Adaptive RSI/Stochastic (ARSIS)As a trader, one of the most important aspects of technical analysis is identifying the dominant cycle of the market. The dominant cycle, also known as the market's "heartbeat," can provide valuable information on the current market trend and potential future price movements. One way to measure the dominant cycle is through the use of the MESA Adaptation - MAMA Cycle function, which is a part of the Dominant Cycle Estimators library.
I have developed an "Adaptive RSI/Stochastic" indicator that incorporates the MAMA Cycle function to provide more accurate and reliable signals. The indicator uses the MAMA Cycle function to calculate the period of the data, which is then used as a parameter in the calculation of the RSI and Stochastic indicators. By adapting the calculation of these indicators to the dominant cycle of the market, the resulting signals are more in tune with the current market conditions and can provide a more accurate representation of the current trend.
The MAMA Cycle function is a powerful tool that utilizes advanced mathematical techniques to accurately calculate the dominant cycle of the market. It takes into account the dynamic nature of the market and adapts the calculation of the period to the current conditions. The result is a more accurate and reliable measurement of the market's dominant cycle, which can be used to improve the performance of other indicators and trading strategies.
In conclusion, the Adaptive RSI/Stochastic indicator that I have developed, which incorporates the MAMA Cycle function, is a valuable tool for any trader looking to improve their technical analysis. By adapting the calculation of the RSI and Stochastic indicators to the dominant cycle of the market, the resulting signals are more in tune with the current market conditions and can provide a more accurate representation of the current trend.
Huge thank you to @lastguru for making this possible!
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Key Points of Adjoining Median (KPAM)This indicator shows more reliable overbought & oversold levels buy combing 3 different level-indicators (i.e., indicators showing overbought/oversold levels).
A median is created by adjoining two of them and then it is assisted by a third one.
This reduces noise in calculating entries when using level indicators.
Note: The extra indicator shown is "Bands Bands (BanB)"
----- HOW TO USE IT -----
Use with price-action trading and with indicators showing the overall trend.
See notes in chart for more explanation.
The high and low levels of the RSI are within a range of 2 & -2 respectively.
The high and low levels for the median range from 4 & -4 respectively.
The Discordance shows how certain the level of the median is.
For example, if a part of the Discordance touches a low level while the median is at a higher level, then it usually indicates that the median is about to reverse.
The more Discordance that is visible, the less certain the current trend of the median is.
----- HOW THIS INDICATOR IS ORIGINAL; WHAT IT DOES AND HOW IT DOES IT -----
This indicator has an original, unique ability to reduce noise when comparing overbought and oversold levels.
It does this by first adjoining the Stochastic and the Stochastic RSI. Second, it creates a median from the two.
Third, the median is compared to the RSI on the same scale to assist in deciding where the median is at in relation to itself.
It shows whether the median lows and highs are near overbought or oversold levels.
----- VERSION -----
This is not a variant of the Stochastic, Stochastic RSI, and/or the RSI.
The focus is on the median that is created by an adjoining of the Stochastic and Stochastic RSI.
The Stochastic and Stochastic RSI are needed in order to obtain and plot the Median and the Discordance.
The RSI is plotted on the same scale to serve as the comparison needed to evaluate the Median levels with more visual accuracy.
Strategy Myth-Busting #6 - PSAR+MA+SQZMOM+HVI - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our sixth one we are automating is " I Tested ''7% Profit Per Day" Scalping Strategy 100 Times ( Unexpected Results ) " from " TradeIQ " which claims to have made 175% profit on the 5 min chart of BTCUSD with a having a 61% win rate in just 32 days.
Originally, we mimicked verbatim the indicators and settings TradeIQ was using however weren't getting promising results anything close to the claim so we decided to try and improve on it. We changed the static Parabolic SAR to be adaptive based upon the timeframe. We did this by using an adjustable multiplier for the PSAR Max. Also, In TradeIQ's revised version he substituted Hawkeye's Volume Indicator in lieu of Squeeze Momentum. We found that including both indicators we were getting better results so included them both. Feel free to experiment more. Would love to see how this could be improved on.
This strategy uses a combination of 4 open-source public indicators:
Parabolic Sar (built in)
10 in 1 MA's by hiimannshu
Squeeze Momentum by lazybear
HawkEYE Volume Indicator by lazybear
Trading Rules
5m timeframe and above. We saw equally good results in the higher (3h - 4h) timeframes as well.
Long Entry:
Parabolic Sar shifts below price at last dot above and then previous bar needs to breach above that.
Price action has to be below both MA's and 50MA needs to be above 200MA
Squeeze Momentum needsd to be in green or close to going green
HawkEYE Volume Indicator needs to be show a green bar on the histagram
Short Entry:
Parabolic Sar shifts above price at last dot below and then previous bar needs to breach below that.
Price action needs to be above both MA's and 50MA needs to be below 200MA
Squeeze Momentum needsd to be in red or close to going red
HawkEYE Volume Indicator needs to be show a red bar on the histagram
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
Koncorde PlusKONCORDE IS ONLY INTENDED TO BE APPLIED TO ASSETS WHERE VOLUME DATA IS PROVIDED.
This indicator is made up of 6 indicators: 4 trend (RSI, MFI, BB, Stochastic) and 2 volume. The 2's for volume are the PVI (positive volume index) and the NVI (negative volume index). These two indicators are the interesting ones as they are programmed to proportionally attribute the volume traded between the strong hands (sharks) and the weak hands (minnows).
As for what time period to use, the bigger the better, since after all what we are doing is data analysis and therefore the more data, the better.
When strong hands (blue histogram) are below zero, they are said to be selling while when they are above zero, they are said to be buying. The same goes for weak hands (green histogram).
Meaning of each zone:
Blue histogram: strong hand (sharks). If it is positive it indicates accumulation and if it is negative distribution.
Green histogram: weak hand (minnows). If it is positive it indicates buy and if it is negative it indicates sale.
Brown histogram: Indicates the trend and depends on previous values of weak hands and trend indicators (RSI, MFI, BB, Stochastic).
Red line: It is an average that smoothes the trend indicated by the brown histogram (default is the EMA).
