Notification Publishing copyrighted material is strictly prohibited. If you believe there is copyrighted material in this section you may use the Copyright Infringement Notification form to submit a claim.How to install
How to install cBots & Indicators
- Download the Indicator or cBot.
- Double-click on the downloaded file. This will install all necessary files in cAlgo.
- Find the indicator/cbot you want to use from the menu on the left.
- Add an instance of the indicator/cBot to run.
- Download the Indicator
- Double-click on the downloaded file. This will install all necessary files in cTrader.
Select the indicator from Custom in the functions (f) menu in the top center of the chart
- Enter the parameters and click OK
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
free 13 Feb 2022
Simple indicator that detects if two candles lows or highs are equal and draws a trend line. Theory being that large funds are using limit orders to buy / sell at a specific price then the IPDA algo will return to this price to clear the book. Setting to allow for brokers spread manipulation and lookback setting to increase candles considered for equal lows / highs. Best TF is 1min
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 07 Dec 2021
This indicator helps you visualize the historical avg daily movement of each day. Please note that the daily bars of cTrader start at 21:00 GMT + 0 Therefore the bars displayed are for Sunday, Monday, Tuesday, Wednesday, and Thursday https://algocorner.gumroad.com/l/YEZveg For bugs, feedback or suggestions, please send an email to firstname.lastname@example.org
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 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
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
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
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
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
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
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
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