# Advantages ofmacd and parabolic sar combined strategy

The momentum trading strategy responds to the short-term stock price fluctuations rather than the fundamental information of a company. That upward or downward momentum indicator generally instantly represents a breakout, which is a price movement through a recognized level of support or resistance usually accompanied by heavy volume and raised volatility for the stock, implying that even a period or two of prolonged momentum will force that stock in the direction of the breakout.

Concomitantly, the technical trader watches the momentum chart and the Level 2 screen to look for verification of a breakout to execute a market order [ 15 ]. Murphy describes how to evaluate momentum by watching at moving averages of stock prices with several time periods.

Moving averages of twenty days or less can gauge short-term momentum, while twenty to one hundred days moving averages are considered as a good standard of short-term momentum and conclusively days moving averages or more can be used to rate long-term momentum. A robust upward momentum can be identified when the shorter-term averages are preceding longer-term averages on the chart and the two averages are diverging providing a buy signal.

Charting is a technical trading precept of visualizing the movement of a stock price between momentous support and resistance levels. A support level is a price level that a stock impedes to go below and is the price level were bull traders use to enter a trade. Another common application of moving averages is setting up intended price supports. Commonly, traders will use the day or day moving average as a support level to verify anticipated movements of stock prices.

On the adverse, technical traders use the day moving average as a resistance level to prognosticate stock prices falling below a significant support level. Traders use the resistance level as a signal to obtain profits or to exit from any open long positions and also use this average as an entry point of a short position because the price often bounces off the resistance and downtrends.

The mathematical average of a stock price over a defined period of time forms a simple moving average. For instance, to calculate a day moving average the open, close, low or high prices of the stock can be used to determine a moving average by adding the referenced stock prices for the last 15 days and then divide the result by The resulting average integrates the past 15 data points to provide the trader a virtual of how the stock is priced the past 15 days [ 17 , 18 ].

Murphy interestingly remarks in his article that stock traders name this tool a moving average and not a typical mean considering that the most recent stock prices are superseded by the new prices as they become attainable imposing the data set to successively moving to account for the new available stock prices warranting the superiority of present prices.

Once the values of the MA have been calculated, they are mapped onto the charts used by technical traders and then joined to formulate a moving average line. Technical traders according to Murphy commit to the use exponential moving averages to diminish the impediment in simple moving averages by exerting more weight to the latest stock prices comparative to the older prices deeming on the specific period of the moving average.

Murphy states that the exponential moving average is more responsive to latest information since it delivers more weight to recent prices. The formula to evaluate the EMA equation is: The divergence between the EMA and SMA is the susceptibility each one displays to changes in the data used in its computation. Precisely, the exponential moving average EMA gives a higher weighting to current prices than the simple moving average SMA does, while the SMA accords the same weighting to all prices.

The two averages are analogous because they are expounded equivalently and used by technical traders to smooth out price fluctuations. Since EMAs stance a stronger weighting on recent data than on older data, they are more responsive to the newest price changes than SMAs are, which causes the effects from EMAs timelier and illustrates why the EMA is the favored average among many traders. Long term investors and swing traders elect to use the simple moving averages to enchant long-term changes.

The EMA is ordinarily more reactive to price changes than the SMA and initiates more signals resulting in prospective more wrong signals and whipsaws. The SMA normally has a slower motion and originates fewer signs that could attest to be more credible but concomitant to remissness profits. A variable moving average is an exponential moving average that based on the volatility of the data automatically modifies the smoothing constant.

The smoothing constant used in the moving average calculation is larger when the date is more volatile giving more weight to the current data. Alternatively, the variable moving average uses a smoothing constant for less volatile data. Strong trending markets are generally less volatile due to the uniformity of daily price fluctuations.

Standard moving averages are not tolerant to changes in volatility suffering to predict correct trends during high volatile markets. On the contrary, variable moving averages by automatically adjusting the smoothing constant perform better in both high and low volatility markets. The higher the volatility index the more volatile the market is, increasing the sensitivity of the moving average Paritech, The parabolic SAR is a technical indicator illustrated on a stock chart as a series of dots placed either above or below the stock price pivoting on the price momentum representing a shape of curve that resembles a parabola.

