Qualitative Smoothed Strength Index***RSI CHART BELOW IS FOR COMPARSION TO SHOW HOE THEY MAKE SIMILIAR PATTERNS*** IT IS NOT PART OF THE INDICATOR***
The Qualitative Smoothed Strength Index (QSSI) is a simplified momentum oscillator whose values will oscillate between 0 and 1 . By converting price differences into binary values and smoothing them with a moving average, it identifies qualitative strength of price movements. This simplification allows traders to easily interpret trends and reversals. The QSSI offers advantages such as noise reduction, clear trend identification, and early signal detection, resulting in less lag compared to traditional oscillators. Traders can customize the indicator based on their preferences and use it across various markets.
QSSI Indicator uses the input function is used to define the input parameters of the indicator. In this case, there are two inputs:
length: The number of periods used for calculating the differences (a, b, c) and their assigned values. Default value is 5.
MAL: The length of the moving average used for smoothing the assigned values. Default value is 14.
The next few lines calculate 'a', 'b', and 'c', which represent the differences between the high, low, and close prices, respectively, and their corresponding previous simple moving averages (SMAs) of specified length. These differences are used to identify price movements.
The code assigns binary values (0 or 1) to a_assigned, b_assigned, and c_assigned, depending on whether the corresponding differences (a, b, c) are greater than 0. This step converts the differences into a binary representation, indicating upward or downward price movements.
Average_assigned calculates the average of the assigned binary values of a, b, and c. This average value represents the overall strength of the price movement.ma_assigned calculates the 14-day moving average of average_assigned, which smoothens the indicator and helps traders identify trends more easily.
The code plots the 14-day moving average (ma_assigned) on the chart as a blue line. It also plots the individual assigned values of a, b, and c as dots on the chart. a_assigned is shown in green, b_assigned in red, and c_assigned in black. These dots indicate the presence of upward or downward movements in the respective price components. By visualizing these dots on the chart, the trader can quickly identify the presence and direction of price movements for each of the price components. This information can be valuable for understanding how the different price elements (high, low, and close) are contributing to the overall trend and strength of the market. Traders can use this data to make more informed decisions, such as confirming the presence of trends, identifying potential reversals, or gauging the overall market sentiment based on the distribution of upward and downward movements across the price components.
Finally, the code draws horizontal dotted lines at levels 0.70 (0.8)and 0.30 (0.2). These levels are typically used to identify overbought (above 0.70 or 0.8) and oversold (below 0.30 or 0.2) conditions in the market.
The Qualitative Smoothed Strength Index (QSSI) provides traders with information about the strength and direction of price movements. By using assigned binary values, the indicator simplifies the interpretation of price data, making it easier to identify trends and potential reversals.
חפש סקריפטים עבור "oscillator"
Signal #1This oscillator calculates the directional strength of the bars using a hydraulic balance mechanism based on a small amount of what I consider a fundamental property of a rod. It does not consider the amplitude of price movement, so can be used as a complement to volume-based oscillators.
This indicator uses simple analysis of past trading volume to determine its support for recent market activity. What I call Volume Buoyancy measures that strength and direction of support.
NOTE
• The command can be used with any symbol timeframe, including seconds.
• Historical values will always produce the same results. During execution, the values will change until the bar closes.
Bộ dao động này tính toán cường độ định hướng của các thanh bằng cách sử dụng cơ chế cân nguyên thủy dựa trên một số lượng nhỏ những gì tôi cho là thuộc tính cơ bản của một thanh. Nó không xem xét biên độ của chuyển động giá, vì vậy có thể được sử dụng như một phần bổ sung cho các bộ dao động dựa trên động lượng.
Chỉ báo này sử dụng phân tích đơn giản về khối lượng giao dịch trong quá khứ để xác định mức độ hỗ trợ của nó đối với hoạt động thị trường gần đây. Cái mà tôi gọi là Độ nổi khối lượng đo lường sức mạnh và hướng của hỗ trợ đó.
LƯU Ý
• Tập lệnh có thể được sử dụng với bất kỳ khung thời gian biểu đồ nào, kể cả giây.
