Introduction to the Course and Goals
Welcome! If you're a software engineer curious about algorithmic trading and have a beginner background in C++
, Python
, Java
, C
, or JavaScript
, this short orientation will get you grounded in what to expect.
- Course goal: Build practical, low-latency HFT components and concepts — from
market data
ingestion to a minimalorder gateway
— implemented in bothC++
(performance-critical) andPython
(rapid prototyping). Think: "from notebook prototype to a tiny, fast microservice." - Target outcomes: Be able to design and implement latency-sensitive pieces of a trading stack, understand kernel/network tweaks, measure latency, and move hot paths from Python to C++ safely.
- Who this is for: Engineers with basic familiarity in languages like
C++
,Python
,Java
,C
, orJS
who want to learn HFT systems engineering. - Time commitment: Plan ~6–8 hours/week for ~8–12 weeks (labs + reading). Labs are incremental: each builds on the previous — market data -> strategy -> execution -> backtesting.
High-level structure (quick map)
ASCII diagram of the minimal HFT data-flow you'll build and test:
1[Exchange Multicast] --> [Market Data Handler] --> [Strategy / Alpha] --> [Order Gateway] --> [Exchange TCP]
2 | | |
3 (parser) (decision) (risk/serialization)
Market Data Handler
: UDP/multicast ingestion, sequence recovery, parsingbinary
messages.Strategy / Alpha
: simple momentum or spread logic (prototype inPython
, migrate hot loops toC++
).Order Gateway
: TCP binary protocols or FIX glue for real order submission.
What you'll learn (concrete):
- Read and parse exchange message formats (
ITCH
,OUCH
), implement a simpleUDP
multicast listener inC++
. - Prototype strategies in
Python
withnumpy/pandas
, profile, then move hotspots to C++ viapybind11
. - Measure latency with hardware timestamps and
pcap
traces; microbenchmark I/O and serialization. - Kernel & NIC tuning basics:
irq affinity
,isolcpus
, RX/TX rings, and offloads.
A micro-analogy (for Java/C/JS folks and even basketball fans)
Building an HFT system is like coaching a basketball team:
Market data
is the crowd noise and scoreboard — the raw sensory input.Strategy
is your playbook; a short, decisive play is like a low-latency hot path.Order gateway
is the point guard executing the shot — timing and coordination matter.
If your favorite player is LeBron James
or Kobe Bryant
, think of moving a play from a slow walk-on to an instant alley-oop — that's the jump from prototype to optimized C++.
Quick practical expectation
- Labs: small, focused; each lab includes a runnable
C++
binary and aPython
notebook. - Assessments: functional correctness + latency/throughput baseline comparisons.
- Safety: all network/NIC tuning steps are demonstrated with rollback tips and VM-friendly alternatives.
Try this now
Below is a tiny C++
program that prints a course micro-plan, shows weekly hours, and prints an ASCII HFT diagram. Run it, then try the challenge at the end of the program by editing the code.
Challenge: Change module durations, add your favorite module (e.g., FPGA intro
or Advanced SIMD
), or replace the favorite_player
with your own sports analogy to personalize output.
1#include <iostream>
2#include <vector>
3#include <string>
4#include <iomanip>
5
6using namespace std;
7
8struct Module {
9 string name;
10 int hours_per_week;
11 int weeks;
12};
13
14int main() {
15 // Personal touch for engineers who like basketball
16 const string favorite_player = "LeBron James"; // change this to your favorite
17
18 vector<Module> modules = {
19 {"Intro & Env Setup", 4, 1},
20 {"Market Data Handler (C++)", 6, 2},
21 {"Strategy Prototyping (Python)", 6, 2},
22 {"Order Gateway & Risk", 5, 2},
23 {"Backtesting & Simulation", 4, 2},
24 {"Profiling & Optimization", 5, 2}
25 };
26
27 cout << "Course: Algorithmic Trading for HFTs using C++ and Python\n";
28 cout << "Goal: Build latency-sensitive trading components.\n\n";
29
30 int total_hours = 0;
31 cout << left << setw(35) << "Module" << setw(10) << "hrs/wk" << setw(8) << "weeks" << "\n";
32 cout << string(60, '-') << "\n";
33 for (auto &m : modules) {
34 cout << left << setw(35) << m.name << setw(10) << m.hours_per_week << setw(8) << m.weeks << "\n";
35 total_hours += m.hours_per_week * m.weeks;
36 }
37
38 cout << "\nEstimated total commitment: " << total_hours << " hours (spread over the course).\n";
39
40 cout << "\nMinimal HFT stack diagram:\n";
41 cout << "[Exchange Multicast] --> [Market Data Handler] --> [Strategy] --> [Order Gateway] --> [Exchange TCP]\n";
42 cout << " (parser) (decision) (serialize & risk)\n";
43
44 cout << "\nA quick tip: Prototype logic in Python, then move hot loops to C++ (pybind11).\n";
45 cout << "Analogy: Make plays as quickly as " << favorite_player << " does alley-oops!\n";
46
47 cout << "\nTry this change: edit the array of modules to add a module named 'FPGA intro' or change hours_per_week.\n";
48 return 0;
49}
Happy hacking — when you're ready, continue to the next screen where we'll set up the C++
toolchain and a Python
virtual environment. Don't forget to modify the code above and run it to make the plan your own!
xxxxxxxxxx
}
using namespace std;
struct Module {
string name;
int hours_per_week;
int weeks;
};
int main() {
// Personal touch for engineers who like basketball
const string favorite_player = "LeBron James"; // change this to your favorite
vector<Module> modules = {
{"Intro & Env Setup", 4, 1},
{"Market Data Handler (C++)", 6, 2},
{"Strategy Prototyping (Python)", 6, 2},
{"Order Gateway & Risk", 5, 2},
{"Backtesting & Simulation", 4, 2},
{"Profiling & Optimization", 5, 2}
};
cout << "Course: Algorithmic Trading for HFTs using C++ and Python\n";
cout << "Goal: Build latency-sensitive trading components.\n\n";