Rube Goldberg Top/Bottom Finder [theUltimator5]This is what I call the Rube Goldberg Top and Bottom Finder. It is an overly complex method of plotting a simple buy or sell label on a chart.
I utilize several standard TA techniques along with several of my own to try and locate ideal Buy/Sell conditions. I came up with the name because there are way too many conditional variables to come up with a single buy or sell condition, when most standard indicators use simple crossovers or levels.
There are two unique triggers that are calculated using completely independent techniques. If both triggers turn true within a small timeframe between each other, the buy/sell trigger turns true and plots a "buy" or "sell" label on the chart.
This indicator was designed to be fully functioning out of the box and can be customized only if the user wishes to. It is effective on all timeframes, but longer timeframes (daily +) may require signal length adjustment for best results.
imgur.com
The signals used in the leading trigger are as follows:
(1)RSI
The user can select among any of the following moving averages (base is EMA) (#3) , and have an RSI generated at a user defined length (base is 14). (#4)
SMA, EMA, DEMA, TEMA, WMA, VWMA, SMMA, HMA, LSMA, ALMA
The user can select whether or not the RSI is filtered with the following options:
None, Kalman, Double EMA, ALMA
The filter conditions are hard coded to minimize the amount of selections that the user is required to make to reduce the user interface complexity.
The user can define overbought (base 70) and oversold (base 30) conditions. (#2)
When the RSI crosses above or below the threshold values, the plot will turn red. This creates condition 1 of the leading trigger.
(2) ADX and DI
This portion of the indicator is a derivative of my ADX Divergence and Gap Monitor indicator.
This technique looks at the ADX value as well as for spikes in either +DI or -DI for large divergences. When the ADX reaches a certain threshold and also outpaces a preset ADX moving average, this creates condition 2 of the leading trigger.
There is an additional built-in functionality in this portion of the indicator that looks for gaps. It triggers when the ADX is below a certain threshold value and either the +DI or -DI spike above a certain threshold value, indicating a sudden gap in price after a period of low volatility.
The user can set whether or nor to show when a gap appears on the chart or as a label on the plot below the chart (disabled by default) . If the user chooses to overlay gaps on the chart, it creates a horizontal fill showing the starting point of the gap. The theory here is that the price will return at some point in the near future to the starting point of the gap.
imgur.com
(3) DI based Multi-Symbol reference and divergence
Part of the script computes both the +DI (positive directional index) and -DI (negative directional index) for the currently selected chart symbol and three reference symbols.
The averaged directional move of the reference symbols are compared to the current ticker on your chart and if the divergence exceeds a certain threshold, then the third condition of the trigger is met.
The components that are referenced are based on what stock/chart you are looking at. The script automatically detects if you are looking at a crypto, and uses a user selectable toggle between Large Cap or Small Cap. (#1) The threshold levels are determined by the asset type and market cap.
The leading trigger highlights under several conditions:
1) All (3) portions of the trigger result in true simultaneously
OR
2) Any of triggers 2 or 3 reach a certain threshold that indicates extreme market/price divergence as well as trigger 1 being overbought or oversold.
AND
3) If the trigger didn't highlight
For the lagging part of the trigger:
The lagging trigger is used as a confirmation after the leading trigger to indicate a possible optimized entry/exit point. It can also be used by itself, as well as the leading indicator.
The lagging indicator utilizes the parabolic Stop And Reverse (SAR). It utilizes the RSI length that is defined in portion 1 of the leading trigger as well as the overbought and oversold thresholds. I have found excellent results in catching reversals because it catches rate-of-change events rather than price reversals alone.
imgur.com
When both the leading triggers FOLLOWED BY the lagging trigger result in true within a user defined timeframe, then the buy or sell trigger results in true, plotting a label on the chart.
All portions of the leading and lagging indicators can be toggled on or off, but most of them are toggled off by default in order to reduce noise on the plot.
imgur.com
The leading, lagging, and buy/sell triggers each have built-in alerts that can be toggled on or off in the alert menu.
I have an optional built-in toggle to show green or red dots on the RSI line using two separate RSI lengths that are amplified and plot based on RSI divergence and strength. This can be used as a visual confirmation (or rejection) against the chart overlay plots.
imgur.com
This indicator is not a strategy, so there are no built-in exits or stop losses.
Pengayun
Gap Reversal Signal with Indicators🔍 Gap Reversal Signal with Indicators — 結合 KD、MACD、SAR 與背離分析的多功能指標
🔍 Gap Reversal Signal with Indicators — A Multi-Tool Signal Indicator Combining KD, MACD, SAR, and Divergence Analysis
中文說明：
本指標結合多種常用技術分析工具，包括 KD 隨機指標、MACD 動能交叉、SAR 趨勢方向、以及 MACD 背離偵測，用以辨識潛在的價格反轉區域。適用於日內交易與波段操作，支援各類市場，如加密貨幣、股票與外匯等。
English Description:
This indicator combines several popular technical tools: Stochastic KD, MACD momentum crossovers, SAR trend direction, and MACD divergence detection. It helps traders identify potential reversal areas and is ideal for both intraday and swing trading. Works well on crypto, stocks, and forex markets.
🧠 功能特點 | Key Features
✅ KD指標（慢速隨機指標）檢測超買超賣並提供%K與%D交叉訊號
✅ Stochastic KD (slow) to detect overbought/oversold zones and crossover signals
✅ MACD金叉/死叉與零軸突破捕捉趨勢轉變與動能反轉
✅ MACD Crossovers + Zero-Line Breaks to capture trend changes and momentum reversals
✅ SAR指標即時顯示多空方向
✅ Parabolic SAR for real-time trend direction indication
✅ MACD背離偵測協助辨識潛在反轉區域
✅ MACD Divergence Detection for identifying hidden trend reversals
✅ 圖形提示與標籤提示可視化呈現各類訊號
✅ Visual Alerts and Labels for easy and quick signal recognition
📈 支援市場 | Supported Markets
📊 台股 / 美股 / 外匯 / 加密貨幣
📊 Taiwan Stocks / US Stocks / Forex / Cryptocurrencies (e.g. BTC, ETH)
🔧 推薦用法 | Recommended Use
搭配缺口策略與支撐壓力位使用
Use with gap-trading strategies and support/resistance zones
用於盤整末期或趨勢反轉的提示
Helpful for end-of-consolidation signals or trend reversals
支援短線與波段交易風格
Suitable for scalping and swing trading styles
💡 把這個指標加入你的圖表，立即體驗多重技術分析所帶來的交易優勢！
💡 Add this indicator to your chart now and experience the power of multi-tool technical analysis!
Stochastic RainbowThe Stochastic Rainbow indicator is a multi-layered momentum oscillator designed to provide a comprehensive view of market dynamics by combining multiple stochastic oscillators of varying periods. This approach allows traders to analyze both short-term and long-term momentum within a single visual framework, enhancing decision-making for entries and exits.
