| ny stocks technical analysis applications averages are | | | | because the calculation was simple; longer periods |
| used to smooth short term price swings, to get a | | | | were used because the movements in those days |
| better indication of the price trend. Let’s | | | | took time to take off and to complete. This tradition |
| have a look at different moving averages and how | | | | is still alive today in the sense that investors still |
| some of the lag, typical to an average, can be | | | | watch these averages. That is the reason why prices |
| compensated. | | | | generally experience support and resistance at the |
| Averages are trend-following indicators. A moving | | | | level of these averages. |
| average of daily prices is the average price of a | | | | The 50-day moving average gives direction to the |
| share over a chosen period, displayed day by day. | | | | medium-time period. The 200-day moving average is |
| For calculating the average, you have to choose a | | | | important for a look at the long-term trend. Around |
| time period. The choice of a time period is always a | | | | the 50- and the 200-day averages, you will almost |
| reflection upon, more or less lag in relation to price | | | | always notice some form of support or resistance. It |
| compared to a greater or smaller smoothing of the | | | | is therefore a good idea displaying the 50- and |
| price data. There are a lot of different averages | | | | 200-day moving averages on your price chart. The |
| used. I will limit this overview to the common ones. | | | | 20-day moving average is most useful as an |
| First let’s talk about the simple moving | | | | inclination indication for short term trend lines. |
| average that is calculated by adding all prices within | | | | If you are a trend following medium term trend |
| the chosen time period, divided by that time period. | | | | trader, you probably keep an eye on one or the |
| That way, each data value has the same weight in | | | | other average. Of course you like a smooth average |
| the average result. The simple average has the best | | | | to stay in the trade as long as possible. Smooth |
| smoothing, but generally also the biggest lag after | | | | means a longer time period. The disadvantage will be |
| price reversals. | | | | too much lag at the main turning points. So you could |
| An exponential moving average gives exponentially | | | | make use of a technique to limit as much as possible |
| more weight, based on a selected percentage, to the | | | | the lagging nature of the average. The principles for |
| more recent prices in a range based on this formula: | | | | limiting the lag of an average were introduced by Dr. |
| EMA= (price * EMA %) + (previous EMA * (1 | | | | Joe Sharp in Stocks & Commodities magazine, |
| – EMA %)) | | | | January 2000. Using a 50-days zero-lagging simple |
| Most investors do not feel comfortable with an | | | | moving average for example will clearly show much |
| expression related to percentage in the exponential | | | | less lag compared to the 50-days standard simple |
| moving average; rather, they feel better using a time | | | | moving average. |
| period. | | | | Another interesting average that can be used to |
| If you want know the percentage in which to work | | | | smooth larger chunks of data without the |
| using a period, this formula gives you the conversion: | | | | disadvantage of a larger lag is the TEMA average or |
| EMA Percentage(%) = 2 / (Time period +1) | | | | Triple Exponential Moving Average. This average was |
| Compared to the simple moving average, the | | | | introduced by Patrick Mulloy in Technical Analysis of |
| exponential moving average will therefore follow | | | | Stocks & Commodities magazine, February 1994. |
| closer the price evolution. This will result in less | | | | Averages of 100 days and more will only show little |
| smoothing compared to the simple moving average. | | | | lag, while the smoothing will be quite good. TEMA is |
| A weighted moving average puts more weight on | | | | not simply a triple exponential moving average, as |
| recent data and less weight on older data. A | | | | you probably would assume from the name. The |
| weighted moving average is calculated by multiplying | | | | intention of TEMA is to limit the typical lag of an |
| each datum with a factor from day | | | | average. |
| “1” till day “n” for the | | | | An ‘n’ day exponential average (EMA) |
| oldest to the most recent data; the result is divided | | | | has a smoothing factor alpha of: |
| by the total of all multiplying factors. In a 20-day | | | | Alpha = 2 / (n + 1) and a delay of: |
| weighted moving average, there is 20 times more | | | | Delay = (n - 1) / 2. The larger the average period n, |
| weight for the price today in proportion to the price | | | | the better the smoothing, but, unfortunately, the |
| 20 days ago. Likewise, the price of yesterday gets | | | | larger the delay. TEMA uses a technique of John |
| 19 times more weight, and so on. The weighted | | | | Wilder Tukey to compensate the delay. The data is |
| average follows the price movement the closest and | | | | sent several times through the same filter and |
| moves in general smoother than the exponential | | | | combined afterward: |
| average. Determining which of these averages to use | | | | TEMA = (3*EMA – 3*EMA(EMA)) + |
| depends on your objective. If you want a trend | | | | EMA(EMA(EMA)) |
| indicator with better smoothing and only little reaction | | | | The application of the TEMA average makes most |
| for short time movements, the simple average is | | | | sense if you want to smooth larger data periods, |
| best. If you want a smoothing where you can still | | | | whereas the delay must remain as small as possible. |
| see and react to the short period swings, then either | | | | Of course you can start making all kinds of |
| the exponential or weighted moving average is the | | | | combinations with the different averaging techniques, |
| better choice. | | | | combining simple, exponential or weighted moving |
| The 20-, 50-, and 200-days simple moving averages | | | | averages with the TEMA and zero-lagging average |
| were mostly used in the past before the advent of | | | | techniques. That way you can create your own |
| personal computers. A simple average was used | | | | average that fits best your way of trading. |