This project class is designed for predicting potential breakout patterns in historical financial market data. It utilizes the Maximum Subarray algorithm with Depth-First Search (DFS) to identify periods of significant price movement.
npm install ccxt
npm install maximumsubarraydfs
import ccxt from 'ccxt'
import MaximumSubarrayDFS from 'maximumsubarraydfs'
/**
* Fetch historical data
*/
const exchange = new ccxt.binance()
const symbol = 'BTC/USDT'
const timeframe = '1h'
const limit = 1000
const historicalData = await exchange.fetchOHLCV(symbol, timeframe, undefined, limit)
/**
* Find maximum subarray
*/
const algoInit = new MaximumSubarrayDFS(historicalData)
const prediction = algoInit.findMaxSubarray()
console.log({ prediction }){
prediction: {
price: 68625.96,
timestamp: 1711562400000,
direction: 'bullish'
}
}
MIT