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!
ค้นหาในสคริปต์สำหรับ "adx"
Aroon Oscillator of Adaptive RSI [Loxx]Aroon Oscillator of Adaptive RSI uses RSI to calculate AROON in attempt to capture more trend and momentum quicker than Aroon or RSI alone. Aroon Oscillator of Adaptive RSI has three different types of RSI calculations and the choice of either fixed, VHF Adaptive, or Band-pass Adaptive cycle measures to calculate RSI.
Arron Oscillator:
The Aroon Oscillator was developed by Tushar Chande in 1995 as part of the Aroon Indicator system. Chande’s intention for the system was to highlight short-term trend changes. The name Aroon is derived from the Sanskrit language and roughly translates to “dawn’s early light.”
The Aroon Oscillator is a trend-following indicator that uses aspects of the Aroon Indicator (Aroon Up and Aroon Down) to gauge the strength of a current trend and the likelihood that it will continue.
Aroon oscillator readings above zero indicate that an uptrend is present, while readings below zero indicate that a downtrend is present. Traders watch for zero line crossovers to signal potential trend changes. They also watch for big moves, above 50 or below -50 to signal strong price moves.
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
Happy trading!
AdxlLibrary "Adxl"
Functions to calculate the Average Directional Index
getDirectionUp(bar, lookback)
Bar high changed from open for bar
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getDirectionDown(bar, lookback)
Bar low changed from open for bar
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getPositiveDirectionalMovement(bar, lookback)
Positive directional movement for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getNegativeDirectionalMovement(bar, lookback)
Negative directional movement for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getTrueRangeMovingAverage(bar, lookback)
True range moving average for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getDirectionUpIndex(bar, lookback)
Direction up index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getDirectionDownIndex(bar, lookback)
Direction down index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getTotalDirectionIndex(bar, lookback)
Total direction index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getAverageDirectionalIndex(bar, lookback)
Average Directional Index (ADX) for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
MarginRockets 5 Mins Ultimate Scalp v15 Mins Scalp on any Pair:
-Model Components:
a.EMA 200
b.VWMA 20
c. ADX
d.DI+/DI-
e.Volume ansd Average Volume
- The Model will give you the Buy/Sell signal but you have to consider:
a.The Candlestick patterns
b.How far the candle from the ema200(Blue line)
c.The vwma can be used as supporting indicator
-Trading Rules:
a.Leverage 10x
b.Take profit always: 2% (20% with leverage)
b.Stop loss is last swing high or low
Hoe all teh best for all of you!!!!!
Solution Zigma - Fibonacci Impulse'Solution Zigma' is strategy for any securities because this strategy use EMA of Fibonacci Level and Plot Like candle easy for analysis trend impulse. This strategy used DMI(ADX) for filter sideway but not greatest indicator, Please use this strategy with Risk Management.
[blackcat] L2 FArden Thomas Voting With Multiple TimeframesLevel 2
Background
For Traders’ Tips of November 2020, the focus is F. Arden Thomas’ article in the August 2020 issue, “Voting With Multiple Timeframes”.
Function
F. Arden Thomas sums up the returns by a stochastic indicator in a voting process over seven different timeframes, and uses the resulting votes for trade signals. He shows us a new way of using the classic stochastic oscillator by combining many timeframes into a single value by voting. By using this voting process, buy and sell signals derived from many intervals become clearly visible on the chart. This is an interesting concept that can be applied to many common indicators such as the RSI or ADX, not just the stochastic.
Although the author creates a voting system by counting the number of times the indicator is in overbought/oversold range, I thought it would be interesting to create a composite indicator by averaging the stochastic value over multiple timeframes into a single indicator that moves along the standard scale.
Remarks
Maroon~ Red color bars for bullish market.
Teal~ Green color bars for bearish market.
This is a Level 2 free and open source indicator.
Feedbacks are appreciated.
Hulk Strategy x35 Leverage 5m chart w/Alerts This strategy is a pullback strategy that utilizes 2 EMAs as a way of identifying trend, MACD as an entry signal, and RSI and ADX to filter bad trades. By using the confirmation of all of these indicators the strategy attempts to catch pullbacks, and it is optimized to wait for high probability setups. Take not that the strategy is optimized for use on BTCUSDT along with 35 times leverage(Using leverage is risky). The Hulk Strategy waits for strong trend confirmation and then attempts to identify pullbacks using MACD and RSI. By using these it identifies strong short term movement against the trend(hence the name Hulk). To use the strategy wait for the strategy to make an entry, and then enter with a stop loss of 1.1% and a take profit of 1.35% with respect to if it is a long or short position. The trade frequency of this strategy is high as it is made for use on the 5m timeframe. But this does not mean you will have to be staring at your computer constantly as an average of 1 trade takes place each day. This will vary a lot though, somedays the strategy enters up to 4 times. I wish you good trading and hope that you like this strategy!
