Enigma

Matrix AI for crypto trading.

Overview

Enigma consists of a few parts:

• Harvester: Fetches market data from various sources
• Composer: Performs calculations such as moving averages on the market data
• Analyzer: Runs investement trials on data to create a dictionary
• Invester: Calls buys/sells using analyzed data

Data Models for market

high: Float
low: Float
open: Float
close: Float
volume: Float
market: String
currency: String
timestamp: Date
interval: String
cap: Float

Data schema for analysis

id: Any - Unique id
name: String // Descripton of data
source: String // Function to get data
created: Date // Date we added this data
timestamp: Date
values: [{
    value: Float
    precision: Float
}]

Data schema for masks

id: Any - Unique id
created: Date // Date we created this mask
value: Any // Reference to analysis column
precision: // Float

Data schema for investement

mask: Any // Mask id
investements[{
    risk: Float // Risk factor
    profit: Float
}]

Collection types

• Currency charts
• Alternative data charts (can be anything quantifiable)
• Analysis grid - one huge table that aggregates everything with precision columns
• Dictionary - holds various mask/data

Importing CSV

Need to convert numbers to floats so convert to json then

mongoimport --db dbName --collection collectionName --file fileName.json --jsonArray

Analysis functions

These can be either standard market analysis functions from Talib/Tulip or other data such as twitter sentiment, blockchain info, etc.

Each function accepts parameters, provides data fetching methods, transfomation, scheduling and storage.

Strategies

Strategies are responsible for triggering trades based on provided data from a runner.