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ruv
543
npm/packages/agentic-synth/examples/stocks/market-data.ts
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543
npm/packages/agentic-synth/examples/stocks/market-data.ts
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/**
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* Stock Market Data Generation Examples
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*
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* Demonstrates realistic OHLCV data generation, technical indicators,
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* multi-timeframe data, market depth, and tick-by-tick simulation.
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*/
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import { AgenticSynth } from '../../../src';
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// ============================================================================
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// OHLCV Data Generation
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// ============================================================================
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interface OHLCVBar {
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timestamp: Date;
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open: number;
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high: number;
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low: number;
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close: number;
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volume: number;
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symbol: string;
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}
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/**
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* Generate realistic OHLCV (candlestick) data with proper market microstructure
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*/
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async function generateOHLCVData() {
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const synth = new AgenticSynth();
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const ohlcvData = await synth.generate<OHLCVBar>({
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count: 390, // One trading day (6.5 hours * 60 minutes)
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template: {
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timestamp: '{{date.recent}}',
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open: '{{number.float(100, 200, 2)}}',
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high: '{{number.float(100, 200, 2)}}',
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low: '{{number.float(100, 200, 2)}}',
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close: '{{number.float(100, 200, 2)}}',
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volume: '{{number.int(100000, 10000000)}}',
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symbol: 'AAPL',
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},
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constraints: [
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// High must be >= max(open, close)
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'bar.high >= Math.max(bar.open, bar.close)',
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// Low must be <= min(open, close)
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'bar.low <= Math.min(bar.open, bar.close)',
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// Volume must be positive
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'bar.volume > 0',
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],
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relationships: [
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{
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type: 'temporal',
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field: 'timestamp',
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interval: '1m', // 1-minute bars
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},
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{
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type: 'continuity',
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sourceField: 'close',
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targetField: 'open',
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description: 'Next bar opens at previous close',
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},
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],
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});
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// Post-process to ensure OHLCV validity
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const validatedData = ohlcvData.map((bar, idx) => {
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if (idx > 0) {
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bar.open = ohlcvData[idx - 1].close; // Open = previous close
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}
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bar.high = Math.max(bar.open, bar.close, bar.high);
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bar.low = Math.min(bar.open, bar.close, bar.low);
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return bar;
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});
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console.log('Generated OHLCV Data (first 5 bars):');
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console.log(validatedData.slice(0, 5));
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return validatedData;
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}
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// ============================================================================
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// Technical Indicators
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// ============================================================================
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interface TechnicalIndicators {
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timestamp: Date;
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price: number;
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sma_20: number;
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sma_50: number;
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rsi_14: number;
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macd: number;
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macd_signal: number;
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bb_upper: number;
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bb_middle: number;
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bb_lower: number;
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volume: number;
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symbol: string;
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}
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/**
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* Generate price data with technical indicators pre-calculated
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*/
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async function generateTechnicalIndicators() {
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const synth = new AgenticSynth();
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// First generate base price series
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const priceData = await synth.generate<{ price: number; volume: number }>({
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count: 100,
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template: {
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price: '{{number.float(150, 160, 2)}}',
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volume: '{{number.int(1000000, 5000000)}}',
