Fibonacci retracementHi all!
This indicator will show you the most recent Fibonacci retracement in the current trend. So if the trend is bullish the Fibonacci retracement will be drawn from swing low to high and from swing high to low in a bearish trend.
The uniqueness in this script lies in the adaptation to trend. To only plot the Fibonacci retracements according to the current market trend.
The trend is determined through break of structures (BOS) and change of characters (CHoCH). A change of character can be of type change of character plus (with a failed swing) and will then be shown as CHoCH+. This is possible through my library 'MarketStructure' (). It only uses break of structures and change of characters to be able to determine the trend, if you want a more detailed picture of the market structure you can use my script 'Market structure' ().
History and what to look for
Fibonacci retracement levels are used by many traders and are levels that are not Fibonacci sequence numbers themselves but they deriver from them. Some examples are:
23,6% - Divide a number by one three places ahead (e.g. 13/55)
38,2% - Divide a number by the one two places ahead (e.g. 21/55)
50% - Not from the Fibonacci sequence, but it's a number that price has reacted from in the past. Markets tend to retrace half a move before continuing
61,8% - The "golden retracement level". It derives from the "golden ratio" and is a core component of the Fibonacci sequence. The further you go in the Fibonacci sequence the preceding number divided by the current number will get closer and closer to this "golden ratio". This level is considered the most important Fibonacci retracement level by many traders
78,6% - Square root of 61.8%. This is often considered a deep correction (but not a trend reversal) and are often used for late entries
These levels are considered "key" and most significant. You want to look for a retracement of the price (down in a bullish trend and up in a bearish trend) to give you good entries.
Settings
For the trend you can set the pivot/swing lengths (right and left) and use the checkbox if you want these pivots to have labels. This can be done in the 'Market strucure' section.
In the 'Fibonacci retracement' section there is settings for the actual Fibonacci retracement. You can enable the trendline, set the color and the style of it. You can select which levels that should be shown by the indicator. There are 11 levels enabled by default, they are; 0-4.236. All settings in this section tries to be as similar to the "Fib Retracement" tool in Tradingview. You can also select the style of these lines (solid, dashed or dotted) and if you want them to extend to the right or not.
After this you can select if the Fibonacci retracement should be reversed or not, if prices should be displayed, if levels should be displayed and if to show the decimal levels or percentages and lastly the font size of these labels.
All defaults are based on the "Fib Retracement" tool by Tradingview.
Visualization
This indicator aims to be as visually similar to the default ("Fib Retracement") tool here on Tradingview. It will plot the Fibonacci retracement (called Auto Fibonacci/Auto fib) according to the trend from the library 'MarketStrucure'. The big differences from the "Fib Retracement" tool by Tradingview is that it's automatic (that adapts to trend), the market structure is visualized through lines and labels (showing 'BOS' for break of structures and 'CHoCH'/'CHoCH+' for change of characters) and that the labels showing information about the levels are positioned to be highly visible (left if <50% otherwise right if in a bullish trend, vice versa in a bearish trend or if reversed).
Don't hesitate if you have any feedback or nice feature suggestions!
Best of trading luck!
Cerca negli script per "trendline"
Intelligent Top & Bottom Finder v9.8 Keyvankh📈 Intelligent Top & Bottom Finder v9.8 Keyvankh
A next-generation all-in-one trading system for precise tops, bottoms, and reversals across all timeframes.
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🟢 Overview
This indicator is a powerful and intelligent solution for detecting market tops and bottoms, key reversals, and S/R zones with institutional-grade accuracy. Designed for traders seeking an edge in any market (crypto, forex, stocks), it combines advanced candlestick recognition, multi-indicator confirmation, smart support/resistance clustering, and strict signal filtering into one seamless tool.
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🔎 How Does It Work?
1. Advanced Support & Resistance Clustering
Automatically detects and draws high-probability support and resistance zones using dynamic ATR-based pivot clustering.
Highlights breakouts and retest (flip) zones in real-time, adapting to changing market structure.
2. Full Candlestick Pattern Recognition
Scans for 15+ classic and advanced patterns: Engulfing, Pin Bar, Doji, Three Bar, Marubozu, Hammer, Shooting Star, Three White Soldiers, Three Black Crows, Tweezer, Morning/Evening Star, Kicker, Belt Hold, and more.
Scores each pattern’s strength based on location (S/R zone, retest, breakout), volume context, and confirmation signals.
3. Multi-Indicator Confirmation Engine**
Integrates and scores confirmation from up to five additional sources:
RSI Games 1.2** (smoothed LTF momentum shifts)
MACD Divergence** (bullish/bearish momentum reversal)
QQE+ v7 Advanced** (dynamic volatility filter)
OBV Trend Filter** (volume-backed trend validation)
Volume Game** (net volume spike and reversal detection)
Each module can be enabled or disabled to fit your personal trading style.
4. Institutional S/R and Retest Logic
Real-time recognition of major trendline breaks, retest zones, and price flips.
Automatic labeling and coloring of S/R zones, retest boxes, and confirmation candles.
5. Smart Buy & Sell Signal Generation**
Combines all scoring modules with strict logical filters and “failsafe override” logic (guaranteeing signal on confirmed hammers, engulfings, etc. even if other filters disagree).
Plots clear “BUY” and “SELL” labels only when a strong, multi-factor signal appears—minimizing noise and maximizing reliability.
Built-in fallback logic (optional) for edge cases.
6. Alerts & Automation Ready
TradingView alerts for all BUY, SELL, or ANY signal conditions—perfect for auto-trading or notification setups.