Crossing Pattern
The pattern gives us a bullish entry signal when the trend (brown histogram) crosses above the average (red line) and is positioned bearish when the trend crosses below the average.
Zero Pattern
When the price trend (brown histogram) tends to zero, it means that there will be a change in its trend. This pattern is for trading in a bullish position.
Spring Pattern
When a cross between the average (red line) and the trend (brown histogram) has already occurred, and in addition the weak hands are above the price trend, that "spring on the mountain" is formed that gives us to understand that the upward trend will be more than evident.
Mirror Pattern
This pattern occurs when there is panic in the market and weak hands are selling (below zero). If at that moment the strong hands are buyers, the price tends to level off to begin the rise later.
This pattern is compatible with the Crossover Pattern, having more guarantees of success. If just after finishing the mirror pattern, the Crossover Pattern plus the Spring Pattern appears, then we have a good chance of winning.
Bear Hug Pattern
This pattern is for bearish positions only. It is the opposite figure to the mirror pattern. That is, we have strong hands clearly selling and weak hands clearly buying and above the price trend (brown histogram). It is the figure where you can see that the strong hands are distributing the assets to the weak hands.
Harpoon Pattern
If when the mirror pattern occurs, the red line crosses the blue histogram, a very strong bullish entry signal is produced.
Add an exit signal which occurs when we are in a spring pattern but the big hands start selling, mostly coinciding with the start of the bear hug pattern.
General rules for operating the Mirror Pattern:
a) Wait for the green histogram to start recovery, rise to positive values; if possible, until it crosses from bottom to top the brown line (brown histogram) and/or red average .
b) The blue histogram should be consistently positive. If it turns and goes towards negative values it can indicate a failed pattern at that same point.
c) Locate the low of the lower candle within the pattern and place the Stop Loss just below it for reference.
d) If we are not sure (we almost never will be) that there will be a turn or if it could finally be a bearish continuation we can use the SL to go short .
Additional:
A panel with performance statistics of the analyzed asset was added.
Added an indicator that shows the cumulative delta volume in the form of triangles at the top of the chart.
Added of user @DonovanWall
PS: Unofficial version, I was guided by the description of the BLAI5 author's website www.blai5.net
DISCLAIMER: For educational and entertainment purposes only. Nothing in this content should be interpreted as financial advice or a recommendation to buy or sell any sort of security or investment including all types of cryptos. DYOR, TYOB.
Kase Peak Oscillator w/ Divergences [Loxx]Kase Peak Oscillator is unique among first derivative or "rate-of-change" indicators in that it statistically evaluates over fifty trend lengths and automatically adapts to both cycle length and volatility. In addition, it replaces the crude linear mathematics of old with logarithmic and exponential models that better reflect the true nature of the market. Kase Peak Oscillator is unique in that it can be applied across multiple time frames and different commodities.
As a hybrid indicator, the Peak Oscillator also generates a trend signal via the crossing of the histogram through the zero line. In addition, the red/green histogram line indicates when the oscillator has reached an extreme condition. When the oscillator reaches this peak and then turns, it means that most of the time the market will turn either at the present extreme, or (more likely) at the following extreme.
This is both a reversal and breakout/breakdown indicator. Crosses above/below zero line can be used for breakouts/breakdowns, while the thick green/red bars can be used to detect reversals
The indicator consists of three indicators:
The PeakOscillator itself is rendered as a gray histogram.
Max is a red/green solid line within the histogram signifying a market extreme.
Yellow line is max peak value of two (by default, you can change this with the deviations input settings) standard deviations of the Peak Oscillator value
White line is the min peak value of two (by default, you can change this with the deviations input settings) standard deviations of the PeakOscillator value
The PeakOscillator is used two ways:
Divergence: Kase Peak Oscillator may be used to generate traditional divergence signals. The difference between it and traditional divergence indicators lies in its accuracy.
PeakOut: The second use is to look for a Peak Out. A Peak Out occurs when the histogram breaks beyond the PeakOut line and then pulls back. A Peak Out through the maximum line will be displayed magenta. A Peak Out, which only extends through the Peak Min line is called a local Peak Out, and is less significant than a normal Peak Out signal. These local Peak Outs are to be relied upon more heavily during sideways or corrective markets. Peak Outs may be based on either the maximum line or the minimum line. Maximum Peak Outs, however, are rarer and thus more significant than minimum Peak Outs. The magnitude of the price move may be greater following the maximum Peak Out, but the likelihood of the break in trend is essentially the same. Thus, our research indicates that we should react equally to a Peak Out in a trendy market and a Peak Min in a choppy or corrective market.
Included:
Bar coloring
Alerts
Strategy Myth-Busting #3 - BB_BUY+SuperTrend - [MYN]This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our third one we are automating is one of the strategies from "The Best 3 Buy And Sell Indicators on Tradingview + Confirmation Indicators ( The Golden Ones ))" from "Online Trading Signals (Scalping Channel)". No formal backtesting was done by them so wanted to validate their claims.
If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 2 open-source public indicators:
BB_Buy and Sell by guikroth (default settings)
SuperTrend from TradingView's Technicals (default settings)
Trading Rules
15 min candles
Long
Long condition when BB_BUY indicates buy signal and SuperTrend is green
Short
Short condition when BB_BUY indicates Sell signal and SuperTrend is red
TriexDev - SuperBuySellTrend (PLUS+)Minimal but powerful.
Have been using this for myself, so thought it would be nice to share publicly. Of course no script is correct 100% of the time, but this is one of if not the best in my basic tools. (This is the expanded/PLUS version)
Github Link for latest/most detailed + tidier documentation
Base Indicator - Script Link
TriexDev - SuperBuySellTrend (SBST+) TradingView Trend Indicator
---
SBST Plus+
Using the "plus" version is optional, if you only want the buy/sell signals - use the "base" version.
## What are vector candles?
Vector Candles (inspired to add from TradersReality/MT4) are candles that are colour coded to indicate higher volumes, and likely flip points / direction changes, or confirmations.
These are based off of PVSRA (Price, Volume, Support, Resistance Analysis).
You can also override the currency that this runs off of, including multiple ones - however adding more may slow things down.
