https://github.com/dimdengd/stock-runner
JS stock algotrading backtester
https://github.com/dimdengd/stock-runner
Last synced: 10 months ago
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JS stock algotrading backtester
- Host: GitHub
- URL: https://github.com/dimdengd/stock-runner
- Owner: dimdenGD
- Created: 2025-07-31T19:31:26.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-05T21:26:14.000Z (10 months ago)
- Last Synced: 2025-08-05T21:27:01.859Z (10 months ago)
- Language: JavaScript
- Homepage:
- Size: 73.2 KB
- Stars: 3
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 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 with `npm install`
3. QuestDB:
- Install from https://questdb.com/download/
- Run it with `./questdb.exe` or `./questdb`
- By default QuestDB uses `admin:quest@localhost:8812/qdb` as credentials. If you just plan on running it locally, you can leave it as is. Otherwise you can set the optional `QUESTDB_USERNAME`, `QUESTDB_PASSWORD`, `QUESTDB_HOST`, `QUESTDB_PORT`, and `QUESTDB_DATABASE` environment variables.
## Getting the data
### Stooq
Free, adjusted for splits
1. Go to https://stooq.com/db/h/
2. Download daily/hourly/5min data and put `nasdaq stocks` etc folders in `data/stooq/`
3. Run the script to import the data from CSV files to QuestDB:
```
node scripts/stooq_ingest.js <1d|1h|5m>
```
4. You can re-run these scripts to update the data.
### Polygon.io
Paid, not recommended because doesn't adjust for splits
1. Create an account at https://polygon.io/
2. Get flat files API key at https://polygon.io/dashboard/keys
3. Set the `POLYGON_ACCESS_KEY_ID` and `POLYGON_SECRET_ACCESS_KEY` environment variables.
4. Run the script to download the data from Polygon to CSV files:
```
node scripts/polygon_download.js <1d|1m>
```
5. Run the script to import the data from CSV files to QuestDB:
```
node scripts/polygon_ingest.js <1d|1m>
```
Importing 1m can take up to 5 hours.
6. You can re-run these scripts to update the data.
## Running a backtest
1. Create a strategy in `strategies/`
2. Run the backtest:
```
node strategies/sma.js
```
## Strategies
### Example strategy on single stock - SMA crossover
```js
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 = getCandles('1d', LONG_LEN);
const lastShort = 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:
### Example strategy on all stocks - SMA crossover
```js
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 MAX_POS_PER_STOCK = 50_000; // Maximum position size per stock
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 }) => {
// Process each filtered stock
for (const s of stocks) {
const { stockName, candle, getCandles, buy, sell, stockBalance } = s;
try {
const lastLong = getCandles('1d', LONG_LEN);
const lastShort = getCandles('1d', SHORT_LEN);
if (!lastLong || !lastShort || lastLong.length < LONG_LEN || lastShort.length < SHORT_LEN) {
continue; // Skip if we don't have enough data
}
const longMA = sma(lastLong);
const shortMA = sma(lastShort);
const price = candle.close;
// Buy signal: short MA crosses above long MA and we have no position
if (stockBalance === 0 && shortMA > longMA) {
const perNameBudget = Math.min(ctx.cashBalance / 10, MAX_POS_PER_STOCK); // Divide cash among up to 10 positions
if (Object.values(ctx.stockBalances).length < 10) {
const qty = Math.floor(perNameBudget / price);
if (qty > 0) {
buy(qty, price);
}
}
}
// Sell signal: short MA crosses below long MA and we have a position
else if (stockBalance > 0 && shortMA < longMA) {
sell(stockBalance, price);
}
} catch (error) {
// Skip this stock if there's an error (e.g., insufficient data)
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:
