Simple Moving Average (SMA)

Simple Moving Average is the simplest type of moving averages. In principle, SMA, is calculated by dividing the last number in the period between the closing and then divide this number by one point. Let me explain, in this example, if you count 5 SMA 1 hour, closing in the last 5 hours, and then divide this number of 5 if you count 30 SMA 5 minutes, add the closing prices over the past 150 minutes (30 * 5) then divide this number of 5 At the same time, SMA could be calculated for any period of time.

Most platforms, all of these calculations for you. The reason why I bother with this component of technical analysis is that it is essential to understand how to calculate the moving average. If you understand how each moving average is calculated, you can create your own decisions on what type is best for you.

Like any other indicator, SMA is a delay. As you can see the average prices, then you actually looked at the "prediction of future prices, but not in the future. Here is an example of how moving averages to reduce the price of activity:

In the table you can use 3 different SMA. As you can see, the greatest period of SMA, is for the best prices. You have probably noticed that the 62 SMA is much further from current prices, from 30 to 5 GHS. This is because with the recent closure of 62 SMA 62 and divided by 62 The greater the number of terms used, the reaction is slower than the evolution of prices. SMA in this diagram shows the general mood in the market during this period. Instead of focusing solely on market prices, moving averages, a broader view and enter the prediction of future prices.

SMA = SUM (CLOSE, N) / N, if:
N = number of periods for the calculation

Exponential Moving Average (EMA)

Although SMA is an excellent tool, one of the biggest problems with it, SMA is extremely vulnerable to sudden jumps (peaks). If you look at the example that the best thing I have in mind:
Suppose you create a 5 SMA in the daily scheme of EUR / USD and the closing for the last 5 days: 1 day to 1.2345, and 1.2350 day 2, 3 days - 1, 2360, Day 4 - 1.2365, Day 5 -- 1.2370. SMA is calculated as follows: (1.2345 1.2350 1.2360 1.2365 1.2370) / 5 = 1.2358. But what if the price of 2 days 1.2300? SMA results will be much smaller, and you get the impression that the price drops, if in fact, may be only 2 days were remote events (eg, reducing the interest rate).

What I am trying to show that SMA can sometimes be too simple. If there is only one way to filter so you do not jumping wrong image and a large part of moving averages. There is, and is called the Exponential Moving Average (EMA).

EMA is a kind of moving average, which is similar to the simple moving average, where more emphasis on more recent data. Exponential Moving Average is also known as an exponentially weighted moving average. "This type of moving average responds quickly past price changes than a simple moving average. In our example above, EMA will be more attention for 3-5 days, which means that the transition to the 2-m is a lower cost and, therefore, have no impact on the moving average. It would be more attention to the dealer what to do now. Although trade is important to see what traders are doing, not what they were doing last week or last month.

EMA = (CLOSE (I) * C) + (EMA (I-1) * (100-P)) if:
CLOSE (I) = the closing price for the current period
EMA (I-1) = exponential moving average of the closing of the previous period
P = proportion of the use of value pricing

Smoothing Moving Average (SMMA)

Smoothed moving average is a kind of cross between a simple moving average and exponential moving average, and only one more use. The moving average, smoothed, recent prices for the same weight of historical faith. In the calculation does not apply to a specific period of time, but it takes all the records should be considered. This is achieved through yesterday? S smoothed moving average to date? S Price. This is the result of yesterday? S smoothed moving average, results to date? S medium.

In a simple moving average, the price data are of equal weight in calculating the average. Even in the simple moving average, the oldest price data from the moving average price will be as new to the computer. The moving average, smoothed with a longer period to determine an average based on the weight of price is calculated as an average. Thus, the prices of old data in a smoothed moving average has never been removed, but have only minimal impact on the moving average, like the exponential moving average places more weight on recent data.

The first value of the smoothed moving average is calculated as a simple moving average (SMA):
SUM1 = SUM (CLOSE, N)
SMMA1 = SUM1 / N

The second and subsequent moving averages are calculated by this formula:
SMMA (I) = (+ SUM1-SMMA1 CLOSE (I)) / N, if:
SUM1 = sum of the closing prices for N periods
= SMMA1 smoothed moving average of the first bar
SMMA (I) = smoothed moving average of the current bar (except the first)
CLOSE (I) = the current price closing
N = smoothing Between

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