FullerOSOBSQZ v1.1.22FullerOSOBSQZ v1.1.x โ OS/OB Levels + Squeeze Anchor + Slope Accel + Alerts
What this script does
Plots Oversold (OS) and Overbought (OB) price levels as horizontal segments (line breaks) that persist for a configurable number of bars.
Tracks two layers of OS/OB logic:
Base triggers (broader detection)
Refined triggers (stricter pattern match layered on top of Base)
Plots a Squeeze anchor level during squeeze โONโ runs and provides squeeze lifecycle alerts (start/release + bull/bear release).
Optionally plots OS/OB start markers (seed points) and slope-acceleration markers for momentum context.
Provides alertconditions for starts, active lines, price interactions, within-N-bar follow-through, squeeze lifecycle, and hold/confirm.
Core Concepts
Mutually inclusive Base + Refined
Refined logic is not a competing system. It is a stricter confirmation layer on top of the Base logic.
You can use Base levels as the โwatchโ context, and Refined levels as a higher-confidence confirmation (or display both).
Line segments (line breaks)
OS/OB levels are drawn as horizontal segments using line-break style plotting. Each segment represents a โreference levelโ that remains valid for a limited number of bars after it triggers.
If a new, more extreme OS/OB triggers while a prior one is active, the plot will step to the new level (by design).
How to read the plots
OS Levels (below price)
These are support reference levels. Common reads:
Touch : price trades into the OS line.
Reclaim : close crosses back above the OS line.
Bounce : price dips below OS intrabar but closes above it (same bar).
Hold/Confirm : close stays above OS for N consecutive bars.
OB Levels (above price)
These are resistance reference levels. Common reads:
Touch : price trades into the OB line.
Reject : price trades above/into OB but closes back below it.
Breakout : close crosses above OB.
Hold/Confirm : close stays below OB for N consecutive bars (bear confirmation) or use breakout/hold logic for bull continuation.
Squeeze Anchor
When squeeze is ON, the script anchors a reference line from the first ON bar and holds it for the duration of the continuous squeeze run.
On squeeze release (OFF), you can interpret direction by where price closes relative to the anchor.
Slope Acceleration Markers
These markers highlight momentum inflection behavior derived from the internal regression/slope logic.
If you see fewer markers than another script, it usually means the underlying trend-gate and/or slope parameters differ (not that the feature is โmissingโ).
Settings โ What they do and how changing them affects signals
1) Base Triggers
Controls the Base OS/OB detection layer.
Changing Base thresholds generally affects:
Frequency : looser = more lines; stricter = fewer lines
Quality : stricter = fewer but cleaner levels
Responsiveness : shorter lookbacks = faster reacting, more noise; longer = slower, smoother
2) Base Lines
Controls the Base OS/OB plotted appearance and segmentation length.
Segment length (forward bars): longer = level remains visible/valid longer; shorter = faster turnover and fewer active segments.
Line width : purely visual emphasis (does not change the underlying detection).
3) Refined Triggers
Controls the stricter confirmation layer (Refined OS/OB).
Refined triggers typically reduce false positives but may occur later than Base.
Use Refined when you want: โOnly alert me on the higher-confidence pattern.โ
4) Refined Colors + Widths
Color and width controls for Refined levels.
Recommended usage:
Keep Base slightly lighter/less prominent.
Make Refined more prominent so confirmations stand out.
5) Trend Context
Trend SMA length (default 62)
Shorter SMA = more sensitive trend context (more โbelow trendโ flips).
Longer SMA = slower trend context (fewer flips, more stability).
Trend mode affects how some context cues render (for example, whether certain momentum markers appear in โbelow-trendโ context).
6) Squeeze
Squeeze ON indicates compression conditions. The script plots a held anchor line during the ON run.
Per-bar render vs static
Per-bar render updates opacity per bar while squeeze is ON (based on your selected strength model).
Static render keeps the anchor appearance constant through the run.
Squeeze opacity model selection
Compression ratio : based on 1 โ (BB width / KC width). Higher = tighter squeeze.
Z-score style : normalizes the BB/KC ratio over a lookback and maps extremes to opacity.
Duration boost : increases opacity with consecutive ON bars up to a cap.
Changing squeeze settings affects:
How early/late squeeze turns ON/OFF
How aggressively โtightnessโ is visually emphasized
How frequently bull/bear release alerts fire
7) Markers
OS/OB Start markers
Shows the first bar where an OS/OB segment begins (Base and/or Refined).
Useful for โN bars after startโ logic and for validating what bar started a segment.
Alerts (built-in alertconditions)
Start alerts
OS Start (Any) โ Base OR Refined start.
OB Start (Any) โ Base OR Refined start.
Active line alerts (true while a line is plotted)
OS Active (Any line)
OB Active (Any line)
Price interaction alerts
OS Touch (Any)
OS Reclaim (Any) โ close crosses above OS line
OS Bounce (Any) โ low below OS line and close above
OS Breakdown (Any) โ close crosses below OS line
OB Touch (Any)
OB Reject (Any) โ price probes above/into OB and closes below
OB Breakout (Any) โ close crosses above OB line
OB Breakdown (Any)
Within N bars after start alerts
Uses the setting: Within N bars after start (default 5).
OS Reclaim within N bars
OS Bounce within N bars
OS Breakdown within N bars
OB Reject within N bars
OB Breakout within N bars
OB Breakdown within N bars
Hold/Confirm alerts
OS Hold/Confirm (N closes above) โ first bar where close stayed above OS for N consecutive bars.
OB Hold/Confirm (N closes below) โ first bar where close stayed below OB for N consecutive bars.
SQZ lifecycle alerts
SQZ Start
SQZ Release
SQZ Bull Release โ release bar close > SQZ anchor
SQZ Bear Release โ release bar close < SQZ anchor
Suggested workflows
Bottom / bounce workflow
Watch: OS Start (Any) or OS Touch (Any)
Confirm: OS Reclaim within N bars + OS Hold/Confirm
Context: SQZ ON and/or SQZ Bull Release to time expansion
Top / rejection workflow
Watch: OB Start (Any) or OB Touch (Any)
Confirm: OB Reject within N bars (or OB Breakdown)
Context: SQZ Bear Release to time expansion lower
Notes
โActive lineโ alerts will be true on every bar while the line is present. For one-shot alerts, prefer the Start or Within-N-bar alerts.
If you change trend, slope, or squeeze parameters compared to a framework strategy script, you should expect differences in marker density and background behavior. The signal is highly parameter-dependent.
โOversold/Overboughtโ levels are currently hardcoded, future version will open up configuration settings.
Stocastico RSI (STOCH RSI)
Multiple Time Frame Stoch-RSIThis indicator is designed to show users the values for default stochastic RSI and default RSI settings across multiple time frames.
I have made many bad trades focusing too closely on one particular time frame and indicators that suggest the price will move one way, to be superseded by a higher timeframe pushing price in another direction.
The timeframes are customisable so you can select your own timeframes, but the default timeframes chosen here are part of the BareNaked Crypto or Naked Nation strategy, looking at timeframes in multiples of 3 for lower timeframes.
The idea in its simplest form is that when timeframes like the 3/6/9m are all over sold or over bought (coloured red or green) then it could be a suitable time to place an order. Or at least be more favourable for your trade.
This indicator as with all indicators is designed as a tool to add to whatever arsenal of strategy or tools you are already using and does not constitute financial advice, just be cause 3/6/9m is in red or green does not guarantee that the trade will go your way.
The orange on the timeframes are generally designed to show users where price can reverse so for example if the stochastic 3m is at 10 and in green, but the 9m is at 65 in orange, it could be that a push up is not finished and the 9m drop from oversold to 65 could be reversed due to a low 3m stochastic number and then 9m goes from 65 back up to 100, and vice versa.
The arrows for direction also allow you to quickly deduce the direction of the stochastic RSI, ^ up, V down, and stable -. this should allow you to see if the stochastic has been rising and is beginning to turn around or not.
Support Resistance + RSI + 4 EMA (Doge_SV)Overview
This comprehensive indicator is designed to provide traders with a "bird's-eye view" of the market by combining three essential technical analysis tools into a single, clean interface. It helps in identifying trend direction, key price levels, and momentum across multiple timeframes without cluttering your workspace.
Key Features
1. Dynamic Support & Resistance (S/R)
The script automatically identifies and plots significant Support and Resistance levels based on pivot points.
Dynamic Zones: It highlights areas where price has historically reacted, helping you find high-probability entry and exit points.
Strength Filtering: Includes a built-in algorithm to display only the most "significant" levels based on their historical strength.
Visual Alerts: Lines and labels change color (Lime for Support, Red for Resistance) based on the current price position.
2. Quad-EMA Trend Ribbon (The "Exponential Moving Averages")
The indicator features four of the most widely used EMAs in professional trading to identify trend hierarchy:
EMA 34 (Green): Short-term momentum and immediate support/resistance.
EMA 89 (Blue): Intermediate-term trend filter (The "Trend Core").
EMA 200 (Black): Long-term trend baseline (The "Institutional Level").
EMA 633 (Purple): Ultra-long-term trend, often used for major cycle analysis.
3. Multi-Timeframe (MTF) RSI Dashboard
Stay informed about overbought or oversold conditions across all timeframes simultaneously.
Real-time Table: A neat table in the corner of your chart displays RSI (14) values from 1 minute up to 1 day.
