Orderbook Delta Bot

A trading bot written in Rust 🦀.

The strategy based on the concept of mean reversion. We look for large deviations in the volume delta of BTC-PERP on FTX until a defined depth. These deviations could be caused by over-enthusiastic and over-leveraged market participants (speculation).

We counter-trade those deviations, and enter short/long positions based on triggers given by a large deviation (> 2 SDs) on the orderbook delta from a 20 period rolling bollinger band.

We are testing this with BTC-PERP on FTX, which has good liquidity and small spreads (and FTX now Binance, praise be to CZ, has the best API in the business). In principle, the scheme could be modified for lower liquidity pairs too, perhaps by adjusting the sampling period and market depth for generating triggers.

We use the definitions:

Name	Definition
bid_ask_delta	Difference between the sum of bid and ask volumes till a defined depth
bb.upper	Upper bollinger band (L=20, SD=2) of bid_ask_delta
bb.lower	Lower bollinger band (L=20, SD=2) of bid_ask_delta

Trigger	Position
bid_ask_delta > bb.upper	short
bid_ask_delta < bb.lower	long

A full analysis of this strategy along with its limitations in dineshpinto/market-analytics.

Installation

Clone the repository

With Git

git clone https://github.com/CreativeDev0508/orderbook-delta-bot.git

With GitHub CLI

gh repo clone CreativeDev0508/orderbook-delta-bot

Set up bot

Bot settings

Rename settings-example.json to settings.json. The default settings are given below.

Place live orders (optional)

• Rename .env.example to .env, and enter in your FTX API keys
• Set "live" : true in settings.json

Install all dependencies and build

cargo build

🫡 Run script

cargo run

Orderbook Delta GUI (optional delta strategy tester)

To test out new delta strategies and visualize them live, use the orderbook-delta-visualizer. It's written in Python, with plotting handled by Dash and Plotly, and contains a set of configurable parameters and strategies. See orderbook-delta-visualizer/ for more details.

orderbook_visualizer.mov

Settings

settings.json contains all the configurable options:

Name	Explanation
market_name	Name of futures market on FTX (default: BTC-PERP)
sampling_time	Time (in seconds) to sample orderbook, each sample is 1s (default: 60)
bb_period	Bollinger band period (default: 20)
bb_std_dev	Bollinger band standard deviation (default: 2)
orderbook_depth	Depth of orderbook to sum (default: 5)
live	Place live orders on FTX, requires API keys in .env (default: false)
order_size	Size of order to place (default: 0.1618 BTC)
tp_percent	Percent move to take profit at (default: 0.2%)
sl_percent	Percent move to stop loss at (default: 0.1%)
write_to_file	Store positions in a csv file for further analysis (default: true)

TODO

• Use Kelly criterion for order sizing (probabilities can be estimated from prior analysis)
• Use dynamic take profit and stop loss based on market movement (this is simply used as protection from getting rekt, not as actual exit points)
• Perform spectral analysis with wider timeframes to identify optimal market conditions
• Switch to websockets API for reduced data query lag
• For more high frequency applications, switching to a library like ccapi is handy. Unfortunately this only exists for C++ right now.

Disclaimer

You should not construe any such information or other material as legal, tax, investment, financial, or other advice. Nothing contained here constitutes a solicitation, recommendation, endorsement, or offer by me or any third party service provider to buy or sell any securities or other financial instruments in this or in any other jurisdiction in which such solicitation or offer would be unlawful under the securities laws of such jurisdiction.

If you plan to use real money, use at your own risk.

Under no circumstances will I be held responsible or liable in any way for any claims, damages, losses, expenses, costs, or liabilities whatsoever, including, without limitation, any direct or indirect damages for loss of profits.