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},
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});
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// Calculate indicators (simplified for demonstration)
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const calculateSMA = (data: number[], period: number): number[] => {
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const sma: number[] = [];
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for (let i = 0; i < data.length; i++) {
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if (i < period - 1) {
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sma.push(data[i]);
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} else {
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const sum = data.slice(i - period + 1, i + 1).reduce((a, b) => a + b, 0);
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sma.push(sum / period);
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}
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}
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return sma;
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};
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const calculateRSI = (data: number[], period: number = 14): number[] => {
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const rsi: number[] = [];
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for (let i = 0; i < data.length; i++) {
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if (i < period) {
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rsi.push(50); // Neutral RSI for initial period
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} else {
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const gains: number[] = [];
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const losses: number[] = [];
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for (let j = i - period + 1; j <= i; j++) {
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const change = data[j] - data[j - 1];
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if (change > 0) gains.push(change);
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else losses.push(Math.abs(change));
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}
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const avgGain = gains.reduce((a, b) => a + b, 0) / period;
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const avgLoss = losses.reduce((a, b) => a + b, 0) / period;
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const rs = avgLoss === 0 ? 100 : avgGain / avgLoss;
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rsi.push(100 - 100 / (1 + rs));
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}
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}
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return rsi;
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};
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const prices = priceData.map((d) => d.price);
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const sma20 = calculateSMA(prices, 20);
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const sma50 = calculateSMA(prices, 50);
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const rsi = calculateRSI(prices);
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const technicalData: TechnicalIndicators[] = priceData.map((bar, idx) => ({
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timestamp: new Date(Date.now() - (priceData.length - idx) * 60000),
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price: bar.price,
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sma_20: Number(sma20[idx].toFixed(2)),
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sma_50: Number(sma50[idx].toFixed(2)),
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rsi_14: Number(rsi[idx].toFixed(2)),
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macd: Number((sma20[idx] - sma50[idx]).toFixed(2)),
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macd_signal: Number((sma20[idx] - sma50[idx]) * 0.9).toFixed(2), // Simplified
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bb_upper: Number((sma20[idx] * 1.02).toFixed(2)),
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bb_middle: Number(sma20[idx].toFixed(2)),
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bb_lower: Number((sma20[idx] * 0.98).toFixed(2)),
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volume: bar.volume,
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symbol: 'AAPL',
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}));
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console.log('Technical Indicators (last 5 bars):');
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console.log(technicalData.slice(-5));
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return technicalData;
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}
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// ============================================================================
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// Multi-Timeframe Data
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// ============================================================================
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interface MultiTimeframeData {
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'1m': OHLCVBar[];
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'5m': OHLCVBar[];
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'1h': OHLCVBar[];
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'1d': OHLCVBar[];
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}
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/**
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* Generate data across multiple timeframes with proper aggregation
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*/
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async function generateMultiTimeframeData(): Promise<MultiTimeframeData> {
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const synth = new AgenticSynth();
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// Generate 1-minute bars (base timeframe)
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const bars1m = await synth.generate<OHLCVBar>({
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count: 1560, // 4 trading days worth of 1-minute data
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template: {
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timestamp: '{{date.recent}}',
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open: '{{number.float(100, 200, 2)}}',
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high: '{{number.float(100, 200, 2)}}',
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low: '{{number.float(100, 200, 2)}}',
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close: '{{number.float(100, 200, 2)}}',
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volume: '{{number.int(10000, 100000)}}',
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symbol: 'AAPL',
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},
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});
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// Aggregate to 5-minute bars
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const bars5m: OHLCVBar[] = [];
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for (let i = 0; i < bars1m.length; i += 5) {
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const chunk = bars1m.slice(i, i + 5);
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if (chunk.length === 5) {
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bars5m.push({
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timestamp: chunk[0].timestamp,
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open: chunk[0].open,
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high: Math.max(...chunk.map((b) => b.high)),
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low: Math.min(...chunk.map((b) => b.low)),
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close: chunk[4].close,
