bitprophet/indicators.js

Crypto trading platform for Binance that uses chat bots as its interface

module.exports = {
	isObject: function(object) {
		return object !== undefined && object !== null && object.constructor == Object
	},
	ema: function(ticks, length, momentum = 100, arraySize = 1) {
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_averages

		var fromJsonObject = this.isObject(ticks[0])
		if(ticks.length < length + momentum + arraySize) return []

		var sma = 0
		var currentValue = 0

		for(var i = ticks.length - length - momentum - arraySize; i < ticks.length - momentum - arraySize; ++i) {
			let value
			if(fromJsonObject) value = parseFloat(ticks[i].close)
			else value = parseFloat(ticks[i])

			if(i == ticks.length - momentum - arraySize - 1) {
				currentValue = value
			}
			else {
				sma += value
			}
		}

		sma /= length

		var weightLastPrice = (2 / (length + 1))
		var ema = (currentValue - sma) * weightLastPrice + sma

		var emaArray = []

		for(let i = 0; i < momentum + arraySize; ++i) {
			var tickIndex = ticks.length - momentum - arraySize + i
			let value
			if(fromJsonObject) value = parseFloat(ticks[tickIndex].close)
			else value = parseFloat(ticks[tickIndex])

			ema = (value - ema) * weightLastPrice + ema

			if(i > momentum - 1) emaArray.push(ema)
		}

		return emaArray
	},
	sma: function(ticks, length, arraySize = 1) {
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_averages

		var fromJsonObject = this.isObject(ticks[0])
		if(ticks.length < length + arraySize - 1) return []

		var averages = []

		for(var i = 0; i < arraySize; ++i) {
			var index = ticks.length - arraySize + i
			var price
			if(fromJsonObject) price = parseFloat(ticks[index].close)
			else price = parseFloat(ticks[index])

			for(var j = 1; j < length; ++j) {
				if(fromJsonObject) price += parseFloat(ticks[index - length + j].close)
				else price += parseFloat(ticks[index - length + j])
			}

			price = price / length
			averages.push(price)
		}

		return averages
	},
	rsi: function(ticks, length, momentum, arraySize = 1) {
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:relative_strength_index_rsi

		var fromJsonObject = this.isObject(ticks[0])
		if(ticks.length < (length + 1) + momentum + arraySize) return []

		var gains = [], losses = []
		var avgGain = 0, avgLoss = 0
		var currentGain = 0, currentLoss = 0

		for(var i = ticks.length - (length + 1) - momentum - arraySize; i < ticks.length - momentum - arraySize; ++i) {
			var value, change

			if(fromJsonObject) {
				value = ticks[i].close
				change = value - ticks[i - 1].close
			}
			else {
				value = ticks[i]
				change = value - ticks[i - 1]
			}

			if(i == ticks.length - momentum - 1) {
				if(change > 0) currentGain = change
				else if(change < 0) currentLoss = change * -1
			}
			else {
				if(change > 0) gains.push(change)
				else if(change < 0) losses.push(change * -1)
			}
		}

		for(let i = 0; i < gains.length; ++i) {
			avgGain += gains[i]
		}

		for(let i = 0; i < losses.length; ++i) {
			avgLoss += losses[i]
		}

		//To build the momentum, we need the first rsis to be calculated using smas
		var smaGains = avgGain / length
		var smaLosses = avgLoss / length

		var weightLastPrice = (2 / (length * 2 + 1))
		var emaGains = (currentGain - smaGains) * weightLastPrice + smaGains
		var emaLosses = (currentLoss - smaLosses) * weightLastPrice + smaLosses

		var rsiArray = []

		for(let i = 0; i < momentum + arraySize; ++i) {
			var tickIndex = ticks.length - momentum - arraySize + i
			let value, change

			if(fromJsonObject) {
				value = ticks[tickIndex].close
				change = value - ticks[tickIndex - 1].close
			}
			else {
				value = ticks[tickIndex]
				change = value - ticks[tickIndex - 1]
			}

			if(change > 0) {
				currentGain = change
				currentLoss = 0
			}
			else if(change < 0) {
				currentGain = 0
				currentLoss = change * -1
			}
			else {
				currentGain = 0
				currentLoss = 0
			}

			emaGains = (currentGain - emaGains) * weightLastPrice + emaGains
			emaLosses = (currentLoss - emaLosses) * weightLastPrice + emaLosses

			if(i > momentum - 1) rsiArray.push(100 - 100 / (1 + emaGains / emaLosses))
		}

		return rsiArray
	},
	stochastic: function(ticks, length, arraySize = 1, smooth = 3) {
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:stochastic_oscillator_fast_slow_and_full

		var fromJsonObject = this.isObject(ticks[0])
		if(ticks.length < length + arraySize + (smooth - 1)) return []