🔧 Indicator Settings and Customization
Select from various moving average methods (e.g., SMA, EMA, DEMA, TEMA, WMA, VWMA, RMA, T3) to smooth the stochastic lines. Different methods can affect the responsiveness of the indicator.
The indicator computes five sets of stochastic oscillators with Fibonacci values.
Each %K line is smoothed using the selected moving average type, and a corresponding %D line is plotted for each %K.
🎨 Visual Interpretation
The Stochastic Rainbow indicator plots multiple %K and %D lines, each with distinct colors for easy differentiation.
Additionally, horizontal dotted lines are drawn at levels 80 (Upper Band), 50 (Midline), and 20 (Lower Band) to indicate overbought, neutral, and oversold conditions, respectively.
📈 Trading Strategies Using Stochastic Rainbow
The multi-layered structure of the Stochastic Rainbow allows for nuanced analysis.
Trend Confirmation:
When all %K lines are above 50 and aligned in ascending order (short-term above long-term), it suggests a strong uptrend.
Conversely, when all %K lines are below 50 and aligned in descending order, it indicates a strong downtrend.
Overbought/Oversold Conditions:
If the shorter-term %K lines (e.g., %K 5,3 and %K 8,3) enter the overbought zone (>80) while longer-term lines remain below, it may signal a potential reversal.
Similarly, if shorter-term lines enter the oversold zone (<20) while longer-term lines remain above, it could indicate an upcoming bullish reversal.
Crossovers:
A bullish signal occurs when a %K line crosses above its corresponding %D line.
A bearish signal occurs when a %K line crosses below its corresponding %D line.
Divergence Analysis:
If price makes a new high while the %K lines do not, it may indicate bearish divergence and a potential reversal.
If price makes a new low while the %K lines do not, it may indicate bullish divergence and a potential reversal.
⚙️ Adjusting Settings for Optimal Use
The Stochastic Rainbow's flexibility allows traders to adjust settings to match their trading style and the specific asset's behavior:
Short-Term Trading: Use shorter periods (e.g., 5 for %K) and more responsive moving averages (e.g., WMA, VWMA, EMA, DEMA, TEMA, HMA) to capture quick market movements.
Long-Term Trading: Opt for longer periods (e.g., 55 for %K) and smoother moving averages (e.g., SMA, RMA, T3) to filter out noise and focus on broader trends.
Volatile Markets: Consider using the T3 moving average for its smoothing capabilities, helping to reduce false signals in choppy markets.
By experimenting with different settings, traders can fine-tune the indicator to better suit their analysis and improve decision-making.
Volume Flow OscillatorVolume Flow Oscillator
Overview
The Volume Flow Oscillator is an advanced technical analysis tool that measures buying and selling pressure by combining price direction with volume. Unlike traditional volume indicators, this oscillator reveals the force behind price movements, helping traders identify strong trends, potential reversals, and divergences between price and volume.
Reading the Indicator
The oscillator displays seven colored bands that fluctuate around a zero line:
Three bands above zero (yellow) indicate increasing levels of buying pressure
Three bands below zero (red) indicate increasing levels of selling pressure
The central band represents the baseline volume flow
Color intensity changes based on whether values are positive or negative
Trading Signals
The Volume Flow Oscillator provides several valuable trading signals:
Zero-line crossovers: When multiple bands cross from negative to positive, potential bullish shift; opposite for bearish
Divergences: When price makes new highs/lows but oscillator bands fail to confirm, signals potential reversal
Volume climax: Extreme readings where outer bands stretch far from zero often precede reversals
Trend confirmation: Strong expansion of bands in direction of price movement confirms genuine momentum
Support/resistance: During trends, bands may remain largely on one side of zero, showing continued directional pressure
Customization
Adjust these key parameters to optimize the oscillator for your trading style:
Lookback Length: Controls overall sensitivity (shorter = more responsive, longer = smoother)
Multipliers: Adjust sensitivity spread between bands for different market conditions
ALMA Settings: Fine-tune how the indicator weights recent versus historical data
VWMA Toggle: Enable for additional smoothing in volatile markets
Best Practices
For optimal results, use this oscillator in conjunction with price action and other confirmation indicators. The multi-band approach helps distinguish between minor fluctuations and significant volume events that might signal important market turns.
Macd, Wt Cross & HVPMacd Wt Cross & HVP – Advanced Multi-Signal Indicator
This script is a custom-designed multi-signal indicator that brings together three proven concepts to provide a complete view of market momentum, reversals, and volatility build-ups. It is built for traders who want to anticipate key market moves, not just react to them.
Why This Combination ?
While each tool has its strengths, their combined use creates powerful signal confluence.
Instead of juggling multiple indicators separately, this script synchronizes three key perspectives into a single, intuitive display—helping you trade with greater clarity and confidence.
1. MACD Histogram – Momentum and Trend Clarity
At the core of the indicator is the MACD histogram, calculated as the difference between two exponential moving averages (EMAs).
Color-coded bars represent momentum direction and intensity:
Green / blue bars: bullish momentum
Red / pink bars: bearish momentum
Color intensity shows acceleration or weakening of trend.
This visual makes it easy to detect trend shifts and momentum divergence at a glance.
2. WT Cross Signals – Early Reversal Detection
Overlaid on the histogram are green and red dots, based on the logic of the WaveTrend oscillator cross:
Green dots = potential bullish cross (buy signal)
Red dots = potential bearish cross (sell signal)
These signals are helpful for identifying reversal points during both trending and ranging phases.
3. Historical Volatility Percentile (HVP) – Volatility Compression Zones
Behind the histogram, purple vertical zones highlight periods of low historical volatility, based on the HVP:
When volatility compresses below a specific threshold, these zones appear.
Such periods are often followed by explosive price moves, making them prime areas for pre-breakout positioning.
By integrating HVP, the script doesn’t just tell you where the trend is—it tells you when the trend is likely to erupt.
How to Use This Script
Use the MACD histogram to confirm the dominant trend and its strength.
Watch for WT Cross dots as potential entry/exit signals in alignment or divergence with the MACD.
Monitor HVP purple zones as warnings of incoming volatility expansions—ideal moments to prepare for breakout trades.
Best results occur when all three elements align, offering a high-probability trade setup.
What Makes This Script Original?
Unlike many mashups, this script was not created by simply merging indicators. Each component was carefully integrated to serve a specific, complementary purpose:
MACD detects directional bias
WT Cross adds precision timing
HVP anticipates volatility-based breakout timing
This results in a strategic tool for traders, useful on multiple timeframes and adaptable to different trading styles (trend-following, breakout, swing).
Stochastic XThe "Stochastic X" script is a customizable momentum oscillator designed to help traders identify potential overbought and oversold conditions, as well as trend reversals, by analyzing the relationship between a security's closing price and its price range over a specified period. This indicator is particularly useful for traders looking to fine-tune their entry and exit points based on momentum shifts.
🔧 Indicator Settings and Customization
The script offers several user-configurable settings to tailor the indicator to specific trading strategies:
In addition to the source type, %K Period, %D Period, and Signal line periods you can now change moving average calculation for the stochastic and signal lines.
