Stock Runner

Because of lack of good backtesting tools in JavaScript, I've decided to build my own. It uses QuestDB to efficiently store and query the data. It's also quite fast and nice to use. You can run a 5 year backtest on ALL stocks in 1 minute (on daily ticks).

Installation

1. Clone the repository.
2. Install dependencies: npm install
3. QuestDB
   • Download from questdb.com/download
   • Run: ./questdb (or ./questdb.exe on Windows)
   • Default: admin:quest@localhost:8812/qdb. For custom setup, set:
     • QUESTDB_USERNAME, QUESTDB_PASSWORD
     • QUESTDB_HOST, QUESTDB_PORT, QUESTDB_DATABASE

---

Getting the data

Stooq (free, only last 6 months for 5m, 2 years for 1h, 20 years for 1d)

1. Go to stooq.com/db/h
2. Download daily/hourly/5m data and place nasdaq stocks, etc., in data/stooq/1d, data/stooq/1h, data/stooq/5m
3. Ingest into QuestDB:

   node scripts/stooq_ingest.js <1d|1h|5m>
   

4. Re-run to update data.

Massive (paid)

1. Get API key from massive.com
2. Set MASSIVE_KEY in .env
3. Run:

   node scripts/massive_download.js <period> <startDate> <skip downloaded tickers>
   

   • Example: node scripts/massive_download.js 1d 2003-09-10 true
   • period can be 1d, 1h, 5m, 1m
   • startDate is the date to start downloading from
   • skip downloaded tickers is a boolean flag to skip already downloaded tickers
4. Ingest into QuestDB:

   node scripts/massive_ingest.js <period>
   

   • Example: node scripts/massive_ingest.js 1d
   • period can be 1d, 1h, 5m, 1m

---

Running a backtest

1. Add a strategy file under strategies/ (see examples below).
2. Run it, e.g.:

   node strategies/sma.js
   

---

API reference

Strategy

import Strategy from '../src/backtest/strategy.js';

const strategy = new Strategy({
    intervals: {
        '1d': { count: 50, main: true },
        '1h': { count: 24, main: false, preload: true },
    },
    onTick: async (context) => { /* ... */ },
});

• intervals - Timeframes your strategy uses. Keys: '1d', '1h', '5m', '1m'.
  • count - Number of bars to keep in lookback (≥ 1).
  • main: true - Exactly one interval must be main; it drives the simulation (one tick per bar).
  • preload - If true, bars are preloaded for speed; non-main intervals can set this to avoid on-demand DB reads.
• onTick - Called every bar (single-stock) or every bar across all stocks (all-stocks). Receives a context object (see below).

Backtest

import Backtest from '../src/backtest/index.js';

const bt = new Backtest({
    strategy,
    startDate: new Date('2020-01-01'),
    endDate: new Date('2025-01-01'),
    startCashBalance: 10_000,
    broker: new IBKR('tiered'),
    logs: { swaps: false, trades: true },
    features: [ // optional
        { name: 'volume', bucketSize: 1_000_000 },
    ],
});

const result = await bt.runOnStock('AAPL');   // single symbol
// or
const result = await bt.runOnAllStocks();     // all symbols in DB

bt.logMetrics(result);

• runOnStock(stockName) - Runs backtest on one ticker; returns metrics object.
• runOnAllStocks() - Runs on all tickers with data in the range; returns metrics object.
• logMetrics(metrics) - Prints summary (CAGR, Sharpe, max drawdown, win rate, etc.) and any open positions.
• buildReport(metrics) - Builds a HTML report with charts and tables.

Metrics returned by getMetrics() / runOnStock / runOnAllStocks:

| Field | Description | |----------------|--------------------------------| | period | [startDate, endDate] | | trades | Number of completed round-trip trades | | totalFees | Sum of broker fees | | totalReturn | (final equity / start cash) − 1 | | avgDaily | Average period return | | CAGR | Compound annual growth rate | | sharpe | Annualized Sharpe ratio | | maxDrawdown | Worst peak-to-trough decline | | geoPeriodRet | Geometric mean period return | | geoAnnualRet | Geometric mean annualized return |

onTick context

Single-stock (runOnStock):

• stockName, candle (current bar), stockBalance, ctx (backtest instance)
• getCandles(intervalName, count, ts?) - returns Promise<Array> of bars (newest to oldest), includes the current bar; ts defaults to current bar.
• buy(quantity, price), sell(quantity, price) - execute at given price (fees applied by broker).
• setFeatures(features) - set features for the trade. Used for calculating profit correlations. You must set features in Backtest options. for example: .setFeatures([0.1, 0.2, 0.3])

All-stocks (runOnAllStocks):

• currentDate, ctx, stocks (array of per-stock objects), raw (all loaded symbols)
• Each element of stocks has: stockName, candle, stockBalance, getCandles, buy, sell, setFeatures (see above).
• Use ctx.cashBalance, ctx.stockBalances for portfolio state. Delisted symbols are detected and positions cleared after missing bars.

