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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 minimal order gateway — implemented in both C++ (performance-critical) and Python (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, or JS 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:

SNIPPET
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, parsing binary messages.
  • Strategy / Alpha: simple momentum or spread logic (prototype in Python, migrate hot loops to C++).
  • 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 simple UDP multicast listener in C++.
  • Prototype strategies in Python with numpy/pandas, profile, then move hotspots to C++ via pybind11.
  • 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 a Python 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.

TEXT/X-C++SRC
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!

CPP
OUTPUT
:001 > Cmd/Ctrl-Enter to run, Cmd/Ctrl-/ to comment