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Mostafa Doustzadeh
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Username:Doustzadeh
Name:Mostafa Doustzadeh
Member since: 20 Mar 2016
Country:Iran

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EURUSD

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Electronics Engineer & Software Developer

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Projection Bandwidth
  2
  0
  642
free  20 Dec 2021
Projection Bands, a new method using trading bands, projects market data forward along the data trend with the maximum and minimum of the projections defining the band. The method provides another means of signaling potential changes for market direction relative to the trend. This shows the % width of the projection bands. A trend reversal is signaled by a high value. Low value may indicate the start of a new trend. This is also a trend strength indicator.   Github: GitHub - Doustzadeh/cTrader-Indicator  
Projection Oscillator
  2
  0
  614
free  20 Dec 2021
The Projection Oscillator is based on the Projection Bands indicator. The Oscillator calculates where the close lies within the band as a percentage. Therefore, an Oscillator value of 50 would mean that the close is in the middle of the band. A value of 100 would mean that the close is equal to the top band, and zero means that it is equal to the low band. The calculation is similar to a Stochastic which uses the raw highest high and lowest low value, whereas the Projection Oscillator adds the regression line component, making it more sensitive. The Projection Oscillator can be interpreted several ways. Look for divergence with price to indicate a trend reversal. Extreme values (over 80 or under 20) indicate overbought/oversold levels. A moving average of the oscillator can be used as a trigger line. A buy/sell signal is generated when the Projection Oscillator to cross above/below the trigger line. The signal is stronger if it happens above 70 or below 30. See also Projection Bands and Projection Bandwidth. Projection Bands were developed by Mel Widner, Ph.D and were originally introduced in his article in the July, 1995 issue of Technical Analysis of Stocks & Commodities magazine.   Github: GitHub - Doustzadeh/cTrader-Indicator  
Projection Bands
  5
  0
  688
free  20 Dec 2021
Projection Bands were developed by Mel Widner, Ph.D and were introduced in an Technical Analysis of Stocks & Commodities magazine article in July, 1995. Projection Bands are made up of two bands outlining minimum and maximum projected boundaries. The Bands are derived using the minimum and maximum prices over a given time period and projecting these forward, parallel to a linear regression line. The Bands are interpreted to signal directional price reversal when when prices reaches their boundary.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  20 Dec 2021
The volatility quality index (VQI) by Thomas Stridsman was firstly published in 2002 on Technical Analysis of Stocks and Commodities magazine. The idea behind the volatility quality index is to point out the difference between bad and good volatility in order to identify better trade opportunities in the market. This forex indicator works using the True Range algorithm in combination with the open, close, high and low prices. Stridsman suggested to buy when VQI has increased in the previous 10 bars (use the SMA) and sell when it has decreased in the previous 10 bars. Use this with your other indicators as a confirmation signal.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  16 Dec 2021
The Kairi Relative Index is an old Japanese metric with unknown origins and waning popularity in the modern day due to more popular indicators such as Welles Wilder's Relative Strength Index (RSI). Traders since the late 1970s have grown accustomed to newer, more modern indicators. Because Kairi has an unknown derivation and is used much less even in certain Japanese indicator loyalty zones of Russia and Asia, its continued use is curious. Add the fact that literally no early writings can be found regarding Kairi. The word itself translates to separate or dissociation. We don't want deviation in our indicators or price separation; we want perfect market timing indicators that follow market trends and turns. The difference between the two indicators is slight and yet varied, the only way to understand the Kairi Index is to compare it with the RSI. To begin with, both are considered oscillators. Oscillator indicators move with a chart line up or down as markets fluctuate. Calculations vary among each oscillator, so each oscillator serves a different market function. RSI and Kairi serve as momentum oscillators and are considered leading indicators. Momentum oscillators measure market prices' rate of change. As prices rise, momentum increases, and a decrease measures a decrease in momentum. Momentum is reflected both in the manner that RSI and Kairi operate and in their calculations.   Github: GitHub - Doustzadeh/cTrader-Indicator  
Tirone Levels
  2
  0
  678
free  15 Dec 2021
