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