Heatmap Logic: The table cells automatically change color based on intensity:
Red/Orange: Overbought (RSI > 70/80)
Green/Dark Green: Oversold (RSI < 30/20)
White: Neutral zone.
How to Use
Trend Alignment: Look for the 4-EMAs to be stacked in order (34 > 89 > 200 > 633 for a Bullish trend).
S/R Confirmation: When price approaches a Red Resistance line, check the RSI Dashboard. If higher timeframes are also Overbought, it increases the probability of a reversal.
Breakout Detection: Use the Support/Resistance lines to identify potential breakouts or "Role Reversal" (where old resistance becomes new support).
BreakPoint LITE - Structure Shift SignalsBreakPoint LITE โ Structure Shift Signals
Spot market structure shifts instantly and trade with clarity.
BreakPoint LITE helps traders identify key swing highs and lows, visualize potential structure shifts, and signal trade opportunities directly on your chart. With simple yet powerful filters like EMA and RSI, plus optional break-and-retest logic, it provides actionable insights while keeping your chart clean. The LITE version focuses on essential signals, making it perfect for traders who want a free, lightweight, and effective market structure tool.
โจ Features (LITE Version)
๐ธ Swing High / Low Detection
๐ธ Break + Retest Signals (optional)
๐ธ EMA Trend Filter (optional)
๐ธ RSI Filter (optional)
๐ธ Cooldown Bars Between Signals
๐ธ On-Chart BUY / SELL Labels
๐ธ Simple HUD Display of Current Trade
๐ธ Fully Free & Lightweight
Note: All PRO features are locked and visually marked, so LITE users are focused on essential functionality.
Make trading decisions based on LITE signals; consider PRO upgrade for full HUD and advanced features.
๐ In-Depth Feature Breakdown
BUY/SELL Labels
๐นPlots clear signals directly on the chart
๐ธ Instant, easy-to-read trade cues
Swing Detection
๐นAutomatically detects swing highs and lows based on user-defined length
๐ธ Identifies critical structure points for trade entries
Break + Retest Signals
๐นOptionally requires price to retest the breakout level before signaling
๐ธ Reduces false signals and improves trade reliability
EMA Trend Filter
๐นFilter signals based on trend relative to EMA
๐ธ Trade with the trend for higher probability setups
RSI Filter
๐นFilter signals using RSI above/below a midline
๐ธ Avoid trades during overbought/oversold extremes
HUD Display
๐นShows the current trade state (Long/Short/None) in a small table
๐ธ Keeps track of market bias at a glance
Cooldown Bars
๐น Prevent repeated signals too close together
๐ธ Reduces signal noise and improves decision clarity
๐ ๏ธ Settings & Customization
โซ๏ธ Swing Length: 1โ50 bars (default 5)
โซ๏ธ Use EMA Filter: On/Off
โซ๏ธ EMA Length: Default 200
โซ๏ธ Use RSI Filter: On/Off
โซ๏ธ RSI Length: Default 14
โซ๏ธ RSI Midline: Default 50
โซ๏ธ Require Break + Retest: On/Off
โซ๏ธ Retest ATR Tolerance: Default 0.5
โซ๏ธ Cooldown Bars After Signal: Default 10
Best Practices
Combine swing signals with EMA/RSI filters for higher accuracy.
Enable break-and-retest for more conservative trading.
Use cooldown bars to avoid repeated signals during volatile conditions.
Keep your chart clean; avoid cluttering with too many indicators.
Getting Started
Add BreakPoint LITE to your chart from the TradingView Public Library.
Adjust swing length, EMA, and RSI settings to your preference.
Enable break-and-retest if you want higher-confidence signals.
Watch for BUY / SELL labels and the simple HUD for trade bias.
๐ณ Unlock BreakPoint PRO for advanced HUD options, high-timeframe structure analysis, ATR-based stop loss/take profit, risk/reward visualization, and full customization. Upgrade to PRO to take your market structure analysis to a professional level!
โ ๏ธ Disclaimer:
BreakPoint โ Structure Shift Signals (LITE) is a technical analysis tool designed to highlight potential market structure shifts. It provides visual signals and trade bias suggestions based on swing highs/lows, optional EMA/RSI filters, and break/retest logic. It does not guarantee profits and should not be considered financial advice.
Users are responsible for their own trades. Always perform your own analysis and manage risk appropriately. Use proper stop-losses and position sizing. Trading involves significant risk of loss, and past performance is not indicative of future results.
By using this indicator, you acknowledge that the author cannot be held liable for any trading losses or financial outcomes resulting from its use.
If you'd like access or have any questions, feel free to reach out to me directly via DM.
Mini RSI+STOCH-RSI+RSI-DIVERGENCE @Marx_CapitalMini version of RSI + STOCHASTIC-RSI with RSI-Divergence detection - all in one, adjustable small table overlayed on your chart. The table box gives RSI and Stoch-RSI values and signals detected RSI divergences.
Uncheck 'Update only on bar close' in indicator settings if the box does not appear right away.
RSI + STOCH RSI - Marx_CapitalSimple RSI + STOCH RSI indicator in one pane. In addition to the standard 30/70 and 20/80 RSI levels you have three adjustable levels (eg. 0, 50, 100) to indicate STOCH RSI overbought/oversold scenarios.
[SM-021] Gaussian Trend System [Optimized]This script is a comprehensive trend-following strategy centered around a Gaussian Channel. It is designed to capture significant market movements while filtering out noise during consolidation phases. This version (v2) introduces code optimizations using Pine Script v6 Arrays and a new Intraday Time Control feature.
1. Core Methodology & Math
The foundation of this strategy is the Gaussian Filter, originally conceptualized by @DonovanWall.
Gaussian Poles: Unlike standard moving averages (SMA/EMA), this filter uses "poles" (referencing signal processing logic) to reduce lag while maintaining smoothness.
Array Optimization: In this specific iteration, the f_pole function has been refactored to utilize Pine Script Arrays. This improves calculation efficiency and rendering speed compared to recursive variable calls, especially when calculating deep historical data.
Channel Logic: The strategy calculates a "Filtered True Range" to create High and Low bands around the main Gaussian line.
Long Entry: Price closes above the High Band.
Short Entry: Price closes below the Low Band.
2. Signal Filtering (Confluence)
To reduce false signals common in trend-following systems, the strategy employs a "confluence" approach using three additional layers:
Baseline Filter: A 200-period (customizable) EMA or SMA acts as a regime filter. Longs are only taken above the baseline; Shorts only below.
ADX Filter (Volatility): The Average Directional Index (ADX) is used to measure trend strength. If the ADX is below a user-defined threshold (default: 20), the market is considered "choppy," and new entries are blocked.
Momentum Check: A Stochastic RSI check ensures that momentum aligns with the breakout direction.
3. NEW: Intraday Session Filter
Per user requests, a time-based filter has been added to restrict trading activity to specific market sessions (e.g., the New York Open).
How it works: Users can toggle a checkbox to enable/disable the filter.
Configuration: You can define a specific time range (Default: 09:30 - 16:00) and a specific Timezone (Default: New York).
Logic: The strategy longCondition and shortCondition now check if the current bar's timestamp falls within this window. If outside the window, no new entries are generated, though existing trades are managed normally.
4. Risk Management
The strategy relies on volatility-based exits rather than fixed percentage stops:
ATR Stop Loss: A multiple of the Average True Range (ATR) is calculated at the moment of entry to set a dynamic Stop Loss.
ATR Take Profit: An optional Reward-to-Risk (RR) ratio can be set to place a Take Profit target relative to the Stop Loss distance.
Band Exit: If the trend reverses and price crosses the opposite band, the trade is closed immediately to prevent large drawdowns.
Credits & Attribution
Original Gaussian Logic: Developed by @DonovanWalll. This script utilizes his mathematical formula for the pole filters.
Strategy Wrapper & Array Refactor: Developed by @sebamarghella.
Community Request: The Intraday Session Filter was added to assist traders focusing on specific liquidity windows.
Disclaimer: This strategy is for educational purposes. Past performance is not indicative of future results. Please use the settings menu to adjust the Session Time and Risk parameters to fit your specific asset class.
Stochastic RSI Forecast [QuantAlgo]๐ข Overview
The Stochastic RSI Forecast extends the classic momentum oscillator by projecting potential future K and D line values up to 10 bars ahead. Unlike traditional indicators that only reflect historical price action, this indicator uses three proprietary forecasting models, each operating on different market data inputs (price structure, volume metrics, or linear trend), to explore potential price paths. This unique approach allows traders to form probabilistic expectations about future momentum states and incorporate these projections into both discretionary and algorithmic trading and/or analysis.
๐ข How It Works
The indicator operates through a multi-stage calculation process that extends the RSI-to-Stochastic chain forward in time. First, it generates potential future price values using one of three selectable forecasting methods, each analyzing different market dimensions (structure, volume, or trend). These projected prices are then processed through an iterative RSI calculation that maintains continuity with historical gain/loss averages, producing forecasted RSI values. Finally, the system applies the full stochastic transformation (calculating the position of each forecasted RSI within its range, smoothing with K and D periods) to project potential future oscillator values.
The forecasting models adapt to market conditions by analyzing configurable lookback periods and recalculating projections on every bar update. The implementation preserves the mathematical properties of the underlying RSI calculation while extrapolating momentum trajectories, creating visual continuity between historical and forecasted values displayed as semi-transparent dashed lines extending beyond the current bar.