P.S. The indicators on my chart are visualizations of the indicators used in the strategy, they are not necessary for the strategy to work though. Also the colored in cloud on the price chart is an EMA cloud and it comes with the strategy when you add it to your chart. This EMA cloud consists of two EMAs a 50 and a 200 EMA.
KINSKI Multi Trend OscillatorThe Multi Trend Oscillator is a tool that combines the ratings of several indicators to facilitate the search for profitable trades. I was inspired by the excellent indicator "Technical Ratings" from Team TradingView to create an alternative with a technically new approach. Therefore, it is not a modified copy of the original, but newly conceived and implemented.
The recommendations of the indicator are based on the calculated ratings from the different indicators included in it. The special thing here is that all settings for the individual indicators can be changed according to your own needs and displayed as a histogram and MA line. This provides an excellent visual control of your own settings. Alarms are also triggered.
Criteria for determining the rating
Relative Strength Index (RSI)
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Relative Strength Index (RSI) Laguerre
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Noise free Relative Strength Index (RSX)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Money Flow Index (MFI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Commodity Channel Index (CCI)
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Moving Average Convergence/Divergence (MACD)
Buy - values of the main line > values of the signal line and rising
Sell - values of the main line < values of the signal line and falling
Neutral - neither Buy nor Sell
Klinger
Buy - indicator >= 0 and rising
Sell - indicator < 0 and falling
Neutral - neither Buy nor Sell
Average Directional Index (ADX)
Buy - indicator > 20 and +DI line crosses over the -DI line and rising
Sell - indicator > 20 and +DI line crosses below the -DI line and falling
Neutral - neither Buy nor Sell
Awesome Oscillator
Buy - Crossover 0 and values are greater than 0, or exceed the zero line
Sell - Crossunder 0 and values are lower than 0, or fall below the zero line
Neutral - neither Buy nor Sell
Ultimate Oscillator
Buy - Crossover oversold level and indicator < oversold level and rising
Sell - Crossunder oversold level and indicator >= oversold level and falling
Neutral - neither Buy nor Sell
Williams Percent Range
Buy - Crossover Oversold Level and Indicator < Oversold Level and rising
Sell - Crossunder Oversold Level and Indicator >= Oversold Level and falling
Neutral - neither Buy nor Sell
Momentum
Buy - Crossover 0 and indicator levels rising
Sell - Crossunder 0 and indicator values falling
Neutral - neither Buy nor Sell
Total Ratings
The numerical value of the rating "Sell" is 0, "Neutral" is 0 and "Buy" is 1. The total rating is calculated as the average of the ratings of the individual indicators and are determined according to the following criteria:
MaxCount = 12 (depending on whether other oscillators are added).
CompareSellStrong = MaxCount * 0.3
CompareMid = MaxCount * 0.5
CompareBuyStrong = MaxCount * 0.7
value <= CompareSellStrong - Strong Sell
value < CompareMid and value > CompareSellStrong - Sell
value == 6 - Neutral
value > CompareMid and value < CompareBuyStrong - Buy
value >= CompareBuyStrong - Strong Buy
Understanding the results
The Multi Trend Oscillator is designed so that its values fluctuate between 0 and currently 12 (maximum number of integrated indicators). Its values are displayed as a histogram with green, red and gray bars. The bars are gray when the value of the indicator is at half of the number of indicators used, currently 12. Increasingly saturated green bars indicate increasing values above 6, and increasingly saturated red bars indicate increasingly decreasing values below 6.
The table at the end of the histogram shows details (can be activated in the settings) about the overall rating and the individual indicators. Its color is determined by the rating value: gray for neutral, green for buy or strong buy, red for sell or strong sell.