This script allows selection among various moving average methods (e.g., SMA, EMA, WMA, T3) for smoothing the %K and signal lines. Different methods can affect the responsiveness of the indicator.
🎨 Interpreting Background Colors
The script enhances visual analysis by changing the background color of the indicator panel based on the %K line's value:
Green Background: Indicates that the %K line is above 50, suggesting bullish momentum.
Red Background: Signifies that the %K line is below 50, pointing to bearish momentum.
Light Green Overlay: Appears when the %K line exceeds 80, highlighting overbought conditions.
Light Red Overlay: Shows up when the %K line falls below 20, indicating oversold conditions.
These visual cues assist traders in quickly assessing market momentum and potential reversal.
📈 Trading Strategies Using Stochastic X
Traders can utilize the Stochastic X indicator in various ways:
Overbought/Oversold Conditions:
A %K value above 80 may suggest that the asset is overbought, potentially signaling a price correction.
A %K value below 20 could indicate that the asset is oversold, possibly leading to a price rebound.
Signal Line Crossovers:
When the %K line crosses above the signal line, it may be interpreted as a bullish signal.
Conversely, a %K line crossing below the signal line might be seen as a bearish signal.
Divergence Analysis:
If the price makes a new high while the %K line does not, this bearish divergence could precede a price decline.
If the price hits a new low but the %K line forms a higher low, this bullish divergence might signal an upcoming price increase.
Trend Confirmation:
Sustained %K values above 50 can confirm an uptrend.
Persistent %K values below 50 may validate a downtrend.
In this chart, observe how the background colors change in response to the %K line's value, providing immediate visual feedback on market conditions. The crossovers between the %K and signal lines offer potential entry and exit points, while the overbought and oversold overlays help identify possible reversal zones.
⚙️ Adjusting Settings for Optimal Use
The Stochastic X indicator's flexibility allows traders to adjust settings to match their trading style and the specific asset's behavior:
Short-Term Trading: Use shorter periods (e.g., 5 for %K) and more responsive moving averages (e.g., WMA, VWMA, EMA, DEMA, TEMA, HMA) to capture quick market movements.
Long-Term Trading: Opt for longer periods (e.g., 14 for %K) and smoother moving averages (e.g., SMA, RMA, T3) to filter out noise and focus on broader trends.
Volatile Markets: Consider using the T3 moving average for its smoothing capabilities, helping to reduce false signals in choppy markets.
By experimenting with different settings, traders can fine-tune the indicator to better suit their analysis and improve decision-making.
Bitcoin Power LawThis is the main body version of the script. The Oscillator version can be found here.
Understanding the Bitcoin Power Law Model
Also called the Long-Term Bitcoin Power Law Model. The Bitcoin Power Law model tries to capture and predict Bitcoin's price growth over time. It assumes that Bitcoin's price follows an exponential growth pattern, where the price increases over time according to a mathematical relationship.
By fitting a power law to historical data, the model creates a trend line that represents this growth. It then generates additional parallel lines (support and resistance lines) to show potential price boundaries, helping to visualize where Bitcoin’s price could move within certain ranges.
In simple terms, the model helps us understand Bitcoin's general growth trajectory and provides a framework to visualize how its price could behave over the long term.
The Bitcoin Power Law has the following function:
Power Law = 10^(a + b * log10(d))
Consisting of the following parameters:
a: Power Law Intercept (default: -17.668).
b: Power Law Slope (default: 5.926).
d: Number of days since a reference point(calculated by counting bars from the reference point with an offset).
Explanation of the a and b parameters:
Roughly explained, the optimal values for the a and b parameters are determined through a process of linear regression on a log-log scale (after applying a logarithmic transformation to both the x and y axes). On this log-log scale, the power law relationship becomes linear, making it possible to apply linear regression. The best fit for the regression is then evaluated using metrics like the R-squared value, residual error analysis, and visual inspection. This process can be quite complex and is beyond the scope of this post.
Applying vertical shifts to generate the other lines:
Once the initial power-law is created, additional lines are generated by applying a vertical shift. This shift is achieved by adding a specific number of days (or years in case of this script) to the d-parameter. This creates new lines perfectly parallel to the initial power law with an added vertical shift, maintaining the same slope and intercept.
In the case of this script, shifts are made by adding +365 days, +2 * 365 days, +3 * 365 days, +4 * 365 days, and +5 * 365 days, effectively introducing one to five years of shifts. This results in a total of six Power Law lines, as outlined below (From lowest to highest):
Base Power Law Line (no shift)
1-year shifted line
2-year shifted line
3-year shifted line
4-year shifted line
5-year shifted line
The six power law lines:
Bitcoin Power Law Oscillator
This publication also includes the oscillator version of the Bitcoin Power Law. This version applies a logarithmic transformation to the price, Base Power Law Line, and 5-year shifted line using the formula: log10(x) .
The log-transformed price is then normalized using min-max normalization relative to the log-transformed Base Power Law Line and 5-year shifted line with the formula:
normalized price = log(close) - log(Base Power Law Line) / log(5-year shifted line) - log(Base Power Law Line)
Finally, the normalized price was multiplied by 5 to map its value between 0 and 5, aligning with the shifted lines.
Interpretation of the Bitcoin Power Law Model:
The shifted Power Law lines provide a framework for predicting Bitcoin's future price movements based on historical trends. These lines are created by applying a vertical shift to the initial Power Law line, with each shifted line representing a future time frame (e.g., 1 year, 2 years, 3 years, etc.).
By analyzing these shifted lines, users can make predictions about minimum price levels at specific future dates. For example, the 5-year shifted line will act as the main support level for Bitcoin’s price in 5 years, meaning that Bitcoin’s price should not fall below this line, ensuring that Bitcoin will be valued at least at this level by that time. Similarly, the 2-year shifted line will serve as the support line for Bitcoin's price in 2 years, establishing that the price should not drop below this line within that time frame.
On the other hand, the 5-year shifted line also functions as an absolute resistance , meaning Bitcoin's price will not exceed this line prior to the 5-year mark. This provides a prediction that Bitcoin cannot reach certain price levels before a specific date. For example, the price of Bitcoin is unlikely to reach $100,000 before 2021, and it will not exceed this price before the 5-year shifted line becomes relevant. After 2028, however, the price is predicted to never fall below $100,000, thanks to the support established by the shifted lines.
In essence, the shifted Power Law lines offer a way to predict both the minimum price levels that Bitcoin will hit by certain dates and the earliest dates by which certain price points will be reached. These lines help frame Bitcoin's potential future price range, offering insight into long-term price behavior and providing a guide for investors and analysts. Lets examine some examples:
Example 1:
In Example 1 it can be seen that point A on the 5-year shifted line acts as major resistance . Also it can be seen that 5 years later this price level now corresponds to the Base Power Law Line and acts as a major support at point B (Note: Vertical yearly grid lines have been added for this purpose👍).