๐ข Key Features
1. Market Structure Model
This algorithm applies price action analysis by tracking break of structure (BOS) and change of character (CHoCH) patterns to identify potential order flow direction. The system detects swing highs and lows using configurable pivot lengths, then analyzes sequences of higher highs or lower lows to determine bullish or bearish structure bias. When price approaches recent swing points, the forecast projects moves in alignment with the established structure, scaled by ATR (Average True Range) for volatility adjustment.
Potential Benefits for Traders:
Explores potential momentum continuation scenarios during established trends
Identifies areas where structure changes might influence momentum
Could be useful for swing traders and position traders who incorporate structure-based analysis
The Structure Influence parameter (0-1 scale) allows blending between pure trend following and structure-weighted forecasts
Helps visualize potential trend exhaustion through weakening structure patterns
2. Volume-Weighted Model
This model analyzes volume patterns by combining On-Balance Volume (OBV), Accumulation/Distribution Line, and volume-weighted price returns to assess potential capital flow. The algorithm calculates directional volume momentum and identifies volume spikes above customizable thresholds to determine accumulation or distribution phases. When volume indicators align directionally, the forecast projects stronger potential moves; when volume diverges from price trends, it suggests possible reversals or consolidation.
Potential Benefits for Traders:
Incorporates volume analysis into momentum forecasting
Attempts to filter price action by volume support or lack thereof
Could be more relevant in markets where volume data is reliable (equities, crypto, major forex pairs)
Volume Influence parameter (0-1 scale) enables adaptation to different market liquidity profiles
Highlights volume climax patterns that sometimes precede trend changes
Could be valuable for traders who incorporate volume confirmation in their analysis
3. Linear Regression Model
This mathematical approach applies least-squares regression fitting to project price trends based on recent price data. Unlike the conditional logic of the other methods, linear regression provides straightforward trend extrapolation based on the best-fit line through the lookback period.
Potential Benefits for Traders:
Delivers consistent, reproducible forecasts based on statistical principles
Works better in trending markets with clear directional bias
Useful for systematic traders building quantitative strategies requiring stable inputs
Minimal parameter sensitivity (primarily controlled by lookback period)
Computationally efficient with fast recalculation on every bar
Serves as a baseline to compare against the more complex structure and volume methods
๐ข Universal Applications Across All Models
Each forecasting method projects potential future stochastic RSI values (K and D lines), which traders can use to:
โถ Anticipate potential crossovers: Visualize possible K/D crosses several bars ahead
โถ Explore overbought/oversold scenarios: Forecast when momentum might return from extreme zones
โถ Assess divergences: Evaluate how oscillator divergences might develop
โถ Inform entry timing: Consider potential points along the forecasted momentum curve for trade entry
โถ Develop systematic strategies: Build rules based on forecasted crossovers, slope changes, or threshold levels
โถ Adapt to market conditions: Switch between methods based on current market character (trending vs range-bound, high vs low volume)
In short, the indicator's flexibility allows traders to combine forecasting projections with traditional stochastic signals, using historical K/D for immediate reference while considering forecasted values for planning and analysis. As with all technical analysis tools, the forecasts represent one possible scenario among many and should be used as part of a broader trading methodology rather than as standalone signals.
Valdex RSI con Filtro MA (Simplificado)๐บ๐ธ VALDEX H-MA: Indicator Description
VALDEX H-MA: Centered RSI with Exponential Filter
This script, VALDEX H-MA, offers a highly streamlined, zero-centered Relative Strength Index (RSI) for impulse and cycle analysis, complemented by a fast Exponential Moving Average (EMA) filter.
It simplifies the classic RSI by centering it at zero, making it easier to read momentum shifts and overbought/oversold conditions relative to the central equilibrium.
Key Features and Customization
Zero-Centered RSI: The RSI is normalized to oscillate between approximately -50 and +50 (instead of 0 to 100), with the key neutral point located exactly at 0. This immediate visual clarity aids in assessing momentum balance.
RSI Length Flexibility: The primary RSI line (RSI Base) can be customized for different trading styles:
Set the Length RSI to 7 for a smoother, faster RSI suitable for scalping and capturing short-term reversals.
Set the Length RSI to 14 for a more standard yet still highly smoothed output, providing a reliable measure of trend momentum (note: this centered version remains smoother than the original 0-100 RSI).
MA Filter (Exponential Moving Average): An adjustable EMA is included as a powerful filter. This MA can be used in two primary ways:
Entry/Exit Signals: Generate trading signals when the RSI Base crosses above or below the MA Filter.
Cycle Smoothing: Use the MA to smooth the short-term cycles of the RSI Base, providing a clearer indication of the underlying momentum direction.
โ๏ธ Technical Description
The core of the VALDEX H-MA indicator relies on the following technical calculations:
RSI Centralization: The RSI Base line is derived from the standard Relative Strength Index (RSI) but is mathematically shifted to be zero-centered:
RSICenteredโ=RSI(0โ100)โโ50
This transformation ensures that the equilibrium point is clearly visible at the zero line.
MA Filter Calculation: The MA Filter is an Exponential Moving Average (EMA) applied directly to the RSICenteredโ output:
MAFilterโ=EMA(RSICenteredโ,Length MA)
The EMA is used for its responsiveness and low lag, making it an effective tool for filtering noise and confirming short-term momentum shifts.
Reference Lines: The indicator includes fixed reference lines at 30 (Overbought), 0 (Equilibrium), and -30 (Oversold) to quickly judge extreme conditions within the centered scale.
MTF Stoch RSI + RSI Signalsthis script will provide Buy and sell signals considering RSI and price action
Ehlers Dominant Cycle Stochastic RSIEhlers Enhanced Cycle Stochastic RSI
OVERVIEW
The Ehlers Enhanced Cycle Stochastic RSI is a momentum oscillator that automatically adjusts its lookback periods based on the dominant market cycle. Unlike traditional Stochastic RSI which uses fixed periods, this indicator detects the current cycle length and scales its calculationsโmaking it responsive in fast markets and stable in slow ones.
The indicator combines John Ehlers' digital signal processing research with the classic Stochastic RSI indicator, then adds a confirmation system to ensure cycle measurements are reliable.
THE THEORY
Traditional oscillators use fixed lookback periods (ie, 14-bar RSI). This creates a fundamental problem: markets don't move in fixed cycles. A 14-period RSI might capture the rhythm perfectly during one market phase, then completely miss it when conditions change.
Ehlers' research demonstrated that price data contains measurable cyclical components. If you can detect the dominant cycle length, you can tune your indicators to match itโlike tuning a radio to the right frequency.
This indicator takes that concept further by using three independent cycle detection methods and only trusting the measurement when they agree:
Hilbert Transform โ A mathematical technique from signal processing that extracts cycle period from the phase relationship between price and its derivative. It is fast but can be noisy.
Autocorrelation Periodogram โ Measures how similar the price series is to lagged versions of itself. The lag with highest correlation reveals the dominant cycle. More stable than Hilbert, but slightly slower to adapt.
Goertzel Algorithm (DFT) โ A frequency-domain approach that calculates spectral power at each candidate period. Identifies which frequencies contain the most energy.
When all three methods converge on similar period estimates, confidence is high. When they disagree, the market may be in a non-cyclical or in transition.
HOW IT CHANGES THE STOCHASTIC RSI
Standard Stochastic RSI:
1. Calculate RSI with fixed period (14 bars)
2. Apply Stochastic formula over fixed period (14 bars)
3. Smooth with fixed periods
Ehlers Enhanced Cycle Stochastic RSI:
1. Detect dominant cycle using three methods
2. Confirm cycle measurement (methods must agree)
3. Calculate RSI with period scaled to the detected cycle
4. Apply Stochastic formula with cycle-scaled lookback
5. Smooth adaptively
The result: when the market is cycling quickly (say, 15-bar cycles), the indicator uses shorter periods and responds faster. When the market stretches into longer cycles (such as 40-bar cycles), it automatically extends its lookback to avoid whipsaws.
The Period Multipliers let you fine-tune this relationship:
โข 1.0 = Use the full detected cycle (smoother, fewer signals)
โข 0.5 = Use half the cycle (more responsive, catches turns earlier)
INTERPRETATION
Reading the Oscillator:
โข K Line (Blue) โ The main signal line. Moves between 0 and 100.
โข D Line (Orange) โ Smoothed version of K. Use for confirmation.
โข Above 80 โ Overbought. Momentum stretched to upside.
โข Below 20 โ Oversold. Momentum stretched to downside.
โข Crossovers โ K crossing above D suggests bullish momentum shift; K crossing below D suggests bearish.
Spectral Dilation (optional):
When enabled, applies a bandpass filter before cycle detection. This isolates the frequency band of interest and reduces noise. Useful for:
โข Very noisy instruments
โข Lower timeframes
โข When confidence stays persistently low
Bli-Rik (Buy and sell based on RSI & SMA)Basis analysis of Stoch RSI + RSI + 34/200 SMA Signals we have identified and generated Buy and sell indication on chart, This will help to guild buy and sell process...