The parabolic SAR is a functional indicator in trending periods and when the trend of the stock is upward a small dot is placed below the price while a dot is placed above the price when the trend is downward. The Parabolic SAR system responds highly in markets with a dominant trend and fails despondently in sideways or non-trending markets. Wilder created an acceleration element into the system. Every day the stop motions in the direction of the latest trend. Initially, the repositioning of the stop is correspondingly slow to enable the trend time to substantiate.

As the acceleration factor rises, the SAR starts to move quicker, subsequently catching up to the price action.

A buy signal occurs when the most recent high price of a stock has been defied imposing the SAR to be positioned at the most recent low stock price. As the price of the stock rises, the dots will rise as well, first slowly and then picking up speed and accelerating with the trend.

The SAR starts to move a little faster as the trend advances and the dots presently catch up to the price action of the stock. The accelerating system of SAR is considerably profitable because it allows the investor to get into a trade position after the dots move closer to the price action, thus verifying that the trend is established.

Also, another lead of the Parabolic SAR trading system is that it is radically automatic, and detaches all of the human sentiments from trading enabling investors to reach a better ordered and uniform trading pattern. The drawback to this system is that most stocks do not build uniform trends and as a result force the SAR to be moving into a spasmodic way preventing the trader to enter and exit with consistent profits [ 19 ].

MACD uses moving averages which are lagging indicators and converts them into momentum oscillators by subtracting the longer-period moving average from the shorter-period moving average. The day EMA is the faster more responsive indicator while the day EMA is the slower indicator less prone to whipsaws.

As the MACD begins to upsurge the gap between the day EMA and the day EMA broadens indicating that the positive momentum increases, in other words, the rate-of-change of the faster moving average is higher than the rate-of-change for the slower moving average indicating a bullish period.

If MACD is negative and declining further, then the negative gap between the faster moving average and the slower moving average is escalating. Downward momentum is accelerating, indicating a bearish period of trading. MACD centerline crossovers occur when the faster moving average crosses the slower moving average. A Positive Divergence, although, it is the least common to transpire, it is the most dependable of the three signals and vanguards larger stock price moves.

A positive divergence is reflected when the MACD instigates an advancement and the security is still in a downtrend and falls below a lower stock price than the last low. Bullish Moving Average Crossovers are probably the most common signals and the least dependable. These crossovers can lead to whipsaws and many deceitful indications if not used in simultaneity with other technical indicators.

This is an evident sign that momentum has converted from negative to positive or from bearish to bullish. From the three signals, moving average crossovers are probably the second most common signals.

Occasionally it is cautious to assign a price filter to the Bullish Moving Average Crossover to safeguard that it will maintain. The buy signal would then originate at the end of the third day. MACD generates bearish signals from three main sources. These signals are mirror reflections of the bullish signals: Trading divergence is a popular method to use the MACD histogram but, unluckily, the divergence trade is not very precise since it fails more than it succeeds.

One of the most collective settings is to locate chart points at which price performs a new high stock price swing or a new low stock price swing but the MACD histogram does not, revealing a divergence among price and momentum.

A negative divergence forms when the security advances or moves sideways, and the MACD declines. If prices are rising, the histogram expands as the rate of the price movement accelerates, and contracts as price movement slow down.

The same principle works in reverse as prices are falling. One of the factors causing traders to enter bad positions with this technique is they enter a trade on a signal from the MACD indicator but exit it based on the move in price. Since the MACD histogram is a derivative of price and not the price itself, this approach is controversial. In other words, stock prices frequently explode up or down levering stops and pressuring traders out of position just before the move practically make a prolonged turn and the trade becomes rewarding.

To determine the incompatibility between entry and exit, a trader can use the MACD histogram for both trade entry and trade exit signals. To do so, the trader trading the negative divergence takes a partial short position at the initial point of divergence, but instead of setting the stop at the nearest swing high based on price, should stop the trade only if the high of the MACD histogram exceeds its previous swing high, indicating that momentum is actually accelerating and the trader is truly wrong on the trade.

If, on the other hand, the MACD histogram does not generate a new swing high, the trader should add to the initial position, continually achieving a higher average price for the short [ 20 ]. One of the primary benefits of MACD according to Murphy is that it incorporates aspects of both momentum and trend in one indicator.

