for trading systems.
C++ for quantitative finance is the second language of the quant developer. Pricing libraries at banks, execution engines at trading firms and large Monte Carlo simulations are written in it, because it gives control of memory and speed that Python does not. This course takes a confident Python programmer to useful, tested modern C++.
What will I build?
A small but real pricing library: payoffs and instruments as classes, Black-Scholes, binomial and Monte Carlo pricers, unit tests for each, and Python bindings so that your research notebook can call the library. Along the way you profile it and make it faster, and learn why memory layout often matters more than clever arithmetic.
How is the course taught?
Audio lessons cover the ideas and the reasons behind them, explainer films walk through the code and the debugger, and the workbooks hold the labs, model solutions and cheat sheets of the language rules that cause most bugs. Your project receives written review from the faculty.
What counts as low latency in trading?
Low latency is a property of the whole path from network card to order, not of a fast language. A C++ program that allocates memory, takes a lock or waits on the kernel at the wrong moment is slower than a careful program in almost anything else. This course is about avoiding those moments.
It depends on the strategy. For a market maker competing for queue position on an electronic exchange, a few microseconds decide who trades. For a strategy holding positions for hours, milliseconds are irrelevant. The course works at the microsecond scale and is clear about which strategies need it.
Who is this course for?
Python programmers heading for quant developer, pricing or trading-systems roles.
What you will be able to do
- Write modern C++ with clear ownership, using the standard library containers and algorithms.
- Build a small option-pricing and Monte Carlo library with tests.
- Profile and speed up numerical code, and explain the effect of memory layout and caches.
- Expose a C++ library to Python and call it from a research notebook.
- Explain where time goes between a packet arriving and an order leaving.
Syllabus, module by module
From Python to C++
Compilation, types, functions, references and the build tools a quant team uses.
Memory and ownership
Stack and heap, RAII, smart pointers and the errors that crash production code.
Classes and templates
Designing instruments and payoffs, virtual functions against templates, and the cost of each.
The standard library
Vectors, maps, algorithms and random-number generators for simulation.
A pricing library
Black-Scholes, binomial trees and Monte Carlo pricers, with unit tests.
The latency budget
Wire, network card, kernel, application and exchange: where microseconds go, and which you control.
Modern C++ for the hot path
Value semantics, templates instead of virtual calls, constexpr, and what the compiler does with them.
What every course contains
Every paid course comes with the first seven and the certificate, whichever level it sits at. The proctored exam and the credential come when the course is taken as part of a Certificate, Diploma or Fellowship. Everything is self-paced: the material is yours to study in any order, at any hour, for the whole of the license.
- Workbooks. Written to train the thinking patterns and the important concepts of the course, with worked problems and the reasoning behind each answer, so that you learn to think the way the subject is thought.
- Audio edition. Focused, well-presented recordings with explainers and examples of the material, made to be interesting, relevant and entertaining, so that the general subject can be learned away from the desk.
- Notes. Pre-produced notes with every fact the course relies on, written out in full, so that nothing has to be transcribed from the films or the audio.
- Cheat sheet. One sheet with every important learning concept of the course on it, to keep beside you during the work and to revise from before the exam.
- Named sources. Every fact in the notes names its source, the paper, the book or the dataset, for anyone who wants to dig in further.
- Explainer films. Focused films, in the style of the sample films on the catalog page, that walk through the most difficult concepts of the course with visual explanations of a high standard.
- Transcript. A full transcript of every film and every audio recording, searchable and quotable.
- Proctored exam. Taken as part of a Certificate, Diploma or Fellowship, the course ends in a proctored multiple-choice questionnaire, with a pass mark of 60% and three retakes included. A course taken on its own is assessed by its coursework and has no exam.
- Verifiable certificate. A certificate of completion that a third party can verify: an employer sends the code on it to the credentials office and receives written confirmation of the course, the date and the result.
- Credential of the program. The Certificate, Diploma or Fellowship of the program, track or path the course belongs to, awarded when every course in it is passed. Which one depends on the program you choose.
How the certificate is earned
Graded lab exercises and a final project: a tested C++ pricing library with Python bindings, reviewed by the faculty in writing. On a pass you receive the Course certificate in C++ for Quantitative Finance and Low-Latency Systems, issued by the Institute with a verification code. A course taken as part of a Certificate, Diploma or Fellowship ends in a proctored online exam with a pass mark of 60%. The fee includes three retakes; each attempt after that carries a reduced proctored exam fee. A course taken on its own is assessed by its coursework and has no exam. Read how certification works.
Before you start
This course assumes the material of the courses below, or the same knowledge gained elsewhere.
This course counts toward
- Certificate in High-Frequency Trading and Market MicrostructureFour courses and a capstone on how orders meet: the limit order book, execution algorithms and their costs, venue routing, market making and the C++ systems that run them.
- Professional Diploma in Algorithmic TradingThe top credential on the practitioner path. Twenty-one courses and an 80-hour capstone covering everything between the mathematics and a book you could defend to a risk committee.
Questions applicants ask
Why learn C++ if I already know Python?
Banks’ pricing libraries, most execution systems and many simulation engines are written in C++, and quant developer roles ask for it. Python is fast to write; C++ is what runs when speed or control of memory matters.
Does this course cover low-latency trading systems?
It lays the ground. Low-Latency C++ Trading Systems, at researcher level, builds on it with lock-free queues, kernel bypass and latency measurement.
Why is C++ used for low latency trading?
It gives direct control over memory layout and allocation, compiles to fast code without a garbage collector, and has decades of tooling for performance work. Some firms also use FPGAs for the very fastest paths; the course explains where those fit.