PVSRA - From MT4 source:
Situation "Climax"
Bars with volume >= 200% of the average volume of the 10 previous chart TFs, and bars
where the product of candle spread x candle volume is >= the highest for the 10 previous
chart time TFs.
Default Colours: Bull bars are green and bear bars are red.
Situation "Volume Rising Above Average"
Bars with volume >= 150% of the average volume of the 10 previous chart TFs.
Default Colours: Bull bars are blue and bear are blue-violet.
A blue or purple bar can mean the chart has reached a top or bottom.
High volume bars during a movement can indicate a big movement is coming - or a top/bottom if bulls/bears are unable to break that point - or the volume direction has flipped.
This can also just be a healthy short term movement in the opposite direction - but at times sets obvious trend shifts.
## Volume Tracking
You can shift-click any candle to get the volume of that candle (in the pair token/stock), if you click and drag - you will see the volume for that range.
## Bollinger Bands
Bollinger Bands can be enabled in the settings via the toggle.
Bollinger Bands are designed to discover opportunities that give investors a higher probability of properly identifying when an asset is oversold (bottom lines) or overbought (top lines).
>There are three lines that compose Bollinger Bands: A simple moving average (middle band) and an upper and lower band.
>The upper and lower bands are typically 2 standard deviations +/- from a 20-day simple moving average, but they can be modified.
---
Base Indicator
## What is ATR?
The average true range (ATR) is a technical analysis indicator, which measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following:
- current high - the current low;
- the absolute value of the current high - the previous close;
- and the absolute value of the current low - the previous close.
The ATR is then a moving average, generally using 10/14 days, of the true ranges.
## What does this indicator do?
Uses the ATR and multipliers to help you predict price volatility, ranges and trend direction.
> The buy and sell signals are generated when the indicator starts
plotting either on top of the closing price or below the closing price. A buy signal is generated when the ‘Supertrend’ closes above the price and a sell signal is generated when it closes below the closing price.
> It also suggests that the trend is shifting from descending mode to ascending mode. Contrary to this, when a ‘Supertrend’ closes above the price, it generates a sell signal as the colour of the indicator changes into red.
> A ‘Supertrend’ indicator can be used on equities, futures or forex, or even crypto markets and also on daily, weekly and hourly charts as well, but generally, it will be less effective in a sideways-moving market.
Thanks to KivancOzbilgic who made the original SuperTrend Indicator this was based off
---
## Usage Notes
Two indicators will appear, the default ATR multipliers are already set for what I believe to be perfect for this particular (double indicator) strategy.
If you want to break it yourself (I couldn't find anything that tested more accurately myself), you can do so in the settings once you have added the indicator.
Basic rundown:
- A single Buy/Sell indicator in the dim colour; may be setting a direction change, or just healthy movement.
- When the brighter Buy/Sell indicator appears; it often means that a change in direction (uptrend or downtrend) is confirmed.
---
You can see here, there was a (brighter) green indicator which flipped down then up into a (brighter) red sell indicator which set the downtrend. At the end it looks like it may be starting to break the downtrend - as the price is hitting the trend line. (Would watch for whether it holds above or drops below at that point)
Another example, showing how sometimes it can still be correct but take some time to play out - with some arrow indicators.
Typically I would also look at oscillators, RSI and other things to confirm - but here it held above the trend lines nicely, so it appeared to be rather obvious.
It's worth paying attention to the trend lines and where the candles are sitting.
Once you understand/get a feel for the basics of how it works - it can become a very useful tool in your trading arsenal.
Also works for traditional markets & commodities etc in the same way / using the same ATR multipliers, however of course crypto generally has bigger moves.
---
You can use this and other indicators to confirm likeliness of a direction change prior to the brighter/confirmation one appearing - but just going by the 2nd(brighter) indicators, I have found it to be surprisingly accurate.
Tends to work well on virtually all timeframes, but personally prefer to use it on 5min,15min,1hr, 4hr, daily, weekly. Will still work for shorter/other timeframes, but may be more accurate on mid ones.
---
This will likely be updated as I go / find useful additions that don't convolute things. The base indicator may be updated with some limited / toggle-able features in future also.
Digital Kahler Stochastic [Loxx]Digital Kahler Stochastic is a Digital Kahler filtered Stochastic. This modification significantly reduces noise.
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI .
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
Calculation
The calculation is simple
Step1: create the CCI
Step 2: Use CCI as Fast MA and smoothed CCI as Slow MA
Step 3: Multiple the Slow and Fast MAs by their respective input ratios, and then divide by their sum. if the result is greater than 0, then the result is 1, if it's less than 0 then the result is -1, then chart the data
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) > 50.0)
temp := 1
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) < 50.0)
temp := -1
Step 4: Profit
Other implementations of Digital Kahler
This is to better understand the process the DK process and it's result, and furthermore, I'm linking these because for many in the Forex community, they see DK filtered indicators as the best implementations of standard indicators.
Digital Kahler MACD
VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones
Digital Kahler CCI
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
Digital Kahler CCI [Loxx]Digital Kahler CCI is a Digital Kahler filtered CCI. This modification significantly reduces noise.
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI .
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
Calculation
The calculation is simple
Step1 : create the CCI
Step 2 : Use CCI as Fast MA and smoothed CCI as Slow MA
Step 3 : Multiple the Slow and Fast MAs by their respective input ratios, and then divide by their sum. if the result is greater than 0, then the result is 1, if it's less than 0 then the result is -1, then chart the data
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) > 50.0)
temp := 1
if ((slowr * slow_k + fastr * fast_k) / (fastr + slowr) < 50.0)
temp := -1
Step 4 : Profit
Other implementations of Digital Kahler
This is to better understand the process the DK process and it's result, and furthermore, I'm linking these because for many in the Forex community, they see DK filtered indicators as the best implementations of standard indicators.
MACD
VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones
Included:
Bar coloring
Signals
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones [Loxx]VHF-Adaptive, Digital Kahler Variety RSI w/ Dynamic Zones is an RSI indicator with adaptive inputs, Digital Kahler filtering, and Dynamic Zones. This indicator uses a Vertical Horizontal Filter for calculating the adaptive period inputs and allows the user to select from 7 different types of RSI.
