All language subtitles for Inside a Real High-Frequency Trading System ｜ HFT Architecture

High -frequency trading systems are
engineered for speed. Not milliseconds,

microseconds. And even nanoseconds. In
this video, we'll dive into the actual

architecture behind these lightning
-fast systems. You'll see how market

ingested, how an in -memory order book
works, how decisions are made using

and strategy engines, and how orders are
routed to exchanges like Nasdaq. All in

the blink of an eye.

We'll walk through a real -world
architecture diagram used in the

breaking down each component from ultra
-low latency NICs, kernel bypass, event

queues, and nanosecond clocks to pre
-trade risk engines and smart order

routers. Whether you are a software
engineer, quant, or just someone who

out over high -performance systems, this
video is for you.

So, what exactly is a high -frequency
trading?

HFT is the use of algorithms and
machines to trade financial instruments,

stocks or options, at extremely high
speeds.

We are talking thousands to millions of
trades per second, all happening faster

than a human can blink.

The goal? To make tiny profits,
sometimes just a fraction of a cent on

trade, but to do it at such high volume
and speed that it adds up to massive

gains. These systems look for tiny
inefficiencies in the market.

like price differences between
exchanges, temporary imbalances in the

or slow price updates, and jump in
before anyone else can.

But to do that, speed is everything.

A single millisecond delay can mean the
difference between making money and

losing money.

And that's why HFT systems are
engineered like race cars.

Every component, from the network car to
the code, is optimized for ultra -low

latency. You might wonder, why does this
exist at all?

Because in financial markets, being
first matters.

The first system to react to market data
can take advantage of it.

Everyone else just follows.

For example, let's say you are running a
market making strategy.

You continuously place a buy order at $9
.99 and a sell order at $10 .01.

Now if someone accepts your sell order
at $10 .01, you just earned a 2 cent

spread. Now imagine doing this thousands
of times across hundreds of stocks

every second. The first step in an HFT
pipeline is receiving market data, the

real -time feed of prices, volumes, and
order book updates from stock exchanges

like NASDAQ and NYSE. But we are not
talking about your everyday API or

WebSocket feed.

HFT system use multicast feeds directly
delivered over ultra -low latency

networks, often inside a co -location
facility.

physically near the exchange server to
reduce travel time.

This data is received through
specialized hardware, an ultra -low

network interface card, and a custom TCP
stack, sometimes even kernel bypass

mechanism like DPDK or SolarFare onload.

These allow the system to handle market
updates in microseconds, skipping the

overhead of regular network stacks.

Then comes the market data feed handler,
a critical component that passes the

raw stream.

decodes the protocol and transforms it
into a format the system can understand.

You can think of it as the translator
between the exchange's language and your

internal logic.

But it has to translate millions of
messages per second without skipping a

Once the market data is ingested and
decoded, the next critical step is

the order book.

That is the live snapshot of all current
buy and sell orders.

HFT systems maintain this entire order
book in memory.

to avoid any disk IO or database
latency.

It's updated in real time with every
incoming message triggering a precise

update. In most systems, you'll see
replicated order books like replica A

replica B kept in sync using in -memory
replication.

This ensures fault tolerance.

So if one replica crashes or lags, the
system can instantly fail over to the

other. Now, the order book isn't just
for record keeping.

It's what drives the rest of the
pipeline.

Every trading decision, every market
-making strategy starts with the current

state of the book.

These updates are then published into an
event stream, ready for other

components like the trading logic, FPGA
engine, or smart router to consume in

near -zero latency.

And as soon as the order book is
updated, the new market state is

an event -driven pipeline, the backbone
of real -time processing in HFT.

This pipeline is built around a lock
-free queue.

optimized for throughput and low
contention.

Why lock -free? Because even the
slightest delay caused by locking

impact trade timing.

Each event, like a pricing change or a
new bid, is stamped using nanosecond

precision clock.

This level of timing and accuracy allows
the system to maintain the exact

sequence of market updates, benchmark
internal component latencies, and most

importantly, sync perfectly with
external systems like FPGA engines and

exchanges.

The result is a precise timestamp stream
of market events that downstream

systems like trading strategies, risk
engines or smart routers can consume in

real time.

In HFT, precision is the power.

