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For those of you in the trenches, I offer ye this tool ⚔️

This is a plotting tool designed to help visualize financial market data 📈 and trading system behavior 🤖 on the smallest timescales 🔎.

As all things in life, when it comes to financial microstructure:the devil 😈 is in the details

Built usingChaco 🌮

See theillustrated example for a deep dive into what this plotting tool can uncover 🔎.

• ⚠️Disclaimer
• ✨Features
• 🧠Illustrated Example
• 🧪Test It Out Right Now
• 🗺️Plots Legend
• 💸Free Advice
• ✏️Data Schema
• 🤔What is "Market Microstructure"?
• 🛞Installation
• 📜Reqs
• 𓊍To Do
• Citation
• License

There is no α here. This is just a fancy wrapper on top of an open-source plotting package.

You shouldB.Y.O.A (Bring Your Own Alpha).

However...for the trained eye 👁️, this simple type of visualization can be immensely helpful.

Here are some useful features to take note of 🥁:

1. ✨Plotmultiple 🤹, asynchronous (unsampled) microstructure elements together onthe sample plot:order book quotes,trades,orders,order acks,fills etc etc
2. ✨Analyze events on seconds, milliseconds, microseconds,nanoseconds 🕳️ : zoom 🔎 in on themost granular time unit available to microstructure behavior
3. ✨All axes are 🔗linked : 🔎zoom in on one product, see what's happening in all others at that same timestamp

To show why a tool like this might be useful,here is an example motivated from things seen in the wild.

Note: This data was painstakingly createdby hand 🤌 to appear quasi-realistic. I am not an artist 🧑‍🎨 nor is this real 🌎 data.

See thelegend 👇 to understand the plots further.

After installing the package either viapip or viasetup.py, run this quick line to see this in action right now:

bash examples/example_1/plot_example.sh

or

python examples/example_1/plot_example.py

Right-click 🖱️ to zoom in on different parts of the plot to see what is happening onsmaller andsmaller timescales 🔎. Consult thelegend orillustrated example for more clarity on how to interpret the plots.

Here is a complete legend of everything the plotter can visualize.

1. Don't log in prod ✏️ (unless logging isn't occuring on the hot path).
2. Make sure the timestamps are from ⏰synchronized clocks ⏰ (better if geosync'd/GPS) with enough precision, otherwise these plots will be uninformative or misleading. If you don't trust others' timestamps, do your own capture.
3. This plotter ismemory intensive 🧠. Don't try to plot too much at once.

This plotting module expects a specificdata schema.

For the uninitiated, here is a⏰ 30 second primer ⏰ on market microstructure.

You can install the repo using pip directly:

pip install git+https://github.com/will-thompson-k/microstructure-plotter

Alternatively you can use the setup.py.

Python 3.7+ recommended.

Here are the package requirements (found in requirements.txt)

• chaco==5.1.0
• enable==5.3.1
• traits==6.4.1
• traitsui==7.4.2
• pandas==1.3.5
• pyqt

• add more order types: modifies, equity order types, etc.
• add "decision boundary" of model: bid/ask edges, etc.
• unit tests

@misc{microstructure-plotter,author= {Thompson,Will},url= {https://github.com/will-thompson-k/microstructure-plotter},year= {2023}}

MIT