Tirone Levels are a series of horizontal lines that identify support and resistance levels. They were developed by John Tirone. Tirone Levels can be drawn using either the Midpoint 1/3-2/3 method or the Mean method. Both methods are intended to help you identify potential support and resistance levels based on the range of prices over a given time period. The interpretation of Tirone Levels is similar to Quadrant Lines. Midpoint Method:   Mean Method:   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  12 Dec 2021
VMA Bands are ATR bands with VMA as its center. For a description of options, refer to VMA: Variable Moving Average (VMA) Indicator   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  12 Dec 2021
A VMA is an EMA that is able to regulate its smoothing percentage based on market inconstancy automatically. Its sensitivity grows by providing more weight to the ongoing data as it generates a better signal indicator for short and long-term markets. The majority of ways for measuring Moving Averages cannot compensate for sideways moving prices versus trending markets and often generate a lot of false signals. Longer-term moving averages are slow to react to reversals in trend when prices move up and down over a long period of time. A Variable Moving Average regulates its sensitivity and lets it function better in any market conditions by using automatic regulation of the smoothing constant. The Variable Moving Average is also known as the VIDYA Indicator. But this version is a modified concept of the VIDYA. The Variable Moving Average was developed by Tushar S. Chande and first presented in his March, 1992 article in Technical Analysis of Stocks & Commodities magazine, in which a standard deviation was used as the Volatility Index. In his October, 1995 article in the same magazine, Chande modified the VIDYA to use his own Chande Momentum Oscillator (CMO) as the Volatility Index, the VMA code below is the result of this modification.   Github: GitHub - Doustzadeh/cTrader-Indicator  
Ulcer Index
  1
  0
  564
free  08 Dec 2021
Developed by Peter Martin and Byron McCann in 1987, the Ulcer Index is a volatility indicator that measures downside risk. It was first introduced in their 1989 book, The Investor's Guide to Fidelity Funds. Originally, the index was designed with mutual funds in mind, which is why it is only focused on downside risk. Mutual funds are designed to make money by increasing in value; the only risk, therefore, is the drawdown or downside. As its name implies, the Ulcer Index measures the drawdown investors can expect to stomach on any given security. Many consider the Ulcer Index superior to the standard deviation and other measures of risk.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  08 Dec 2021
Developed by Etienne Botes and Douglas Siepman, the Vortex Indicator consists of two oscillators that capture positive and negative trend movement. In creating this indicator, Botes and Seipman drew on the work of Welles Wilder and Viktor Schauberger, who is considered the father of implosion technology. Despite a rather involved formula, the indicator is quite easy to interpret. A bullish signal triggers when the positive trend indicator crosses above the negative trend indicator or a key level. A bearish signal triggers when the negative trend indicator crosses above the positive trend indicator or a key level. The Vortex Indicator is either above or below these levels, which means it always has a clear bullish or bearish bias.   Github: GitHub - Doustzadeh/cTrader-Indicator  
TTM Squeeze
  2
  0
  1010
free  07 Dec 2021
TTM Squeeze is a volatility and momentum indicator introduced by John Carter of Trade the Markets (now Simpler Trading), which capitalizes on the tendency for price to break out strongly after consolidating in a tight trading range. The volatility component of the TTM Squeeze indicator measures price compression using Bollinger Bands and Keltner Channels. If the Bollinger Bands are completely enclosed within the Keltner Channels, that indicates a period of very low volatility. This state is known as the squeeze. When the Bollinger Bands expand and move back outside of the Keltner Channel, the squeeze is said to have “fired”: volatility increases and prices are likely to break out of that tight trading range in one direction or the other. The on/off state of the squeeze is shown with small dots on the zero line of the indicator: red dots indicate the squeeze is on, and green dots indicate the squeeze is off. The TTM Squeeze indicator also uses a momentum oscillator to show the expected direction of the move when the squeeze fires. This histogram oscillates around the zero line; increasing momentum above the zero line indicates an opportunity to purchase long, while momentum falling below the zero line can indicate a shorting opportunity.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  07 Dec 2021