AJFFRSI+QQEROC Uses Jurik RSI for smooth, responsive momentum measurement
Incorporates QQE features for trend strength and dynamic trailing stop signals
Designed for clearer, more reliable overbought/oversold and reversal signals on TradingView
Suitable for intraday, swing, and longer-term analysis
Not a financial advice. DYOR
Stochastic BTC OptimizedEnhanced Stochastic for Bitcoin (BTC) โ Optimized for Daily Timeframe
This enhanced Stochastic oscillator is specifically fine-tuned for BTC/USD on the 1D timeframe, leveraging historical data from Bitstamp (2011โ2025) to minimize false signals and maximize reliability in Bitcoin's volatile swings.
Unlike the classic Stochastic (14, 3, 3), this version uses optimized parameters:
- K Period = 21 โ smoother reaction, better suited for BTCโs macro cycles
- D Period = 3, Smooth K = 3 โ reduces noise while preserving responsiveness
- Overbought = 85, Oversold = 15 โ accounts for BTCโs tendency to trend strongly within extreme zones without immediate reversal
โ
Smart Signal Logic:
Buy/sell signals appear only when %K crosses %D inside the oversold (โค15) or overbought (โฅ85) zones, and only the first signal is shown to avoid whipsaws.
Visual Enhancements:
- Thick lines when %K/%D are in overbought/oversold zones
- Green/red background highlights on valid signals
- Optional up/down arrows for clear entry visualization
- Customizable colors, line widths, and transparency
๐ No alerts included โ clean, focused on price action and momentum.
๐ก Pro Tip: For even higher accuracy, use this indicator in combination with a long-term trend filter (e.g., EMA 200). The oscillator excels in ranging or retracement phases but should not be used alone in strong parabolic moves.
Based on Mozilla Public License v2.0 โ feel free to use, modify, and share. Perfect for swing traders and long-term Bitcoin analysts seeking high-probability reversal zones.
ะฟะตัะตะฒะพะด ะฝะฐ ััััะบะธะน
ะฃะปัััะตะฝะฝัะน Stochastic ะดะปั Bitcoin (BTC) โ ะพะฟัะธะผะธะทะธัะพะฒะฐะฝ ะดะปั ะดะฝะตะฒะฝะพะณะพ ัะฐะนะผััะตะนะผะฐ
ะญัะพั ัะปัััะตะฝะฝัะน ะพััะธะปะปััะพั Stochastic ัะฟะตัะธะฐะปัะฝะพ ะฝะฐัััะพะตะฝ ะฟะพะด BTC/USD ะฝะฐ ะดะฝะตะฒะฝะพะผ ะณัะฐัะธะบะต, ั ััััะพะผ ะธััะพัะธัะตัะบะธั
ะดะฐะฝะฝัั
Bitstamp (2011โ2025), ััะพะฑั ะผะธะฝะธะผะธะทะธัะพะฒะฐัั ะปะพะถะฝัะต ัะธะณะฝะฐะปั ะธ ะฟะพะฒััะธัั ะฝะฐะดัะถะฝะพััั ะฒ ััะปะพะฒะธัั
ะฒััะพะบะพะน ะฒะพะปะฐัะธะปัะฝะพััะธ ะฑะธัะบะพะธะฝะฐ.
ะ ะพัะปะธัะธะต ะพั ะบะปะฐััะธัะตัะบะพะณะพ Stochastic (14, 3, 3), ััะฐ ะฒะตััะธั ะธัะฟะพะปัะทัะตั ะพะฟัะธะผะธะทะธัะพะฒะฐะฝะฝัะต ะฟะฐัะฐะผะตััั:
- ะะตัะธะพะด K = 21 โ ะฑะพะปะตะต ะฟะปะฐะฒะฝะฐั ัะตะฐะบัะธั, ะปัััะต ัะพะพัะฒะตัััะฒัะตั ะผะฐะบัะพัะธะบะปะฐะผ BTC
- ะะตัะธะพะด D = 3, ะกะณะปะฐะถะธะฒะฐะฝะธะต K = 3 โ ัะฝะธะถะฐะตั ััะผ, ัะพั
ัะฐะฝัั ะพัะทัะฒัะธะฒะพััั
- ะฃัะพะฒะตะฝั ะฟะตัะตะบัะฟะปะตะฝะฝะพััะธ = 85, ะฟะตัะตะฟัะพะดะฐะฝะฝะพััะธ = 15 โ ััะธััะฒะฐะตั ัะบะปะพะฝะฝะพััั BTC ะบ ัะธะปัะฝัะผ ััะตะฝะดะฐะผ ะฒ ัะบัััะตะผะฐะปัะฝัั
ะทะพะฝะฐั
ะฑะตะท ะฝะตะผะตะดะปะตะฝะฝะพะณะพ ัะฐะทะฒะพัะพัะฐ
โ
ะะฝัะตะปะปะตะบััะฐะปัะฝะฐั ะปะพะณะธะบะฐ ัะธะณะฝะฐะปะพะฒ:
ะะพะบัะฟะบะฐ/ะฟัะพะดะฐะถะฐ ะพัะพะฑัะฐะถะฐะตััั ัะพะปัะบะพ ะฟัะธ ะฟะตัะตัะตัะตะฝะธะธ %K ะธ %D ะฒะฝัััะธ ะทะพะฝั ะฟะตัะตะฟัะพะดะฐะฝะฝะพััะธ (โค15) ะธะปะธ ะฟะตัะตะบัะฟะปะตะฝะฝะพััะธ (โฅ85), ะธ ัะพะปัะบะพ ะฟะตัะฒัะน ัะธะณะฝะฐะป ัะธะบัะธััะตััั, ััะพะฑั ะธะทะฑะตะถะฐัั ยซั
ะปัััะพะฒยป.
ะฃะปัััะตะฝะฝะฐั ะฒะธะทัะฐะปะธะทะฐัะธั:
- ะะธัะฝัะต ะปะธะฝะธะธ, ะบะพะณะดะฐ %K/%D ะฝะฐั
ะพะดัััั ะฒ ัะบัััะตะผะฐะปัะฝัั
ะทะพะฝะฐั
- ะะตะปัะฝัะน/ะบัะฐัะฝัะน ัะพะฝ ะฟัะธ ะฟะพัะฒะปะตะฝะธะธ ัะธะณะฝะฐะปะพะฒ
- ะะฟัะธะพะฝะฐะปัะฝัะต ัััะตะปะบะธ ะดะปั ัััะบะพะณะพ ะพัะพะฑัะฐะถะตะฝะธั ัะพัะตะบ ะฒั
ะพะดะฐ
- ะะฐัััะพะนะบะฐ ัะฒะตัะพะฒ, ัะพะปัะธะฝั ะปะธะฝะธะน ะธ ะฟัะพะทัะฐัะฝะพััะธ
๐ ะะตะท ะฐะปะตััะพะฒ โ ัะธัััะน ะธะฝััััะผะตะฝั, ััะพะบััะธัะพะฒะฐะฝะฝัะน ะฝะฐ ัะตะฝะต ะธ ะธะผะฟัะปััะต.
๐ก ะกะพะฒะตั ะฟัะพัะตััะธะพะฝะฐะปะฐ: ะดะปั ะตัั ะฑะพะปััะตะน ัะพัะฝะพััะธ ะธัะฟะพะปัะทัะนัะต ััะพั ะธะฝะดะธะบะฐัะพั ะฒะผะตััะต ั ััะตะฝะดะพะฒัะผ ัะธะปัััะพะผ (ะฝะฐะฟัะธะผะตั, EMA 200). ะััะธะปะปััะพั ะปัััะต ะฒัะตะณะพ ัะฐะฑะพัะฐะตั ะฒ ัะฐะทะฐั
ะบะพะฝัะพะปะธะดะฐัะธะธ ะธะปะธ ะพัะบะฐัะฐ, ะฝะพ ะฝะต ััะพะธั ะฟัะธะผะตะฝััั ะตะณะพ ะฒ ะพะดะธะฝะพัะบั ะฒะพ ะฒัะตะผั ัะธะปัะฝัั
ะฟะฐัะฐะฑะพะปะธัะตัะบะธั
ะดะฒะธะถะตะฝะธะน.
ะะฐ ะพัะฝะพะฒะต Mozilla Public License v2.0 โ ัะฒะพะฑะพะดะฝะพ ะธัะฟะพะปัะทัะนัะต, ะผะพะดะธัะธัะธััะนัะต ะธ ะดะตะปะธัะตัั. ะะดะตะฐะปะตะฝ ะดะปั ัะฒะธะฝะณ-ััะตะนะดะตัะพะฒ ะธ ะฐะฝะฐะปะธัะธะบะพะฒ Bitcoin, ะธัััะธั
ะทะพะฝั ั ะฒััะพะบะพะน ะฒะตัะพััะฝะพัััั ัะฐะทะฒะพัะพัะฐ.
Stochastic Hash Strat [Hash Capital Research]# Stochastic Hash Strategy by Hash Capital Research
## ๐ฏ What Is This Strategy?
The **Stochastic Slow Strategy** is a momentum-based trading system that identifies oversold and overbought market conditions to capture mean-reversion opportunities. Think of it as a "buy low, sell high" approach with smart mathematical filters that remove emotion from your trading decisions.
Unlike fast-moving indicators that generate excessive noise, this strategy uses **smoothed stochastic oscillators** to identify only the highest-probability setups when momentum truly shifts.