The following alarms are triggered:
Multi Trend Oscillator: Sell
Multi Trend Oscillator: Strong Sell
Multi Trend Oscillator: Buy
Multi Trend Oscillator: Strong Buy
R-Smart - Relative Strength On observing the market for years I learned that Relative Strength will help us in staying invested in strong bullish stocks (relative to primary indices of your country, in my case it's Nifty 50 for India). Once you identify a strong stock, it's important to know if the stock is trending and is in momentum. To identify, trends and momentum, I used ADX and MACD indicators respectively as part of the R-Smart.
In R-Smart, I used Relative Strength primarily to plot the chart, if the Histogram is positive (greater than 0) then the security is bullish. But then how do we know that it's in trend and having momentum. Well the below color code will help you identify them
1. Histogram in Green : Strong Bullish
2. Histogram in Blue : Weak Bullish
3. Histogram in Orange: Bearish
Apart from the above indicator, I would like to use Super Trend to know the immediate support/resistances on the chart.
# StayInvested
# StayProfitable
# ManageYourRisk
Adaptive Oscillator constructor [lastguru]Adaptive Oscillators use the same principle as Adaptive Moving Averages. This is an experiment to separate length generation from oscillators, offering multiple alternatives to be combined. Some of the combinations are widely known, some are not. Note that all Oscillators here are normalized to -1..1 range. This indicator is based on my previously published public libraries and also serve as a usage demonstration for them. I will try to expand the collection (suggestions are welcome), however it is not meant as an encyclopaedic resource , so you are encouraged to experiment yourself: by looking on the source code of this indicator, I am sure you will see how trivial it is to use the provided libraries and expand them with your own ideas and combinations. I give no recommendation on what settings to use, but if you find some useful setting, combination or application ideas (or bugs in my code), I would be happy to read about them in the comments section.
The indicator works in three stages: Prefiltering, Length Adaptation and Oscillators.
Prefiltering is a fast smoothing to get rid of high-frequency (2, 3 or 4 bar) noise.
Adaptation algorithms are roughly subdivided in two categories: classic Length Adaptations and Cycle Estimators (they are also implemented in separate libraries), all are selected in Adaptation dropdown. Length Adaptation used in the Adaptive Moving Averages and the Adaptive Oscillators try to follow price movements and accelerate/decelerate accordingly (usually quite rapidly with a huge range). Cycle Estimators, on the other hand, try to measure the cycle period of the current market, which does not reflect price movement or the rate of change (the rate of change may also differ depending on the cycle phase, but the cycle period itself usually changes slowly).
Chande (Price) - based on Chande's Dynamic Momentum Index (CDMI or DYMOI), which is dynamic RSI with this length
Chande (Volume) - a variant of Chande's algorithm, where volume is used instead of price
VIDYA - based on VIDYA algorithm. The period oscillates from the Lower Bound up (slow)
VIDYA-RS - based on Vitali Apirine's modification of VIDYA algorithm (he calls it Relative Strength Moving Average). The period oscillates from the Upper Bound down (fast)
Kaufman Efficiency Scaling - based on Efficiency Ratio calculation originally used in KAMA
Deviation Scaling - based on DSSS by John F. Ehlers
Median Average - based on Median Average Adaptive Filter by John F. Ehlers
Fractal Adaptation - based on FRAMA by John F. Ehlers
MESA MAMA Alpha - based on MESA Adaptive Moving Average by John F. Ehlers
MESA MAMA Cycle - based on MESA Adaptive Moving Average by John F. Ehlers , but unlike Alpha calculation, this adaptation estimates cycle period
Pearson Autocorrelation* - based on Pearson Autocorrelation Periodogram by John F. Ehlers
DFT Cycle* - based on Discrete Fourier Transform Spectrum estimator by John F. Ehlers
Phase Accumulation* - based on Dominant Cycle from Phase Accumulation by John F. Ehlers
Length Adaptation usually take two parameters: Bound From (lower bound) and To (upper bound). These are the limits for Adaptation values. Note that the Cycle Estimators marked with asterisks(*) are very computationally intensive, so the bounds should not be set much higher than 50, otherwise you may receive a timeout error (also, it does not seem to be a useful thing to do, but you may correct me if I'm wrong).
The Cycle Estimators marked with asterisks(*) also have 3 checkboxes: HP (Highpass Filter), SS (Super Smoother) and HW (Hann Window). These enable or disable their internal prefilters, which are recommended by their author - John F. Ehlers . I do not know, which combination works best, so you can experiment.
Chande's Adaptations also have 3 additional parameters: SD Length (lookback length of Standard deviation), Smooth (smoothing length of Standard deviation) and Power ( exponent of the length adaptation - lower is smaller variation). These are internal tweaks for the calculation.