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volume: chunk.reduce((sum, b) => sum + b.volume, 0),
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symbol: 'AAPL',
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});
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}
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}
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// Aggregate to 1-hour bars
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const bars1h: OHLCVBar[] = [];
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for (let i = 0; i < bars1m.length; i += 60) {
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const chunk = bars1m.slice(i, i + 60);
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if (chunk.length === 60) {
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bars1h.push({
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timestamp: chunk[0].timestamp,
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open: chunk[0].open,
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high: Math.max(...chunk.map((b) => b.high)),
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low: Math.min(...chunk.map((b) => b.low)),
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close: chunk[59].close,
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volume: chunk.reduce((sum, b) => sum + b.volume, 0),
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symbol: 'AAPL',
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});
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}
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}
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// Aggregate to 1-day bars
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const bars1d: OHLCVBar[] = [];
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for (let i = 0; i < bars1m.length; i += 390) {
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const chunk = bars1m.slice(i, i + 390);
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if (chunk.length === 390) {
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bars1d.push({
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timestamp: chunk[0].timestamp,
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open: chunk[0].open,
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high: Math.max(...chunk.map((b) => b.high)),
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low: Math.min(...chunk.map((b) => b.low)),
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close: chunk[389].close,
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volume: chunk.reduce((sum, b) => sum + b.volume, 0),
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symbol: 'AAPL',
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});
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}
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}
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console.log('Multi-timeframe data generated:');
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console.log(`1m bars: ${bars1m.length}`);
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console.log(`5m bars: ${bars5m.length}`);
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console.log(`1h bars: ${bars1h.length}`);
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console.log(`1d bars: ${bars1d.length}`);
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return {
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'1m': bars1m,
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'5m': bars5m,
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'1h': bars1h,
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'1d': bars1d,
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};
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}
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// ============================================================================
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// Market Depth Data (Order Book)
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// ============================================================================
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interface OrderBookLevel {
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price: number;
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size: number;
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orders: number;
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}
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interface MarketDepth {
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timestamp: Date;
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symbol: string;
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bids: OrderBookLevel[];
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asks: OrderBookLevel[];
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spread: number;
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midPrice: number;
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}
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/**
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* Generate realistic Level 2 market depth data (order book)
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*/
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async function generateMarketDepth() {
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const synth = new AgenticSynth();
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const midPrice = 150.0;
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const tickSize = 0.01;
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const depth = 20; // 20 levels on each side
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const marketDepth = await synth.generate<MarketDepth>({
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count: 100,
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template: {
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timestamp: '{{date.recent}}',
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symbol: 'AAPL',
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bids: [],
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asks: [],
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spread: 0,
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midPrice: midPrice,
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},
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});
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// Generate order book levels
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const enrichedDepth = marketDepth.map((snapshot) => {
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const bids: OrderBookLevel[] = [];
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const asks: OrderBookLevel[] = [];
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// Generate bid side (below mid price)
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for (let i = 0; i < depth; i++) {
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bids.push({
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price: Number((midPrice - i * tickSize).toFixed(2)),
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size: Math.floor(Math.random() * 10000) + 100,
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orders: Math.floor(Math.random() * 50) + 1,
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});
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}
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// Generate ask side (above mid price)
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for (let i = 0; i < depth; i++) {
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asks.push({
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price: Number((midPrice + (i + 1) * tickSize).toFixed(2)),
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size: Math.floor(Math.random() * 10000) + 100,
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orders: Math.floor(Math.random() * 50) + 1,
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});
