noastud / fundingrate Goto Github PK

= SPEC-001: Kraken Funding Rate Arbitrage Bot :sectnums: :toc:

== Background

The goal of this project is to create a locally hosted web application using Node.js that serves as a funding rate arbitrage bot for the Kraken cryptocurrency exchange. This bot will monitor funding rates in real-time, identify arbitrage opportunities, and alert users to these opportunities. In the future, the application may be expanded to include other exchanges, but the initial focus is solely on Kraken.

== Requirements

Must Have:

• Real-time data fetching from Kraken
• Display of funding rates and arbitrage opportunities
• Notification system using Discord for alerting on potential arbitrage opportunities

Should Have:

• Dashboard with charts to visualize funding rates
• Tables to list arbitrage opportunities
• Basic and clean design using a popular UI framework like React

Could Have:

• Historical data analysis
• Advanced user settings and preferences
• Integration with other exchanges

Won't Have:

• User authentication and registration (single-user system)
• Expansion to other exchanges (initially)

== Method

=== Architecture Design

The application will be designed using a modular architecture to ensure scalability and ease of maintenance. The primary components of the architecture are:

1. Frontend: A React-based user interface.
2. Backend: A Node.js server to handle API requests and business logic.
3. Database: MongoDB for storing historical funding rates and arbitrage opportunities.
4. APIs: Integration with Kraken's APIs for fetching real-time data.
5. Notification System: Integration with Discord to send alerts.

[plantuml] @startuml package "Frontend" { [React Application] }

package "Backend" { [Node.js Server] [Arbitrage Module] }

package "Database" { [MongoDB] }

package "External APIs" { [Kraken API 1] [Kraken API 2] }

package "Notification System" { [Discord Bot] }

[React Application] --> [Node.js Server] : "User Interactions" [Node.js Server] --> [Arbitrage Module] : "Arbitrage Logic" [Node.js Server] --> [MongoDB] : "Data Storage" [Arbitrage Module] --> [Kraken API 1] : "Fetch Real-time Data" [Arbitrage Module] --> [Kraken API 2] : "Fetch Real-time Data" [Arbitrage Module] --> [Discord Bot] : "Send Notifications" @enduml

=== Database Schema

The MongoDB database will have the following collections:

1. FundingRates: To store funding rates fetched from Kraken.
2. ArbitrageOpportunities: To store identified arbitrage opportunities.

Schema definitions:

// FundingRates collection schema
const fundingRateSchema = new mongoose.Schema({
  timestamp: Date,
  rate: Number,
  pair: String
});

// ArbitrageOpportunities collection schema
const arbitrageOpportunitySchema = new mongoose.Schema({
  timestamp: Date,
  pair: String,
  rateDifference: Number,
  opportunityDetails: String
});

=== Components

1. React Application: Provides the user interface for interacting with the bot, including dashboards, charts, and tables.
2. Node.js Server: Handles API requests and implements the business logic for arbitrage.
3. Arbitrage Module: Implements the logic for fetching data from Kraken, analyzing funding rates, and identifying arbitrage opportunities.
4. Notification System: Sends alerts to users about potential arbitrage opportunities via Discord.

== Implementation

=== Step 1: Setup Development Environment

1. Install Node.js and npm (Node Package Manager) on your local machine.
2. Install MongoDB and start the MongoDB server.
3. Set up a new Node.js project and initialize it with npm init.
4. Install necessary dependencies:

   npm install express mongoose axios
   npm install react react-dom
   npm install @discordjs/rest discord-api-types discord.js

=== Step 2: Develop Backend

1. Initialize Express Server:

   • Create an Express server to handle API requests.

   const express = require('express');
   const mongoose = require('mongoose');
   const bodyParser = require('body-parser');
   
   const app = express();
   app.use(bodyParser.json());
   
   mongoose.connect('mongodb://localhost:27017/arbitrageBot', { useNewUrlParser: true, useUnifiedTopology: true });
   
   app.listen(3000, () => {
     console.log('Server running on port 3000');
   });

2. Fetch and Store Data from Kraken:

   • Use Axios to fetch data from Kraken APIs and store it in MongoDB.

   const axios = require('axios');
   
   async function fetchFundingRates() {
     const response = await axios.get('KRACKEN_API_URL_1');
     // Process and store data in MongoDB
   }
   
   async function fetchArbitrageOpportunities() {
     const response = await axios.get('KRACKEN_API_URL_2');
     // Process and store data in MongoDB
   }
   
   setInterval(fetchFundingRates, 60000); // Fetch every minute
   setInterval(fetchArbitrageOpportunities, 60000); // Fetch every minute

3. Discord Notification System:

   • Set up a Discord bot and use it to send notifications.

   const { Client, Intents } = require('discord.js');
   const client = new Client({ intents: [Intents.FLAGS.GUILDS, Intents.FLAGS.GUILD_MESSAGES] });
   
   client.once('ready', () => {
     console.log('Discord bot is ready');
   });
   
   async function sendDiscordNotification(message) {
     const channel = client.channels.cache.get('YOUR_DISCORD_CHANNEL_ID');
     if (channel) {
       channel.send(message);
     }
   }
   
   client.login('YOUR_DISCORD_BOT_TOKEN');

4. Arbitrage Logic:

   • Implement the logic to analyze funding rates and identify arbitrage opportunities.

   function analyzeArbitrage() {
     // Fetch data from MongoDB, analyze it, and identify opportunities
     // Use sendDiscordNotification to alert users
   }
   
   setInterval(analyzeArbitrage, 60000); // Analyze every minute

=== Step 3: Develop Frontend

1. Create React Application:

   • Set up a new React application to provide the user interface.

   npx create-react-app arbitrage-bot-ui
   cd arbitrage-bot-ui
   npm start

2. Develop UI Components:

   • Implement components for displaying funding rates and listing arbitrage opportunities.

   // Example: Display Funding Rates Component
   import React, { useEffect, useState } from 'react';
   import axios from 'axios';
   
   function FundingRates() {
     const [rates, setRates] = useState([]);
   
     useEffect(() => {
       async function fetchData() {
         const response = await axios.get('/api/funding-rates');
         setRates(response.data);
       }
       fetchData();
     }, []);
   
     return (
       <table>
         <thead>
           <tr>
             <th>Pair</th>
             <th>Rate</th>
             <th>Timestamp</th>
           </tr>
         </thead>
         <tbody>
           {rates.map(rate => (
             <tr key={rate.timestamp}>
               <td>{rate.pair}</td>
               <td>{rate.rate}</td>
               <td>{new Date(rate.timestamp).toLocaleString()}</td>
             </tr>
           ))}
         </tbody>
       </table>
     );
   }
   
   export default FundingRates;

=== Step 4: Testing and Deployment

1. Testing:

   • Test each component and integration point thoroughly.
   • Perform system testing to ensure all requirements are met.

2. Deployment:

   • Deploy the Node.js server and MongoDB instance locally.
   • Serve the React application using a tool like serve.

   npm install -g serve
   serve -s build

== Milestones

1. Week 1: Setup development environment and create initial project structure.
2. Week 2: Implement backend services including data fetching and notification system.
3. Week 3: Develop frontend components and integrate with backend.
4. Week 4: Implement arbitrage logic and finalize the application.
5. Week 5: Testing and deployment.

== Gathering Results

To evaluate whether the requirements were addressed properly and the performance of the system post-production:

1. User Feedback: Collect feedback on the usability and effectiveness of the bot.
2. System Monitoring: Monitor the performance and accuracy of arbitrage detection.
3. Bug Fixes and Enhancements: Address any issues and implement necessary improvements based on feedback.