Knowing exactly when something happened
is just as important as knowing what

happened. Now, we enter the most
hardware optimized part of the pipeline.

FPGA acceleration.

FPGA stands for Field Programmable Gate
Array.

a type of reconfigurable chip that can
run custom logic at the speed of

hardware, without the overhead of CPU or
OS.

In HFT, FPGAs are used for tick -to
-trade execution, meaning the moment a

or market event arrives, it's evaluated
by logic on the FPGA, and a trading

decision can be made in sub -microsecond
latency.

Why is this important?

Because again, every microsecond counts.

By the time a CPU thread spins up, the
FPGA has already evaluated the

opportunity and fired off an order.

These FPGAs are often directly connected
to the event queue, receive nanosecond

timestamped events and run predefined
trading strategies.

Think arbitrage, market making or code
stuffing, all wired into silicon.

Some firms even go a step further. They
push the entire decision making logic

into the FPGA to bypass software
completely.

Of course, this also comes with
complexity.

FPGA code is written in Verilog or VHDL,
and every logic path must be

deterministic. But when done right, it
gives you the fastest edge in the

Now, while FPGAs handle ultra -low
latency scenarios,

most trading logic still runs on
software -based strategy engines.

A market -making engine listens to the
event stream, evaluates the current

of the order book, and makes rapid
decisions.

For example, should we code tighter,
should we widen the spread, or should we

pull our orders?

Let's say the latest bid is at $9 .99
and the best ask is at $10 .01.

So your engine might place a buy at $9
.99 and sell at $10 .01 to capture the

spread. But it constantly recalculates
based on market movements, volatility

inventory risk.

These engines can be rule -based,
statistical or even use lightweight

learning models.

But whatever the strategy is, The focus
is on speed and predictability.

Once a decision is made, the order is
pushed to the smart order router, which

takes care of where and how to execute,
possibly across multiple exchanges.

The strategy engine is the brain of the
system, but a brain that thinks in

microseconds.

Once a trading strategy decides to place
an order, it's not blindly fired off to

an exchange.

It's first routed through a smart order
router.

A component that decides where and how
to send the order for optimal execution.

Should it go to NASDAQ, NYSE or should
it be a market order or a limit order?

The router evaluates multiple venues in
real time based on liquidity, latency,

fill probability and even rebate
structures.

But before the order goes out, it passes
through pre -trade risk checks.

And these are absolutely critical for
preventing financial disasters.

The risk engine ensures you are not
overspending.

The order isn't too big and the strategy
isn't misfiring due to a bug.

These checks are automated and happen in
microseconds.

If anything looks off, the order is
blocked before it ever hits the

Once cleared, the smart router sends the
order to the selected exchange and the

execution log flows back into the system
for audit, analysis and learning.

This final checkpoint ensures that speed
never overrides safety.

After a trade is executed, It's the
order management system, OMS, that

and logs everything.

The OMS keeps a complete record of
orders sent, status updates such as

partially filled, rejected, the
execution timestamps, and the routes

It acts like the central nervous system
of the trading platform, coordinating

between exchangers, strategy engines,
and reporting systems.

Meanwhile, a monitoring and metric stack
runs in parallel, capturing latency

data, system health, and performance
metrics for every component.

You'll typically see a latency dashboard
showing tick -to -trade times, metrics

collectors tracking throughput, error
rates, and queue depths, and alerts if

component slows down or behaves
abnormally.

All of this is key for post -trade
analysis, compliance reporting, and

continuous optimization.

In HFT, even a few microseconds of
slowness can lead to missed

major losses.

So, real -time monitoring isn't
optional. It's part of the competitive

from ingesting market data to making
split -second decisions and executing

trades in microseconds.

It's a beautiful mix of hardware
acceleration, event -driven software,

nanosecond precision, and ruthless
optimization, all built to save off

possible delay.

If you are into system design, low
-latency engineering, or just love

under the hood of high -performance
infrastructure, make sure to like this

video, subscribe to the channel, and hit
the bell icon so you don't miss the

next deep dive.

And hey, let me know in the comments
which part of the architecture blew your

mind the most.

Would you want a deeper dive on strategy
logic, FPGAs or matching engines?

See you in the next one.