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}
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const bestBid = bids[0].price;
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const bestAsk = asks[0].price;
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return {
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...snapshot,
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bids,
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asks,
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spread: Number((bestAsk - bestBid).toFixed(2)),
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midPrice: Number(((bestBid + bestAsk) / 2).toFixed(2)),
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};
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});
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console.log('Market Depth (first snapshot):');
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console.log({
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timestamp: enrichedDepth[0].timestamp,
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bestBid: enrichedDepth[0].bids[0],
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bestAsk: enrichedDepth[0].asks[0],
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spread: enrichedDepth[0].spread,
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totalBidVolume: enrichedDepth[0].bids.reduce((sum, b) => sum + b.size, 0),
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totalAskVolume: enrichedDepth[0].asks.reduce((sum, a) => sum + a.size, 0),
|
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});
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return enrichedDepth;
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||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Tick-by-Tick Data
|
||||
// ============================================================================
|
||||
|
||||
interface Tick {
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||||
timestamp: Date;
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||||
symbol: string;
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||||
price: number;
|
||||
size: number;
|
||||
side: 'buy' | 'sell';
|
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exchange: string;
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conditions: string[];
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||||
}
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||||
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||||
/**
|
||||
* Generate high-frequency tick-by-tick trade data
|
||||
*/
|
||||
async function generateTickData() {
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||||
const synth = new AgenticSynth();
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||||
const tickData = await synth.generate<Tick>({
|
||||
count: 10000, // 10k ticks (typical for a few minutes of active trading)
|
||||
template: {
|
||||
timestamp: '{{date.recent}}',
|
||||
symbol: 'AAPL',
|
||||
price: '{{number.float(149.5, 150.5, 2)}}',
|
||||
size: '{{number.int(1, 1000)}}',
|
||||
side: '{{random.arrayElement(["buy", "sell"])}}',
|
||||
exchange: '{{random.arrayElement(["NASDAQ", "NYSE", "BATS", "IEX"])}}',
|
||||
conditions: [],
|
||||
},
|
||||
constraints: [
|
||||
'tick.size > 0',
|
||||
'tick.price > 0',
|
||||
],
|
||||
relationships: [
|
||||
{
|
||||
type: 'temporal',
|
||||
field: 'timestamp',
|
||||
interval: '10ms', // High-frequency ticks
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
// Add trade conditions (regulatory tags)
|
||||
const enrichedTicks = tickData.map((tick) => {
|
||||
const conditions: string[] = [];
|
||||
|
||||
if (tick.size >= 100) conditions.push('BLOCK');
|
||||
if (tick.size >= 10000) conditions.push('INSTITUTIONAL');
|
||||
if (Math.random() < 0.05) conditions.push('ODD_LOT');
|
||||
if (Math.random() < 0.1) conditions.push('EXTENDED_HOURS');
|
||||
|
||||
return {
|
||||
...tick,
|
||||
conditions,
|
||||
};
|
||||
});
|
||||
|
||||
// Calculate tick statistics
|
||||
const buyTicks = enrichedTicks.filter((t) => t.side === 'buy');
|
||||
const sellTicks = enrichedTicks.filter((t) => t.side === 'sell');
|
||||
const avgBuyPrice =
|
||||
buyTicks.reduce((sum, t) => sum + t.price, 0) / buyTicks.length;
|
||||
const avgSellPrice =
|
||||
sellTicks.reduce((sum, t) => sum + t.price, 0) / sellTicks.length;
|
||||
|
||||
console.log('Tick Data Statistics:');
|
||||
console.log({
|
||||
totalTicks: enrichedTicks.length,
|
||||
buyTicks: buyTicks.length,
|
||||
sellTicks: sellTicks.length,
|
||||
avgBuyPrice: avgBuyPrice.toFixed(2),
|
||||
avgSellPrice: avgSellPrice.toFixed(2),
|
||||
priceImbalance: (avgBuyPrice - avgSellPrice).toFixed(4),
|
||||
avgTradeSize:
|
||||
enrichedTicks.reduce((sum, t) => sum + t.size, 0) / enrichedTicks.length,
|
||||
});
|
||||
|
||||
return enrichedTicks;
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Market Microstructure Patterns
|
||||
// ============================================================================
|
||||
|
||||
interface MicrostructureMetrics {
|
||||
timestamp: Date;
|
||||
symbol: string;
|
||||
effectiveSpread: number;
|
||||
realizedSpread: number;
|
||||
priceImpact: number;
|
||||
toxicity: number; // Adverse selection measure
|
||||
orderImbalance: number;
|
||||
volatility: number;
|
||||
}
|
||||
|
||||
/**
|
||||
* Generate market microstructure metrics for analysis
|
||||
*/
|
||||
async function generateMicrostructureMetrics() {
|
||||
const synth = new AgenticSynth();
|
||||
|
||||
const metrics = await synth.generate<MicrostructureMetrics>({
|
||||
count: 390, // One trading day
|
||||
template: {
|
||||
timestamp: '{{date.recent}}',
|
||||
symbol: 'AAPL',
|
||||
effectiveSpread: '{{number.float(0.01, 0.05, 4)}}',
|
||||
realizedSpread: '{{number.float(0.005, 0.03, 4)}}',
|
||||
priceImpact: '{{number.float(0.001, 0.02, 4)}}',
|
||||
toxicity: '{{number.float(0, 1, 4)}}',
|
||||
orderImbalance: '{{number.float(-1, 1, 4)}}',
|
||||
volatility: '{{number.float(0.01, 0.05, 4)}}',
|
||||
},
|
||||
constraints: [
|
||||
'metrics.effectiveSpread >= metrics.realizedSpread',
|
||||
'metrics.toxicity >= 0 && metrics.toxicity <= 1',
|
||||
'metrics.orderImbalance >= -1 && metrics.orderImbalance <= 1',
|
||||
],
|
||||
});
|
||||
|
||||
console.log('Microstructure Metrics (sample):');
|
||||
console.log(metrics.slice(0, 5));
|
||||
|
||||
return metrics;
|
||||
}
|
||||
|
||||
// ============================================================================
|
||||
// Main Execution
|
||||
// ============================================================================
|
||||
|
||||
async function main() {
|
||||
console.log('='.repeat(80));
|
||||
console.log('Stock Market Data Generation Examples');
|
||||
console.log('='.repeat(80));
|
||||
console.log();
|
||||
|
||||
try {
|
||||
console.log('1. Generating OHLCV Data...');
|
||||
await generateOHLCVData();
|
||||
console.log();
|
||||
|
||||
console.log('2. Generating Technical Indicators...');
|
||||
await generateTechnicalIndicators();
|
||||
console.log();
|
||||
|
||||
console.log('3. Generating Multi-Timeframe Data...');
|
||||
await generateMultiTimeframeData();
|
||||
console.log();
|
||||
|
||||
console.log('4. Generating Market Depth...');
|
||||
await generateMarketDepth();
|
||||
console.log();
|
||||
|
||||
console.log('5. Generating Tick Data...');
|
||||
await generateTickData();
|
||||
console.log();
|
||||
|
||||
console.log('6. Generating Microstructure Metrics...');
|
||||
await generateMicrostructureMetrics();
|
||||
console.log();
|
||||
|
||||
console.log('All examples completed successfully!');
|
||||
} catch (error) {
|
||||
console.error('Error generating market data:', error);
|
||||
process.exit(1);
|
||||
}
|
||||
}
|
||||
|
||||
// Run if executed directly
|
||||
if (require.main === module) {
|
||||
main();
|
||||
}
|
||||
|
||||
export {
|
||||
generateOHLCVData,
|
||||
generateTechnicalIndicators,
|
||||
generateMultiTimeframeData,
|
||||
generateMarketDepth,
|
||||
generateTickData,
|
||||
generateMicrostructureMetrics,
|
||||
};
|
||||
Reference in New Issue
Block a user