Combining smas and emas
Technical analysis for Forex mostly consists of a variety of Forex technical studies. Each of these studies can be interpreted to generate buy and sell signals or to help predict market direction. Traders find the prevailing trend to make themselves aware of the general market direction. To identify the long-term trend the daily, weekly and monthly charts are most ideally suited. When the technical trader identifies the overall trend, they will usually begin identifying the trend of their chosen trading timeframes.
The points where a chart experiences recurring upward or downward pressure are known as support and resistance levels. The support levels exist at the lows and the resistance levels exist at the highs. When the levels are broken, the generally become the opposite. An example of this would be a support level breaking to the downside. It would often become a new resistance level. In a market that is on the rise, a broken resistance level could become support for the upward trend.
Likewise, a support level that is broken in a market that is on the decline could become a new resistance level for the downward trend. If you are looking for simple yet helpful tools to confirm the direction of market trends, you could turn to the trend lines.
To draw an upward straight line, you would connect at least two successful lows however, you would preferably connect more. It is necessary that each successive point on the line be higher than the previous point. An upward trend is a solid way to find support lines and levels. To chart the downward lines you would also connect two or more points. The validity of a trend line is, in part, related to the number of points that are connected.
To identify the overall trend, moving averages can be very helpful. The moving averages show the average price of a currency at a specific point over a specific period of time. Moving averages are not perfect. To counteract this issue, it is best to use a short period of time when using moving averages.
A simple moving average SMA is simply the average of prices of a security or index over a specific time span, such as 5, 10, 20, or 50 days. They are called moving averages because they are calculated for each trading day for the previous period, so at the end of a trading day, the last day is added, while the earliest day of the previous average is dropped. Most moving averages are based on closing prices, but they can be based on opening, high, low, or mean prices.
Whichever price is chosen must be used consistently to give the best indication of trend. For example, to calculate a day simple moving average, which can be denoted as SMA 10 , based on closing prices, the closing prices of the last 10 days are added, then divided by After the next trading day, the earliest day of the previous average is replaced by the latest day.
Since a simple moving average is only an average where the last value is added and the first value is dropped for each day, a simple moving average can also be calculated using a spreadsheet's AVERAGE function. Thus, with Microsoft Excel, this moving average can be calculated thus:. The input variables to the AVERAGE function can be references to cells with imported stock prices, which makes their calculation even easier.
Because moving averages are based on data in a preceding period, they are lagging indicators. They can only indicate a trend that is already in place. Moving averages based on shorter time spans more closely reflect the underlying current trend, but they are also more sensitive to the volatility of the markets, which can generate many false signals. To minimize false signals, especially in a whipsaw market that trades within a narrow range, multiple moving averages of different time spans are used together.
Traders often use crossovers , where the graph of the shorter moving average crosses over a longer moving average, as a good indication of a new trend. Traders will often use the crossovers as a buy or sell signal and as a good price to set trailing stops. So if the shorter moving average crosses above the longer-term average, then this indicates a beginning of an uptrend, while a downward cross may indicate the beginning of a downtrend. However, even crossovers may give false signals, particularly in whipsaw markets, so moving averages are often used with other technical indicators as a confirmation of the trend change.
The problem with simple moving averages is that the earliest day of the time period has the same weight in the average as the most recent day. If the earliest day was volatile, but the market has recently calmed, then the volatile day will have a large influence on the average—known as a drop-off effect —which would not best represent the current market. To correct this anomaly, exponential moving averages EMA are used, where greater weight is given to more recent prices.
This greater weight causes the EMA to follow the underlying prices more closely most of the time than the SMA of the same duration. Although moving averages can be calculated in many different ways, the traditional method of calculating the EMA is to add an additional day to the simple moving average, but to give greater weight to the last day. The formula to calculate the weight of the last day is:.
So if XYZ stock had a day moving average of 25 yesterday , and the stock closed at 26 today, then:. There are many variations of the exponential moving average. Many of these variations base their calculations of the EMA on the volatility of the market. Moving averages can easily be calculated using a spreadsheet or the software of a trading platform.
Most major websites that provide stock prices, such as Yahoo , Google , and Bloomberg , also provide free charting tools that include moving averages. Most of these tools also allow multiple moving averages to be plotted in the same graph—even SMAs and EMAs can be combined in the same graph.
As stated earlier, moving averages can be calculated in many ways, and, likewise, can be used in many different ways. There is no persuading evidence that any method is better than any other, especially since there are infinite possible combinations of moving averages and other technical indicators.