Example 2:
In Example 2, the price level at point C on the 3-year shifted line becomes a major support three years later at point D, now aligning with the Base Power Law Line.
Finally, let's explore some future price predictions, as this script provides projections on the weekly timeframe :
Example 3:
In Example 3, the Bitcoin Power Law indicates that Bitcoin's price cannot surpass approximately $808K before 2030 as can be seen at point E, while also ensuring it will be at least $224K by then (point F).
WaveTrend [LazyBear] with Long/Short LabelsWaveTrend Oscillator with Entry Signals (LONG/SHORT) – Advanced Edition
This indicator is based on the renowned WaveTrend Oscillator by LazyBear, a favorite among professional traders for spotting trend reversals with precision.
🚀 Features:
Original WaveTrend formula with dual-line structure (WT1 & WT2).
Customizable overbought and oversold zones for visual clarity.
Automatic LONG and SHORT signals plotted directly on the chart:
✅ LONG: When WT1 crosses above WT2 below the oversold zone.
❌ SHORT: When WT1 crosses below WT2 above the overbought zone.
Momentum histogram shows strength of market moves.
Fully optimized for Pine Script v5 and lightweight across all timeframes.
🔍 How to use:
Combine with support/resistance levels or candlestick reversal patterns.
Works best on 15min, 1H, or 4H charts.
Suitable for all markets: crypto, stocks, forex, indices.
📊 Ideal for:
Traders seeking clean, reliable entry signals.
Reversal strategies with technical confluence.
Visual confirmation of WaveTrend crossovers without manual interpretation.
💡 Pro Tip: Combine with EMA or RSI filters to further enhance accuracy.
Volume Spike Filter### Volume Spike Detector with Alerts
**Overview:**
This indicator helps traders quickly identify unusual spikes in trading volume by comparing the current volume against a simple moving average (SMA) threshold. It's particularly useful for beginners seeking clear signals of increased market activity.
**Settings:**
* **SMA Length:** Defines the period for calculating the average volume (default = 20).
* **Multiplier:** Determines how much the volume must exceed the SMA to be considered a spike (default = 1.5).
* **Highlight Spikes:** Toggle to visually highlight spikes on the chart (default = enabled).
**Signals:**
* 🟩 **Highlighted Background:** Indicates a volume spike that surpasses the defined threshold.
* 🏷️ **"Vol Spike" Label:** Clearly marks the exact bar of the spike for quick reference.
**Usage:**
Use these clear volume spike alerts to identify potential trading opportunities, confirmations, or shifts in market momentum. Combine this with other technical indicators for enhanced analysis.
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
TASC 2025.06 Cybernetic Oscillator█ OVERVIEW
This script implements the Cybernetic Oscillator introduced by John F. Ehlers in his article "The Cybernetic Oscillator For More Flexibility, Making A Better Oscillator" from the June 2025 edition of the TASC Traders' Tips . It cascades two-pole highpass and lowpass filters, then scales the result by its root mean square (RMS) to create a flexible normalized oscillator that responds to a customizable frequency range for different trading styles.
█ CONCEPTS
Oscillators are indicators widely used by technical traders. These indicators swing above and below a center value, emphasizing cyclic movements within a frequency range. In his article, Ehlers explains that all oscillators share a common characteristic: their calculations involve computing differences . The reliance on differences is what causes these indicators to oscillate about a central point.
The difference between two data points in a series acts as a highpass filter — it allows high frequencies (short wavelengths) to pass through while significantly attenuating low frequencies (long wavelengths). Ehlers demonstrates that a simple difference calculation attenuates lower-frequency cycles at a rate of 6 dB per octave. However, the difference also significantly amplifies cycles near the shortest observable wavelength, making the result appear noisier than the original series. To mitigate the effects of noise in a differenced series, oscillators typically smooth the series with a lowpass filter, such as a moving average.
Ehlers highlights an underlying issue with smoothing differenced data to create oscillators. He postulates that market data statistically follows a pink spectrum , where the amplitudes of cyclic components in the data are approximately directly proportional to the underlying periods. Specifically, he suggests that cyclic amplitude increases by 6 dB per octave of wavelength.
Because some conventional oscillators, such as RSI, use differencing calculations that attenuate cycles by only 6 dB per octave, and market cycles increase in amplitude by 6 dB per octave, such calculations do not have a tangible net effect on larger wavelengths in the analyzed data. The influence of larger wavelengths can be especially problematic when using these oscillators for mean reversion or swing signals. For instance, an expected reversion to the mean might be erroneous because oscillator's mean might significantly deviate from its center over time.
To address the issues with conventional oscillator responses, Ehlers created a new indicator dubbed the Cybernetic Oscillator. It uses a simple combination of highpass and lowpass filters to emphasize a specific range of frequencies in the market data, then normalizes the result based on RMS. The process is as follows:
Apply a two-pole highpass filter to the data. This filter's critical period defines the longest wavelength in the oscillator's passband.
Apply a two-pole SuperSmoother (lowpass filter) to the highpass-filtered data. This filter's critical period defines the shortest wavelength in the passband.
Scale the resulting waveform by its RMS. If the filtered waveform follows a normal distribution, the scaled result represents amplitude in standard deviations.
The oscillator's two-pole filters attenuate cycles outside the desired frequency range by 12 dB per octave. This rate outweighs the apparent rate of amplitude increase for successively longer market cycles (6 dB per octave). Therefore, the Cybernetic Oscillator provides a more robust isolation of cyclic content than conventional oscillators. Best of all, traders can set the periods of the highpass and lowpass filters separately, enabling fine-tuning of the frequency range for different trading styles.
█ USAGE
The "Highpass period" input in the "Settings/Inputs" tab specifies the longest wavelength in the oscillator's passband, and the "Lowpass period" input defines the shortest wavelength. The oscillator becomes more responsive to rapid movements with a smaller lowpass period. Conversely, it becomes more sensitive to trends with a larger highpass period. Ehlers recommends setting the smallest period to a value above 8 to avoid aliasing. The highpass period must not be smaller than the lowpass period. Otherwise, it causes a runtime error.
The "RMS length" input determines the number of bars in the RMS calculation that the indicator uses to normalize the filtered result.
This indicator also features two distinct display styles, which users can toggle with the "Display style" input. With the "Trend" style enabled, the indicator plots the oscillator with one of two colors based on whether its value is above or below zero. With the "Threshold" style enabled, it plots the oscillator as a gray line and highlights overbought and oversold areas based on the user-specified threshold.
Below, we show two instances of the script with different settings on an equities chart. The first uses the "Threshold" style with default settings to pass cycles between 20 and 30 bars for mean reversion signals. The second uses a larger highpass period of 250 bars and the "Trend" style to visualize trends based on cycles spanning less than one year:
Disparity Index with Volatility ZonesDisparity Index with Volatility Zones
is a momentum oscillator that measures the percentage difference between the current price and its simple moving average (SMA). This allows traders to identify overbought/oversold conditions, assess momentum strength, and detect potential trend reversals or continuations.
