QuantScript Examples — Trading Strategy & Indicator Code Samples

Beginner indicator console.log

Hello World

The simplest QuantScript script — declare an indicator and print to the console.

QuantScript

indicator("Hello World");

console.log("Hello, World!");

Beginner variables math

Variables and Math

Declare variables with let and const, perform arithmetic, and output results.

QuantScript

indicator("Math Example");

let x = 10;
const PI = 3.14159;

let sum = x + 5;
let product = x * 2;
let power = 2 ** 8;

console.log("Sum: " + tostring(sum));
console.log("Product: " + tostring(product));
console.log("Power: " + tostring(power));

Beginner data df.forEach OHLCV

OHLCV Data Display

Access Open, High, Low, Close, Volume data for each bar using df.forEach().

QuantScript

indicator("OHLCV Display");

df.forEach((frame) => {
    let openPrice = frame.open;
    let highPrice = frame.high;
    let lowPrice = frame.low;
    let closePrice = frame.close;
    let volume = frame.volume;

    if (bar_index < 5) {
        console.log("Bar " + tostring(bar_index));
        console.log("  Open: " + tostring(openPrice));
        console.log("  Close: " + tostring(closePrice));
        console.log("  Volume: " + tostring(volume));
    }
});

Beginner ta.sma chart.plot

Simple Moving Average Indicator

Calculate and plot a Simple Moving Average using ta.sma().

QuantScript

indicator("SMA Indicator");

const SMA_LENGTH = 20;

df.forEach((frame) => {
    let sma = ta.sma(frame.close, SMA_LENGTH);
    chart.plot(sma, "SMA 20", "#FF0000");
});

Intermediate ta.sma ta.ema ta.crossover

Multiple Indicators with Crossover Detection

Plot multiple moving averages and detect bullish/bearish crossover signals.

QuantScript

indicator("Multiple Indicators");

df.forEach((frame) => {
    let fastSMA = ta.sma(frame.close, 10);
    let slowSMA = ta.sma(frame.close, 20);
    let ema = ta.ema(frame.close, 20);

    chart.plot(fastSMA, "Fast SMA", "#00FF00");
    chart.plot(slowSMA, "Slow SMA", "#FF0000");
    chart.plot(ema, "EMA", "#0000FF");

    let isCrossUp = ta.crossover(fastSMA, slowSMA);
    let isCrossDown = ta.crossunder(fastSMA, slowSMA);

    if (isCrossUp) {
        console.log("BULLISH CROSSOVER at bar " + tostring(bar_index));
    }
    if (isCrossDown) {
        console.log("BEARISH CROSSOVER at bar " + tostring(bar_index));
    }
});

Intermediate strategy ta.sma backtest

SMA Crossover Strategy

A complete backtestable strategy that enters long on SMA crossover and exits on crossunder.

QuantScript

strategy("SMA Crossover",
    initial_capital: 100000,
    default_qty_type: "fixed",
    default_qty_value: 100
);

df.forEach((frame) => {
    let fastSMA = ta.sma(frame.close, 10);
    let slowSMA = ta.sma(frame.close, 20);

    chart.plot(fastSMA, "Fast SMA", "#00FF00");
    chart.plot(slowSMA, "Slow SMA", "#FF0000");

    let crossUp = ta.crossover(fastSMA, slowSMA);
    let crossDown = ta.crossunder(fastSMA, slowSMA);

    if (crossUp) {
        strategy.entry("Long", "long");
    }
    if (crossDown) {
        strategy.close("Long");
    }
});

Intermediate strategy ta.rsi chart.hline

RSI Overbought/Oversold Strategy

Buy when RSI is oversold (<30), sell when overbought (>70).

QuantScript

strategy("RSI Strategy",
    initial_capital: 50000,
    default_qty_type: "percent_of_equity",
    default_qty_value: 10
);

const RSI_LENGTH = 14;

df.forEach((frame) => {
    let rsi = ta.rsi(frame.close, RSI_LENGTH);

    chart.plot(rsi, "RSI", "#FF00FF");
    chart.hline(30, "Oversold", "#00FF00");
    chart.hline(70, "Overbought", "#FF0000");

    if (rsi < 30 && strategy.position_size == 0) {
        strategy.entry("RSI Long", "long");
    }
    if (rsi > 70 && strategy.position_size > 0) {
        strategy.close("RSI Long");
    }
});

Advanced strategy strategy.exit stop-loss

Strategy with Stop Loss & Take Profit

Enter on SMA breakout with automatic exit orders for risk management.

QuantScript

strategy("Strategy with Exits",
    initial_capital: 100000,
    default_qty_type: "fixed",
    default_qty_value: 50
);

const STOP_LOSS_PCTS = 2.0;
const TAKE_PROFIT_PCTS = 4.0;

df.forEach((frame) => {
    let sma = ta.sma(frame.close, 20);
    let crossUp = ta.crossover(frame.close, sma);

    if (crossUp && strategy.position_size == 0) {
        strategy.entry("Breakout Long", "long");

        let entryPrice = frame.close;
        let stopPrice = entryPrice * (1 - STOP_LOSS_PCTS / 100);
        let targetPrice = entryPrice * (1 + TAKE_PROFIT_PCTS / 100);

        strategy.exit("Exit Long", "Breakout Long",
            stop: stopPrice,
            limit: targetPrice
        );
    }
});

Intermediate ta.macd destructuring

MACD Indicator

Use array destructuring to unpack the three MACD components and plot them.

QuantScript

indicator("MACD");

df.forEach((frame) => {
    let [macdLine, signalLine, histogram] = ta.macd(frame.close, 12, 26, 9);

    chart.plot(macdLine, "MACD", "#0000FF");
    chart.plot(signalLine, "Signal", "#FF0000");
    chart.plot(histogram, "Histogram", "#00FF00");
});

Intermediate ta.bbands destructuring

Bollinger Bands

Plot Bollinger Bands using array destructuring on the ta.bbands() return value.

QuantScript

indicator("Bollinger Bands");

df.forEach((frame) => {
    let [lower, middle, upper] = ta.bbands(frame.close, 20, 2);

    chart.plot(lower, "Lower Band", "#808080");
    chart.plot(middle, "Middle Band", "#0000FF");
    chart.plot(upper, "Upper Band", "#808080");
});