Oscillators section offer you a choice of Oscillator algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
CMO - Chande Momentum Oscillator
RSI - Relative Strength Index
Volume-scaled RSI - my own version of RSI. It scales price movements by the proportion of RMS of volume
Momentum RSI - RSI of price momentum
Rocket RSI - inspired by RocketRSI by John F. Ehlers (not an exact implementation)
MFI - Money Flow Index
LRSI - Laguerre RSI by John F. Ehlers
LRSI with Fractal Energy - a combo oscillator that uses Fractal Energy to tune LRSI gamma
Fractal Energy - Fractal Energy or Choppiness Index by E. W. Dreiss
Efficiency ratio - based on Kaufman Adaptive Moving Average calculation
DMI - Directional Movement Index (only ADX is drawn)
Fast DMI - same as DMI, but without secondary smoothing
If no Adaptation is selected (None option), you can set Length directly. If an Adaptation is selected, then Cycle multiplier can be set.
Before an Oscillator, a High Pass filter may be executed to remove cyclic components longer than the provided Highpass Length (no High Pass filter, if Highpass Length = 0). Both before and after the Oscillator a Moving Average can be applied. The following Moving Averages are included: SMA, RMA, EMA, HMA , VWMA, 2-pole Super Smoother, 3-pole Super Smoother, Filt11, Triangle Window, Hamming Window, Hann Window, Lowpass, DSSS. For more details on these Moving Averages, you can check my other Adaptive Constructor indicator:
The Oscillator output may be renormalized and postprocessed with the following Normalization algorithms:
Stochastic - Stochastic
Super Smooth Stochastic - Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
Inverse Fisher Transform - Inverse Fisher Transform
Noise Elimination Technology - a simplified Kendall correlation algorithm "Noise Elimination Technology" by John F. Ehlers
Except for Inverse Fisher Transform, all Normalization algorithms can have Length parameter. If it is not specified (set to 0), then the calculated Oscillator length is used.
More information on the algorithms is given in the code for the libraries used. I am also very grateful to other TradingView community members (they are also mentioned in the library code) without whom this script would not have been possible.
DMI RSI AO 3 indicators in 1 overlayThis is simple indicators that plot 3 indicators DMI, RSI and AO on 1 pane
How to use: you can add on your chart and edit color and display in setting page of indicators
The directional movement index (DMI) is an indicator developed by J. Welles Wilder in 1978 that identifies in which direction the price of an asset is moving. The indicator does this by comparing prior highs and lows and drawing two lines: a positive directional movement line (+DI) and a negative directional movement line (-DI). An optional third line, called the average directional index (ADX), can also be used to gauge the strength of the uptrend or downtrend.
When +DI is above -DI, there is more upward pressure than downward pressure in the price. Conversely, if -DI is above +DI, then there is more downward pressure on the price. This indicator may help traders assess the trend direction. Crossovers between the lines are also sometimes used as trade signals to buy or sell.
The relative strength index (RSI) is a momentum indicator used in technical analysis that measures the magnitude of recent price changes to evaluate overbought or oversold conditions in the price of a stock or other asset. The RSI is displayed as an oscillator (a line graph that moves between two extremes) and can have a reading from 0 to 100. The indicator was originally developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, “New Concepts in Technical Trading Systems.”1
Traditional interpretation and usage of the RSI are that values of 70 or above indicate that a security is becoming overbought or overvalued and may be primed for a trend reversal or corrective pullback in price. An RSI reading of 30 or below indicates an oversold or undervalued condition.
Awesome Oscillator is developed by famous technical analyst and charting enthusiast Bill Williams. Awesome Oscillator (AO) is an indicator that is non-limiting oscillator, providing insight into the weakness or the strength of a stock. The Awesome Oscillator is used to measure market momentum and to affirm trends or to anticipate possible reversals. It does this by effectively comparing the recent market momentum, with the general momentum over a wider frame of reference.