What is VHF Adaptive Cycle?
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
What is Digital Kahler?
From Philipp Kahler's article for www.traders-mag.com, August 2008. "A Classic Indicator in a New Suit: Digital Stochastic"
Digital Indicators
Whenever you study the development of trading systems in particular, you will be struck in an extremely unpleasant way by the seemingly unmotivated indentations and changes in direction of each indicator. An experienced trader can recognise many false signals of the indicator on the basis of his solid background; a stupid trading system usually falls into any trap offered by the unclear indicator course. This is what motivated me to improve even further this and other indicators with the help of a relatively simple procedure. The goal of this development is to be able to use this indicator in a trading system with as few additional conditions as possible. Discretionary traders will likewise be happy about this clear course, which is not nerve-racking and makes concentrating on the essential elements of trading possible.
How Is It Done?
The digital stochastic is a child of the original indicator. We owe a debt of gratitude to George Lane for his idea to design an indicator which describes the position of the current price within the high-low range of the historical price movement. My contribution to this indicator is the changed pattern which improves the quality of the signal without generating too long delays in giving signals. The trick used to generate this “digital” behavior of the indicator. It can be used with most oscillators like RSI or CCI .
First of all, the original is looked at. The indicator always moves between 0 and 100. The precise position of the indicator or its course relative to the trigger line are of no interest to me, I would just like to know whether the indicator is quoted below or above the value 50. This is tantamount to the question of whether the market is just trading above or below the middle of the high-low range of the past few days. If the market trades in the upper half of its high-low range, then the digital stochastic is given the value 1; if the original stochastic is below 50, then the value –1 is given. This leads to a sequence of 1/-1 values – the digital core of the new indicator. These values are subsequently smoothed by means of a short exponential moving average . This way minor false signals are eliminated and the indicator is given its typical form.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included:
Bar coloring
4 signal types
Alerts
Loxx's Expanded Source Types
Loxx's Moving Averages
Loxx's Variety RSI
Loxx's Dynamic Zones
Moving Average Filters Add-on w/ Expanded Source Types [Loxx]Moving Average Filters Add-on w/ Expanded Source Types is a conglomeration of specialized and traditional moving averages that will be used in most of indicators that I publish moving forward. There are 39 moving averages included in this indicator as well as expanded source types including traditional Heiken Ashi and Better Heiken Ashi candles. You can read about the expanded source types clicking here . About half of these moving averages are closed source on other trading platforms. This indicator serves as a reference point for future public/private, open/closed source indicators that I publish to TradingView. Information about these moving averages was gleaned from various forex and trading forums and platforms as well as TASC publications and other assorted research publications.
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Included moving averages
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA, it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA.
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average (DEMA) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA. It's also considered a leading indicator compared to the EMA, and is best utilized whenever smoothness and speed of reaction to market changes are required.
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA (Simple Moving Average). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA.
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Hull Moving Average - HMA
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points.
IE/2 - Early T3 by Tim Tilson
The IE/2 is a Moving Average that uses Linear Regression slope in its calculation to help with smoothing. It's a worthy Moving Average on it's own, even though it is the precursor and very early version of the famous "T3 Indicator".
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA (Simple Moving Average) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and it's smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA (Least Squares Moving Average)
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA. Although it's similar to the Simple Moving Average, the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track price better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average. The Linear Weighted Moving Average calculates the average by assigning different weight to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrows price.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA.
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average (SMA), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen a an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA (Smoothed Moving Average). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a a Two pole Butterworth filter combined with a 2-bar SMA (Simple Moving Average) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA. They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
The TMA and Sine Weighted Moving Average Filter are almost identical at times.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, it's signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers.
Volume Weighted EMA - VEMA
Utilizing tick volume in MT4 (or real volume in MT5), this EMA will use the Volume reading in its decision to plot its moves. The more Volume it detects on a move, the more authority (confirmation) it has. And this EMA uses those Volume readings to plot its movements.
Studies show that tick volume and real volume have a very strong correlation, so using this filter in MT4 or MT5 produces very similar results and readings.
Zero Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers, as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA, this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
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What are Heiken Ashi "better" candles?
The "better formula" was proposed in an article/memo by BNP-Paribas (In Warrants & Zertifikate, No. 8, August 2004 (a monthly German magazine published by BNP Paribas, Frankfurt), there is an article by Sebastian Schmidt about further development (smoothing) of Heikin-Ashi chart.)
They proposed to use the following:
(Open+Close)/2+(((Close-Open)/( High-Low ))*ABS((Close-Open)/2))
instead of using :
haClose = (O+H+L+C)/4
According to that document the HA representation using their proposed formula is better than the traditional formula.
What are traditional Heiken-Ashi candles?
The Heikin-Ashi technique averages price data to create a Japanese candlestick chart that filters out market noise.
Heikin-Ashi charts, developed by Munehisa Homma in the 1700s, share some characteristics with standard candlestick charts but differ based on the values used to create each candle. Instead of using the open, high, low, and close like standard candlestick charts, the Heikin-Ashi technique uses a modified formula based on two-period averages. This gives the chart a smoother appearance, making it easier to spots trends and reversals, but also obscures gaps and some price data.
Expanded generic source types:
Close = close
Open = open
High = high
Low = low
Median = hl2
Typical = hlc3
Weighted = hlcc4
Average = ohlc4
Average Median Body = (open+close)/2
Trend Biased = (see code, too complex to explain here)
Trend Biased (extreme) = (see code, too complex to explain here)
Included:
-Toggle bar color on/off
-Toggle signal line on/off
Jurik CFB Adaptive, Elder Force Index w/ ATR Channels [Loxx]Jurik CFB Adaptive, Elder Force Index w/ ATR Channels is a variation of Elder Force Index that better adapts to trends by calculating dynamic lengths for the traditional Elder Force Index calculation. ATR channels are added to show levels of price extremes or exhaustion of price either up or down. Elder Force Index is typically used for spotting reversals on the weekly timeframe.
What is the Elder Force Index?