		var stochasticsSharp = []

		for(let i = 0; i < arraySize + (smooth - 1); ++i) {
			var currentIndex = ticks.length - (arraySize + (smooth - 1)) + i
			var currentClose, lowestLow, highestHigh

			if(fromJsonObject) {
				currentClose = ticks[currentIndex].close
				lowestLow = ticks[currentIndex].low
				highestHigh = ticks[currentIndex].high
			}
			else {
				currentClose = ticks[currentIndex]
				lowestLow = ticks[currentIndex]
				highestHigh = ticks[currentIndex]
			}

			for(let j = 0; j < length; ++j) {
				var lowest, highest
				if(fromJsonObject) {
					lowest = ticks[currentIndex - j - 1].low
					highest = ticks[currentIndex - j - 1].high
				}
				else {
					lowest = ticks[currentIndex - j - 1]
					highest = ticks[currentIndex - j - 1]
				}
				if(lowest < lowestLow) lowestLow = lowest
				if(highest > highestHigh) highestHigh = highest
			}

			stochasticsSharp.push((currentClose - lowestLow) / (highestHigh - lowestLow))
		}

		var stochastics = []

		for(var i = smooth - 1; i < stochasticsSharp.length; ++i) {
			var stoch = stochasticsSharp[i]
			for(var j = 1; j < smooth; ++j) {
				stoch += stochasticsSharp[i - j]
			}

			stoch /= smooth

			stochastics.push(parseFloat(stoch * 100).toFixed(2))
		}

		return stochastics
	},
	bollingerBands: function(ticks, length, deviation = 2, arraySize = 1) {
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:bollinger_bands

		var fromJsonObject = this.isObject(ticks[0])
		var bands = []
		var movingAverages = this.sma(ticks, length, arraySize)

		for(var i = 0; i < movingAverages.length; ++i) {
			var movingAverage = movingAverages[i]

			var sum = 0
			for(var j = ticks.length - length; j < ticks.length; ++j) {
				var close
				if(fromJsonObject) close = parseFloat(ticks[j - movingAverages.length + i + 1].close)
				else close = parseFloat(ticks[j - movingAverages.length + i + 1])

				sum += Math.pow((close - movingAverage), 2)
			}

			deviation = Math.sqrt(sum / (length - 1)) * 2
			bands.push([movingAverage - deviation, movingAverage, movingAverage + deviation])
		}

		return bands
	},
	ichimoku: function(ticks, conversionPeriods = 10, basePeriods = 30, laggingSpan2Periods = 60, displacement = 30, arraySize = 1) {
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:ichimoku_cloud

		function donchian(startIndex, length) {
			var lowest = 0, highest = 0
			for(var i = 0; i < length; ++i) {
				var index = startIndex - length + i + 1
				if(i == 0) {
					lowest = parseFloat(ticks[index].low)
					highest = parseFloat(ticks[index].high)
				}
				else {
					var low = parseFloat(ticks[index].low)
					if(low < lowest) lowest = low
					var high = parseFloat(ticks[index].high)
					if(high > highest) highest = high
				}
			}

			return (lowest + highest) / 2.
		}

		var ichimokuArray = []
		for(var i = 0; i < arraySize; ++i) {
			var index = ticks.length - arraySize - 1 - displacement + i
			var conversionLine = donchian(index, conversionPeriods)
			var baseLine = donchian(index, basePeriods)
			var leadLine1 = (conversionLine + baseLine) / 2.
			var leadLine2 = donchian(index, laggingSpan2Periods)
			ichimokuArray.push([conversionLine, baseLine, leadLine1, leadLine2])
		}

		return ichimokuArray
	},
	heikinAshi: function(ticks, arraySize = -1) {
		//Heikin Ashi candlesticks are best for swing trading (not daytrading) and are used to identify market trends
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:chart_analysis:heikin_ashi
		//arraySize = -1, calculate Heikin Ashi for all ticks
		//arraySize = n, where n >= 1, calculate Heikin Ashi for the last n ticks

		var ha = []
		var startingTick = arraySize == -1 ? 0 : ticks.length - arraySize
		for(var i = startingTick; i < ticks.length; i++) {
			var o = parseFloat(ticks[i].open)
			var h = parseFloat(ticks[i].high)
			var l = parseFloat(ticks[i].low)
			var c = parseFloat(ticks[i].close)

			var hac = (o + h + l + c) / 4
			var hao = (o + c) / 2
			var hah = i == startingTick ? h : Math.max(h, hao, hac)
			var hal = i == startingTick ? l : Math.min(l, hao, hac)
			ha.push({open: hao, high: hah, low: hal, close: hac})
		}
		return ha
	},
	macd: function(ticks, shortEma = 12, longEma = 26, signal = 9, arraySize = 1) {
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:moving_average_convergence_divergence_macd