NormalizedOscillatorsLibrary "NormalizedOscillators"
Collection of some common Oscillators. All are zero-mean and normalized to fit in the -1..1 range. Some are modified, so that the internal smoothing function could be configurable (for example, to enable Hann Windowing, that John F. Ehlers uses frequently). Some are modified for other reasons (see comments in the code), but never without a reason. This collection is neither encyclopaedic, nor reference, however I try to find the most correct implementation. Suggestions are welcome.
rsi2(upper, lower) RSI - second step
Parameters:
upper : Upwards momentum
lower : Downwards momentum
Returns: Oscillator value
Modified by Ehlers from Wilder's implementation to have a zero mean (oscillator from -1 to +1)
Originally: 100.0 - (100.0 / (1.0 + upper / lower))
Ignoring the 100 scale factor, we get: upper / (upper + lower)
Multiplying by two and subtracting 1, we get: (2 * upper) / (upper + lower) - 1 = (upper - lower) / (upper + lower)
rms(src, len) Root mean square (RMS)
Parameters:
src : Source series
len : Lookback period
Based on by John F. Ehlers implementation
ift(src) Inverse Fisher Transform
Parameters:
src : Source series
Returns: Normalized series
Based on by John F. Ehlers implementation
The input values have been multiplied by 2 (was "2*src", now "4*src") to force expansion - not compression
The inputs may be further modified, if needed
stoch(src, len) Stochastic
Parameters:
src : Source series
len : Lookback period
Returns: Oscillator series
ssstoch(src, len) Super Smooth Stochastic (part of MESA Stochastic) by John F. Ehlers
Parameters:
src : Source series
len : Lookback period
Returns: Oscillator series
Introduced in the January 2014 issue of Stocks and Commodities
This is not an implementation of MESA Stochastic, as it is based on Highpass filter not present in the function (but you can construct it)
This implementation is scaled by 0.95, so that Super Smoother does not exceed 1/-1
I do not know, if this the right way to fix this issue, but it works for now
netKendall(src, len) Noise Elimination Technology by John F. Ehlers
Parameters:
src : Source series
len : Lookback period
Returns: Oscillator series
Introduced in the December 2020 issue of Stocks and Commodities
Uses simplified Kendall correlation algorithm
Implementation by @QuantTherapy:
rsi(src, len, smooth) RSI
Parameters:
src : Source series
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
vrsi(src, len, smooth) Volume-scaled RSI
Parameters:
src : Source series
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
This is my own version of RSI. It scales price movements by the proportion of RMS of volume
mrsi(src, len, smooth) Momentum RSI
Parameters:
src : Source series
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
Inspired by RocketRSI by John F. Ehlers (Stocks and Commodities, May 2018)
rrsi(src, len, smooth) Rocket RSI
Parameters:
src : Source series
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
Inspired by RocketRSI by John F. Ehlers (Stocks and Commodities, May 2018)
Does not include Fisher Transform of the original implementation, as the output must be normalized
Does not include momentum smoothing length configuration, so always assumes half the lookback length
mfi(src, len, smooth) Money Flow Index
Parameters:
src : Source series
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
lrsi(src, in_gamma, len) Laguerre RSI by John F. Ehlers
Parameters:
src : Source series
in_gamma : Damping factor (default is -1 to generate from len)
len : Lookback period (alternatively, if gamma is not set)
Returns: Oscillator series
The original implementation is with gamma. As it is impossible to collect gamma in my system, where the only user input is length,
an alternative calculation is included, where gamma is set by dividing len by 30. Maybe different calculation would be better?
fe(len) Choppiness Index or Fractal Energy
Parameters:
len : Lookback period
Returns: Oscillator series
The Choppiness Index (CHOP) was created by E. W. Dreiss
This indicator is sometimes called Fractal Energy
er(src, len) Efficiency ratio
Parameters:
src : Source series
len : Lookback period
Returns: Oscillator series
Based on Kaufman Adaptive Moving Average calculation
This is the correct Efficiency ratio calculation, and most other implementations are wrong:
the number of bar differences is 1 less than the length, otherwise we are adding the change outside of the measured range!
For reference, see Stocks and Commodities June 1995
dmi(len, smooth) Directional Movement Index
Parameters:
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
Based on the original Tradingview algorithm
Modified with inspiration from John F. Ehlers DMH (but not implementing the DMH algorithm!)