Dr. Alexander Elder is one of the contributors to a newer generation of technical indicators. His force index is an oscillator that measures the force, or power, of bulls behind particular market rallies and of bears behind every decline.1
The three key components of the force index are the direction of price change, the extent of the price change, and the trading volume. When the force index is used in conjunction with a moving average, the resulting figure can accurately measure significant changes in the power of bulls and bears.1 In this way, Elder has taken an extremely useful solitary indicator, the moving average, and combined it with his force index for even greater predictive success.
What is Composite Fractal Behavior ( CFB )?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
Adaptive Qualitative Quantitative Estimation (QQE) [Loxx]Adaptive QQE is a fixed and cycle adaptive version of the popular Qualitative Quantitative Estimation (QQE) used by forex traders. This indicator includes varoius types of RSI caculations and adaptive cycle measurements to find tune your signal.
Qualitative Quantitative Estimation (QQE):
The Qualitative Quantitative Estimation (QQE) indicator works like a smoother version of the popular Relative Strength Index (RSI) indicator. QQE expands on RSI by adding two volatility based trailing stop lines. These trailing stop lines are composed of a fast and a slow moving Average True Range (ATR).
There are many indicators for many purposes. Some of them are complex and some are comparatively easy to handle. The QQE indicator is a really useful analytical tool and one of the most accurate indicators. It offers numerous strategies for using the buy and sell signals. Essentially, it can help detect trend reversal and enter the trade at the most optimal positions.
Wilders' RSI:
The Relative Strength Index ( RSI ) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements. Essentially RSI , when graphed, provides a visual mean to monitor both the current, as well as historical, strength and weakness of a particular market. The strength or weakness is based on closing prices over the duration of a specified trading period creating a reliable metric of price and momentum changes. Given the popularity of cash settled instruments (stock indexes) and leveraged financial products (the entire field of derivatives); RSI has proven to be a viable indicator of price movements.
RSX RSI:
RSI is a very popular technical indicator, because it takes into consideration market speed, direction and trend uniformity. However, the its widely criticized drawback is its noisy (jittery) appearance. The Jurk RSX retains all the useful features of RSI , but with one important exception: the noise is gone with no added lag.
Rapid RSI:
Rapid RSI Indicator, from Ian Copsey's article in the October 2006 issue of Stocks & Commodities magazine.
RapidRSI resembles Wilder's RSI , but uses a SMA instead of a WilderMA for internal smoothing of price change accumulators.
VHF Adaptive Cycle:
Vertical Horizontal Filter (VHF) was created by Adam White to identify trending and ranging markets. VHF measures the level of trend activity, similar to ADX DI. Vertical Horizontal Filter does not, itself, generate trading signals, but determines whether signals are taken from trend or momentum indicators. Using this trend information, one is then able to derive an average cycle length.
Band-pass Adaptive Cycle:
Even the most casual chart reader will be able to spot times when the market is cycling and other times when longer-term trends are in play. Cycling markets are ideal for swing trading however attempting to “trade the swing” in a trending market can be a recipe for disaster. Similarly, applying trend trading techniques during a cycling market can equally wreak havoc in your account. Cycle or trend modes can readily be identified in hindsight. But it would be useful to have an objective scientific approach to guide you as to the current market mode.
There are a number of tools already available to differentiate between cycle and trend modes. For example, measuring the trend slope over the cycle period to the amplitude of the cyclic swing is one possibility.
We begin by thinking of cycle mode in terms of frequency or its inverse, periodicity. Since the markets are fractal ; daily, weekly, and intraday charts are pretty much indistinguishable when time scales are removed. Thus it is useful to think of the cycle period in terms of its bar count. For example, a 20 bar cycle using daily data corresponds to a cycle period of approximately one month.
When viewed as a waveform, slow-varying price trends constitute the waveform's low frequency components and day-to-day fluctuations (noise) constitute the high frequency components. The objective in cycle mode is to filter out the unwanted components--both low frequency trends and the high frequency noise--and retain only the range of frequencies over the desired swing period. A filter for doing this is called a bandpass filter and the range of frequencies passed is the filter's bandwidth.
Included:
-Toggle on/off bar coloring
-Customize RSI signal using fixed, VHF Adaptive, and Band-pass Adaptive calculations
-Choose from three different RSI types
Visuals:
-Red/Green line is the moving average of RSI
-Thin white line is the fast trend
-Dotted yellow line is the slow trend
Happy trading!
Template Signal IndicatorThis script is an example on how to create a custom indicator that produce start/end long/short deal signals based on configurable conditions from internal and external indicators.
This indicator can be used as an external indicator to other strategies like "Template Trailing Strategy" that will execute the deals and enter the desired positions based on the signals produced by this script.
Combining this script with the aforementioned strategy (or any other compatible) has the advantage that you can backrest the results of your custom deal conditions. Also additional functionality that is provided by the strategy can be utilized (e.g. Take Profit Targets, Trailing Stop Loss etc.).
In this particular example I combined the RSI and Stoch RSI indicators (internal) with the "Trend Explorer" indicator (external) so it produces buy and sell signals based on the logic I defined in the input tab of this indicator. To combine "indicators on indicators" you need Pro+ TV subscription.
The convention I use to communicate the signals is the following (2 -> enter long, 1 -> exit long, -2 -> enter short, -1 ->exit short). However, this convention is also configurable in the consumer/strategy script "Template Trailing Strategy" so make sure that both script "speak the same language" before procced.
Wick Pressure by SiddWolfMultiple Wicks forming at OverSold & OverBought levels create Buying and Selling Pressure. This Script tries to capture the essence of the buy and sell pressure created by those wicks. Wick pressure shows that the trend is Exhausted.
How it works:
This Wick Pressure Indicator checks for three candles forming the wicks in overbought and oversold zones. The zones are set by RSI and can be changed in settings. Those three candles should form a bit long wick and length of the wick is determined by ATR. The ATR multiple can be changed from settings. And then the script draws a box in the area formed by three candle wicks.
Confluence:
This indicator should not be used on its own. You should include it in your existing trading strategy. Any indicator should be rigorously tested before making any real trades.
Settings is the Key:
Settings are key to all of my indicators. Play around with it a bit. Change the ATR multiplier. Read the tooltips to understand what each settings mean. Tooltips are the (i) button in-front of each settings.