Developed by William Blau and introduced in Stocks & Commodities Magazine, the True Strength Index (TSI) is a momentum oscillator based on a double smoothing of price changes. Even though several steps are needed for calculation, the indicator is actually pretty straightforward. By smoothing price changes, TSI captures the ebbs and flows of price action with a steadier line that filters out the noise. As with most momentum oscillators, chartists can derive signals from overbought/oversold readings, centerline crossovers, bullish/bearish divergences and signal line crossovers. The True Strength Index (TSI) is an oscillator that fluctuates between positive and negative territory. As with many momentum oscillators, the centerline defines the overall bias. The bulls have the momentum edge when TSI is positive and the bears have the edge when it's negative. As with MACD, a signal line can be applied to identify upturns and downturns. Signal line crossovers are, however, quite frequent and require further filtering with other techniques. Chartists can also look for bullish and bearish divergences to anticipate trend reversals; however, keep in mind that divergences can be misleading in a strong trend. TSI is somewhat unique because it tracks the underlying price quite well. In other words, the oscillator can capture a sustained move in one direction or the other. The peaks and troughs in the oscillator often match the peaks and troughs in price. In this regard, chartists can draw trend lines and mark support/resistance levels using TSI. Line breaks can then be used to generate signals.   Github: GitHub - Doustzadeh/cTrader-Indicator  
StochRSI
  1
  0
  1547
free  07 Dec 2021
Developed by Tushar Chande and Stanley Kroll, StochRSI is an oscillator that measures the level of RSI relative to its high-low range over a set time period. StochRSI applies the Stochastics formula to RSI values, rather than price values, making it an indicator of an indicator. The result is an oscillator that fluctuates between 0 and 1. In their 1994 book, The New Technical Trader, Chande and Kroll explain that RSI can oscillate between 80 and 20 for extended periods without reaching extreme levels. Notice that 80 and 20 are used for overbought and oversold instead of the more traditional 70 and 30. Traders looking to enter a stock based on an overbought or oversold reading in RSI might find themselves continuously on the sidelines. Chande and Kroll developed StochRSI to increase sensitivity and generate more overbought/oversold signals. StochRSI measures the value of RSI relative to its high/low range over a set number of periods. The number of periods used to calculate StochRSI is transferred to RSI in the formula. For example, 14-day StochRSI would use the current value of 14-day RSI and the 14-day high-low range for 14-day RSI. 14-day StochRSI equals 0 when RSI is at its lowest point for 14 days. 14-day StochRSI equals 1 when RSI is at its highest point for 14 days. 14-day StochRSI equals 0.5 when RSI is in the middle of its 14-day high-low range. 14-day StochRSI equals 0.2 when RSI is near the low of its 14-day high-low range. 14-day StochRSI equals 0.80 when RSI is near the high of its 14-day high-low range.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  06 Dec 2021
Created by Martin Pring, Special K is a momentum indicator that combines short-, intermediate- and long-term velocity into one complete series, thereby giving us true summed cyclicality. It has two functions: first, to identify primary trend reversals at a relatively early stage; second, to use that information for timing short-term pro-trend price moves.   Github: GitHub - Doustzadeh/cTrader-Indicator  
Know Sure Thing (KST)
  0
  0
  831
free  06 Dec 2021
Developed by Martin Pring, Know Sure Thing (KST) is a momentum oscillator based on the smoothed rate-of-change for four different timeframes. Pring first described the indicator in the 1992 “Summed Rate of Change (KST)” in Stocks & Commodities magazine. In short, KST measures price momentum for four different price cycles, combining them into a single momentum oscillator. Like any other unbound momentum oscillator, chartists can use KST to look for divergences, signal line crossovers, and centerline crossovers. Pring frequently applied trend lines to KST. Although trend line signals do not occur often, Pring notes that such breaks reinforce signal line crossovers. Short-term Daily = KST(10,15,20,30,10,10,10,15,9) Medium-term Weekly = KST(10,13,15,20,10,13,15,20,9) Long-term Monthly = KST(9,12,18,24,6,6,6,9,9)   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  06 Dec 2021
The Percentage Volume Oscillator (PVO) is a momentum oscillator for volume. The PVO measures the difference between two volume-based moving averages as a percentage of the larger moving average. As with MACD and the Percentage Price Oscillator (PPO), it is shown with a signal line, a histogram and a centerline. The PVO is positive when the shorter volume EMA is above the longer volume EMA and negative when the shorter volume EMA is below. This indicator can be used to define the ups and downs for volume, which can then be used to confirm or refute other signals. Typically, a breakout or support break is validated when the PVO is rising or positive. Generally speaking, volume is above average when the PVO is positive and below average when the PVO is negative. A negative and rising PVO indicates that volume levels are increasing. A positive and falling PVO indicates that volume levels are decreasing. Chartists can use this information to confirm or refute movements on the price chart. Even though the PVO is based on a momentum oscillator formula, it is important to remember that moving averages lag.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  06 Dec 2021
