Finding Exponential Moving Averages (EMA) with the power of JavaScript

Question

Finding Exponential Moving Averages (EMA) with the power of JavaScript

Can EMA be calculated using JavaScript?

I am attempting to apply the following formula for EMA:

EMA = array[i] * K + EMA(previous) * (1 – K)

Where K represents the smooth factor:

K = 2/(N + 1)

And N is the range of values that I want to consider

If I have an array of values like this, where the values increase over time:

var data = [15,18,12,14,16,11,6,18,15,16];

The objective is to create a function that can return the array of EMAs. Each value in the array, except the very first "range" value, will have a corresponding EMA. By having the related EMA value for each item in the data array, I can either use all of them or just the last one to predict the next value.

function calculateEMA(array, range) {
var k = 2/(range + 1);
...
}

I'm struggling to implement this function and would appreciate any assistance.

javascript arrays moving-average

Answer 1

Answer №1

It seems like you're looking for a function that calculates the Exponential Moving Average (EMA) for each index greater than 0 in an array. The first index will return the same value as the input array.

function calculateEMA(inputArray, range) {
  var k = 2 / (range + 1);
  // Initialize the EMA array with the first item from the input
  var emaArray = [inputArray[0]];
  
  // Calculate EMA for remaining items based on previous values
  for (var i = 1; i < inputArray.length; i++) {
    emaArray.push(inputArray[i] * k + emaArray[i - 1] * (1 - k));
  }
  
  return emaArray;
}

This code snippet should help you achieve your goal.

Answer 2

It seems like you're looking for a function that calculates the Exponential Moving Average (EMA) for each index greater than 0 in an array. The first index will return the same value as the input array.

function calculateEMA(inputArray, range) {
  var k = 2 / (range + 1);
  // Initialize the EMA array with the first item from the input
  var emaArray = [inputArray[0]];
  
  // Calculate EMA for remaining items based on previous values
  for (var i = 1; i < inputArray.length; i++) {
    emaArray.push(inputArray[i] * k + emaArray[i - 1] * (1 - k));
  }
  
  return emaArray;
}

This code snippet should help you achieve your goal.

Answer 3

Answer №2

Here is an alternative approach to implementing the EMA.

const calculateEMA = (arr, range) => arr.reduce((prevArr, currVal, index) => {
  return index ? prevArr.concat(2 * currVal / (range + 1) + prevArr[prevArr.length - 1] * (range - 1) / (range + 1)) : prevArr;
}, [arr[0]]);
      
const dataArr = [15, 18, 12, 14, 16, 11, 6, 18, 15, 16];
const emaRange = 3;

console.log(calculateEMA(dataArr, emaRange));

Answer 4

Here is an alternative approach to implementing the EMA.

const calculateEMA = (arr, range) => arr.reduce((prevArr, currVal, index) => {
  return index ? prevArr.concat(2 * currVal / (range + 1) + prevArr[prevArr.length - 1] * (range - 1) / (range + 1)) : prevArr;
}, [arr[0]]);
      
const dataArr = [15, 18, 12, 14, 16, 11, 6, 18, 15, 16];
const emaRange = 3;

console.log(calculateEMA(dataArr, emaRange));

Answer 5

Answer №3

Recursion is a fascinating concept, and I find it particularly intriguing when applied to EMA functions. Forget about managing arrays with this example.

function calculateMultiplier(N) { return 2 / (N + 1) }

function exponentialMovingAverage(tIndex, N, data) {
    if (!data[tIndex-1] || (tIndex) - (N) < 0) return undefined;
    const multiplier = calculateMultiplier(N);
    const currentPrice = data[tIndex];
    const previousEMA = exponentialMovingAverage(tIndex-1, N, data) || data[tIndex-1]
    return (currentPrice - previousEMA) * multiplier + yEMA
}

Answer 6

Recursion is a fascinating concept, and I find it particularly intriguing when applied to EMA functions. Forget about managing arrays with this example.

function calculateMultiplier(N) { return 2 / (N + 1) }

function exponentialMovingAverage(tIndex, N, data) {
    if (!data[tIndex-1] || (tIndex) - (N) < 0) return undefined;
    const multiplier = calculateMultiplier(N);
    const currentPrice = data[tIndex];
    const previousEMA = exponentialMovingAverage(tIndex-1, N, data) || data[tIndex-1]
    return (currentPrice - previousEMA) * multiplier + yEMA
}

Answer 7

Answer №4

I wanted to provide a fresh perspective on the calculation method used in technical analysis and indicators like Binance and TradingView.

In this approach, the Simple Moving Average (SMA) serves as the initial step in deriving the Exponential Moving Average (EMA).

When analyzing a series of candles, ticks, or prices within a period or interval of 5, the process unfolds as follows:

1st Tick - undefined
2nd Tick - undefined
3rd Tick - undefined
4th Tick - undefined
5th Tick - SMA (sum of first 5 ticks / period)
6th Tick - EMA (((price - prevEMA) * exponent) + prevEMA)

To calculate the Exponential Moving Average for technical analysis:

const calcEMA = (prices) => {
  let sum = 0
    let averages = []
    let prevEMA = undefined
    let tickIndex = 1

    for (const price of prices) {

      if (tickIndex < period) {
        tickIndex++
          sum = sum + price
          averages.push(undefined)
      } else {

        if (prevEMA) {
          // EMA
          prevEMA = ((price - prevEMA) * exponent) + prevEMA
        } else {
          // SMA
          prevEMA = ((sum + price) / period)
        }

        averages.push(prevEMA)

      }
    }
  return averages
}

calcEMA([
    81.59, 81.06, 82.87, 83.0, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36, 85.53, 86.54, 86.89, 87.77, 87.29,
])

Answer 8

I wanted to provide a fresh perspective on the calculation method used in technical analysis and indicators like Binance and TradingView.

In this approach, the Simple Moving Average (SMA) serves as the initial step in deriving the Exponential Moving Average (EMA).

When analyzing a series of candles, ticks, or prices within a period or interval of 5, the process unfolds as follows:

1st Tick - undefined
2nd Tick - undefined
3rd Tick - undefined
4th Tick - undefined
5th Tick - SMA (sum of first 5 ticks / period)
6th Tick - EMA (((price - prevEMA) * exponent) + prevEMA)

To calculate the Exponential Moving Average for technical analysis:

const calcEMA = (prices) => {
  let sum = 0
    let averages = []
    let prevEMA = undefined
    let tickIndex = 1

    for (const price of prices) {

      if (tickIndex < period) {
        tickIndex++
          sum = sum + price
          averages.push(undefined)
      } else {

        if (prevEMA) {
          // EMA
          prevEMA = ((price - prevEMA) * exponent) + prevEMA
        } else {
          // SMA
          prevEMA = ((sum + price) / period)
        }

        averages.push(prevEMA)

      }
    }
  return averages
}

calcEMA([
    81.59, 81.06, 82.87, 83.0, 83.61, 83.15, 82.84, 83.99, 84.55, 84.36, 85.53, 86.54, 86.89, 87.77, 87.29,
])

Finding Exponential Moving Averages (EMA) with the power of JavaScript

Answer №1

Answer №2

Answer №3

Answer №4

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