Market arbitrage

This bot implements a market arbitrage strategy using various cryptocurrencies on different exchanges.

The bot uses the most popular open-source trading library ccxt in order to find best price spread on the market.

Requirements

Dokcer

Installation

git clone https://github.com/antonga23/market_arbitrage.git

cd market_arbitrage

docker build ./ -t $image_name

docker run -p $port:3000 -d --name $container_name $image_name

docker logs -f $container_name

Usage

First, you need to specify the markets you are going to target. Here is a list of supported markets by the ccxt library:

exchanges = [
    "binance",
    "bittrex",
    "hitbtc",
    "poloniex",
    "luno",
    "bitmex",
    "ice3x",
]

In order for the bot to be able to fetch market data, it needs an API Key and a Secret Token for each market (exchange) you are going to target:

exchangesData = {
    "ice3x": {
        "apiKey": "",
        "secret": "",
        "transactionFee": 0.001
    },
    "binance": {
        "apiKey": "",
        "secret": "",
        "transactionFee": 0.001
    },
    "bittrex": {
        "apiKey": "",
        "secret": "",
        "transactionFee": 0.0025
    },
    "poloniex": {
        "apiKey": "",
        "secret": "",
        "transactionFee": 0.0025
    },
    "luno": {
        "apiKey": "",
        "secret": "",
        "transactionFee": 0.002
    },
}

Secondly, you need to specify for which symbols should the bot look, here is a list of the most common ones:

symbols = [
    "ETH/ZAR",
    "BTC/ZAR",
    "BTC/ETH",
    "BCH/USDT",
    "DASH/USDT",
    "XMR/USDT",
    "LTC/USDT",
]

You can also specify min spread and min profit that you are interested in:

min_spread = 1 ## as percentages 
min_profit = 0 ## as percentages

Take in mind that there are two ways to create buy orders: create_market_buy_order and create_limit_buy_order. You should decide for yourself what method fits you better.

For more information on how each method works, take a look at the official ccxt documentation.

Also huge credit to @Andrei Zgirvaci