• Các giá trị lịch sử sẽ luôn tạo ra các kết quả giống nhau. Trong thời gian thực, các giá trị sẽ thay đổi cho đến khi thanh đóng lại.
Krong Stochastic_PicteIn technical analysis of securities trading the "stochastic indicator" is a "momentum indicator" that uses support and resistance levels. Dr. George Lane developed this indicator in the late 1950s. The term stochastic refers to the point of a current price in relation to its price range over a period of time. This method attempts to predict price turning points by comparing the closing price of a security to its price range.
The 5-period stochastic oscillator in a daily timeframe is defined as follows:
where H5 and L5 are the highest and lowest prices in the last 5 days respectively, while %D is the 3-day moving average of %K (the last 3 values of %K). Usually this is a simple moving average , but can be an exponential moving average for a less standardized weighting for more recent values. There is only one valid signal in working with %D alone — a divergence between %D and the analyzed security."
"in reality the "stochs" are just the rank of price plus a "sma" and have no predictive powers and are only a lagging description of price which helps with providing some context but treating it as anything more has led many to make wrong assumptions based on its direction or its value. "
The term stochastic is from the "stochastic process" which is a random process that can be defined as a collection of random variables that is indexed by some mathematical set, meaning that each random variable of the stochastic process is uniquely associated with an element in the set.
Which makes the use of the term by Dr . George Lane pretty ironic.
"This indicator is an attempt to improve upon the concept by sampling more of the data and combining multiple ranks to have a more accurate picture of price movement. Also hopefully to educate people about its shortcomings as well.
The concept was inspired by a crypto youtuber but we wanna make sure the community understands that this is not a "copy" its merely a "bioequivalent" made from diligent and methodical reverse engineering . so please if you use this and still wanted to purchase it please refer to the closed source equivalent.
We hope the community gets a kick out of it but more importantly get a different perspective on the mechanics of the stochastic oscillator. We also encourage modification and reuse of the code since we passed on a few ideas for exact graphical duplication. "
BUY EXAMPLES:
SELL EXAMPLES:
Stochastic RSI + RSI + MFI + RVI + Divergence IndicatorThis script is a simple edit of my previous script "Stoch.RSI+RSI+MFI+CM_Williams_Vix_Fix_V3"
It plots up to 4 oscillators (Stochastic RSI, RSI, MFI, RVI) and divergences between RSI and price. By default only Stochastic RSI, RSI and Regular divergences are enabled. But you can also enable the remaining oscillators and hidden divergences from the script settings.
So basically there are few, but significant, differences between this script and the original one.
Changelog:
- Removed the CM_Williams_Vix_fix code.
- Added RVI plot.
- Added divergences detection.
@Bezzus
Linda Raschke - PF3This is PF3 indicator where there are confluence agreement of 3 oscillators. Means the market is giving its most!
Adaptive SMI Ergodic StrategyThe Adaptive SMI Ergodic Strategy aims to capture the momentum and direction of a financial asset by leveraging the Stochastic Momentum Index Indicator (SMI) in an ergodic form. The strategy uses two lengths for the SMI, a shorter and a longer one, and an Exponential Moving Average (EMA) to serve as the signal line. Additionally, the strategy incorporates customizable overbought and oversold thresholds to improve the probability of successful trade execution.
How It Works:
Long Entry: A long position is taken when the ergodic SMI crosses over the EMA signal line, and both the SMI and EMA are below the oversold threshold.
Short Entry: A short position is initiated when the ergodic SMI crosses under the EMA signal line, and both the SMI and EMA are above the overbought threshold.
The strategy plots the SMI in yellow and the EMA signal line in purple. Horizontal lines indicate the overbought and oversold thresholds, and a colored background helps in visually identifying these zones.
Parameters:
Long Length: The length of the long EMA in SMI calculation.
Short Length: The length of the short EMA in SMI calculation.
Signal Line Length: The length for the EMA serving as the signal line.
Oversold: Customizable threshold for the oversold condition.
Overbought: Customizable threshold for the overbought condition.