FAQs:
Q. Does the indicator Repaint ?
--- No. None of my indicators repaints. What you see now is what's drawn in real time.
Q. Indicator doesn't show anything ?
--- Maybe you've messed up the settings so reset it. or try different coin/stock.
Q. Does this indicator give financial advice?
--- No. Nope. Nein. Não. नहीं.
Conclusion:
This indicator is very basic but if used correctly it can be very powerful. Hit me up if you'd like to see the screener/scanner for this or any of my indicators. If you have any questions or suggestions feel free to comment below. I'd love to connect with you. Thank you.
~ SiddWolf
The Namib FlowThis is an alert/notification system consisting of the building on the following existing indicators:
Hull Suite by InSilico
Follow Line Indicator by Dreadblitz
QQE MOD by Mihkel00
It is not my strategy - it is based on a video I watched.
It will give and alert/notification once the following conditions are aligned:
Bullish Alert
Hull Suite Line Fully Green
Follow Line Indicator Blue
QQE MOD Green
First Bullish Candle after the three indicators hit the conditions as described above.
Bearish Alert
Hull Suite Line Fully Red
Follow Line Indicator Red
QQE MOD Red
First Bearish Candle after the three indicators hit the conditions as described above.
Notes:
This alert system only works on the first three candles (bullish or bearish after the Hull Suite band color change) otherwise there would be too many candles.
The buy is at the close of the candle.
The SL is at the follow line indicator.
The TP is at a RRR of 1:2.
Comments appreciated.
Goethe B - Mutiple Leading Indicator PackageGoethe B is an Indicator Package that contains multiple leading and lagging indicators.
The background is that shows the local trend is calculated by either two Moving Averages or by a Kumo Cloud. By default the Kumo Cloud calculation is used.
What is the main oscillator?
- The main oscillator is TSV, or time segmented volume. It is one of the more interesting leading indicators.
What is the top bar?
-The top bar shows a trend confirmation based on the wolfpack ID indicator.
What are those circles on the second top bar?
-Those are Divergences of an internally calculated PVT oscillator. Red for Regular-Bearish, Green for Regular-Bullish.
What are those circles on the main oscillator?
-These are Divergences. Red for Regular-Bearish. Orange for Hidden-Bearish. Green for Regular-Bullish. Aqua for Hidden-Bullish.
What are those circles on the second lower bar?
-Those are Divergences of an internally calculated CCI indicator. Red for Regular-Bearish, Green for Regular-Bullish.
What is the lower bar?
-The lower bar shows a trend confirmation based on the Acceleration Oscillator, in best case it showes how far in the trend the current price action is.
What are those orange or aqua squares?
- These are TSI (true strength indicator) entry signals . They are calculated by the TSI entry signal, the TSI oscillator threshold.
Most settings of the indicator package can be modified to your liking and based on your chosen strategy might have to be modified. Please keep in mind that this indicator is a tool and not a strategy, do not blindly trade signals, do your own research first! Use this indicator in conjunction with other indicators to get multiple confirmations.
pandas_taLibrary "pandas_ta"
Level: 3
Background
Today is the first day of 2022 and happy new year every tradingviewers! May health and wealth go along with you all the time. I use this chance to publish my 1st PINE v5 lib : pandas_ta
This is not a piece of cake like thing, which cost me a lot of time and efforts to build this lib. Beyond 300 versions of this script was iterated in draft.
Function
Library "pandas_ta"
PINE v5 Counterpart of Pandas TA - A Technical Analysis Library in Python 3 at github.com
The Original Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns.
I realized most of indicators except Candlestick Patterns because tradingview built-in Candlestick Patterns are even more powerful!
I use this to verify pandas_ta python version indicators for myself, but I realize that maybe many may need similar lib for pine v5 as well.
Function Brief Descriptions (Pls find details in script comments)
bton --> Binary to number
wcp --> Weighted Closing Price (WCP)
counter --> Condition counter
xbt --> Between
ebsw --> Even Better SineWave (EBSW)
ao --> Awesome Oscillator (AO)
apo --> Absolute Price Oscillator (APO)
xrf --> Dynamic shifted values
bias --> Bias (BIAS)
bop --> Balance of Power (BOP)
brar --> BRAR (BRAR)
cci --> Commodity Channel Index (CCI)
cfo --> Chande Forcast Oscillator (CFO)
cg --> Center of Gravity (CG)
cmo --> Chande Momentum Oscillator (CMO)
coppock --> Coppock Curve (COPC)
cti --> Correlation Trend Indicator (CTI)
dmi --> Directional Movement Index(DMI)
er --> Efficiency Ratio (ER)
eri --> Elder Ray Index (ERI)
fisher --> Fisher Transform (FISHT)
inertia --> Inertia (INERTIA)
kdj --> KDJ (KDJ)
kst --> 'Know Sure Thing' (KST)
macd --> Moving Average Convergence Divergence (MACD)
mom --> Momentum (MOM)
pgo --> Pretty Good Oscillator (PGO)
ppo --> Percentage Price Oscillator (PPO)
psl --> Psychological Line (PSL)
pvo --> Percentage Volume Oscillator (PVO)
qqe --> Quantitative Qualitative Estimation (QQE)
roc --> Rate of Change (ROC)
rsi --> Relative Strength Index (RSI)
rsx --> Relative Strength Xtra (rsx)
rvgi --> Relative Vigor Index (RVGI)
slope --> Slope
smi --> SMI Ergodic Indicator (SMI)
sqz* --> Squeeze (SQZ) * NOTE: code sufferred from very strange error, code was commented.