As a trend-following indicator, it will not be wrong for very long. The use of moving averages ensures that the indicator will eventually follow the movements of the underlying security. As a momentum indicator, MACD has the ability to foreshadow moves in the underlying security. MACD divergences can be key factors in predicting a trend change.

A Negative Divergence signals that bullish momentum is waning, and there could be a potential change in trend from bullish to bearish. This can serve as an alert for traders to take some profits in long positions, or for aggressive traders to consider initiating a short position. MACD can be applied to daily, weekly or monthly charts. MACD represents the convergence and divergence of two moving averages. However, any combination of moving averages can be used. The set of moving averages used in MACD can be tailored for each individual security.

For weekly charts, a faster set of moving averages may be appropriate. For volatile stocks, slower moving averages may be needed to help smooth the data. Given that level of flexibility, each individual should adjust the MACD to suit his or her own trading style, objectives and risk tolerance.

Moving averages, be they simple, exponential or weighted, and are lagging indicators. Even though MACD represents the difference between two moving averages, there can still be some lag in the indicator itself. This is more likely to be the case with weekly charts than daily charts.

The plot of this difference is presented as a histogram, making centerline crossovers and divergences easily identifiable. If you will recall, a moving average crossover occurs when MACD moves above or below the trigger line.

MACD is not particularly good for identifying overbought and oversold levels. Even though it is possible to identify levels that historically represent overbought and oversold levels, MACD does not have any upper or lower limits to bind its movement. MACD can continue to overextend beyond historical extremes. MACD calculates the absolute difference between two moving averages and not the percentage difference.

MACD is calculated by subtracting one moving average from the other. As a security increases in price, the difference both positive and negative between the two moving averages is destined to grow. This makes it difficult to compare MACD levels over a long period of time, especially for stocks that have grown exponentially. As described in Investors. Buy the leading stock in a leading industry. Stable earnings growth in the industry supports the industry is prospering and the company is prepared to breakout.

This strategy does not necessitate technical analysis of former stock prices and volume of trading or fundamental analysis of financial statements, valuation of cash flows, and assessment of prospective growth rates for the assortment of securities.

The Dogs of the Dow strategy obliges the investor to classify from the highest to the lowest the dividend yields dividends divided by the price of the stock of the thirty stocks comprising the Dow Jones Industrial Average. After one year, the 30 Dow stocks are rated anew, and the stocks with the ten highest dividend yields are retained.

If a stock is no longer among the ten, it is sold and superseded by a new Dow dog that is one of the ten stocks with the highest dividend yield [ 10 ]. Technical analysis appraises equity securities by evaluating the statistics of preceding stock prices and volume caused by market activity. Exactly, as there are many investment techniques on the fundamental analysis, there are as well many various types of technical traders. Technicians can depend on chart patterns, technical indicators and oscillators.

The field of technical analysis is based on the three suppositions: Moving averages are primarily the most recognized technical indicators used to decide the direction of trading stocks.

Every moving average model is the consequence of a statistical computation of an averaging number of preceding information plotted into a chart enabling traders to watch at smoothed data rather than focusing on daily price movements inherited in all financial markets.

Moving averages they do not foresee new trends but as lagging indicators validate trends once they have been recognized. A stock is up trending when the price is above a moving average and the average is slopping upwards. Conversely, a down trending stock is portending with a down slopping average.

Frequently, traders hold a long position buy when the price of a stock is trading above the moving average and a short position sell when the stock price trades below the moving average [ 14 ]. The momentum trading strategy responds to the short-term stock price fluctuations rather than the fundamental information of a company. That upward or downward momentum indicator generally instantly represents a breakout, which is a price movement through a recognized level of support or resistance usually accompanied by heavy volume and raised volatility for the stock, implying that even a period or two of prolonged momentum will force that stock in the direction of the breakout.

Concomitantly, the technical trader watches the momentum chart and the Level 2 screen to look for verification of a breakout to execute a market order [ 15 ].