Historical Context: The SMI Indicator
The Stochastic Momentum Index (SMI) was developed by William Blau in the early 1990s as an enhancement to traditional stochastic oscillators. The SMI provides a range of values like a traditional stochastic, but it differs in that it calculates the distance of the current close relative to the median of the high/low range, as opposed to the close relative to the low. As a result, the SMI is less erratic and more responsive, offering a clearer picture of market trends.
In recent years, the SMI has been adapted into ergodic forms to facilitate smoother data analysis, reduce lag, and improve trading accuracy. The Adaptive SMI Ergodic Strategy leverages these modern enhancements to offer a more robust, customizable trading strategy that aligns with various market conditions.
Chef MomentumChef momentum is a simple stochastic indicator that uses the hull moving average (hma). The oscillator can be used like most oscillators available.
Default setting:
%K length: 25
%K smoothing: 100
The user can adapt the parameters to study other values.
how to use :
When the length of the stoch K crossover hline 25 , a green circle appears which indicates the potential arrival of momentum.
When the length of the stock K crossover hline 80 , a red circle appears indicating the potential end of the momentum.
KPOS (Keltner Position)Shows closing prices relative to dynamic keltner channel (STARC bands), normalized as oscillator. Default settings are same as Adam H Grimes' who has posted some statistics on the bands. KPOS values show position of closing price relative to lower bands (as a percentage), such that 0 = lower band, 50 = ema (midpoint), and 100 = upper band. Bands can be widened or narrowed by adjusting ATR Multiple. Best used with confluence of support and resistance to identify momentum breakouts, continuations, and divergences.
wabba.1What you see is the close - hullMA (user defined length (source = open)) displayed as an oscillator.
When the red line crosses the green line from below 0 it could mean a short position = (red dot)
When the green line crosses the red line from below 0 it could mean a long position = ( green dot )
Enjoy:)
Noro's Shift Close Strategy v1.0It is Noro's Shift MA strategy, but looks as the oscillator. Positions open at the time of closing of a candle. Not the limit order. It is possible to use a pyramiding.
Stochastic RSI with Crossover AlertsThis draws your Stochastic RSI just like normal except it adds red or green squares everytime there is a crossover at the bottom or the top of the oscillator. Green crossover is bullish, red is bearish.
BTC/Dominance RSI by Sajad BagheriTitle: "BTC/Dominance RSI by Sajad Bagheri"
Description: "Combines BTC Price RSI (Red) and BTC Dominance RSI (Green) to detect trend conflicts and overbought/oversold conditions."
Category: Oscillators
Tags: #BTC, #Dominance, #RSI, #Bitcoin
Access: Public/Private
RSI Difference (Fast and Slow)Introduction
Oscillators like the RSI are fundamental tools for identifying trends in financial markets. Their ability to measure price momentum allows traders to detect overbought, oversold levels, and divergences, anticipating trend changes. Are there ways to improve the use of traditional RSI? How can we obtain more detailed information about current trends? This indicator answers these questions by expanding the functionalities of the traditional RSI and offering an additional tool for analysis.
How does it work?
This indicator provides a framework for trend analysis based on the following setup:
Fast RSI
Slow RSI
SMA of the fast RSI
SMA of the slow RSI
Histogram
Custom Indicator Settings
My preferred configuration is based on the 13 and 55 moving averages. The rest of the setup is as follows:
I typically use the 13 and 55 moving averages to configure both the RSI and short- and long-term moving averages.
Interpretation and Signals: Including a Long-Period RSI
Including a long-period RSI helps identify key patterns in market behavior. Crossovers between the two can be used to establish entry patterns:
If the fast RSI crosses above the slow RSI, this could indicate a long-entry pattern.
If the fast RSI crosses below the slow RSI, this could indicate a short-entry pattern.
Interpretation and Signals: Including Moving Averages
Including moving averages for both the short- and long-period RSI can help identify the base trend of the movement and, consequently:
Avoid false signals.
Trade in favor of the trend.
A simple way to start working with these is to use the crossover of the moving averages to identify the current trend:
If the short-period SMA is above the long-period SMA, the trend is bullish.
If the short-period SMA is below the long-period SMA, the trend is bearish.
Interpretation and Signals: The Histogram
The histogram represents the difference between the moving averages. If the histogram is positive, the short average is above the long average. If the histogram is below zero, the short average is below the long average. Divergences with price provide signals of potential exhaustion in the movement, indicating a possible reversal.
