Moving Averages:
Simply put Moving Averages are a math calculation that averages out a series of numeric values. A moving average series can be calculated for any time series. In finance it is most often applied to stock and derivative prices, percentage returns, yields and trading volumes. There are three universal types of moving averages to calculate. The simple moving average is one of the most popular indicators used and is easy to calculate. There is also a weighted and an exponential moving average which are more sensitive to price fluctuations but more complicated to formulate.
The Following Topics were Covered.
1. How many types of moving averages are there to use.
2. How to calculate a moving average.
3. Which inputs to average?
4. Time dimensions for moving averages.
5. Cross over signals.
6. Moving average channels.
7. Filters on moving average signals using Stochastics, MACD and other indicators.
8. Use of Fibonacci as moving average settings.
9. Use of Pivot Points as a moving average system.
Simple Moving Average (SMA)
Here is how to calculate a Simple Moving Average (SMA). If we take the close of the last ten periods add them together then divide by ten we get the mean or average of the last ten periods. As a new period is added we drop the oldest time period.
|
Period |
Price |
|
1 |
1352 |
|
2 |
1360 |
|
3 |
1325 |
|
4 |
1256 |
|
5 |
1280 |
|
6 |
1220 |
|
7 |
1210 |
|
8 |
1450 |
|
9 |
1440 |
|
10 |
1460 |
Simple Moving Average = SUM of Prices/10
13353/10 = 1335.3
weighted moving average (WMA)
A weighted average is any average that has multiplying factors to give different weights to different data points. But in technical analysis a weighted moving average (WMA) has the specific meaning of weights which decrease arithmetically. Weighted M/A’s give a greater weight to more recent price data. These are complicated and need the aid of a computer.
WMA = the latest day has weight n, the second latest n-1, etc, down to zero.
Exponential moving averages:
Exponential moving averages (also called exponentially weighted moving averages). The EMA applies weighting factors which decrease exponentially. EMA’s reduce the lag by applying more weight to recent prices relative to older prices. The shorter the EMA’s period, the more weight that will be applied to the most recent price.
EMA = (Price (current) – EMA (previous) (x Multiplier) + EMA (previous)
Advantages of Moving Averages:
1. Defines average price changes over time and smoothes out trading noise.
2. Excellent trend trading tool.
3. Used to identify, triggers, entries, support and resistance levels.
4. Can be used in trading systems & one can study the back-tested performance results.
Disadvantages of Moving Averages:
1. M/A’s lag behind markets price changes.
2. Not effective in choppy markets.
3. Not effective in discovering price extensions.
4. Can’t predict turning points like Fibonacci or Pivot analysis only changes in trends
Values to be used in Moving Averages:
Highs
Lows
Close
Opens
Average of range (High-Low)
Average of typical price (HLC/3)
Volume
Volatility measurements
There are several ways to identify the direction of the trend with moving averages. If we look at the relationship between prices and the moving average we can study not only the direction of the moving average but the location of price in relationship to the moving average values and the crossovers points of interest.
The Rules of Moving Average:
If the moving average is rising, and prices are above the M/A, the trend is considered up.
If the moving average is declining, and prices are below the M/A, the trend is considered down.
An additional filter to trigger a signal on a price change would be if the close is above or below the moving average. Another method is if the entire range of the price components (O, H, L, C) are trading above or below the moving average. Another filter is if those factors are for more than one session.
The Time periods to be used in Chart for Moving Averages:
The question some traders have is which time periods should they program a moving average for Several time considerations include lining the moving average with a specific time frame such as the number 5 which equals a full trading week. A 20 day and 40 day M/A works out to one and two month moving average.
Day traders can break down the use of multiple time frame analysis such as a 15 minute period and a 5 minute period (which is divisible by 3). Traders can and often do tie in time periods with the Fibonacci numbers series. Which are 1,1,2,3,5,8,13,21, 34, 55, 89, 144, 23, etc. The more popular numbers used are 3,5, 8 13 and 21. Futures traders use shorter time periods, equity traders generally use longer term periods. Just remember that the shorter the time periods used that they are more sensitive to price changes.
Multiple Moving Averages
When we introduce more than one moving average with multiple time periods it helps identify shorter term and longer term trends and changes within those time frames. This concept can be used to identify support and resistance levels to help you increase profits and reduce risks. Always remember that the closing price causes a crossover: that is when a signal is generated.
There are two terms technicians use to identify trend changes:
Dead Cross- bearish or negative cross-over of a s horter term M/A than a longer term M/A.
Golden Cross- Bullish or positive cross-over of a shorter term M/A than a longer term M/A.
Moving Average Convergence/Divergence (MACD):
Moving Average Convergence/Divergence otherwise known as MACD in simplest terms is an indicator that shows when a short-term moving average crosses over a longer term moving average. Gerald Appel developed this indicator as we know it today and it is my understanding that he developed it for the purpose of stock trading. It is composed of using three exponential moving averages.
MACD signals react quickly to changes in the market that is why a lot of analysts including myself use it. It helps clear the picture when moving average crossovers occur. It measures the relative strength between where current prices are as compared to past time frames from a short term perspective to a longer term perspective. MACD signals are generated after the market has moved in an opposite direction of the original trend, and therefore is why it is considered a lagging indicator.
Some general points to help you understand how to use this indicator are first; when the fast line crosses above the slow line a buy signal is generated. The opposite is true for sell signals. MACD also has a zero base line. If MACD line is above the zero line prices are usually trending higher. The opposite is true if MACD is declining below the zero line.
Another method, and more reliable, however one that does not form often is a pattern called bullish convergence. This is where the market price itself makes a lower low from a previous low but the underlying MACD pattern makes a higher low. This indicates that the low is weak or “false” bottom and can resort to a turn around for a price reversal. MACD has the same principles as far as a sell signal with what is known as Bearish Divergence. This is where the market price itself makes a higher high from a previous high but the underlying MACD crossover lines make a lower high. This indicates that the second high is a “weak” high and can resort to a turn around for a lower price reversal. We see more divergence patterns in the histogram component than we do in the actual moving average MACD lines.