		/*
        MACD Line: Fast EMA - Slow EMA
        Signal Line: EMA of MACD Line
        MACD Histogram: MACD Line - Signal Line
        */

		var momentum = 100
		var emaArraySize = arraySize + momentum + signal
		var emaShort = this.ema(ticks, shortEma, momentum, emaArraySize)
		var emaLong = this.ema(ticks, longEma, momentum, emaArraySize)

		var macdLine = []
		for(var i = 0; i < emaArraySize; ++i) {
			macdLine.push(emaShort[emaShort.length - emaArraySize + i] - emaLong[emaLong.length - emaArraySize + i])
		}

		var signalLine = this.ema(macdLine, signal, momentum, arraySize)

		var histogramArray = []
		for(i = 0; i < arraySize; ++i) {
			var histogram = macdLine[macdLine.length - arraySize + i] - signalLine[i]
			histogramArray.push(histogram)
		}

		var macd = []
		for(i = 0; i < arraySize; ++i) {
			macd.push({line: macdLine[macdLine.length - arraySize + i], signal: signalLine[i], histogram: histogramArray[i]})
		}

		return macd
	},
	zigzag: function(ticks, deviation = 5, arraySize = -1) {
		//Determines percent deviation in price changes, presenting frequency and volatility in deviation. Also helps determine trend reversals.
		//Read more: http://stockcharts.com/school/doku.php?id=chart_school:technical_indicators:zigzag
		//arraySize = -1, calculate ZigZag for all ticks
		//arraySize = n, where n >= 1, calculate the ZigZag for the last n ticks

		var turningPoints = []
		var basePrice = -1
		var lastDeviation = 0
		deviation /= 100.

		var startingTick = arraySize == -1 ? 0 : ticks.length - arraySize
		//Calculate all turning points that have a deviation equal or superior to the argument received
		for(var i = startingTick; i < ticks.length; ++i) {
			var close = parseFloat(ticks[i].close)
			var high = parseFloat(ticks[i].high)
			var low = parseFloat(ticks[i].low)
			var positiveDeviation = high / basePrice - 1
			var negativeDeviation = low / basePrice - 1

			if(basePrice == -1) {
				basePrice = close
				lastDeviation = 0
				turningPoints.push({timePeriod: i, value: close, deviation: lastDeviation})
				continue
			}

			//Is it a positive turning point or is it higher than the last positive one?
			if(positiveDeviation >= deviation || (positiveDeviation > 0 && lastDeviation > 0)) {
				if(lastDeviation > 0) {
					positiveDeviation += lastDeviation
					turningPoints.pop()
				}

				turningPoints.push({timePeriod: i, value: high, deviation: positiveDeviation})
				lastDeviation = positiveDeviation
				basePrice = high
			}
			//Is it a positive turning point or is it lower than the last negative one?
			else if(negativeDeviation <= -deviation || (negativeDeviation < 0 && lastDeviation < 0)) {
				if(lastDeviation < 0) {
					negativeDeviation += lastDeviation
					turningPoints.pop()
				}

				turningPoints.push({timePeriod: i, value: low, deviation: negativeDeviation})
				lastDeviation = negativeDeviation
				basePrice = low
			}
			//Add always the last one as a turning point, just to make our life easier for the next calculation
			else if(i == ticks.length - 1) {
				if(positiveDeviation > 0) turningPoints.push({timePeriod: i, value: high, deviation: positiveDeviation})
				else turningPoints.push({timePeriod: i, value: low, deviation: negativeDeviation})
			}
		}

		var zigzag = []
		//Add the turning points to the returning array, calculate the values between those turning points and add them as well
		for(i = 0; i < turningPoints.length; ++i) {
			var turningPoint = turningPoints[i]
			zigzag.push({timePeriod: turningPoint.timePeriod, value: turningPoint.value, deviation: parseFloat((turningPoint.deviation * 100).toFixed(2)),
				turningPoint: turningPoint.deviation > deviation || turningPoint.deviation < -deviation})

			if(turningPoint.timePeriod >= ticks.length -1) continue

			var nextTurningPoint = turningPoints[i + 1]
			for(var j = turningPoint.timePeriod + 1; j < nextTurningPoint.timePeriod; ++j) {
				var distanceToTP = j - turningPoint.timePeriod
				var distanceTPs = nextTurningPoint.timePeriod - turningPoint.timePeriod
				var value = turningPoint.value + (nextTurningPoint.value - turningPoint.value) / distanceTPs * distanceToTP
				var currentDeviation = value / turningPoint.value

				zigzag.push({timePeriod: j, value: value, deviation: parseFloat((currentDeviation * 100).toFixed(2)),
					turningPoint: false})
			}
		}