🔍 Core Concept:
The Disparity Index (DI) is calculated as:
DI = 100 × (Price − SMA) / SMA
A positive DI indicates the price is trading above its moving average (potential bullish sentiment), while a negative DI suggests the price is below the average (potential bearish sentiment).
This version of the Disparity Index introduces a dual-zone volatility framework, offering deeper insight into the market's current state.
🧠 What Makes This Version Unique?
1. High Volatility Zones
When DI crosses above +1.0% or below –1.0%, it often indicates the start or continuation of a strong trend.
Sustained readings beyond these thresholds typically align with trending phases, offering opportunities for momentum-based entries.
A reversal back within ±1.0% after exceeding these levels can suggest a shift in momentum — similar to how RSI exits the overbought/oversold zones before reversals.
These thresholds act as dynamic markers for breakout confirmation and potential trend exhaustion.
2. Low Volatility Zones
DI values between –0.5% and +0.5% define the low-volatility zone, shaded for visual clarity.
This area typically indicates market indecision, sideways price action, or consolidation.
Trading within this range may favor range-bound or mean-reversion strategies, as trend momentum is likely limited.
The logic is similar to interpreting a flat ADX, tight Bollinger Bands, or contracting Keltner Channels — all suggesting consolidation.
⚙️ Features:
Customizable moving average length and input source
Adjustable thresholds for overbought/oversold and low-volatility zones
Optional visual fill between low-volatility bounds
Clean and minimal chart footprint (non-essential plots hidden by default)
📈 How to Use:
1. Trend Confirmation:
A break above +1.0% can be used as a bullish continuation signal.
A break below –1.0% may confirm bearish strength.
Long periods above/below these thresholds support trend-following entries.
2. Reversal Detection:
If DI returns below +1.0% after exceeding it, bullish momentum may be fading.
If DI rises above –1.0% after falling below, bearish pressure may be weakening.
These shifts resemble overbought/oversold transitions in oscillators like RSI or Stochastic, and can be paired with divergence, volume, or price structure analysis for higher reliability.
3. Sideways Market Detection:
DI values within ±0.5% indicate low volatility or a non-trending environment.
Traders may avoid breakout entries during these periods or apply range-trading tactics instead.
Observing transitions out of the low-volatility zone can help anticipate breakouts.
4. Combine with Other Indicators:
DI signals can be enhanced using tools like MACD, Volume Oscillators, or Moving Averages.
For example, a DI breakout beyond ±1.0% supported by a MACD crossover or volume spike can help validate trend initiation.
This indicator is especially powerful when paired with Bollinger Bands:
A simultaneous price breakout from the Bollinger Band and DI moving beyond ±1.0% can help identify early trend inflection points.
This combination supports entering positions early in a developing trend, improving the efficiency of trend-following strategies and enhancing decision-making precision.
It also helps filter false breakouts when DI fails to confirm the move outside the band.
This indicator is designed for educational and analytical purposes and works across all timeframes and asset classes.
It is particularly useful for traders seeking a clear framework to identify momentum strength, filter sideways markets, and improve entry timing within a larger trading system.
4H Golden Cross - The Sign of GloryCalculates the golden cross on the 4-hour timeframe
Displays the result on any timeframe
Draws a green vertical beam (a vertical line or background stripe) on the bar where the golden cross happened, so it’s clearly visible regardless of your chart timeframe
This is used to see the effectiveness of the 4h golden cross without having to change timeframes continually
RCI Strategy [PineIndicators]RCI Strategy
This strategy leverages the Rank Correlation Index (RCI) — a statistical oscillator that measures the relationship between time and price rank — combined with a configurable moving average filter. It offers clean, rule-based entries and exits, and visually enhanced trade tracking via labeled markers and boxes on the chart.
The RCI Strategy is well-suited for momentum traders looking to capture directional shifts with confirmation through RCI smoothing.
Core Logic
1. Rank Correlation Index (RCI)
Measures how closely price changes correlate with time rankings.
Values range between -100 and +100.
Thresholds at ±80 help identify potential reversals or extremes.
2. RCI Smoothing via Moving Average
A moving average (MA) is applied to the RCI to smooth out fluctuations.
Supported MA types:
SMA
EMA
SMMA (RMA)
WMA
VWMA
Users can disable the smoothing by selecting "None".
Trade Entry Logic
Long Entry: RCI crosses above the selected moving average.
Short Entry: RCI crosses below the moving average.
Entries are restricted by trade direction settings:
Long Only
Short Only
Long & Short
Visual Features
RCI Panel Display
Plots RCI line and its moving average in a separate pane.
Horizontal guide lines at 0, +80, and -80 help visualize signal zones.
Trade Labels on Chart
Buy Label: Plotted when a long entry is executed.
Close Label: Plotted when any position is closed.
Triangle markers for visual emphasis on direction change.
Trade Visualization Boxes
A colored box is drawn between entry and exit prices.
Green = profitable trade; Red = losing trade.
Two horizontal lines connect entry and exit prices for reference.
Customization Parameters
RCI Source: Select input price for the RCI (default: close).
RCI Length: Set sensitivity of the oscillator.
MA Type and Length: Choose and configure the smoothing filter.
Trade Direction Mode: Define whether to allow Long, Short, or both.
Use Cases
Swing traders who want to trade directional reversals with statistical backing.
Traders seeking a clean and visual strategy based on rank momentum.
Environments where both trend and range dynamics occur.
Conclusion
The RCI Strategy is a non-repainting, rule-based trading model that combines rank correlation momentum with smoothed trend logic. Its clean visual markers, labeled trades, and flexible MA filters make it a valuable tool for discretionary and systematic traders alike.
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.
Hurst Exponent Oscillator [PhenLabs]📊 Hurst Exponent Oscillator -
Version: PineScript™ v5
📌 Description
The Hurst Exponent Oscillator (HEO) by PhenLabs is a powerful tool developed for traders who want to distinguish between trending, mean-reverting, and random market behaviors with clarity and precision. By estimating the Hurst Exponent—a statistical measure of long-term memory in financial time series—this indicator helps users make sense of underlying market dynamics that are often not visible through traditional moving averages or oscillators.
Traders can quickly know if the market is likely to continue its current direction (trending), revert to the mean, or behave randomly, allowing for more strategic timing of entries and exits. With customizable smoothing and clear visual cues, the HEO enhances decision-making in a wide range of trading environments.
🚀 Points of Innovation
Integrates advanced Hurst Exponent calculation via Rescaled Range (R/S) analysis, providing unique market character insights.
Offers real-time visual cues for trending, mean-reverting, or random price action zones.
User-controllable EMA smoothing reduces noise for clearer interpretation.
Dynamic coloring and fill for immediate visual categorization of market regime.
Configurable visual thresholds for critical Hurst levels (e.g., 0.4, 0.5, 0.6).
Fully customizable appearance settings to fit different charting preferences.