Murphy describes how to evaluate momentum by watching at moving averages of stock prices with several time periods. Moving averages of twenty days or less can gauge short-term momentum, while twenty to one hundred days moving averages are considered as a good standard of short-term momentum and conclusively days moving averages or more can be used to rate long-term momentum.

A robust upward momentum can be identified when the shorter-term averages are preceding longer-term averages on the chart and the two averages are diverging providing a buy signal. Charting is a technical trading precept of visualizing the movement of a stock price between momentous support and resistance levels. A support level is a price level that a stock impedes to go below and is the price level were bull traders use to enter a trade.

Another common application of moving averages is setting up intended price supports. Commonly, traders will use the day or day moving average as a support level to verify anticipated movements of stock prices. On the adverse, technical traders use the day moving average as a resistance level to prognosticate stock prices falling below a significant support level. Traders use the resistance level as a signal to obtain profits or to exit from any open long positions and also use this average as an entry point of a short position because the price often bounces off the resistance and downtrends.

The mathematical average of a stock price over a defined period of time forms a simple moving average. For instance, to calculate a day moving average the open, close, low or high prices of the stock can be used to determine a moving average by adding the referenced stock prices for the last 15 days and then divide the result by The resulting average integrates the past 15 data points to provide the trader a virtual of how the stock is priced the past 15 days [ 17 , 18 ].

Murphy interestingly remarks in his article that stock traders name this tool a moving average and not a typical mean considering that the most recent stock prices are superseded by the new prices as they become attainable imposing the data set to successively moving to account for the new available stock prices warranting the superiority of present prices.

Once the values of the MA have been calculated, they are mapped onto the charts used by technical traders and then joined to formulate a moving average line. Technical traders according to Murphy commit to the use exponential moving averages to diminish the impediment in simple moving averages by exerting more weight to the latest stock prices comparative to the older prices deeming on the specific period of the moving average.

Murphy states that the exponential moving average is more responsive to latest information since it delivers more weight to recent prices.

The formula to evaluate the EMA equation is: The divergence between the EMA and SMA is the susceptibility each one displays to changes in the data used in its computation. Precisely, the exponential moving average EMA gives a higher weighting to current prices than the simple moving average SMA does, while the SMA accords the same weighting to all prices. The two averages are analogous because they are expounded equivalently and used by technical traders to smooth out price fluctuations.

Since EMAs stance a stronger weighting on recent data than on older data, they are more responsive to the newest price changes than SMAs are, which causes the effects from EMAs timelier and illustrates why the EMA is the favored average among many traders. Long term investors and swing traders elect to use the simple moving averages to enchant long-term changes.

The EMA is ordinarily more reactive to price changes than the SMA and initiates more signals resulting in prospective more wrong signals and whipsaws. The SMA normally has a slower motion and originates fewer signs that could attest to be more credible but concomitant to remissness profits.

A variable moving average is an exponential moving average that based on the volatility of the data automatically modifies the smoothing constant. The smoothing constant used in the moving average calculation is larger when the date is more volatile giving more weight to the current data. Alternatively, the variable moving average uses a smoothing constant for less volatile data.

Strong trending markets are generally less volatile due to the uniformity of daily price fluctuations. Standard moving averages are not tolerant to changes in volatility suffering to predict correct trends during high volatile markets. On the contrary, variable moving averages by automatically adjusting the smoothing constant perform better in both high and low volatility markets. The higher the volatility index the more volatile the market is, increasing the sensitivity of the moving average Paritech, The parabolic SAR is a technical indicator illustrated on a stock chart as a series of dots placed either above or below the stock price pivoting on the price momentum representing a shape of curve that resembles a parabola.

The parabolic SAR is a functional indicator in trending periods and when the trend of the stock is upward a small dot is placed below the price while a dot is placed above the price when the trend is downward.

The Parabolic SAR system responds highly in markets with a dominant trend and fails despondently in sideways or non-trending markets. Wilder created an acceleration element into the system.

Every day the stop motions in the direction of the latest trend. Initially, the repositioning of the stop is correspondingly slow to enable the trend time to substantiate. As the acceleration factor rises, the SAR starts to move quicker, subsequently catching up to the price action. A buy signal occurs when the most recent high price of a stock has been defied imposing the SAR to be positioned at the most recent low stock price.