		return zigzag
	},
	waveTrend: function(ticks, channelLength, avgLength, arraySize = 1) {
		//Read more: https://www.tradingview.com/script/2KE8wTuF-Indicator-WaveTrend-Oscillator-WT/

		var momentum = 100
		var hlc3 = []
		for(var i = 0; i < ticks.length; ++i) {
			hlc3.push((parseFloat(ticks[i].high) + parseFloat(ticks[i].low) + parseFloat(ticks[i].close)) / 3.)
		}

		var esa = this.ema(hlc3, channelLength, momentum, hlc3.length - momentum - channelLength)

		var esaDiff = []

		for(let i = 0; i < esa.length; ++i) {
			esaDiff.push(Math.abs(hlc3[hlc3.length - esa.length + i] - esa[i]))
		}

		var d = this.ema(esaDiff, channelLength, momentum, esaDiff.length - momentum - channelLength)

		var ci = []

		for(let i = 0; i < d.length; ++i) {
			ci.push((hlc3[hlc3.length - d.length + i] - esa[esa.length - d.length + i]) / (0.015 * d[i]))
		}

		var waveTrendArray = this.ema(ci, avgLength, momentum, arraySize)

		return waveTrendArray
	},
	nextSupportBase: function(ticks, length, startBackRead = 1, confirmationsNeeded = 2, percentageBounce = 1.01) {
		//Indicator based on Quickfingers Luc's technique: https://www.youtube.com/watch?v=vgcFe_XO_LQ

		var referenceLowValue = this.lowestValue(ticks, startBackRead, 0)
		var nextBase = referenceLowValue

		var confirmations = -1
		var indexNextBase = -1
		for(var i = startBackRead; i < length; ++i) {
			var index = ticks.length - 1 - i
			var tickLow = ticks[index].low

			if(tickLow <= nextBase) {
				nextBase = tickLow
				indexNextBase = index
				confirmations = 0
				continue
			}
			else if(confirmations >= 0 && tickLow > nextBase) {
				confirmations++

				if(confirmations >= confirmationsNeeded) {

					var highestPoint = -1
					for(var j = indexNextBase + 1; j < length; ++j) {
						var tickHigh = ticks[j].high
						if(tickHigh > highestPoint) highestPoint = tickHigh
					}
					if(highestPoint / nextBase > percentageBounce) break
					else {
						confirmations = 0
						continue
					}
				}
			}
		}

		if(confirmations != confirmationsNeeded) return null
		return nextBase
	},
	measureMaxDiff: function(ticks, length, measureWicks = false) {
		//Percentual difference between the high and low from the last length of ticks

		var highValue = ticks[ticks.length - 1].close
		var lowValue = highValue

		for(var i = 0; i < length; ++i) {
			var high, low
			if(measureWicks) {
				high = ticks[ticks.length - 1 - i].high
				low = ticks[ticks.length - 1 - i].low
			}
			else {
				var open = ticks[ticks.length - 1 - i].open
				var close = ticks[ticks.length - 1 - i].close
				if(open > close) {
					high = open
					low = close
				}
				else {
					high = close
					low = open
				}
			}
			if(high > highValue) highValue = high
			else if(low < lowValue) lowValue = low
		}

		return (highValue - lowValue) / lowValue * 100
	},
	highestValue: function(ticks, length, startBackRead = 1) {
		//Returns the highest value from the last length of ticks

		var highValue = ticks[ticks.length - 1 - startBackRead].high
		for(var i = startBackRead; i < length; ++i) {
			var high = ticks[ticks.length - 1 - i].high
			if(high > highValue) highValue = high
		}

		return highValue
	},
	lowestValue: function(ticks, length, startBackRead = 1) {
		//Returns the lowest value from the last length of ticks

		var lowValue = ticks[ticks.length - 1 - startBackRead].low
		for(var i = startBackRead; i < length; ++i) {
			var low = ticks[ticks.length - 1 - i].low
			if(low < lowValue) lowValue = low
		}

		return lowValue
	},
	average: function(values) {
		//Returns the average of the input array

		var avgValues = 0
		for(var i = 0; i < values.length; ++i) {
			avgValues += parseFloat(values[i])
		}
		return avgValues /= values.length
	},
	volume24h: function(ticks, intervalMin) {
		//Returns the volume for the last 24h.
		//intervalMin is the ticks' interval in minutes, so when using the interval 1h, intervalMin = 60

		var volume24h = 0
		for(var i = ticks.length - (24 * 60 / intervalMin); i < ticks.length; ++i) {
			var high = parseFloat(ticks[i].high)
			var low = parseFloat(ticks[i].low)
			var avgPrice = (high - low) / 2. + low
			volume24h += parseFloat(ticks[i].volume) * avgPrice
		}
		return volume24h
	}
}