The Percentage Price Oscillator (PPO) is a momentum oscillator that measures the difference between two moving averages as a percentage of the larger moving average. As with its cousin, MACD, the Percentage Price Oscillator is shown with a signal line, a histogram and a centerline. Signals are generated with signal line crossovers, centerline crossovers, and divergences. Because these signals are no different than those associated with MACD, this article will focus on a few differences between the two. First, PPO readings are not subject to the price level of the security. Second, PPO readings for different securities can be compared, even when there are large differences in the price. While MACD measures the absolute difference between two moving averages, PPO makes this a relative value by dividing the difference by the slower moving average (26-day EMA). PPO is simply the MACD value divided by the longer moving average. The result is multiplied by 100 to move the decimal place two spots. MACD levels are affected by the price of a security. A high-priced security will have higher or lower MACD values than a low-priced security, even if volatility is basically equal. This is because MACD is based on the absolute difference in the two moving averages.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  06 Dec 2021
Developed by Carl Swenlin, the DecisionPoint Price Momentum Oscillator (PMO) is an oscillator based on a Rate of Change (ROC) calculation that is smoothed twice with exponential moving averages that use a custom smoothing process. Because the PMO is normalized, it can also be used as a relative strength tool. Stocks can thus be ranked by their PMO value as an expression of relative strength. An indicator that looks very similar to the PMO is the MACD (Moving Average Convergence-Divergence) indicator invented by Gerald Appel. The main difference between the PMO and MACD is the absolute value of each indicator.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  04 Dec 2021
The Triple Exponential Moving Average (TEMA) reduces the lag of traditional EMAs, making it more responsive and better-suited for short-term trading. Shortly after developing the Double Exponential Moving Average (DEMA) in 1994, Patrick Mulloy took the concept a step further and created the Triple Exponential Moving Average (TEMA). Like its predecessor DEMA, the TEMA overlay uses the lag difference between different EMAs to adjust a traditional EMA. However, TEMA's formula uses a triple-smoothed EMA in addition to the single- and double-smoothed EMAs employed in the formula for DEMA. The offset created using these three EMAs produces a moving average that stays even closer to the price bars than DEMA.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  03 Dec 2021
The Double Exponential Moving Average (DEMA) reduces the lag of traditional EMAs, making it more responsive and better-suited for short-term traders. DEMA was developed by Patrick Mulloy, and introduced in the January 1994 issue of Technical Analysis of Stocks & Commodities magazine. The overlay uses the lag difference between a single-smoothed EMA and a double-smoothed EMA to offset the single-smoothed EMA. This offset produces a moving average that remains smooth, but stays closer to the price bars than either the single- or double-smoothed traditional EMA.   Github: GitHub - Doustzadeh/cTrader-Indicator  
free  02 Dec 2021
Developed by Marc Chaikin, the Accumulation Distribution Line is a volume-based indicator designed to measure the cumulative flow of money into and out of a security. Chaikin originally referred to the indicator as the Cumulative Money Flow Line. As with cumulative indicators, the Accumulation Distribution Line is a running total of each period's Money Flow Volume. First, a multiplier is calculated based on the relationship of the close to the high-low range. Second, the Money Flow Multiplier is multiplied by the period's volume to come up with a Money Flow Volume. A running total of the Money Flow Volume forms the Accumulation Distribution Line. Chartists can use this indicator to affirm a security's underlying trend or anticipate reversals when the indicator diverges from the security price.   Github: GitHub - Doustzadeh/cTrader-Indicator  
Squeeze Break
  3
  0
  3836
free  15 Nov 2021