---
## ๐ก Why This Strategy Works
Most traders fail because they:
- **Chase prices** after big moves (buying high, selling low)
- **Overtrade** in choppy, directionless markets
- **Exit too early** or hold losses too long
This strategy solves all three problems:
1. **Entry Discipline**: Only trades when the stochastic oscillator crosses in extreme zones (oversold for longs, overbought for shorts)
2. **Cooldown Filter**: Prevents revenge trading by forcing a waiting period after each trade
3. **Fixed Risk/Reward**: Pre-defined stop-loss and take-profit levels ensure consistent risk management
**The Math Behind It**: The stochastic oscillator measures where the current price sits relative to its recent high-low range. When it's below 25, the market is oversold (time to buy). When above 70, it's overbought (time to sell). The crossover with its moving average confirms momentum is shifting.
---
## ๐ Best Markets & Timeframes
### โญ OPTIMAL PERFORMANCE:
**Crude Oil (WTI) - 12H Timeframe**
- **Why it works**: Oil markets have predictable volatility patterns and respect technical levels
**AAVE/USD - 4H to 12H Timeframe**
- **Why it works**: DeFi tokens exhibit strong momentum cycles with clear extremes
### โ
Also Works Well On:
- **BTC/USD** (12H, Daily) - Lower frequency but high win rate
- **ETH/USD** (8H, 12H) - Balanced volatility and liquidity
- **Gold (XAU/USD)** (Daily) - Classic mean-reversion asset
- **EUR/USD** (4H, 8H) - Lower volatility, requires patience
### โ Avoid Using On:
- Timeframes below 4H (too much noise)
- Low-liquidity altcoins (wide spreads kill performance)
- Strongly trending markets without pullbacks (Bitcoin in 2021)
- News-driven instruments during major events
---
## ๐๏ธ Understanding The Settings
### Core Stochastic Parameters
**Stochastic Length (Default: 16)**
- Controls the lookback period for price comparison
- Lower = faster reactions, more signals (10-14 for volatile markets)
- Higher = smoother signals, fewer trades (16-21 for stable markets)
- **Pro tip**: Use 10 for crypto 4H, 16 for commodities 12H
**Overbought Level (Default: 70)**
- Threshold for short entries
- Lower values (65-70) = more trades, earlier entries
- Higher values (75-80) = fewer but higher-conviction trades
- **Sweet spot**: 70 works for most assets
**Oversold Level (Default: 25)**
- Threshold for long entries
- Higher values (25-30) = more trades, earlier entries
- Lower values (15-20) = fewer but stronger bounce setups
- **Sweet spot**: 20-25 depending on market conditions
**Smooth K & Smooth D (Default: 7 & 3)**
- Additional smoothing to filter out whipsaws
- K=7 makes the indicator slower and more reliable
- D=3 is the signal line that confirms the trend
- **Don't change these unless you know what you're doing**
---
### Risk Management
**Stop Loss % (Default: 2.2%)**
- Automatically exits losing trades
- Should be 1.5x to 2x your average market volatility
- Too tight = death by a thousand cuts
- Too wide = uncontrolled losses
- **Calibration**: Check ATR indicator and set SL slightly above it
**Take Profit % (Default: 7%)**
- Automatically exits winning trades
- Should be 2.5x to 3x your stop loss (reward-to-risk ratio)
- This default gives 7% / 2.2% = 3.18:1 R:R
- **The golden rule**: Never have R:R below 2:1
---
### Trade Filters
**Bar Cooldown Filter (Default: ON, 3 bars)**
- **What it does**: Forces you to wait X bars after closing a trade before entering a new one
- **Why it matters**: Prevents emotional revenge trading and overtrading in choppy markets
- **Settings guide**:
- 3 bars = Standard (good for most cases)
- 5-7 bars = Conservative (oil, slow-moving assets)
- 1-2 bars = Aggressive (only for experienced traders)
**Exit on Opposite Extreme (Default: ON)**
- Closes your long when stochastic hits overbought (and vice versa)
- Acts as an early profit-taking mechanism
- **Leave this ON** unless you're testing other exit strategies
**Divergence Filter (Default: OFF)**
- Looks for price/momentum divergences for additional confirmation
- **When to enable**: Trending markets where you want fewer but higher-quality trades
- **Keep OFF for**: Mean-reverting markets (oil, forex, most of the time)
---
## ๐ Quick Start Guide
### Step 1: Set Up in TradingView
1. Open TradingView and navigate to your chart
2. Click "Pine Editor" at the bottom
3. Copy and paste the strategy code
4. Click "Add to Chart"
5. The strategy will appear in a separate pane below your price chart
### Step 2: Choose Your Market
**If you're trading Crude Oil:**
- Timeframe: 12H
- Keep all default settings
- Watch for signals during London/NY overlap (8am-11am EST)
**If you're trading AAVE or crypto:**
- Timeframe: 4H or 12H
- Consider these adjustments:
- Stochastic Length: 10-14 (faster)
- Oversold: 20 (more aggressive)
- Take Profit: 8-10% (higher targets)
### Step 3: Wait for Your First Signal
**LONG Entry** (Green circle appears):
- Stochastic crosses up below oversold level (25)
- Price likely near recent lows
- System places limit order at take profit and stop loss
**SHORT Entry** (Red circle appears):
- Stochastic crosses down above overbought level (70)
- Price likely near recent highs
- System places limit order at take profit and stop loss
**EXIT** (Orange circle):
- Position closes either at stop, target, or opposite extreme
- Cooldown period begins
### Step 4: Let It Run
The biggest mistake? **Interfering with the system.**
- Don't close trades early because you're scared
- Don't skip signals because you "have a feeling"
- Don't increase position size after a big win
- Don't revenge trade after a loss
**Follow the system or don't use it at all.**
---
### Important Risks:
1. **Drawdown Pain**: You WILL experience losing streaks of 5-7 trades. This is mathematically normal.
2. **Whipsaw Markets**: Choppy, range-bound conditions can trigger multiple small losses.
3. **Gap Risk**: Overnight gaps can cause your actual fill to be worse than the stop loss.
4. **Slippage**: Real execution prices differ from backtested prices (factor in 0.1-0.2% slippage).
---
## ๐ง Optimization Guide
### When to Adjust Settings:
**Market Volatility Increased?**
- Widen stop loss by 0.5-1%
- Increase take profit proportionally
- Consider increasing cooldown to 5-7 bars
**Getting Too Few Signals?**
- Decrease stochastic length to 10-12
- Increase oversold to 30, decrease overbought to 65
- Reduce cooldown to 2 bars
**Getting Too Many Losses?**
- Increase stochastic length to 18-21 (slower, smoother)
- Enable divergence filter
- Increase cooldown to 5+ bars
- Verify you're on the right timeframe
### A/B Testing Method:
1. **Run default settings for 50 trades** on your chosen market
2. Document: Win rate, profit factor, max drawdown, emotional tolerance
3. **Change ONE variable** (e.g., oversold from 25 to 20)
4. Run another 50 trades
5. Compare results
6. Keep the better version
**Never change multiple settings at once** or you won't know what worked.
---
## ๐ Educational Resources
### Key Concepts to Learn:
**Stochastic Oscillator**
- Developed by George Lane in the 1950s
- Measures momentum by comparing closing price to price range
- Formula: %K = (Close - Low) / (High - Low) ร 100
- Similar to RSI but more sensitive to price movements
**Mean Reversion vs. Trend Following**
- This is a **mean reversion** strategy (price returns to average)
- Works best in ranging markets with defined support/resistance
- Fails in strong trending markets (2017 Bitcoin, 2020 Tech stocks)
- Complement with trend filters for better results
**Risk:Reward Ratio**
- The cornerstone of profitable trading
- Winning 40% of trades with 3:1 R:R = profitable
- Winning 60% of trades with 1:1 R:R = breakeven (after fees)
- **This strategy aims for 45% win rate with 2.5-3:1 R:R**
### Recommended Reading:
- *"Trading Systems and Methods"* by Perry Kaufman (Chapter on Oscillators)
- *"Mean Reversion Trading Systems"* by Howard Bandy
- *"The New Trading for a Living"* by Dr. Alexander Elder
---
## ๐ ๏ธ Troubleshooting
### "I'm not seeing any signals!"
**Check:**
- Is your timeframe 4H or higher?
- Is the stochastic actually reaching extreme levels (check if your asset is stuck in middle range)?
- Is cooldown still active from a previous trade?
- Are you on a low-liquidity pair?
**Solution**: Switch to a more volatile asset or lower the overbought/oversold thresholds.
---
### "The strategy keeps losing money!"
**Check:**
- What's your win rate? (Below 35% is concerning)
- What's your profit factor? (Below 0.8 means serious issues)
- Are you trading during major news events?
- Is the market in a strong trend?
**Solution**:
1. Verify you're using recommended markets/timeframes
2. Increase cooldown period to avoid choppy markets
3. Reduce position size to 5% while you diagnose
4. Consider switching to daily timeframe for less noise
---
### "My stop losses keep getting hit!"
**Check:**
- Is your stop loss tighter than the average ATR?
- Are you trading during high-volatility sessions?
- Is slippage eating into your buffer?
**Solution**:
1. Calculate the 14-period ATR
2. Set stop loss to 1.5x the ATR value
3. Avoid trading right after market open or major news
4. Factor in 0.2% slippage for crypto, 0.1% for oil
---
## ๐ช Pro Tips from the Trenches
### Psychological Discipline
**The Three Deadly Sins:**
1. **Skipping signals** - "This one doesn't feel right"
2. **Early exits** - "I'll just take profit here to be safe"
3. **Revenge trading** - "I need to make back that loss NOW"
**The Solution:** Treat your strategy like a business system. Would McDonald's skip making fries because the cashier "doesn't feel like it today"? No. Systems work because of consistency.