Only ADX is returned
Rescaled to fit -1 to +1
Unlike most oscillators, there is no src parameter as DMI works directly with high and low values
fdmi(len, smooth) Fast Directional Movement Index
Parameters:
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
Same as DMI, but without secondary smoothing. Can be smoothed later. Instead, +DM and -DM smoothing can be configured
doOsc(type, src, len, smooth) Execute a particular Oscillator from the list
Parameters:
type : Oscillator type to use
src : Source series
len : Lookback period
smooth : Internal smoothing algorithm
Returns: Oscillator series
Chande Momentum Oscillator (CMO) is RSI without smoothing. No idea, why some authors use different calculations
LRSI with Fractal Energy is a combo oscillator that uses Fractal Energy to tune LRSI gamma, as seen here: www.prorealcode.com
doPostfilter(type, src, len) Execute a particular Oscillator Postfilter from the list
Parameters:
type : Oscillator type to use
src : Source series
len : Lookback period
Returns: Oscillator series
Kahlman HullMA / WT Cross StrategyA strategy created using Hull Moving Average and WT Cross .
Hull Moving Average turns green and WT Cross crossover this is a long. Otherwise short.
Stop Loss and Take Profit settings are available. You can set it to the level you want or turn it off.
According to my measurements, it shows the best performance in the 4-hour period. But you can find the best settings that are correct from the Strategy settings.
CapX Core SignalsThis is an indicator that generates Long and Short Signals on multiple marketable instruments such as Indices, Stocks and Crypto. This indicator has almost everything for intraday and Swing trading. Works perfectly on multiple timeframe and give signal on real time. Tested on Indices.
We make use of Relative Strength and Moving Averages to Generate Signal but at the same time, a signal is confirmed by Volatility Indicators and trend. This way we are able generate a few signals but more precise one. While generating a signal, system gives us Stop Loss Level Instantly which is calculated from Average Ture Range.
MACD Level Modified - The Smooth Line help reduce false break out
RSI is confirmed with Crossover of RSI and EMA
ADX level used to Identify Volatility ,
ATR Multiplied with float factor to give Stop Loss Range. - User get option to input ATR Float Value
EMA 9, EMA 14 and EMA 21 Used to Identify Short trend in market
DEMA 100 and DEMA 200 used to find Long Trend in Market
Support Resistance Levels marked
What makes this Indicator Unique is that it is free from clutters, indicators and signals. Less Number of signals but precise one are only generated. Charts are not cluttered with many drawing or indicators so you get a clear view of price actions and you can further work on chart and candle Pattern.
We have placed a Information Dashboard on top right corner that work real time to give you exact trend checked with EMA and Confirmed by other moving averages. The Dashboard also informs about On Going Market volatility in simple words and gives faster signal in color coded cells.
sma RSI & sudden buy and sell Strategy v1This strategy uses mostly three things:-
1. average RSI (sma rsi over a period)
2. sudden buy and sudden sell (usually to infer the change in trend or direction)
3. various EMAs ( used as a filter)
I mostly build it to work on a 3min crypto chart but it should work on any timeframe or any symbol.
Settings - Length -RSI length (hardly needed to be changed but sometimes it doubles the net profit)(+/-2)
instant length - a sudden increase or decrease in the price calculated by the length of RSI (+/-10)
Bars - No of candles to verify before starting /closing the strategy (+/-20)
Lookbackno2 - another variable to verify ema opening/closing (hardly needed to change)
emas - values of different EMAs (you can change if you want but I don't recommend it though)
over40 and over60 - the value of overbuying and overselling(+/-10)
In future, I will probably add ADX or use machine learning to filter out results
It works well considering 0.05% commission per entry and exit (total of 1% per trade)
you can message me for any query or suggestions.
_3_Period_Dashboard_A Dashboard to check the current and previous two bar values of some commonly used indicators:
==> RSI
==> ADX
==> DI +
==> DI -
==> MACD
==> MACD Signal
==> Stochastic k
==> Stochastic d
NSDT Indicator PanelThis indicator places a table on the bottom of the chart where each section changes color based on settings in each individual indicator. It provides a way to quickly glance at the chart and see the overall direction of the market with the combination of indicators.
All settings for each individual indicator are editable, so you can customize them to your unique specifications.
NSDT HAMA Candles STRATThis is a STRATEGY based on our popular HAMA Candles Indicator.
It is an "Always On" strategy, meaning it will stay in a Long position until the Short criteria shows up, and then it will close the Long position and immediately enter a Short position.
Since this is a strategy, we added a few more components. The most notable one is the grid at the top right that shows the statistics of whatever the current settings are. The user can change the MA lengths and see the potential results update in real time.
Since this is Always On and uses Moving Averages, we added an ADX setting to help filter our trades in a ranging/choppy market.