Description: This indicator is based on a strategy mentioned in John Carter's book, Mastering the Trade. The basic idea behind the strategy is that markets tend to move from periods of low volatility to high volatility and vice versa. The strategy aims to capture moves from low to high volatility. For gauging this he uses two common indicators - Bollinger Bands and Keltner Channels. He also uses the Momentum indicator to provide a trade bias as some as the Bollinger Bands come back outside the Keltner Channels. The Squeeze Break indicator combines this into a signal indicator and has the following components: A positive Green histogram means that the Bollinger Bands are outside the Keltner Channels and the market is lightly to be trending or volatile. The stronger the histogram the stronger the directional price move. A negative Red histogram means that the Bollinger Bands are inside the Keltner Channels and the market is lightly to be consolidating. The stronger the red histogram the tighter price action is becoming. Incorporated into the indicator is a Momentum indicator. According to the strategy J. Carter goes long when the Bollinger Bands break outside the Keltner Bands and the Momentum indicator is above the zero line. He goes short when the Momentum indicator is below the zero line. This indicator tends to be better with the larger timeframes. This indicator based on MetaTrader 4 and it has been rewrote for cTrader. Screenshots:   Github: GitHub - Doustzadeh/cTrader-Indicator  
Bollinger Bands %B
  0
  5
  4151
free  15 Nov 2021
Introduction: %B quantifies a security's price relative to the upper and lower Bollinger Band. There are six basic relationship levels: %B equals 1 when price is at the upper band %B equals 0 when price is at the lower band %B is above 1 when price is above the upper band %B is below 0 when price is below the lower band %B is above .50 when price is above the middle band (20-day SMA) %B is below .50 when price is below the middle band (20-day SMA)   Signals: Overbought/Oversold %B can be used to identify overbought and oversold situations. However, it is important to know when to look for overbought readings and when to look for oversold readings. As with most momentum oscillators, it is best to look for short-term oversold situations when the medium-term trend is up and short-term overbought situations when the medium-term trend is down. In other words, look for opportunities in the direction of the bigger trend, such as a pullback within a bigger uptrend. Define the bigger trend before looking for overbought or oversold readings.   Screenshots:   Github: GitHub - Doustzadeh/cTrader-Indicator
TCCI
  2
  0
  5035
free  15 Nov 2021
Description: This indicator based on MetaTrader 4 and it has been rewrote for cTrader.   BUY: When TCCI line change to Blue (must wait for the second candle closed) SELL: When TCCI line change to Red (must wait for the second candle closed) CUT LOSS: When TCCI line change again to the previous color. (must wait for the second candle closed) CUT PROFIT: When TCCI line change again to the previous color, too. (must wait for the second candle closed)   Screenshots:
Waddah Attar Explosion
  6
  0
  4213
free  15 Nov 2021
Description: Waddah Attar Explosion is a indicator and the essence of the forex indicator is to transform the accumulated history data. Waddah Attar Explosion provides for an opportunity to detect various peculiarities and patterns in price dynamics which are invisible to the naked eye. Based on this information, traders can assume further price movement and adjust their strategy accordingly. This indicator based on MetaTrader 4 and it has been rewrote for cTrader.   Screenshots:   Github: GitHub - Doustzadeh/cTrader-Indicator
Snake Force
  1
  0
  3982
free  15 Nov 2021
Description: Snake Force is great indicator for determine Support and Resistance. This indicator based on MetaTrader 4 and it has been rewrote for cTrader.   Note: This is my first indicator. This indicator reprints itself.   Screenshots:
DSS Bressert
  2
  0
  3621
free  15 Nov 2021
DSS Bressert - Double Smoothed Stochastic Indicator by Walter Bressert Its calculation algorithm is very similar to that of stochastic indicator. The value above 80 signifies the overbuying, the value below 20 signifies the overselling.   Description: One after the other, William Blau and Walter Bressert each presented a version of the Double Smoothed Stochastics. Two exponentially smoothed MAs are used to even out the input values (H, L and C), in a similar way to the well-known stochastic formula.   Calculation: Calculation of the DSS indicator according to Bressert is similar to stochastics. 1.) The numerator: first the difference between the current close and the period low is formed. The denominator: here the difference between the period high minus the period low is calculated. Now the quotient of numerator and denominator is calculated, exponentially smoothed and then multiplied by 100. 2.) The method is analogous to 1.) with the distinction that now the prices of the newly calculated price series of 1.) is used.                     Parameters: The adjustable period length can be chosen from 2 to 500. The most common settings will have a period length ranging from 5 to 30. In addition, the indicator can be smoothed in the interval from 1 to 50. Meaningful smoothing values lie in the short-term range. Interpretation: The application of the DSS is comparable with that of the stochastic method. Accordingly, values above 70 or 80 must be regarded as overbought and values below 20 or 30 as oversold. A rise of the DSS above its center line should be viewed as bullish, and a fall of the DSS below its center line as bearish.   Github: GitHub - Doustzadeh/cTrader-Indicator  
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