---
### Position Management
**Scaling In/Out** (Advanced)
- Enter 50% position at signal
- Add 50% if stochastic reaches 10 (oversold) or 90 (overbought)
- Exit 50% at 1.5x take profit, let the rest run
**This is NOT for beginners.** Master the basic system first.
---
### Market Awareness
**Oil Traders:**
- OPEC meetings = volatility spikes (avoid or widen stops)
- US inventory reports (Wed 10:30am EST) = avoid trading 2 hours before/after
- Summer driving season = different patterns than winter
**Crypto Traders:**
- Monday-Tuesday = typically lower volatility (fewer signals)
- Thursday-Sunday = higher volatility (more signals)
- Avoid trading during exchange maintenance windows
---
## โ๏ธ Legal Disclaimer
This trading strategy is provided for **educational purposes only**.
- Past performance does not guarantee future results
- Trading involves substantial risk of loss
- Only trade with capital you can afford to lose
- No one associated with this strategy is a licensed financial advisor
- You are solely responsible for your trading decisions
**By using this strategy, you acknowledge that you understand and accept these risks.**
---
## ๐ Acknowledgments
Strategy development inspired by:
- George Lane's original Stochastic Oscillator work
- Modern quantitative trading research
- Community feedback from hundreds of backtests
Built with โค๏ธ for retail traders who want systematic, disciplined approaches to the markets.
---
**Good luck, stay disciplined, and trade the system, not your emotions.**
Dual MACD With Pilot Background + + Stoch RSI Alert HELL 2macd 1 chart time macd 2 4x chart time with over bought and over sold stoc rsi alerts
SMI Color Red/Green๐ TradingView Description โ SMI Red/Green Momentum Line
๐ฅ Stochastics Momentum Index (SMI) โ Dynamic Red/Green Version
This indicator is an enhanced and modernized version of the Stochastic Momentum Index (SMI), designed to deliver a more visual, intuitive, and responsive view of trend momentum.
It includes:
โ๏ธ Smoothed SMI
โ๏ธ Dynamic Red/Green momentum coloring
โ๏ธ Signal EMA line
โ๏ธ Overbought/Oversold zones with shading
๐จ Dynamic Red/Green SMI Line
The main SMI line automatically changes color based on momentum direction:
Green โ Bullish momentum (SMI rising)
Red โ Bearish momentum (SMI falling)
This provides instant visual feedback and highlights early momentum changes even before traditional signal-line crossovers.
๐ Indicator Structure
1๏ธโฃ Smoothed SMI
The SMI is calculated using the priceโs position inside its range and then smoothed with an SMA to reduce noise.
2๏ธโฃ EMA Signal Line
A customizable EMA acts as a signal line, providing:
Clear bullish/bearish crossovers
Trend confirmation
Cleaner entry/exit signals
3๏ธโฃ Overbought / Oversold Zones
Extreme levels are highlighted using color-filled zones:
Red Zone (Overbought) โ potential bearish reversal
Green Zone (Oversold) โ potential bullish reversal
Levels are fully adjustable.
๐ก How to Use It
The indicator works exceptionally well across all timeframes.
The most powerful signals are:
โ๏ธ SMI crossing above/below the EMA
SMI crosses above EMA โ bullish signal
SMI crosses below EMA โ bearish signal
โ๏ธ Leaving Overbought/Oversold zones
SMI exits the oversold zone โ potential long setup
SMI exits the overbought zone โ potential short setup
โ๏ธ Color shifts (momentum direction)
Red โ Green : early bullish momentum
Green โ Red : early bearish momentum
Perfect for scalping, day trading, and swing trading.
๐ Why This Version Is Better
Extremely visual momentum reading
Noise reduction through smoothing
Instantly readable color-coded trend
Strong OB/OS zone visualization
Works on any market and timeframe
Great in combination with RSI, MACD, HMA, ALMA, and trend filters
If you'd like, I can also write:
๐น a SEO-optimized title,
๐น recommended TradingView tags,
๐น or a shorter promotional description.
MACD FROM HELLthis is a double macd with 2 time frames macd 1 is chart macd 4 is 4X meaning the 1hr becomes the 4hr and it uses the histogram coloring for added detail ,, on top of that it has stochastic rsi Alerts set to trigger when k line goes above 99.9 or below 0.01 and exits ,, alert triggers on exit
BIAS RSI STOCH MACD Displaysimple but effective to prevent chart clutter.
Hi Traders! Today Iโm showing you a **custom indicator** that combines **BIAS, RSI, Stochastic, and MACD** in one easy-to-read panel. Letโs break it down:
1๏ธโฃ **BIAS** โ Shows how far the price is from its moving average.
* Positive BIAS โ price is above the average.
* Negative BIAS โ price is below the average.
2๏ธโฃ **RSI (Relative Strength Index)** โ Measures momentum.
* Above 70 โ overbought
* Below 30 โ oversold
* **50 line added** โ midpoint for trend direction
3๏ธโฃ **Stochastic (STOCH)** โ Confirms momentum like RSI.
* Above 80 โ overbought
* Below 20 โ oversold
4๏ธโฃ **MACD (Moving Average Convergence Divergence)** โ Shows trend and momentum.
* Histogram colors indicate strength
* Lines show trend direction
5๏ธโฃ **Visual Table** โ On the top right, you can see all current indicator values at a glance, with color coding for easy interpretation.
6๏ธโฃ **Plots & Levels** โ
* BIAS, RSI, Stoch are plotted clearly
* RSI has **midline at 50** for trend reference
* Standard overbought/oversold levels highlighted
โ
**How to Use:**
* Look for RSI or Stoch crossing midline or extreme levels for potential entries.
* Check MACD histogram and lines for confirmation of trend strength.
* Use BIAS to see if price is stretched from the moving average.
This indicator is perfect for **momentum, trend, and mean-reversion traders**, giving multiple signals in one pane without clutter.
---
Range Oscillator Strategy + Stoch Confirm๐น Short summary
This is a free, educational long-only strategy built on top of the public โRange Oscillatorโ by Zeiierman (used under CC BY-NC-SA 4.0), combined with a Stochastic timing filter, an EMA-based exit filter and an optional risk-management layer (SL/TP and R-multiple exits). It is NOT financial advice and it is NOT a magic money machine. Itโs a structured framework to study how range-expansion + momentum + trend slope can be combined into one rule-based system, often with intentionally RARE trades.
โโโโโโโโโโโโโโโโโโโโโโโโ
0. Legal / risk disclaimer
โโโโโโโโโโโโโโโโโโโโโโโโ
โข This script is FREE and public. I do not charge any fee for it.
โข It is for EDUCATIONAL PURPOSES ONLY.
โข It is NOT financial advice and does NOT guarantee profits.
โข Backtest results can be very different from live results.
โข Markets change over time; past performance is NOT indicative of future performance.
โข You are fully responsible for your own trades and risk.
Please DO NOT use this script with money you cannot afford to lose. Always start in a demo / paper trading environment and make sure you understand what the logic does before you risk any capital.
โโโโโโโโโโโโโโโโโโโโโโโโ
1. About default settings and risk (very important)
โโโโโโโโโโโโโโโโโโโโโโโโ
The script is configured with the following defaults in the `strategy()` declaration:
โข `initial_capital = 10000`
โ This is only an EXAMPLE account size.
โข `default_qty_type = strategy.percent_of_equity`
โข `default_qty_value = 100`
โ This means 100% of equity per trade in the default properties.
โ This is AGGRESSIVE and should be treated as a STRESS TEST of the logic, not as a realistic way to trade.
TradingViewโs House Rules recommend risking only a small part of equity per trade (often 1โ2%, max 5โ10% in most cases). To align with these recommendations and to get more realistic backtest results, I STRONGLY RECOMMEND you to:
1. Open **Strategy Settings โ Properties**.
2. Set:
โข Order size: **Percent of equity**
โข Order size (percent): e.g. **1โ2%** per trade
3. Make sure **commission** and **slippage** match your own broker conditions.
โข By default this script uses `commission_value = 0.1` (0.1%) and `slippage = 3`, which are reasonable example values for many crypto markets.
If you choose to run the strategy with 100% of equity per trade, please treat it ONLY as a stress-test of the logic. It is NOT a sustainable risk model for live trading.
โโโโโโโโโโโโโโโโโโโโโโโโ
2. What this strategy tries to do (conceptual overview)
โโโโโโโโโโโโโโโโโโโโโโโโ
This is a LONG-ONLY strategy designed to explore the combination of:
1. **Range Oscillator (Zeiierman-based)**
- Measures how far price has moved away from an adaptive mean.
- Uses an ATR-based range to normalize deviation.
- High positive oscillator values indicate strong price expansion away from the mean in a bullish direction.
2. **Stochastic as a timing filter**
- A classic Stochastic (%K and %D) is used.
- The logic requires %K to be below a user-defined level and then crossing above %D.
- This is intended to catch moments when momentum turns up again, rather than chasing every extreme.
3. **EMA Exit Filter (trend slope)**
- An EMA with configurable length (default 70) is calculated.