As the price of the stock rises, the dots will rise as well, first slowly and then picking up speed and accelerating with the trend. The SAR starts to move a little faster as the trend advances and the dots presently catch up to the price action of the stock. The accelerating system of SAR is considerably profitable because it allows the investor to get into a trade position after the dots move closer to the price action, thus verifying that the trend is established.

Also, another lead of the Parabolic SAR trading system is that it is radically automatic, and detaches all of the human sentiments from trading enabling investors to reach a better ordered and uniform trading pattern.

The drawback to this system is that most stocks do not build uniform trends and as a result force the SAR to be moving into a spasmodic way preventing the trader to enter and exit with consistent profits [ 19 ]. MACD uses moving averages which are lagging indicators and converts them into momentum oscillators by subtracting the longer-period moving average from the shorter-period moving average.

The day EMA is the faster more responsive indicator while the day EMA is the slower indicator less prone to whipsaws.

As the MACD begins to upsurge the gap between the day EMA and the day EMA broadens indicating that the positive momentum increases, in other words, the rate-of-change of the faster moving average is higher than the rate-of-change for the slower moving average indicating a bullish period.

If MACD is negative and declining further, then the negative gap between the faster moving average and the slower moving average is escalating. Downward momentum is accelerating, indicating a bearish period of trading. MACD centerline crossovers occur when the faster moving average crosses the slower moving average. A Positive Divergence, although, it is the least common to transpire, it is the most dependable of the three signals and vanguards larger stock price moves. A positive divergence is reflected when the MACD instigates an advancement and the security is still in a downtrend and falls below a lower stock price than the last low.

Bullish Moving Average Crossovers are probably the most common signals and the least dependable. These crossovers can lead to whipsaws and many deceitful indications if not used in simultaneity with other technical indicators.

This is an evident sign that momentum has converted from negative to positive or from bearish to bullish. From the three signals, moving average crossovers are probably the second most common signals.

Occasionally it is cautious to assign a price filter to the Bullish Moving Average Crossover to safeguard that it will maintain. The buy signal would then originate at the end of the third day. MACD generates bearish signals from three main sources. These signals are mirror reflections of the bullish signals: Trading divergence is a popular method to use the MACD histogram but, unluckily, the divergence trade is not very precise since it fails more than it succeeds.

One of the most collective settings is to locate chart points at which price performs a new high stock price swing or a new low stock price swing but the MACD histogram does not, revealing a divergence among price and momentum. A negative divergence forms when the security advances or moves sideways, and the MACD declines.

If prices are rising, the histogram expands as the rate of the price movement accelerates, and contracts as price movement slow down. The same principle works in reverse as prices are falling. One of the factors causing traders to enter bad positions with this technique is they enter a trade on a signal from the MACD indicator but exit it based on the move in price.

Since the MACD histogram is a derivative of price and not the price itself, this approach is controversial. In other words, stock prices frequently explode up or down levering stops and pressuring traders out of position just before the move practically make a prolonged turn and the trade becomes rewarding.

To determine the incompatibility between entry and exit, a trader can use the MACD histogram for both trade entry and trade exit signals. To do so, the trader trading the negative divergence takes a partial short position at the initial point of divergence, but instead of setting the stop at the nearest swing high based on price, should stop the trade only if the high of the MACD histogram exceeds its previous swing high, indicating that momentum is actually accelerating and the trader is truly wrong on the trade.

If, on the other hand, the MACD histogram does not generate a new swing high, the trader should add to the initial position, continually achieving a higher average price for the short [ 20 ]. One of the primary benefits of MACD according to Murphy is that it incorporates aspects of both momentum and trend in one indicator. As a trend-following indicator, it will not be wrong for very long.

The use of moving averages ensures that the indicator will eventually follow the movements of the underlying security. As a momentum indicator, MACD has the ability to foreshadow moves in the underlying security. MACD divergences can be key factors in predicting a trend change.

A Negative Divergence signals that bullish momentum is waning, and there could be a potential change in trend from bullish to bearish. This can serve as an alert for traders to take some profits in long positions, or for aggressive traders to consider initiating a short position.

MACD can be applied to daily, weekly or monthly charts. MACD represents the convergence and divergence of two moving averages.