Indicator Details
This indicator builds upon the traditional RSI by integrating additional features that enhance its utility for traders. Here’s how each component is calculated and how they contribute to the originality of the script:
Fast RSI and Slow RSI: The fast RSI is calculated using a shorter lookback period, allowing it to capture rapid changes in momentum. The slow RSI uses a longer period to smooth out fluctuations and provide a broader view of the trend. These two RSIs work together to identify significant momentum shifts.
SMA of RSI values: The simple moving averages (SMA) of the fast and slow RSI help filter out noise and provide clear crossover signals. The SMAs are calculated using standard formulas but applied to the RSI values rather than price data, which adds a layer of insight into momentum trends.
Histogram calculation: The histogram represents the difference between the SMA of the fast RSI and the SMA of the slow RSI. This value gives a visual representation of the convergence or divergence of momentum. When the histogram crosses zero, it signifies a potential shift in the underlying trend.
This indicator combines multiple layers of analysis: fast and slow momentum, trend confirmation through SMAs, and divergence detection via the histogram. This multi-dimensional approach provides traders with a more comprehensive tool for trend analysis and decision-making.
Conclusion
This article has explored how to use this indicator to identify trends, leverage entry patterns, and analyze divergences by combining the fast RSI, slow RSI, their moving averages, and a histogram. Additionally, I’ve detailed how I usually interpret this indicator:
Identifying RSI patterns to anticipate momentum changes.
Using SMAs to confirm base trends.
Leveraging the histogram to detect divergences and potential price reversals.
Dynamic ZonesA port of the MT4 indicator of Mladen Rakic found at www.mql5.com
which is based on Dynamic Zones that was originally published in Stocks & Commodities 1996 issue.
Dynamic Zones is meant to be applied to oscillators to get dynamic overbought and oversold levels
quantified using statistical methods.
Parabolic Stoch SAR VisualizerParabolic Stoch SAR Visualizer — Momentum-Driven Trend Precision Tool
Overview:
Parabolic Stoch SAR Visualizer is a thoughtfully engineered hybrid indicator that blends momentum oscillation and trend-following mechanics into one robust system. By applying a custom Parabolic SAR calculation directly on a double-smoothed stochastic oscillator (rather than on price), it generates cleaner signals with enhanced trend detection and fewer false positives than typical Parabolic RSI or standard SAR variants.
Unique Functionality:
Momentum smoothing : The base stochastic %K undergoes double smoothing via consecutive simple moving averages, significantly cutting down random noise and erratic swings common in raw stochastic readings. This stabilizes momentum tracking, isolating true price strength and weakness.
Custom Parabolic SAR on smoothed momentum : Traditional SAR algorithms operate on price data, acting as trailing stops. This indicator repurposes SAR to work on smoothed stochastic values, effectively converting it into a momentum-driven directional filter. This yields a more adaptive and responsive trend signal focused on genuine momentum shifts instead of price noise.
Bounded SAR range and adjustable acceleration : SAR values are mathematically restricted between 0 and 100, aligning with the stochastic scale to prevent distortions. Traders can customize acceleration parameters (start, increment, max) to fine-tune trend sensitivity relative to market volatility or specific strategies.
Signal clarity through filterin g: Minimum bar spacing and minimum SAR movement thresholds between plotted dots reduce chart clutter, highlighting only meaningful trend changes and filtering out insignificant fluctuations.
Enhanced visuals : The oscillator line smoothly transitions its color gradient between defined uptrend and downtrend hues, intuitively signaling momentum strength. Parabolic SAR dots are offset from the oscillator line with multi-layered glow effects, making trend flips easy to spot at a glance.
Trading Application:
Trend identification : Momentum-based SAR dots offer precise marking of trend shifts, helping traders avoid false breakouts and premature trades.
Entry and exit timing : Combining the double-smoothed stochastic oscillator and SAR dots creates a reliable framework to confirm momentum shifts and optimal trade entries or exits.
Customizable for volatility regimes : Adjustable acceleration and filtering parameters allow scalpers to increase signal sensitivity, while swing traders can dial back noise for smoother trend recognition.
Visual clarity for fast decisions : Gradient color coding and glowing SAR dots facilitate immediate momentum assessment without complex analysis, empowering quicker, more confident trade actions.
Advantages over Parabolic RSI and similar indicators:
Parabolic RSI’s direct application of SAR on RSI often results in noisy, choppy signals prone to whipsaws. This indicator’s double-smoothed stochastic foundation delivers a cleaner, steadier signal.
Applying SAR to smoothed momentum rather than price transforms it into a directional filter that better captures true market strength with reduced lag.
Adaptive plotting thresholds and enhanced visuals minimize clutter and ambiguity, improving trader focus and execution speed.
Sri_Momentum Sri_Momentum - Advanced Oscillator for Market Trends
Description
The Sri_Momentum is a powerful momentum-based oscillator that helps traders analyze price trends and market strength. This indicator utilizes two simple moving averages (SMA) to calculate the Awesome Oscillator (AO) and a signal line for trend confirmation. The histogram dynamically changes color based on the crossover between AO and the signal line, providing clear bullish and bearish signals.
✅ Awesome Oscillator (AO) Calculation - Measures market momentum using a fast and slow SMA.
✅ Signal Line for Confirmation - A smoothed moving average of AO to help traders identify trend shifts.
✅ Dynamic Histogram Color Coding - Easy-to-interpret histogram with four colors indicating trend strength and direction.
✅ Custom Sensitivity Input - Adjusts the AO calculation to fine-tune responsiveness.
✅ Zero Line Reference - A baseline to differentiate bullish and bearish momentum.
How It Works
Fast SMA (default: 5-period) and Slow SMA (default: 34-period) are calculated based on the average of high and low prices.
AO (Awesome Oscillator) = (Fast SMA - Slow SMA) * Sensitivity
Signal Line = Smoothed AO using a 7-period SMA
Histogram Color Logic:
🔵 Strong Bullish → AO > Signal & AO ≥ 0 (Green)
🔴 Weak Bullish → AO > Signal & AO < 0 (Light Red)
🟢 Weak Bearish → AO < Signal & AO ≥ 0 (Light Green)
🔥 Strong Bearish → AO < Signal & AO < 0 (Dark Red)
How to Use the Sri_Momentum Indicator
📌 Bullish Momentum → When AO crosses above the Signal Line, and the histogram turns green.
📌 Bearish Momentum → When AO crosses below the Signal Line, and the histogram turns red.
📌 Trend Strength → Darker colors indicate stronger trends; lighter colors suggest weaker trends.
📌 Zero Line Crossover → If AO moves above zero, it suggests bullish strength; if below zero, bearish control.
MA Deviation
Script description
A script that displays the deviation rate of the specified moving average line.
You can non-display the oscillator line by setting it.
Default setting
Moving average divergence rate : 25 SMA
Oscillator line (50) : display
Oscillator line (75) : non-display
Oscillator line (100) : non-display
スクリプトの説明
指定した移動平均線の乖離率を表示するスクリプトです。
設定によりオシレーター上の水平線の表示非表示を切り替えることができます。
デフォルト設定
移動平均乖離率：25 SMA
水平線(50)：表示
水平線(75)：非表示
水平線(100)：非表示
Pulse DPO with Z-Score📌 Pulse DPO with Z-Score — Indicator Description (English)
The Pulse DPO (Detrended Price Oscillator) helps identify major market cycle tops and bottoms by removing long-term trends and focusing on shorter-term price cycles.
This enhanced version includes:
A normalized oscillator (0–100) based on recent price deviations.
A smoothed signal to reduce noise.
A Z-Score transformation, scaling the output to a range from –3 to +3, where:
–3 represents extreme oversold conditions (former normalized value = 100),
+3 represents extreme overbought conditions (former normalized value = 1).
🔍 How it works:
The indicator subtracts a delayed moving average from price to isolate short-term cycles (DPO logic).
It then normalizes the oscillator within a lookback window.
Finally, it converts this to a Z-Score scale for easier interpretation of extremes.
🟢 Suggested Usage:
Consider Long entries or Short exits when Z-Score reaches –2 to –3 (deep oversold).
Consider Short entries or Long exits when Z-Score reaches +2 to +3 (deep overbought).
Use in combination with other signals for higher-confidence setups.
RSI and CCICombined RSI and CCI Indicator for MetaTrader
The Combined RSI and CCI Indicator is a powerful hybrid momentum oscillator designed to merge the strengths of two popular indicators—the Relative Strength Index (RSI) and the Commodity Channel Index (CCI)—into a single, visually intuitive chart window. This tool enhances traders’ ability to identify overbought and oversold conditions, divergences, trend strength, and potential reversal zones with improved precision.
Purpose
By integrating RSI and CCI, this indicator helps filter out false signals that often occur when using each tool independently. It is especially useful for swing trading, trend confirmation, and spotting high-probability entry/exit zones. This dual-oscillator approach combines RSI’s relative momentum insights with CCI’s deviation-based analysis to produce a more reliable signal structure.
Key Features
Dual Oscillator Display: Plots both RSI and CCI on the same subwindow for easy comparison and correlation analysis.
Customizable Parameters:
RSI Period and Level (default: 14)
CCI Period and Typical Price Type (default: 20, TP)
Overbought/Oversold Levels for both indicators
Color-Coded Zones:
Background highlights when both RSI and CCI enter overbought/oversold territory, signaling high potential reversal zones.
Combined Signal Logic (Optional Feature):
Buy Signal: RSI < 30 and CCI < -100
Sell Signal: RSI > 70 and CCI > 100
These can be visualized as arrows or plotted as signal markers.
Trend Filter Overlay (Optional):
Can be combined with a moving average or price action filter to confirm trend direction before accepting signals.
Divergence Detection (Advanced Option):
Optional plotting of bullish or bearish divergence where both indicators diverge from price action.
Multi-Timeframe Compatibility:
Allows the use of higher timeframe RSI/CCI values to confirm signals on lower timeframes.
Benefits
Improved Signal Accuracy: Using both RSI and CCI together helps avoid false breakouts and whipsaws.
More Informed Decision-Making: Correlating momentum (RSI) with deviation (CCI) provides a well-rounded picture of market behavior.
Efficient Charting: Saves screen space and cognitive load by combining two indicators into one clean panel.
Scalable Strategy Integration: Can be used in discretionary trading or coded into automated strategies/alerts.
Use Case Example
In a ranging market, the indicator highlights zones where both RSI and CCI are oversold, alerting traders to potential bounce opportunities.
In trending markets, it confirms trend strength when RSI and CCI are both aligned with trend direction.
When RSI is diverging from price but CCI isn’t, it can be a clue of weakening momentum, helping traders scale out or avoid traps.
This combined indicator offers a versatile, high-performance toolset for traders looking to elevate their technical analysis by leveraging multiple momentum perspectives simultaneously.
RSI %b Signal [H1 Backtesting]-----------------------------------------------------------------
This simple strategy base on RSI, EMA, Bollinger Bands to get Buy and Sell Signal with detail as below:
-----------------------------------------------------------------
1.Define Oscillator Line
+ Oscillator Line is smoothed by ema(28) of RSI(14) on H1 Timeframe
2.Define Overbought and Oversold
+ Apply Bollinger Bands BB(80,3) on Oscillator Line and calculate %b
+ Overbought Zone marked above level 0.8
+ Oversold Zone marked below level 0.2
3.Buy Signal
+ Entry Long Position when %b crossover Point of Entry Long
+ Deafault Point of Entry Long is 0.2
+ Buy signal marked by Green dot
4.Sell Signal
+ Entry Short Position when %b crossunder Point of Entry Short
+ Deafault Point of Entry Short is 0.8
+ Sell signal marked by Red dot
5.Exit Signal
+ Exit Position (both Long and Short) when %b go into Overbought Zone or Oversold Zone
+ Exit signal marked by Yellow dot
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Nilpyx - Buy, sell signalThis indicator detects market entry signals.
Green Oscillator = Buy
Blue Oscillator = Do nothing
Red oscillator = Sell
// ESP
Oscilador verde = compra
Oscilador azul = No hacer nada
Oscilador rojo = venta