🔧 Core Components
Log Returns Calculation: Computes log returns of the selected price source to feed into the Hurst calculation, ensuring robust and scale-independent analysis.
Rescaled Range (R/S) Analysis: Assesses the dispersion and cumulative deviation over a rolling window, forming the core statistical basis for the Hurst exponent estimate.
Smoothing Engine: Applies Exponential Moving Average (EMA) smoothing to the raw Hurst value for enhanced clarity.
Dynamic Rolling Windows: Utilizes arrays to maintain efficient, real-time calculations over user-defined lengths.
Adaptive Color Logic: Assigns different highlight and fill colors based on the current Hurst value zone.
🔥 Key Features
Visually differentiates between trending, mean-reverting, and random market modes.
User-adjustable lookback and smoothing periods for tailored sensitivity.
Distinct fill and line styles for each regime to avoid ambiguity.
On-chart reference lines for strong trending and mean-reverting thresholds.
Works with any price series (close, open, HL2, etc.) for versatile application.
🎨 Visualization
Hurst Exponent Curve: Primary plotted line (smoothed if EMA is used) reflects the ongoing estimate of the Hurst exponent.
Colored Zone Filling: The area between the Hurst line and the 0.5 reference line is filled, with color and opacity dynamically indicating the current market regime.
Reference Lines: Dash/dot lines mark standard Hurst thresholds (0.4, 0.5, 0.6) to contextualize the current regime.
All visual elements can be customized for thickness, color intensity, and opacity for user preference.
📖 Usage Guidelines
Data Settings
Hurst Calculation Length
Default: 100
Range: 10-300
Description: Number of bars used in Hurst calculation; higher values mean longer-term analysis, lower values for quicker reaction.
Data Source
Default: close
Description: Select which data series to analyze (e.g., Close, Open, HL2).
Smoothing Length (EMA)
Default: 5
Range: 1-50
Description: Length for smoothing the Hurst value; higher settings yield smoother but less responsive results.
Style Settings
Trending Color (Hurst > 0.5)
Default: Blue tone
Description: Color used when trending regime is detected.
Mean-Reverting Color (Hurst < 0.5)
Default: Orange tone
Description: Color used when mean-reverting regime is detected.
Neutral/Random Color
Default: Soft blue
Description: Color when market behavior is indeterminate or shifting.
Fill Opacity
Default: 70-80
Range: 0-100
Description: Transparency of area fills—higher opacity for stronger visual effect.
Line Width
Default: 2
Range: 1-5
Description: Thickness of the main indicator curve.
✅ Best Use Cases
Identifying if a market is regime-shifting from trending to mean-reverting (or vice versa).
Filtering signals in automated or systematic trading strategies.
Spotting periods of randomness where trading signals should be deprioritized.
Enhancing mean-reversion or trend-following models with regime-awareness.
⚠️ Limitations
Not predictive: Reflects current and recent market state, not future direction.
Sensitive to input parameters—overfitting may occur if settings are changed too frequently.
Smoothing can introduce lag in regime recognition.
May not work optimally in markets with structural breaks or extreme volatility.
💡 What Makes This Unique
Employs advanced statistical market analysis (Hurst exponent) rarely found in standard toolkits.
Offers immediate regime visualization through smart dynamic coloring and zone fills.
🔬 How It Works
Rolling Log Return Calculation:
Each new price creates a log return, forming the basis for robust, non-linear analysis. This ensures all price differences are treated proportionally.
Rescaled Range Analysis:
A rolling window maintains cumulative deviations and computes the statistical “range” (max-min of deviations). This is compared against the standard deviation to estimate “memory”.
Exponent Calculation & Smoothing:
The raw Hurst value is translated from the log of the rescaled range ratio, and then optionally smoothed via EMA to dampen noise and false signals.
Regime Detection Logic:
The smoothed value is checked against 0.5. Values above = trending; below = mean-reverting; near 0.5 = random. These control plot/fill color and zone display.
💡 Note:
Use longer calculation lengths for major market character study, and shorter ones for tactical, short-term adaptation. Smoothing balances noise vs. lag—find a best fit for your trading style. Always combine regime awareness with broader technical/fundamental context for best results.
Parabolic RSI Strategy [ChartPrime × PineIndicators]This strategy combines the strengths of the Relative Strength Index (RSI) with a Parabolic SAR logic applied directly to RSI values.
Full credit to ChartPrime for the original concept and indicator, licensed under the MPL 2.0.
It provides clear momentum-based trade signals using an innovative method that tracks RSI trend reversals via a customized Parabolic SAR, enhancing traditional oscillator strategies with dynamic trend confirmation.
How It Works
The system overlays a Parabolic SAR on the RSI, detecting trend shifts in RSI itself rather than on price, offering early reversal insight with visual and algorithmic clarity.
Core Components
1. RSI-Based Trend Detection
Calculates RSI using a customizable length (default: 14).
Uses upper and lower thresholds (default: 70/30) for overbought/oversold zones.
2. Parabolic SAR Applied to RSI
A custom Parabolic SAR function tracks momentum within the RSI, not price.
This allows the system to capture RSI trend reversals more responsively.
Configurable SAR parameters: Start, Increment, and Maximum acceleration.
3. Signal Generation
Long Entry: Triggered when the SAR flips below the RSI line.
Short Entry: Triggered when the SAR flips above the RSI line.
Optional RSI filter ensures that:
Long entries only occur above a minimum RSI (e.g. 50).
Short entries only occur below a maximum RSI.
Built-in logic prevents new positions from being opened against trend without prior exit.
Trade Modes & Controls
Choose from:
Long Only
Short Only
Long & Short
Optional setting to reverse positions on opposite signal (instead of waiting for a flat close).
Visual Features
1. RSI Plotting with Thresholds
RSI is displayed in a dedicated pane with overbought/oversold fill zones.
Custom horizontal lines mark threshold boundaries.
2. Parabolic SAR Overlay on RSI
SAR dots color-coded for trend direction.
Visible only when enabled by user input.
3. Entry & Exit Markers
Diamonds: Mark entry points (above for shorts, below for longs).
Crosses: Mark exit points.
Strategy Strengths
Provides early momentum reversal entries without relying on price candles.
Combines oscillator and trend logic without repainting.
Works well in both trending and mean-reverting markets.
Easy to configure with fine-tuned filter options.
Recommended Use Cases
Intraday or swing traders who want to catch RSI-based reversals early.
Traders seeking smoother signals than price-based Parabolic SAR entries.
Users of RSI looking to reduce false positives via trend tracking.
Customization Options
RSI Length and Thresholds.
SAR Start, Increment, and Maximum values.
Trade Direction Mode (Long, Short, Both).
Optional RSI filter and reverse-on-signal settings.
SAR dot color customization.
Conclusion
The Parabolic RSI Strategy is an innovative, non-repainting momentum strategy that enhances RSI-based systems with trend-confirming logic using Parabolic SAR. By applying SAR logic to RSI values, this strategy offers early, visualized, and filtered entries and exits that adapt to market dynamics.