Brokers

• Broker (base) - No fees; override calculateFees(quantity, price, side) for custom logic.
• IBKR - Interactive Brokers:
  • new IBKR('tiered') or new IBKR('fixed')
  • Tiered: $0.0035/share, min $0.35, max 1% notional + clearing/regulatory.
  • Fixed: $0.005/share, min $1, max 1% notional.
  • Optional second argument: slippage (decimal, e.g. 0.001 = 0.1%).
• Alpaca - Commission-free U.S. equity; regulatory fees only:
  • new Alpaca(slippage?)
  • Commission: $0. Sells: FINRA TAF $0.000195/share (max $9.79, qty cap 50,205). All: CAT $0.0000265/share. Rounded up to nearest penny.
  • slippage - fraction (e.g. 0.001 = 0.1%), default 0.

---

Strategies

Single stock - SMA crossover

import Strategy from '../src/backtest/strategy.js';
import Backtest from '../src/backtest/index.js';
import IBKR from '../src/brokers/ibkr.js';

const SHORT_LEN = 25;
const LONG_LEN = SHORT_LEN * 2;

const sma = candles => candles.reduce((sum, c) => sum + c.close, 0) / candles.length;

const smaCrossover = new Strategy({
    intervals: {
        '1d': { count: LONG_LEN, main: true },
    },
    onTick: async ({ candle, getCandles, buy, sell, stockBalance }) => {
        const lastLong = await getCandles('1d', LONG_LEN);
        const lastShort = await getCandles('1d', SHORT_LEN);

        const longMA = sma(lastLong);
        const shortMA = sma(lastShort);
        const price = candle.close;

        if (stockBalance === 0 && shortMA > longMA) {
            buy(3, price);
        }
        else if (stockBalance > 0 && shortMA < longMA) {
            sell(stockBalance, price);
        }
    }
});

const bt = new Backtest({
    strategy: smaCrossover,
    startDate: new Date('2020-07-14'),
    endDate: new Date('2025-07-30'),
    startCashBalance: 10_000,
    broker: new IBKR('tiered'),
    logs: { swaps: false, trades: true }
});

const result = await bt.runOnStock('AAPL');
bt.logMetrics(result);

Result:

All stocks - SMA crossover

import Strategy from '../src/backtest/strategy.js';
import Backtest from '../src/backtest/index.js';
import IBKR from '../src/brokers/ibkr.js';

const SHORT_LEN = 14;
const LONG_LEN = SHORT_LEN * 2;

const sma = candles => candles.reduce((sum, c) => sum + c.close, 0) / candles.length;

const smaCrossover = new Strategy({
    intervals: {
        '1d': { count: LONG_LEN, main: true },
    },
    onTick: async ({ stocks, currentDate, ctx }) => {
        for (const s of stocks) {
            const { stockName, candle, getCandles, buy, sell, stockBalance } = s;

            try {
                const lastLong = await getCandles('1d', LONG_LEN);
                const lastShort = await getCandles('1d', SHORT_LEN);

                if (!lastLong || !lastShort) {
                    continue;
                }

                const longMA = sma(lastLong);
                const shortMA = sma(lastShort);
                const price = candle.close;

                if (stockBalance === 0 && shortMA > longMA) {
                    const perNameBudget = ctx.cashBalance / 10;
                    if (Object.values(ctx.stockBalances).length < 10) {
                        const qty = Math.floor(perNameBudget / price);
                        if (qty > 0) buy(qty, price);
                    }
                }
                else if (stockBalance > 0 && shortMA < longMA) {
                    sell(stockBalance, price);
                }
            } catch (_) {
                continue;
            }
        }
    }
});

const bt = new Backtest({
    strategy: smaCrossover,
    startDate: new Date('2024-07-14'),
    endDate: new Date('2025-07-30'),
    startCashBalance: 100_000,
    broker: new IBKR('tiered'),
    logs: { swaps: false, trades: true }
});

const result = await bt.runOnAllStocks();
bt.logMetrics(result);

Result: