Two fairly common deviations on the simple moving average are the weighted moving average and the exponential moving average. These types of moving averages are calculated in different ways, but they both have the same goal: to place more emphasis on recent prices.

Why would a trader want to explore more complex moving averages? Well, the major advantage one of these more complicated moving averages has over the simple moving average is that it's better at revealing a change in trend more quickly. Being able to detect trend changes faster helps to make you a more agile trader. Also, traders (especially short-term traders), have very short memories. Ask me what the market did yesterday, and I'm pretty sure I can give you a quick answer. Ask me what it did two Fridays ago, and I would be quickly pulling up a chart (a candlestick chart, of course!) to get you an answer. Because a short-term trader places more emphasis on more recent price action, using a charting method that does the same typically works better for shorter term styles of trading. Weighted and exponential moving averages both emphasize recent price action, and the only substantial difference between the two is the method of calculation.

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If you were to rank the three most commonly used types of moving averages — simple, weighted, and exponential — according to their emphasis on recent price action, exponential moving averages, which place a lot of emphasis on recent prices, would top the list. Weighted moving averages would be a close second and simple moving averages a distant last.

Figure 11-5:

A 5-day and 20-day moving average compared together.

Figure 11-5:

A 5-day and 20-day moving average compared together.

Calculating a weighted moving average

To calculate a weighted moving average, multiply the most recent stock price by the total number of prices in your chosen time frame. Then multiply the second most recent stock price by the total number of prices minus one, and — using the same method — work your way back to the first price in your time frame.

For Figure 11-6, I've taken the same five-day data used for the simple moving average in Figure 11-4 and calculated a weighted moving average. Note: For Day 5, the weighted close is equal to 5 x 113.87 or 569.35, while the weighted close for Day 1 is simply the closing price x 1 (114.70). To determine the weighted moving average, the weighted closing prices are added up and divided by the sum of the weights. In this case, that number is

[(1 x Day 1 closing price) + (2 x Day 2 closing price) + (3 x Day 3 closing price) + (4 x Day 4 closing price) + (5 x Day 5 closing price)] * 15.

Figure 11-6:

calculation of a 5-day weighted moving average.

Day |
Close |
Weighted Close |

1 |
114.70 |
114.70 |

2 |
114.73 |
229.46 |

3 |
114.14 |
342.42 |

4 |
113.56 |
454.24 |

5 |
113.87 |
15 Total Total / 15 ## 1710.17 114.01Refer to Figure 11-4 and Figure 11-6 for the difference between the simple moving average and the weighted moving average. There's a pretty significant difference! The lower recent prices mean that the weighted moving average is quite a bit lower. ## Catcutating an exponential moving averageYou can calculate an exponential moving average in a handful of different ways, and I suggest that you use . . . none of them. The math involved in the calculations is a bit complex, and for your purposes, I recommend leaving the hard work to a charting package. (See Chapter 4 for more info on popular charting software.) |

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