Credit to ChartPrime for the original methodology, published under MPL-2.0.
Multi-Indicator Swing [TIAMATCRYPTO]v6# Strategy Description:
## Multi-Indicator Swing
This strategy is designed for swing trading across various markets by combining multiple technical indicators to identify high-probability trading opportunities. The system focuses on trend strength confirmation and volume analysis to generate precise entry and exit signals.
### Core Components:
- **Supertrend Indicator**: Acts as the primary trend direction filter with optimized settings (Factor: 3.0, ATR Period: 10) to balance responsiveness and reliability.
- **ADX (Average Directional Index)**: Confirms the strength of the prevailing trend, filtering out sideways or choppy market conditions where the strategy avoids taking positions.
- **Liquidity Delta**: A volume-based indicator that analyzes buying and selling pressure imbalances to validate trend direction and potential reversals.
- **PSAR (Optional)**: Can be enabled to add additional confirmation for trend changes, turned off by default to reduce signal filtering.
### Key Features:
- **Flexible Direction Trading**: Choose between long-only, short-only, or bidirectional trading to adapt to market conditions or account restrictions.
- **Conservative Risk Management**: Implements fixed percentage-based stop losses (default 2%) and take profits (default 4%) for a positive risk-reward ratio.
- **Realistic Backtesting Parameters**: Includes commission (0.1%) and slippage (2 points) to reflect real-world trading conditions.
- **Visual Signals**: Clear buy/sell arrows with customizable sizes for easy identification on the chart.
- **Information Panel**: Dynamic display showing active indicators and current risk settings.
### Best Used On:
Daily timeframes for cryptocurrencies, forex, or stock indices. The strategy performs optimally on assets with clear trending behavior and sufficient volatility.
### Default Settings:
Optimized for conservative position sizing (5% of equity per trade) with an initial capital of $10,000. The backtesting period (2021-2023) provides a statistically significant sample of varied market conditions.
RSI Candle Trend🎯 Purpose:
This TradingView script is designed to visualize trend strength using RSI values as candle data, instead of traditional price candles. It transforms RSI data into custom candles using various smoothing and filtering methods (like Heikin-Ashi, Linear Regression, Rational Quadratic Filter, or McGinley Dynamic). It allows traders to:
📌Track RSI-based momentum using visual candle representation
📌Apply advanced smoothing/filters to the RSI to reduce noise
📌Highlight candle trend strength using dynamic coloring
📌Identify overbought/oversold zones using reference lines (RSI 80 and 20)
🧩 How It Works:
It calculates RSI values for open, high, low, close prices.
These RSI values are then optionally smoothed with user-selected moving averages (EMA, SMA, etc.).
Depending on the selected mode (Normal, Heikin-Ashi, Linear, Rational Quadratic), the RSI values are transformed into synthetic candles.
Candles are colored cyan (uptrend) or red (downtrend) based on RSI movement.
⚙️ Key Inputs:
Method: Type of moving average to smooth the RSI (e.g. EMA, SMA, VWMA, etc.)
Length: Length for RSI and smoothing filters
Candle: Type of candle transformation (Normal, Heikin-Ashi, Linear, Rational Quadratic)
Rational Quadratic: Parameter for the Rational Quadratic smoothing method
📊 Outputs:
Custom candles plotted using RSI-transformed values
Candle colors based on RSI strength:
Cyan for strong bullish RSI movement
Red for strong bearish RSI movement
Horizontal lines at RSI levels 80 and 20 (overbought/oversold)
🧠 Why Use This Indicator?
Unlike traditional RSI indicators that show a line, this tool:
Converts RSI into candle-style visualization
Helps traders visually interpret trend strength, reversals, or continuation patterns
Offers more refined control over RSI behavior and filtering
Provides a unique blend of momentum and candle analysis
❗Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
AP IFTCCIv2/IFTStoch/IFTRSI Multi-TimeframeMulti-Timeframe IFT-CCI/Stoch/RSI Composite
This enhanced indicator combines three powerful oscillators—Inverse Fisher Transform (IFT) versions of the Commodity Channel Index (CCI), Stochastic, and Relative Strength Index (RSI)—into a unified multi-timeframe analysis tool. Originally developed by John Ehlers (pioneer of cyclical analysis and signal processing in trading systems) and adapted by KIVANC (@fr3762), this version adds dual-timeframe capability to compare indicator values across different chart resolutions.
Key Features:
Triple Oscillator Composite
IFT-CCI: Smoothed CCI values transformed via Ehlers' Inverse Fisher Transform (blue-gold)
IFT-Stochastic: Classic stochastic oscillator processed through IFT (blue)
IFT-RSI: RSI oscillator converted to IFT format (magenta)
Composite Average Line: Combined average of all three indicators (green)
Multi-Timeframe Analysis
Compare primary and secondary timeframes (e.g., 1H vs. 4H, daily vs. weekly)
Primary timeframe plots use solid lines with 80% opacity
Secondary timeframe (optional) uses dashed/circle markers with 40% opacity
Key Levels
Overbought (+0.75) and oversold (-0.75) reference lines
Zero-centerline for momentum direction bias
Applications:
Trend Confirmation: Align higher timeframe signals with lower timeframe entries
Divergence Detection: Spot inter-timeframe discrepancies in momentum
Regime Filter: Use higher timeframe composite values to filter trades
Technical Basis:
Inverse Fisher Transform: Compresses oscillator values into bounded (-1 to +1) range while emphasizing extreme moves
Dual WMA Smoothing: Combines initial calculation smoothing (WMA1) with final output smoothing (WMA2)
Exponential Scaling: (e^2x - 1)/(e^2x + 1) formula converts Gaussian-like distributions to bounded outputs
Credits:
Original Concept: John Ehlers (IFT methodology, cyclical analysis foundations)
Initial Implementation: KIVANC (@fr3762 on Twitter) for the base IFT-CCI/Stoch/RSI script
Multi-Timeframe Adaptation: for cross-resolution analysis capabilities
This tool is particularly effective for traders seeking to align multiple timeframes while using Ehlers' noise-reduction techniques. The composite average line provides a consensus view, while the individual oscillators help identify component strength/weakness.
Market Sentiment Index US Top 40 [Pt]▮Overview
Market Sentiment Index US Top 40 [Pt} shows how the largest US stocks behave together. You pick one simple measure—High Low breakouts, Above Below moving average, or RSI overbought/oversold—and see how many of your chosen top 10/20/30/40 NYSE or NASDAQ names are bullish, neutral, or bearish.
This tool gives you a quick view of broad-market strength or weakness so you can time trades, confirm trends, and spot hidden shifts in market sentiment.
