Parabolic SAR strategy

This strategy is a short-term scalping approach that aims to capture small price moves using the Parabolic SAR and Commodity Channel Index (CCI) for entry and exit signals.

Parabolic SAR (Stop and Reverse) is a trend-following indicator plotted as dots above or below price. Dots below price indicate a bullish trend, while dots above price indicate a bearish trend. The CCI identifies overbought and oversold conditions by comparing an asset’s average price to its moving average and standard deviation; high values signal overbought conditions, and low values signal oversold conditions.

In this strategy, Parabolic SAR and CCI are calculated manually rather than using built-in methods.

Overall, the strategy combines these indicators and includes a filter to avoid trading in directionless markets.

tip

This example strategy is machine generated using Gunbot AI. Review its behavior carefully in a simulated bot instance before using parts of this code in production.

// initialize customStratStore within pairLedger object
gb.data.pairLedger.customStratStore = gb.data.pairLedger.customStratStore || {};

// forced wait time reduces risk of double orders
function checkTime() {
  return !gb.data.pairLedger.customStratStore.timeCheck || typeof gb.data.pairLedger.customStratStore.timeCheck !== "number" 
    ? (gb.data.pairLedger.customStratStore.timeCheck = Date.now(), false) 
    : (Date.now() - gb.data.pairLedger.customStratStore.timeCheck > 8000);
}
const enoughTimePassed = checkTime();

// set timestamp for checkTime in next round
const setTimestamp = () => gb.data.pairLedger.customStratStore.timeCheck = Date.now();

// calculate Parabolic SAR
function parabolicSAR(high, low, accelerationFactor, maxAccelerationFactor, prevSAR, prevEP, prevAF) {
  let SAR = prevSAR;
  let EP = prevEP;
  let AF = prevAF;
  if (prevSAR === null || prevEP === null || prevAF === null) {
    SAR = low[0];
    EP = high[0];
    AF = accelerationFactor;
  } else {
    if (prevSAR < low[0]) {
      SAR = prevSAR + prevAF * (prevEP - prevSAR);
      SAR = Math.min(SAR, high[0]);
    } else if (prevSAR > high[0]) {
      SAR = prevSAR + prevAF * (prevEP - prevSAR);
      SAR = Math.max(SAR, low[0]);
    } else {
      if (prevEP > high[0]) {
        EP = high[0];
        AF = Math.min(AF + accelerationFactor, maxAccelerationFactor);
      } else if (prevEP < low[0]) {
        EP = low[0];
        AF = Math.min(AF + accelerationFactor, maxAccelerationFactor);
      }
      SAR = prevSAR + prevAF * (prevEP - prevSAR);
      SAR = Math.min(SAR, high[0]);
      SAR = Math.max(SAR, low[0]);
    }
  }
  return [SAR, EP, AF];
}

// calculate Commodity Channel Index (CCI)
function cci(high, low, close, period) {
  const typicalPrices = [];
  for (let i = 0; i < period; i++) {
    typicalPrices.push((high[i] + low[i] + close[i]) / 3);
  }
  const typicalPriceSMA = typicalPrices.reduce((a, b) => a + b, 0) / period;
  const meanDeviation = typicalPrices.reduce((a, b) => a + Math.abs(b - typicalPriceSMA), 0) / period;
  const cci = (typicalPrices[0] - typicalPriceSMA) / (0.015 * meanDeviation);
  return cci;
}

// calculate indicators
const sar = parabolicSAR(gb.data.candlesHigh, gb.data.candlesLow, 0.02, 0.2, null, null, null)[0];
const cciValue = cci(gb.data.candlesHigh, gb.data.candlesLow, gb.data.candlesClose, 20);

// log indicators
console.log(`Parabolic SAR: ${sar}`);
console.log(`CCI: ${cciValue}`);

if (enoughTimePassed) {
  const buyConditions = sar > gb.data.candlesClose[1] && cciValue < -100 && !gb.data.gotBag;
  const sellConditions = sar < gb.data.candlesClose[1] && cciValue > 100 && gb.data.gotBag;

  // fire orders when conditions are met
  if (buyConditions) {
    const buyAmount = parseFloat(gb.data.pairLedger.whatstrat.TRADING_LIMIT) / gb.data.bid;
    gb.method.buyMarket(buyAmount, gb.data.pairName);
    setTimestamp();
  } else if (sellConditions) {
    gb.method.sellMarket(gb.data.quoteBalance, gb.data.pairName);
    setTimestamp();
  }
}
      
// Code is machine generated, review it and run in simulator mode first

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