- The slope of the EMA is monitored: when the slope turns negative while in a long position, and the filter is enabled, it triggers an exit condition.
- This acts as a trend-protection exit: if the medium-term trend starts to weaken, the strategy exits even if the oscillator has not yet fully reverted.
4. **Optional risk-management layer**
- Percentage-based Stop Loss and Take Profit (SL/TP).
- Risk/Reward (R-multiple) exit based on the distance from entry to SL.
- Implemented as OCO orders that work *on top* of the logical exits.
The goal is not to create a โholy grailโ system but to serve as a transparent, configurable framework for studying how these concepts behave together on different markets and timeframes.
โโโโโโโโโโโโโโโโโโโโโโโโ
3. Components and how they work together
โโโโโโโโโโโโโโโโโโโโโโโโ
(1) Range Oscillator (based on โRange Oscillator (Zeiierman)โ)
โข The script computes a weighted mean price and then measures how far price deviates from that mean.
โข Deviation is normalized by an ATR-based range and expressed as an oscillator.
โข When the oscillator is above the **entry threshold** (default 100), it signals a strong move away from the mean in the bullish direction.
โข When it later drops below the **exit threshold** (default 30), it can trigger an exit (if enabled).
(2) Stochastic confirmation
โข Classic Stochastic (%K and %D) is calculated.
โข An entry requires:
- %K to be below a user-defined โCross Levelโ, and
- then %K to cross above %D.
โข This is a momentum confirmation: the strategy tries to enter when momentum turns up from a pullback rather than at any random point.
(3) EMA Exit Filter
โข The EMA length is configurable via `emaLength` (default 70).
โข The script monitors the EMA slope: it computes the relative change between the current EMA and the previous EMA.
โข If the slope turns negative while the strategy holds a long position and the filter is enabled, it triggers an exit condition.
โข This is meant to help protect profits or cut losses when the medium-term trend starts to roll over, even if the oscillator conditions are not (yet) signalling exit.
(4) Risk management (optional)
โข Stop Loss (SL) and Take Profit (TP):
- Defined as percentages relative to average entry price.
- Both are disabled by default, but you can enable them in the Inputs.
โข Risk/Reward Exit:
- Uses the distance from entry to SL to project a profit target at a configurable R-multiple.
- Also optional and disabled by default.
These exits are implemented as `strategy.exit()` OCO orders and can close trades independently of oscillator/EMA conditions if hit first.
โโโโโโโโโโโโโโโโโโโโโโโโ
4. Entry & Exit logic (high level)
โโโโโโโโโโโโโโโโโโโโโโโโ
A) Time filter
โข You can choose a **Start Year** in the Inputs.
โข Only candles between the selected start date and 31 Dec 2069 are used for backtesting (`timeCondition`).
โข This prevents accidental use of tiny cherry-picked windows and makes tests more honest.
B) Entry condition (long-only)
A long entry is allowed when ALL the following are true:
1. `timeCondition` is true (inside the backtest window).
2. If `useOscEntry` is true:
- Range Oscillator value must be above `entryLevel`.
3. If `useStochEntry` is true:
- Stochastic condition (`stochCondition`) must be true:
- %K < `crossLevel`, then %K crosses above %D.
If these filters agree, the strategy calls `strategy.entry("Long", strategy.long)`.
C) Exit condition (logical exits)
A position can be closed when:
1. `timeCondition` is true AND a long position is open, AND
2. At least one of the following is true:
- If `useOscExit` is true: Oscillator is below `exitLevel`.
- If `useMagicExit` (EMA Exit Filter) is true: EMA slope is negative (`isDown = true`).
In that case, `strategy.close("Long")` is called.
D) Risk-management exits
While a position is open:
โข If SL or TP is enabled:
- `strategy.exit("Long Risk", ...)` places an OCO stop/limit order based on the SL/TP percentages.
โข If Risk/Reward exit is enabled:
- `strategy.exit("RR Exit", ...)` places an OCO order using a projected R-multiple (`rrMult`) of the SL distance.
These risk-based exits can trigger before the logical oscillator/EMA exits if price hits those levels.
โโโโโโโโโโโโโโโโโโโโโโโโ
5. Recommended backtest configuration (to avoid misleading results)
โโโโโโโโโโโโโโโโโโโโโโโโ
To align with TradingView House Rules and avoid misleading backtests:
1. **Initial capital**
- 10 000 (or any value you personally want to work with).
2. **Order size**
- Type: **Percent of equity**
- Size: **1โ2%** per trade is a reasonable starting point.
- Avoid risking more than 5โ10% per trade if you want results that could be sustainable in practice.
3. **Commission & slippage**
- Commission: around 0.1% if that matches your broker.
- Slippage: a few ticks (e.g. 3) to account for real fills.
4. **Timeframe & markets**
- Volatile symbols (e.g. crypto like BTCUSDT, or major indices).
- Timeframes: 1H / 4H / **1D (Daily)** are typical starting points.
- I strongly recommend trying the strategy on **different timeframes**, for example 1D, to see how the behaviour changes between intraday and higher timeframes.
5. **No โcaution warningโ**
- Make sure your chosen symbol + timeframe + settings do not trigger TradingViewโs caution messages.
- If you see warnings (e.g. โtoo few tradesโ), adjust timeframe/symbol or the backtest period.
โโโโโโโโโโโโโโโโโโโโโโโโ
5a. About low trade count and rare signals
โโโโโโโโโโโโโโโโโโโโโโโโ
This strategy is intentionally designed to trade RARELY:
โข It is **long-only**.
โข It uses strict filters (Range Oscillator threshold + Stochastic confirmation + optional EMA Exit Filter).
โข On higher timeframes (especially **1D / Daily**) this can result in a **low total number of trades**, sometimes WELL BELOW 100 trades over the whole backtest.
TradingViewโs House Rules mention 100+ trades as a guideline for more robust statistics. In this specific case:
โข The **low trade count is a conscious design choice**, not an attempt to cherry-pick a tiny, ultra-profitable window.
โข The goal is to study a **small number of high-conviction long entries** on higher timeframes, not to generate frequent intraday signals.
โข Because of the low trade count, results should NOT be interpreted as statistically strong or โprovenโ โ they are only one sample of how this logic would have behaved on past data.
Please keep this in mind when you look at the equity curve and performance metrics. A beautiful curve with only a handful of trades is still just a small sample.
โโโโโโโโโโโโโโโโโโโโโโโโ
6. How to use this strategy (step-by-step)
โโโโโโโโโโโโโโโโโโโโโโโโ
1. Add the script to your chart.
2. Open the **Inputs** tab:
- Set the backtest start year.
- Decide whether to use Oscillator-based entry/exit, Stochastic confirmation, and EMA Exit Filter.
- Optionally enable SL, TP, and Risk/Reward exits.
3. Open the **Properties** tab:
- Set a realistic account size if you want.
- Set order size to a realistic % of equity (e.g. 1โ2%).
- Confirm that commission and slippage are realistic for your broker.
4. Run the backtest:
- Look at Net Profit, Max Drawdown, number of trades, and equity curve.
- Remember that a low trade count means the statistics are not very strong.
5. Experiment:
- Tweak thresholds (`entryLevel`, `exitLevel`), Stochastic settings, EMA length, and risk params.
- See how the metrics and trade frequency change.
6. Forward-test:
- Before using any idea in live trading, forward-test on a demo account and observe behaviour in real time.
โโโโโโโโโโโโโโโโโโโโโโโโ
7. Originality and usefulness (why this is more than a mashup)
โโโโโโโโโโโโโโโโโโโโโโโโ
This script is not intended to be a random visual mashup of indicators. It is designed as a coherent, testable strategy with clear roles for each component:
โข Range Oscillator:
- Handles mean vs. range-expansion states via an adaptive, ATR-normalized metric.
โข Stochastic:
- Acts as a timing filter to avoid entering purely on extremes and instead waits for momentum to turn.
โข EMA Exit Filter:
- Trend-slope-based safety net to exit when the medium-term direction changes against the position.
โข Risk module:
- Provides practical, rule-based exits: SL, TP, and R-multiple exit, which are useful for structuring risk even if you modify the core logic.
It aims to give traders a ready-made **framework to study and modify**, not a black box or โsignalsโ product.
โโโโโโโโโโโโโโโโโโโโโโโโ
8. Limitations and good practices
โโโโโโโโโโโโโโโโโโโโโโโโ
โข No single strategy works on all markets or in all regimes.
โข This script is long-only; it does not short the market.
โข Performance can degrade when market structure changes.
โข Overfitting (curve fitting) is a real risk if you endlessly tweak parameters to maximise historical profit.
Good practices:
- Test on multiple symbols and timeframes.
- Focus on stability and drawdown, not only on how high the profit line goes.
- View this as a learning tool and a basis for your own research.
โโโโโโโโโโโโโโโโโโโโโโโโ
9. Licensing and credits
โโโโโโโโโโโโโโโโโโโโโโโโ
โข Core oscillator idea & base code:
- โRange Oscillator (Zeiierman)โ
- ยฉ Zeiierman, licensed under CC BY-NC-SA 4.0.
โข Strategy logic, Stochastic confirmation, EMA Exit Filter, and risk-management layer:
- Modifications by jokiniemi.
Please respect both the original license and TradingView House Rules if you fork or republish any part of this script.