▮Key Features
► Three Simple Modes
High Low Index: counts stocks making new highs or lows over your lookback period
Above Below MA: flags stocks trading above or below their moving average
RSI Sentiment: marks overbought or oversold stocks and plots a small histogram
► Universe Selection
Top 10, 20, 30, or 40 symbols from NYSE or NASDAQ
Option to weight by market cap or treat all symbols equally
► Timeframe Choice
Use your chart’s timeframe or any intraday, daily, weekly, or monthly resolution
► Histogram Smoothing
Two optional moving averages on the sentiment bars
Markers show when the faster average crosses above or below the slower one
► Ticker Table
Optional on-chart table showing each ticker’s state in color
Grid or single-row layout with adjustable text size and color settings
▮Inputs
► Mode and Lookback
Pick High Low, Above Below MA, or RSI Sentiment
Set lookback length (for example 10 bars)
If using Above Below MA, choose the moving average type (EMA, SMA, etc.)
► Universe Setup
Market: NYSE or NASDAQ
Number of symbols: 10, 20, 30, or 40
Weights: on or off
Timeframe: blank to match chart or pick any other
► Moving Averages on Histogram
Enable fast and slow averages
Set their lengths and types
Choose colors for averages and markers
► Table Options
Show or hide the symbol table
Select text size: tiny, small, or normal
Choose layout: grid or one-row
Pick colors for bullish, neutral, and bearish cells
Show or hide exchange prefixes
▮How to Read It
► Sentiment Bars
Green means bullish
Red means bearish
Near zero means neutral
► Zero Line
Separates bullish from bearish readings
► High Low Line (High Low mode only)
Smooth ratio of highs versus lows over your lookback
► MA Crosses
Fast MA above slow MA hints rising breadth
Fast MA below slow MA hints falling breadth
► Ticker Table
Each cell colored green, gray, or red for bull, neutral, or bear
▮Use Cases
► Confirm Market Trends
Early warning when price makes highs but breadth is weak
Catch rallies when breadth turns strong while price is flat
► Spot Sector Rotation
Switch between NYSE and NASDAQ to see which group leads
Watch tech versus industrial breadth to track money flow
► Filter Trade Signals
Enter longs only when breadth is bullish
Consider shorts when breadth turns negative
► Combine with Other Indicators
Use RSI Sentiment with trend tools to spot overextended moves
Add volume indicators in High Low mode for breakout confirmation
► Timeframe Analysis
Daily for big-picture bias
Intraday (15-min) for precise entries and exits
Supertrend + Stochastic RSIThe Supertrend + Stochastic RSI indicator is designed for scalping and short-term trading, combining the trend-following power of the Supertrend with the momentum insights of the Stochastic RSI to generate reliable buy and sell signals. This indicator aims to reduce false signals by requiring confirmation from both trend direction and momentum, making it suitable for traders targeting quick, high-probability trades in fast-moving markets on lower timeframes (e.g., 1-minute to 15-minute charts).
How It Works
The indicator integrates two technical components to produce actionable signals:
Supertrend for Trend Direction:
The Supertrend, calculated with a default length of 10 and a factor of 3.0, identifies the prevailing trend. It plots a line above or below the price, turning green when the trend is bullish (price above Supertrend) and red when bearish (price below Supertrend). This helps traders stay aligned with the market’s direction, reducing trades against the trend.
Stochastic RSI for Momentum Confirmation:
The Stochastic RSI, computed over a 14-period RSI with 3-period smoothing for %K and %D lines, measures momentum. A buy signal is generated when the %K line crosses above the oversold level (default: 20), indicating potential upward momentum, while a sell signal occurs when %K crosses below the overbought level (default: 80), suggesting downward momentum.
Signal Generation
Signals are produced only when both conditions align, using the previous bar’s values to prevent repainting:
Buy Signal: The Stochastic RSI %K crosses above the oversold level, and the Supertrend confirms a bullish trend (price above Supertrend). Displayed as a green upward triangle below the bar.
Sell Signal: The Stochastic RSI %K crosses below the overbought level, and the Supertrend confirms a bearish trend (price below Supertrend). Displayed as a red downward triangle above the bar.
Adaptive Volume-Weighted RSI (AVW-RSI)Concept Summary
The AVW-RSI is a modified version of the Relative Strength Index (RSI), where each price change is weighted by the relative trading volume for that period. This means periods of high volume (typically driven by institutions or “big money”) have a greater influence on the RSI calculation than periods of low volume.
Why AVW-RSI Helps Traders
Avoids Weak Signals During Low Volume
Standard RSI may show overbought/oversold zones even during low-volume periods (e.g., during lunch hours or after news).
AVW-RSI gives less weight to these periods, avoiding misleading signals.
Amplifies Strong Momentum Moves
If RSI is rising during high volume, it's more likely driven by institutional buying—AVW-RSI reflects that stronger by weighting the RSI component.
Filters Out Retail Noise
By prioritizing high-volume candles, it naturally discounts fakeouts caused by thin markets or retail-heavy moves.
Highlights Institutional Entry/Exit
Useful for spotting hidden accumulation/distribution that classic RSI would miss.
How It Works (Calculation Logic)
Traditional RSI Formula Recap
RSI = 100 - (100 / (1 + RS))
RS = Average Gain / Average Loss (over N periods)
Modified Step – Apply Volume Weight
For each period
Gain_t = max(Close_t - Close_{t-1}, 0)
Loss_t = max(Close_{t-1} - Close_t, 0)
Weight_t = Volume_t / AvgVolume(N)
WeightedGain_t = Gain_t * Weight_t
WeightedLoss_t = Loss_t * Weight_t
Weighted RSI
AvgWeightedGain = SMA(WeightedGain, N)
AvgWeightedLoss = SMA(WeightedLoss, N)
RS = AvgWeightedGain / AvgWeightedLoss
AVW-RSI = 100 - (100 / (1 + RS))
Visual Features on Chart
Line Color Gradient
Color gets darker as volume weight increases, signaling stronger conviction.
Overbought/Oversold Zones
Traditional: 70/30
Suggested AVW-RSI zones: Use dynamic thresholds based on historical volatility (e.g., 80/20 for high-volume coins).
Volume Spike Flags
Mark RSI turning points that occurred during volume spikes with a special dot/symbol.
Trading Strategies with AVW-RSI
1. Weighted RSI Divergence
Regular RSI divergence becomes more powerful when volume is high.
AVW-RSI divergence with volume spike is a strong signal of reversal.
2. Trend Confirmation
RSI crossing above 50 during rising volume is a good entry signal.
RSI crossing below 50 with high volume is a strong exit or short trigger.
3. Breakout Validation
Price breaking resistance + AVW-RSI > 60 with volume = Confirmed breakout.
Price breaking but AVW-RSI < 50 or on low volume = Potential fakeout.
Example Use Case
Stock XYZ is approaching a resistance zone. A trader sees:
Standard RSI: 65 → suggests strength.
Volume is 3x the average.
AVW-RSI: 78 → signals strong momentum with institutional backing.
The trader enters confidently, knowing this isn't just low-volume hype.
Limitations / Tips
Works best on liquid assets (Forex majors, large-cap stocks, BTC/ETH).
Should be used alongside price action and volume analysis—not standalone.
Periods of extremely high volume (news events) might need smoothing to avoid spikes.