sqz_pro --> Squeeze PRO(SQZPRO)
xfl --> Condition filter
stc --> Schaff Trend Cycle (STC)
stoch --> Stochastic (STOCH)
stochrsi --> Stochastic RSI (STOCH RSI)
trix --> Trix (TRIX)
tsi --> True Strength Index (TSI)
uo --> Ultimate Oscillator (UO)
willr --> William's Percent R (WILLR)
alma --> Arnaud Legoux Moving Average (ALMA)
xll --> Dynamic rolling lowest values
dema --> Double Exponential Moving Average (DEMA)
ema --> Exponential Moving Average (EMA)
fwma --> Fibonacci's Weighted Moving Average (FWMA)
hilo --> Gann HiLo Activator(HiLo)
hma --> Hull Moving Average (HMA)
hwma --> HWMA (Holt-Winter Moving Average)
ichimoku --> Ichimoku Kinkō Hyō (ichimoku)
jma --> Jurik Moving Average Average (JMA)
kama --> Kaufman's Adaptive Moving Average (KAMA)
linreg --> Linear Regression Moving Average (linreg)
mgcd --> McGinley Dynamic Indicator
rma --> wildeR's Moving Average (RMA)
sinwma --> Sine Weighted Moving Average (SWMA)
ssf --> Ehler's Super Smoother Filter (SSF) © 2013
supertrend --> Supertrend (supertrend)
xsa --> X simple moving average
swma --> Symmetric Weighted Moving Average (SWMA)
t3 --> Tim Tillson's T3 Moving Average (T3)
tema --> Triple Exponential Moving Average (TEMA)
trima --> Triangular Moving Average (TRIMA)
vidya --> Variable Index Dynamic Average (VIDYA)
vwap --> Volume Weighted Average Price (VWAP)
vwma --> Volume Weighted Moving Average (VWMA)
wma --> Weighted Moving Average (WMA)
zlma --> Zero Lag Moving Average (ZLMA)
entropy --> Entropy (ENTP)
kurtosis --> Rolling Kurtosis
skew --> Rolling Skew
xev --> Condition all
zscore --> Rolling Z Score
adx --> Average Directional Movement (ADX)
aroon --> Aroon & Aroon Oscillator (AROON)
chop --> Choppiness Index (CHOP)
xex --> Condition any
cksp --> Chande Kroll Stop (CKSP)
dpo --> Detrend Price Oscillator (DPO)
long_run --> Long Run
psar --> Parabolic Stop and Reverse (psar)
short_run --> Short Run
vhf --> Vertical Horizontal Filter (VHF)
vortex --> Vortex
accbands --> Acceleration Bands (ACCBANDS)
atr --> Average True Range (ATR)
bbands --> Bollinger Bands (BBANDS)
donchian --> Donchian Channels (DC)
kc --> Keltner Channels (KC)
massi --> Mass Index (MASSI)
natr --> Normalized Average True Range (NATR)
pdist --> Price Distance (PDIST)
rvi --> Relative Volatility Index (RVI)
thermo --> Elders Thermometer (THERMO)
ui --> Ulcer Index (UI)
ad --> Accumulation/Distribution (AD)
cmf --> Chaikin Money Flow (CMF)
efi --> Elder's Force Index (EFI)
ecm --> Ease of Movement (EOM)
kvo --> Klinger Volume Oscillator (KVO)
mfi --> Money Flow Index (MFI)
nvi --> Negative Volume Index (NVI)
obv --> On Balance Volume (OBV)
pvi --> Positive Volume Index (PVI)
dvdi --> Dual Volume Divergence Index (DVDI)
xhh --> Dynamic rolling highest values
pvt --> Price-Volume Trend (PVT)
Remarks
I also incorporated func descriptions and func test script in commented mode, you can test the functino with the embedded test script and modify them as you wish.
This is a Level 3 free and open source indicator library.
Feedbacks are appreciated.
This is not the end of pandas_ta lib publication, but it is start point with pine v5 lib function and I will add more and more funcs into this lib for my own indicators.
Function Name List:
bton()
wcp()
count()
xbt()
ebsw()
ao()
apo()
xrf()
bias()
bop()
brar()
cci()
cfo()
cg()
cmo()
coppock()
cti()
dmi()
er()
eri()
fisher()
inertia()
kdj()
kst()
macd()
mom()
pgo()
ppo()
psl()
pvo()
qqe()
roc()
rsi()
rsx()
rvgi()
slope()
smi()
sqz_pro()
xfl()
stc()
stoch()
stochrsi()
trix()
tsi()
uo()
willr()
alma()
wcx()
xll()
dema()
ema()
fwma()
hilo()
hma()
hwma()
ichimoku()
jma()
kama()
linreg()
mgcd()
rma()
sinwma()
ssf()
supertrend()
xsa()
swma()
t3()
tema()
trima()
vidya()
vwap()
vwma()
wma()
zlma()
entropy()
kurtosis()
skew()
xev()
zscore()
adx()
aroon()
chop()
xex()
cksp()
dpo()
long_run()
psar()
short_run()
vhf()
vortex()
accbands()
atr()
bbands()
donchian()
kc()
massi()
natr()
pdist()
rvi()
thermo()
ui()
ad()
cmf()
efi()
ecm()
kvo()
mfi()
nvi()
obv()
pvi()
dvdi()
xhh()
pvt()
[JL] Cross CandlesI made Stoch candle yesterday, and want to compare other indicators.
So I code this one including 8 indicators on this version:
Stochastic Cross K and D
RSI Cross RSI and an average RSI
Moving Average Cross short and long
MACD Cross MACD and Signal
Stochastic RSI Cross K and D
DMI Cross Plus and minus
Parabolic SAR Cross close and sar
Super Trend Cross direction and 0
I personally like Stochastic, RSI and Stochastic RSI as they are less lagged.
Feel free to post suggestions about other indicators. I am happy to update it.
Swing Dream - PAINT BARS | MA | EMA | DMA | VWAP | TABLE | ADR %- Swing Dream -
Script created for breakout-swing traders, in the style of QullaMaggie * , Dan Zanger, Oliver Kell, and Stockbee.
The following indicators are used by most successful breakout-swing traders such as mentioned above.
(As published) it contains:
Painted Bars, also known as inside/outside candles. Used for candle analysis and to determine breakout pivots & levels. For instance; use it in different timeframes and seek formations (ex, 3-1-2). For further inspiration, study Rob Smith's The Strat .
MA, Simple Moving Averages (Basic levels = 10,20,50,200). Use this indicator to define resistance/support areas as well as the overall long/swing-term trend. In breakout strategies such as EP, Flags, etc this can be used for trailing stops; an example, post-breakout, let the price ride the 20ma before exiting your position.