โโโโโโโโโโโโโโโโโโโโโโโโ
10. No payments / no vendor pitch
โโโโโโโโโโโโโโโโโโโโโโโโ
โข This script is completely FREE to use on TradingView.
โข There is no paid subscription, no external payment link, and no private signals group attached to it.
โข If you have questions, please use TradingViewโs comment system or private messages instead of expecting financial advice.
Use this script as a tool to learn, experiment, and build your own understanding of markets.
โโโโโโโโโโโโโโโโโโโโโโโโ
11. Example backtest settings used in screenshots
โโโโโโโโโโโโโโโโโโโโโโโโ
To avoid any confusion about how the results shown in screenshots were produced, here is one concrete example configuration:
โข Symbol: BTCUSDT (or similar major BTC pair)
โข Timeframe: 1D (Daily)
โข Backtest period: from 2018 to the most recent data
โข Initial capital: 10 000
โข Order size type: Percent of equity
โข Order size: 2% per trade
โข Commission: 0.1%
โข Slippage: 3 ticks
โข Risk settings: Stop Loss and Take Profit disabled by default, Risk/Reward exit disabled by default
โข Filters: Range Oscillator entry/exit enabled, Stochastic confirmation enabled, EMA Exit Filter enabled
If you change any of these settings (symbol, timeframe, risk per trade, commission, slippage, filters, etc.), your results will look different. Please always adapt the configuration to your own risk tolerance, market, and trading style.
Stochastic RSI - WT Confluence Signal Detectors (TraderDemircan)Description
What This Indicator Does:
This indicator combines two powerful momentum oscillatorsโWaveTrend and Stochastic RSIโto identify high-probability trading signals through confluence. Instead of relying on a single indicator that may generate false signals, this tool only triggers buy/sell alerts when both oscillators simultaneously confirm extreme market conditions and trend reversals. This confluence approach significantly reduces noise and helps traders focus on the most reliable setups.
Key Features:
Dual-Oscillator Confluence: Generates signals only when both WaveTrend crossovers and Stochastic RSI extreme levels align
Normalized Scale Display: Both oscillators are plotted on a unified -100 to +100 scale for easy visual comparison
Visual Signal Confirmation: Clear intersection points marked with colored circles, plus optional candle coloring at crossover moments
Customizable Thresholds: Adjust overbought/oversold levels for both oscillators to match your trading style and asset volatility
Clean Visual Presentation: Optional area fill showing WaveTrend momentum difference, making divergences easier to spot
How It Works:
The indicator operates on a confluence principle where multiple conditions must align:
For BUY Signals (Green):
WaveTrend 1 crosses above WaveTrend 2 (bullish crossover)
WaveTrend is in oversold territory (below -53 or -60)
Stochastic RSI K-line is below 20 (oversold)
For SELL Signals (Red):
WaveTrend 1 crosses below WaveTrend 2 (bearish crossover)
WaveTrend is in overbought territory (above 53 or 60)
Stochastic RSI K-line is above 80 (overbought)
WaveTrend Component:
Uses the hlc3 price (average of high, low, close) to calculate a channel index that identifies market momentum waves. The two WaveTrend lines (WT1 and WT2) act similarly to MACD, where crossovers indicate momentum shifts. The oscillator ranges from approximately -100 to +100, with extreme values suggesting potential reversals.
Stochastic RSI Component:
Applies stochastic calculations to RSI values rather than raw price, creating a more sensitive momentum indicator. Values above 80 indicate overbought conditions (potential selling opportunity), while values below 20 indicate oversold conditions (potential buying opportunity). The indicator includes both K-line (faster) and D-line (slower, smoothed) for additional confirmation.
Normalization Technology:
To enable direct visual comparison, the Stochastic RSI (normally 0-100 scale) is normalized to match WaveTrend's -100 to +100 scale. This allows traders to see both oscillators' movements in relation to the same reference levels, making divergences and convergences more apparent.
How to Use:
For Trend Traders:
Wait for confluence signals in the direction of the larger trend
Use buy signals in uptrends as entry points during pullbacks
Use sell signals in downtrends as entry points during bounces
For Reversal Traders:
Focus on confluence signals at major support/resistance levels
Look for divergences between price and oscillators before confluence signals
Consider stronger signals when both oscillators reach extreme levels (WT beyond ยฑ60, Stoch beyond 20/80)
For Scalpers:
Lower the WaveTrend Channel Length (default 10) to 5-7 for more frequent signals
Tighten overbought/oversold thresholds slightly (e.g., WT: ยฑ50, Stoch: 30/70)
Use on lower timeframes (5m, 15m) with strict stop losses
Settings Guide:
WaveTrend Parameters:
Channel Length (10): Controls sensitivity. Lower = more signals but more noise. Higher = fewer but more reliable signals
Average Length (21): Smoothing period for WT2. Higher values reduce whipsaws
Overbought Levels (60/53): Two-tier system. Breaching 60 indicates strong overbought, 53 is moderate
Oversold Levels (-60/-53): Mirror of overbought levels for downside extremes
Stochastic RSI Parameters:
K-Smooth (3): Smoothing for the K-line. Higher = smoother but delayed
D-Smooth (3): Additional smoothing for the D-line signal
RSI Period (14): Standard RSI calculation period
Stoch Period (14): Stochastic calculation lookback
Oversold (20) / Overbought (80): Classic thresholds for extreme conditions
Visual Options:
Show WT Difference Area: Displays the momentum difference between WT1 and WT2 as a blue shaded area
Show WT Intersection Points: Marks crossover points with colored circles (red for bearish, green for bullish)
Color Candles at Intersection: Changes candle colors at crossover moments (blue for bearish, yellow for bullish)
Show Stoch Over Signals: Displays when Stochastic RSI breaches extreme levels
What Makes This Original:
While WaveTrend and Stochastic RSI are established indicators, this script's originality lies in:
Confluence Logic: The specific combination requiring simultaneous confirmation from both oscillators in extreme zones, not just simple crossovers
Normalization Approach: Displaying both oscillators on the same -100 to +100 scale for direct visual comparison, which is not standard
Multi-Tier Overbought/Oversold: Using two levels (60/53) instead of one, allowing for nuanced signal strength assessment
Integrated Visual System: Combining area fills, intersection markers, and candle coloring in a coordinated display that shows momentum flow at a glance
Important Considerations:
This is a momentum-based oscillator system, which performs best in ranging or trending markets with clear swings
In strong trending markets, the oscillator may remain in extreme zones for extended periods (remain overbought during strong uptrends, oversold during strong downtrends)
Confluence signals are intentionally rare to maintain qualityโexpect fewer signals than with single-indicator systems
Always combine with price action analysis, support/resistance levels, and proper risk management
Not recommended for extremely low volatility or thin markets where oscillators may produce erratic readings
Best Timeframes:
Intraday: 15m, 1H (with tighter parameters)
Swing Trading: 4H, Daily (with default parameters)
Position Trading: Daily, Weekly (with extended Channel Length 15-20)
Typical Use Cases:
Identifying exhaustion points in trending markets
Timing entries during pullbacks in established trends
Spotting potential reversal zones at key price levels
Filtering out weak momentum signals during consolidation
MTF Stoch RSI + MACD SummaryโMTF Stoch RSI + MACD Summaryโ is a multi-timeframe momentum and trend analysis indicator designed for TradingView. Its primary function is to consolidate Stochastic RSI and MACD readings from multiple user-defined timeframesโranging from weekly to intradayโinto a compact, color-coded summary table. This allows traders to assess the alignment or divergence of momentum and trend signals across different time horizons within a single chart view, providing an efficient means to identify potential trend continuations or reversals.
The script begins by defining input parameters for both indicators. For the Stochastic RSI, the user can adjust the RSI period, stochastic length, and smoothing factors for K and D lines, while for the MACD, it allows customization of the fast and slow exponential moving average lengths. Additionally, the script offers flexibility through five user-defined timeframes, enabling multi-level signal comparison. Theme and color customization options are also included to enhance visual clarity, allowing users to personalize the display according to preference or chart background.
The computational core of the script calculates the RSI based on a chosen price source (typically the closing price) and applies a stochastic transformation with smoothing to determine momentum extremesโclassifying them as overbought, mid-high, mid-low, or oversold depending on their numeric range. The MACD component, computed as the difference between the fast and slow EMAs, is evaluated to determine its state: whether it is crossing upward, crossing downward, above zero, or below zero. These states represent shifts in market momentum and potential trend direction. Both Stochastic RSI and MACD values are retrieved from each selected timeframe using the request.security() function, allowing the indicator to integrate higher and lower timeframe data in real time.
Each indicator reading is then converted into a descriptive label and paired with a specific background color for intuitive visual classification. The script organizes this information into a dynamic table displayed at the top-right corner of the chart. This table consists of three columnsโtimeframe, Stoch RSI status, and MACD statusโand automatically updates with the latest market data on every bar close. Through this tabular format, traders can quickly interpret market conditions without having to switch between multiple charts or apply numerous separate indicators.
Overall, the MTF Stoch RSI + MACD Summary acts as a comprehensive dashboard that integrates momentum and trend indicators across multiple timeframes. By presenting data in a simplified visual layout, it enables traders to make more informed decisions based on the consistency of market signals. This facilitates clearer identification of overbought or oversold conditions, confirmation of trend strength, and early detection of potential reversals, making it a valuable tool for multi-timeframe technical analysis.
