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
importccxtfrom'ccxt'importMaximumSubarrayDFSfrom'maximumsubarraydfs'/** * Fetch historical data */constexchange=newccxt.binance()constsymbol='BTC/USDT'consttimeframe='1h'constlimit=1000consthistoricalData=awaitexchange.fetchOHLCV(symbol,timeframe,undefined,limit)/** * Find maximum subarray */constalgoInit=newMaximumSubarrayDFS(historicalData)constprediction=algoInit.findMaxSubarray()console.log({ prediction }){
prediction: {
price: 68625.96,
timestamp: 1711562400000,
direction: 'bullish'
}
}
MIT