So you're curious about market making but don't want to commit to expensive hardware? I get it. That's exactly why I decided to test the waters using a Raspberry Pi, a tiny computer that costs less than $100 but packs enough punch to run automated trading strategies 24/7.
This guide walks you through setting up Hummingbot, an open-source market making bot, on a Raspberry Pi 4. Fair warning: this isn't a "click and profit" situation. You'll need some patience, a bit of technical know-how, and realistic expectations about what market making actually involves.
Market making sounds fancy, but it's essentially providing liquidity to exchanges by placing both buy and sell orders. You profit from the spread between these orders, but you're also exposed to market volatility. If prices swing dramatically, you could end up holding assets that lose value faster than your spread profits accumulate.
Before diving in, spend time understanding market making strategies. The Hummingbot documentation is excellent for this. Don't skip the learning phase—your capital will thank you later.
For those looking to explore automated trading strategies without the hardware setup hassle, 👉 platforms like Pionex offer built-in trading bots that can get you started immediately while you learn the ropes.
Here's what you'll need to get started:
Raspberry Pi 4 (4GB RAM works fine; 8GB is better if available)
High-speed microSD card (at least 32GB)
USB Type-C charger (3 Amperes minimum)
MicroSD card reader
Optional but recommended: A case with a cooling fan
Optional: LAN cable (though WiFi works perfectly)
I spent around $75 for everything during a sale. Not bad considering this setup can run multiple trading strategies simultaneously once configured properly.
This setup assumes you have stable internet and uninterrupted power. Market making bots need constant uptime. Random disconnections mean missed opportunities and potentially unfilled orders that could leave you exposed.
I'm running this wirelessly on my home network without issues, but your mileage may vary depending on your internet reliability.
Download the 64-bit Raspberry Pi OS. The 32-bit version causes dependency nightmares, so don't even think about it. You'll find the beta 64-bit version on the Raspberry Pi forums.
Use the Raspberry Pi Imager tool to write the OS to your SD card. Select "Use Custom" and load the 64-bit image you downloaded.
If you're like me and don't have a spare monitor lying around, you'll need to connect to your Pi remotely via SSH. Here's the trick: after writing the OS to the SD card, create a blank file named "ssh" (no extension) in the boot directory. This tells the Pi to enable SSH on first boot.
For WiFi setup, create a file called wpa_supplicant.conf in the same boot directory:
ctrl_interface=DIR=/var/run/wpa_supplicant GROUP=netdev
update_config=1
country=US
network={
ssid="YourWiFiName"
psk="YourPassword"
key_mgmt=WPA-PSK
}
Replace the country code with yours, add your WiFi credentials, and you're set.
Pop the SD card into your Pi and power it on. After a minute or two, log into your router's admin panel (usually 192.168.1.1) and find the IP address assigned to your Raspberry Pi.
Using PuTTY (on Windows) or Terminal (on Mac/Linux), connect to your Pi:
ssh pi@[your-pi-ip-address]
Default password is "raspberry". Change it immediately using passwd once you're in.
Hummingbot requires Python 3.7 specifically. Newer versions cause compatibility issues. First, check your default Python version:
python --version
Set Python 3.7 as default:
sudo update-alternatives --install /usr/bin/python python /usr/bin/python3.7 2
Miniforge is a lightweight conda distribution that works perfectly on ARM architecture:
wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-aarch64.sh
sh Miniforge3-Linux-aarch64.sh
Follow the prompts and let it initialize your shell. Close and reopen your terminal afterward.
Don't use the default Python 3.8 that conda wants to install. Stick with 3.7:
conda create --name hummingbot python=3.7
conda activate hummingbot
This is where I hit multiple roadblocks. Installing dependencies on ARM architecture isn't always straightforward. Here's the order that worked for me:
conda install pandas numpy
pip install cython cachetools aiohttp ruamel.yaml
The eth_account package was particularly stubborn. Regular installation failed repeatedly until I specified an older version:
pip install "eth_account==0.4.0"
Then install the remaining dependencies:
pip install aiokafka sqlalchemy binance python-binance ujson websockets signalr-client-aio web3 prompt_toolkit 0x-order-utils 0x-contract-wrappers eth_bloom pyperclip telegram python-telegram-bot pyjwt mypy_extensions bitstring pyblake2 pysha3
Clone the repository:
git clone https://github.com/CoinAlpha/hummingbot.git
Compile it:
cd hummingbot && ./clean && ./compile
Run it:
bin/hummingbot.py
If you see the Hummingbot command line interface, congratulations! You've made it through the hardest part.
Getting Hummingbot installed is just the beginning. Actually configuring strategies, connecting to exchanges, and managing your bot requires another learning curve entirely. The Hummingbot documentation and YouTube channel are your best friends here.
For those interested in exploring automated market making without the technical setup, 👉 specialized crypto trading platforms provide user-friendly alternatives with similar functionality built right in.
If things aren't working, verify your Python and conda versions:
python --version # Should show 3.7.x
conda -V
pip -V
Check your installed packages with conda list and compare with working installations. Version mismatches are usually the culprit.
Want to run multiple strategies simultaneously? Look into TMux, a terminal multiplexer that lets you run several Hummingbot instances in parallel. This turns your Raspberry Pi into a proper trading station.
Setting up a market making bot on Raspberry Pi is definitely doable, but it's not plug-and-play. You'll troubleshoot dependency issues, wrestle with version conflicts, and probably reinstall things a few times. But once it's running, you have a low-cost, low-power trading setup that can operate continuously.
Is it worth it? That depends on your goals. If you're learning about algorithmic trading and want hands-on experience with the infrastructure, absolutely. If you just want to profit from market making strategies, consider whether the time investment matches your objectives.
Either way, start small, test thoroughly, and never risk more than you can afford to lose. Market making isn't passive income—it's active risk management with profit potential.
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