EMA, Exponential Moving Averages with periods inspired by Qullamaggie (10,20,65). Use this on shorter timeframes (ex, 1h) and for the same principles as MAs.
VWAP, Volume-Weighted Average Price. As for the previous, utilize this as a level indicator to find areas of resistance/support. Good for swing-trading as it implies whenever holders are profitable or not.
DMA, Displaced Moving Average (Horizontal). Personally, I use this a lot. Works very well for trailing stops (post breakout) and "bounce" areas. Choose your own offset and period.
ADR%, Average Daily Range Percentage. Displayed in the table and used to define a symbol's volatility. A very good tool for Qullamaggie-style trading. Personally, I try to find setups with over 6% ADR. Basic definition; low ADR% = Increased chance of a symbol to move slower and in smaller ranges. A higher value equals the opposite.
Table. A table with basic symbol-related information. Could save you plenty of time whenever you scan or search for new swing setups. Looking to add more features here.
Why should you use this script? Well, instead of having tens of different indicators, use this script and combine everything together with EP, Flag, or breakout principles. Suited for every plan, and more efficient in my opinion.
View settings to turn on/off different indicators.
* If you're looking for an introduction and further explanation of how Qullamaggie uses mentioned indicators, I could recommend checking out his website, stream, or participation in "Chat With Traders".
At last, I want to credit: @jkcqld @neolao @TheScrutiniser
This Script will get updated and improved.
// TechFille006
PYRAMIDING BTCUSDTPERP1H [ALERTS VERSION]BINANCE:BTCUSDTPERP
Hello
This my upgraded (ALERTs) version of my previous bots, uses diffrent indicators
WARING
THIS STRATEGY WORKS ONLY ON BTCUSDTPERP ON BINANCE 60MIN (like my previous ones) !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
- it depends on specyfic volume and wick based on binance
Soo, I was tried to make a bot with more trades to make more real results.
Trends are change, and the problem with configuration on bots is that, while we searching the best cofigurations , this was best configuration in the past,
to prepare bot for the futures moves , we have to make as much trades as possible.
This bot is pure definition of pyramiding, uses 2 entries, and when all the conditions are true, then will open a trades
The way it works is simple, bot use 6 difrent indicators to open longs/shorts and for the define trend
This specific configuration works the best at
TP: 1.4%
SL: 9%
This is bot only for lev 1x
Dont try it for bigger leverage, becouse when sl hits, which sometimes happend, the lost will be huge
Why sl is so big?
Bot is programed to replace sl with other entries
for example
close longs and open shorts
normal lose is around 3-5% (while trend is changed), so sl will only destroys results
this bot using 6 difrent indicators:
ADX
RSI
VOLUME
RANGE FILTER
MA 5-10-30
MACD by KivancOzbilgic
ADX - makes a solid view to trend without any scam wick :
Long only on green bars
Shorts only on red bars
That's helps my strategy to define a right trend
there is also a orange option for unidentified trends
RSI - value helps strategy to stop trade in right time
When RSI is overbought strategy don't open new longs
also when RSI is oversold strategy don't open new shorts
Volume - volume is the most important indicator for the strategy,
to avoid open trades on flat chart, new trades are open after a strong volume
wicks
RANGE FILTER- this indicator is for the better view of trends, define trends
MA 5-10-30 - like previous ones this is for better view of trends, and correctly define the trends
MACD by KivancOzbilgic - this indicator is based of MACD RELOADED by Kivanc Ozbilgic
Also like previous ones, indicator should help defined correct trends
Enjoy ;)
Silen's Financials Debt & EquityThis Script shows Debt (red) & Equity (green), as well as Total Equity and Net Income in a preformatted way for a symbol. Total revenue's and Net income's visibility is turned off by default and can be activated in the indicator settings. 🍳
Disclaimer: Any content in this script can be completely replicated by using Tradingview's Build-In Financial Indicators: Total debt, Total equity, Net income and Total revenue. It requires a lot of formatting work to get them to this state though. 👌
However, you are going to need 4 Financial Indicators clogging 🚽 your screen. With this indicator you have them preformatted as an overlay on your chart so you know exactly what's going on with your ticker's financials. 💰
I recommend only using Debt & Equity OR Total Equity & Net Income together. Although displaying all 4 indicators together is possible, it will make your chart quite messy.
This is how the indicator looks like for Total equity and Net Income:
This Script (2) is part of a Series that will contain 3 scripts to help you easily evaluate if a stock is trading in harmony with its fundamentals or not. ☯
Script 1 already exists:
Script 3 will be a Fair Value Indicator. 📣
Script 1 and 2 combined will look like this: 🌄
If you have any questions, let me know! 🙂
RSI + MA StrategyHello, everyone!
We have just released an innovative strategy for TradingView. It allows you to facilitate the trading process when you have to use both indicators.
This strategy is:
User-friendly
Configurable
Equipped with the combination of Relative Strength Index (RSI) and Moving Average (MA) indicators
Designed with all required functions to manage positions
Features
The RSI+MA strategy can:
Identify entry points for Long and Short positions.
Depict RSI and MA values concerning each other.
Reduce visual congestion and import usability thanks to using a combo of 2 indicators.
Allow using pivot trading. The RSI+MA strategy will enter a Long position according to the Short position conditions. And vice versa.
Note! If you want to open a Long position, the RSI line should cross MA from top to bottom. If you want to open a Short position, RSI has to cross MA from bottom to top.
Parameters
We have equipped our strategy with more than 14 additional parameters. So, you can configure the EA according to your needs!
Inputs :
Use Reverse Trade — allows swapping Long and Short positions opening conditions.
Resolution — allows you to view an indicator with data on a higher or lower timeframe on the current chart.
RSI Length
RSI Source: Open, High, Low, Close, HL2, HLC3, OHLC4
Show MA — allows you to enable or disable MA displaying.
MA Length
MA Offset
Style:
RSI — RSI indicator line color and style settings.
MA — MA indicator line color and style configuration.
Upper Band — allows customizing line style, color, and RSI upper bound value.
Lower Band — allows you to customize line style, color, and RSI lower bound value.
Background — background color setting within the RSI upper and lower borders.
Precision — number of decimals for RSI values.
Note! Try RSI+MA on your demo account first before going live.