The settings will need to be adjusted to find the best fit for your instrument, chart time, and risk management plan.
Volume Zone Oscillator (VZO)My interpretation of Walid Khalil's Volume Zone Oscillator (VZO) as published in the 2009 International Federation of Technical Analysis Journal.
This VZO indicator is also the same as Danielle Shay's popular Simpler Trading TurboVZO indicator.
ABOUT:
The oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction.
HOW TO USE THE INDICATOR:
The default period is 14 but can be adjusted after backtesting.
The VZO points to a positive trend when it rises above and maintains the 5% level, and a negative trend when it falls below the 5% level and fails to turn higher. Oscillations between the 5% and 40% levels mark a bullish trend zone, while oscillations between -40% and 5% mark a bearish trend zone. Meanwhile, readings above 40% signal an overbought condition, while readings above 60% signal an extremely overbought condition. Alternatively, readings below -40% indicate an oversold condition, which becomes extremely oversold below -60%.
Kahlil recommends confirming VZO signals with a 14-period average directional index (ADX), with values greater than 18 pointing to a trending market - search Tradingview's built-in indicators for the Directional Movement Index (DMI).
INTRADAY SCALPING:
Whilst the VZO is already smoothed with an exponential moving average, the indicator settings include an additional 'smoothing' function to remove any excess 'noise' in the plots for intraday use.
Mazuuma Churn IndicatorThis indicator was specifically made to confirm a periode of sideways movement (churn) on Bitcoin. It can probably be used for other cryptocurrencies as well. I use it on the daily timeframe.
Yellow means "Unconfirmed".
Orange means "Partially Confirmed".
Red means "Confirmed"
The indicator is not perfect, so use your common sense.
Churn starts when at least 2 of the conditions below are met (use also your common sense):
1. ATR < MA 20 on ATR
2. Distance to EMA 200 must be ≤ 16% at “Open churn”
3. EMA 12 on RSI between 40 and 60
4. ADX < 25
The above are weighted. Meaning no 1 has most significance. The numbers can be tweaked.
Reversal coming
* The indicators above break out, especially the ATR
* Color shift of the Heikin Ashi candle on weekly timeframe
* Engulfing candle on weekly timeframe
Because of the offset of the EMA 200, the precision of the Churn predictor can be off after a VERY big spike up or down, e.g. dec 2017. After such a spike use your common sense.
Personally I use this for bot trading, i.e. turn off trend following bots when in sideways market and use grid bots or other means of trading instead.
Price Action [Morty]This price action indicator uses the higher timeframe SSL channel to identify trends.
The long entry signal is a bullish candlestick pattern when the price retraces to EMA20 in an uptrend.
The short entry signal is a bearish candlestick pattern when the price retraces to the EMA20 in a downrend.
Currently, this indicator shows engulfing patterns, pin bar patterns, 2 bar reversal patterns and harami patterns.
It also shows a volatility squeeze signal when the Bollinger bands is within the Kelter channels.
The buy and sell signal can also be filter by the ADX indicator greater than a threshold.
You can set your stoploss to the previous low/high when you go long/short.
The risk/reward ratio could be 1 to 1.5.
This indicator can be used in any market.
DMI (Multi timeframe) DI Strategy [KL]Directional Movement Index Strategy
Entry conditions:
- (a) when DI+ > DI- on timeframe #1, and
- (b) Confirmation: when DI+ > DI- on timeframe #2
In the shown example, timeframe1 was same as the chart (1H) and timeframe2 was 1D.
Stop Loss: ATR based trailing stop
About DMI
Can refer to Investopedia for general understanding.
Applications of DMI in this strategy:
- Assumes uptrend when DI+ is above DI- (when green DI+ lines above red DI-), vice versa for downtrend. This is checked in two different timeframes that can be set by user in settings.
- DX is ignored, it doesn't give a direction of the trend. But if DX was applied, it would be a good indicator for quantifying the strength of uptrend/downtrend. This measurement would typically be read along a threshold (i.e. if below 20, then market is likely consolidating). All of these have been commented out (ignored by pinescript's interpreter via //) in the codes, as said; we are not using DX for sake of simplicity.
Visualizations
To make the chart look cleaner, DMI plots have been simplified to just down/up arrows placed at bottom of the chart.
Referring to the example chart:
- Green arrows : when DI+ > DI- for both timeframes, implies uptrend
- Red arrows: other way around (DI+ < DI-), implies downtrend
