The Macd (Moving Average Convergence/Divergence) is an indicator designed by Gerald Appel. This is a delayed indicator, convergence divergence of moving averages, as it is constructed with moving averages; for the same reason its use is more indicated in trend phases.
The Macd indicator consists of two lines that intersect and cross the equilibrium line at level 0. The two lines are the Macd line, the other is the signal line, or "signal line", for convenience of display this is represented by a series of points. Sometimes it is also displayed in histograms (vertical segments), while the signal line maintains its linear appearance.
The Mac indicator is constructed through the difference of two exponential moving averages:
MACD = Ema12 - Ema26
Where: Ema12 = 12-period exponential moving average; Ema26 = 26-period exponential moving average.
It is possible to observe that, when the two moving averages cross in the zone of the prices, the difference of their value is null and therefore also the Macd will have value 0 and will be found with the histogram in correspondence of the equilibrium line.
When the two moving averages cross from bottom to top, the indicator histogram changes from negative to positive; vice versa, when the cross is from top to bottom, the indicator histogram changes from positive to negative.
The second line of the Macd is the signal line, and is calculated with the following formula:
Signal line = Ema9(MACD)
The signal line can also intersect the histograms of the indicator and follow its progress with a certain delay; this should be understandable, as the line is derived from applying a moving average to the Macd itself.
Like many other indicators, the Macd allows to observe possible divergences between the evolution of prices and the evolution of prices. Therefore, you can look for bullish (bearish) divergences if during a down trend/uptrend the oscillator does not confirm the new minimum/maximum reached by the price movement.
The main objective of the professional users of Technical Analysis is to identify the main trend followed by prices. For this reason, it is necessary to reduce as much as possible the background noise coming from the market (in technical jargon we speak of "noise"), that is those movements made by prices caused by information asymmetries.
The moving averages are divided into three types:
Simple moving average (Sma/Simple/Moving/Average) is the easiest type to calculate, it is determined by summing the closing prices "P" by a hypothetical number "n" of days and dividing the result by the total number of days. One of the drawbacks of this indicator is that it considers remote and recent quotations to be equal.
If we indicate the last of the "n" days by "t", the formula for calculating the simple moving average is as follows:
Simple (t) = (P(t) + P8t-1) + P(t-2) + P(t-3) + ...) / n
The weighted moving average tries to eliminate its main flaw, considering that it takes more account of recent values than of the farthest values. In determining this value, greater weight is given to the most recent values, since they represent more accurately what is happening on the market.
If, for example, you want to calculate, starting from today, an average of 5 days, you should multiply by 1 the first value of the series (the survey of 5 days ago), by 2 the second (the survey of 4 days ago) and continue until the last value (the survey of today) to multiply by 5.
The total given by the sum of all the quotations multiplied by the relative weight should then be divided by the sum of the weights themselves which, in this example, would be 15 (1+2+3+4+5).
Exponential moving average is the most used type by traders and traders. It allows the analysis of a rather long historical series, while attaching more importance to the most recent data in order to identify the short-term trend followed by the market.
The formula for calculating them is as follows:
Multiplicative coefficient = cm = (2/(n+1))
For example, for a time span of 5 periods the multiplicative coefficient is (2/(5+1)) = 0,333
The formula for calculating a moving average exponential at time t is as follows:
Ema = Ema(t,-1) + cm * (C-Ema(t,-1))
Where: Ema(t,-1)= the value of the exponential moving average to the previous period; cm= the multiplier coefficient; C= the last closing price.
It is used to identify a condition for prices:
Also, when crossing the balance line:
It should also be considered that, being built on the basis of moving averages, the Macd can give false signals, which come mainly at the same time as the phases of lateral course. The indicator shows a delay effect with respect to the quotations, which is generally rather contained and in some cases providential for the filter action that is accompanied.
It is a suitable tool for the construction of multiframe operational strategies; its logic is based on applying the indicator to the same title on different time scans and attributing a score to the negative/positive state, based on the cross between the indicator and the signal line in each graph.
To implement multiframe operational strategies, we take for example four-time scans, two fast scans, with a 1-hour and 4-hour timeframe and two lenses, with a 1 daily and 1 weekly timeframe, each of which is rated, taking into account that the slower scans weigh more because they have more lasting effects.
The maximum score that can be awarded is 10 and it will be sufficient to obtain a score of 6 to have a positive indication. You can then calculate the score based on multiframe logic.
If you look at slow and fast charts and relative crossings, you can calculate the score they give and see if the overall score is positive or negative, if it exceeds 6, the system is a bullish condition; if it is less than 6 the setting will become bearish. The system may give false signals but can be further filtered by considering positive cross signals below the equilibrium line
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