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*⚙️ Customizable Inputs
Enable/Disable any module (RSI Games, MACD, OBV, QQE+, Candlestick Scanner, Volume Game)
Minimum Confirmations** required for a signal (1–10)
Pivot/Zone Sensitivity:** ATR multiplier, pivots per cluster, retest bar duration
LTF (Lower Timeframe) Confirmation:** Fully configurable
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📊 How To Use**
Apply on any timeframe and symbol**—crypto, stocks, forex, indices.
Use as a **standalone reversal/entry tool** or to confirm your own technical setups.
Combine with your favorite momentum, trend, or volume indicators for advanced confluence.
Set up **TradingView alerts** for auto-trading, Telegram/email notifications, or trade journaling.
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🟢 What Makes This Unique?
All-in-one multi-indicator fusion:** No more juggling a dozen scripts.
Institutional logic:** Goes beyond basic signals with true S/R, retest, and volume logic.
Full transparency:** Source code is clear and commented (if published open-source).
Fast and reliable:** Optimized for minimal lag and maximum accuracy.
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⚠️ Disclaimer**
This indicator is a tool to assist with trade timing and risk management. **No system is 100% accurate.** Always use in conjunction with your own analysis and risk management practices.
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📚 Credits & License**
Created by Keyvan Khodakhah.
You may use, modify, or share this script under the (mozilla.org).
Please credit the original author if you fork or reuse in public.
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Questions, feedback, or collaboration? Contact: Keyvankh
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Precision in technical analysis comes from layers of confluence and discipline. This tool brings that precision to your chart.
Retracement Bar🔍 Retracement Bar – RB
The Retracement Bar (RB) indicator is designed to highlight potential reversal zones by identifying candles where price shows a clear rejection from the extremes. It helps traders spot moments where institutional inventory rebalancing may be occurring — often a precursor to a strong move in the opposite direction.
RB highlights bars that:
Have a relatively small real body compared to the total candle range.
Show a long wick (upper or lower) that exceeds a user-defined percentage of the candle range.
Suggest a potential rejection of price — upward or downward — based on candle structure.
When these conditions are met, a triangle symbol is plotted:
🔻 Red triangle above a candle suggests a possible short opportunity.
🔺 Green triangle below a candle suggests a possible long opportunity.
This indicator does not repaint and triggers only at candle close.
📈 Example – Long Entry
Signal: A green triangle appears below a candle (suggesting rejection of lower prices).
Steps:
Wait for the current RB candle to close.
On the next candle:
Enter long if price breaks above the high of the RB candle.
Alternatively, wait for a pullback and enter based on confirmation (e.g., bullish engulfing, hammer, trendline bounce).
Place a stop-loss just below the low of the RB candle.
Set a target:
Based on a 2:1 risk-reward ratio.
Or use the next resistance/Fibonacci level.
📉 Example – Short Entry
Signal: A red triangle appears above a candle (suggesting rejection of higher prices).
Steps:
Wait for the current RB candle to close.
On the next candle:
Enter short if price breaks below the low of the RB candle.
Or wait for confirmation (e.g., bearish engulfing, shooting star, breakdown from a level).
Place a stop-loss just above the high of the RB candle.
Set a target:
2:1 risk-reward ratio.
Or the next support/Fibonacci zone.
✅ Recommended Filters for Better Results:
Confluence with support/resistance zones.
Trend alignment or reversal context.
Additional confirmation from price action patterns or oscillators.
Volume analysis for entry strength.
🙏 Acknowledgment
Special thanks to Rob Hoffman for inspiring this concept through his original Inventory Retracement Bar (IRB) idea — this indicator is a reinterpretation meant to visually and practically support discretionary price action traders.
Trade Insight Entry Check List📌 Trade Insight™ Entry Checklist Indicator
This indicator is designed for Smart Money Concepts (SMC) and Price Action traders who prioritize precision, patience, and psychological discipline.
It helps you validate your trade setup across four essential categories before execution:
🔍 Technical Criteria
✅ Higher Time Frame (HTF) Key Level respected
✅ 4H Candle Closure Confirmation
✅ Trendline 3rd Touch Validation
✅ Liquidity Sweep or Shift (price fails to break HH/LL)
✅ Lower Time Frame (LTF) Order Flow Shift Confirmed
💰 Risk Management
✅ Risk-to-Reward Ratio ≥ 1:2
✅ Risk Amount Fully Affordable (Capital Preservation mindset)
🧠 Psychological Readiness
✅ No F.O.M.O (Fear of Missing Out)
✅ No FEAR-based decisions
✅ No GREED influence
✅ No REVENGE trading
Strategy Builder With IndicatorsThis strategy script is designed for traders who enjoy building systems using multiple indicators.
Please note: This script does not include any built-in indicators. Instead, it works by referencing the plot outputs of the indicators you’ve already added to your chart.
For example, if you add a MACD and an ATR indicator to your chart, you can assign their plot values as inputs in the settings panel of this strategy.
• MACD as a trigger
• ATR as a filter
How Filters Work
Filters check whether certain conditions are met before a trade can be opened. For instance, if you set a filter like ATR > 30, then no trade will be executed unless that condition is true — even if the trigger fires.
All filters are linked, meaning every active filter must be satisfied for a trade to occur.
How Triggers Work
Triggers are what actually fire a trade signal — such as a moving average crossover or RSI breaking above a specific level. Unlike filters, triggers are independent. Only one active trigger needs to be true for the trade to execute.
Thanks to its modular structure, this strategy can be used with any indicator of your choice.
⸻
Risk Management Features
In the settings, you’ll find flexible options for:
• Stop Loss (SL)
• Trailing Stop Loss (TSL)
• Multi Take-Profit (TP)
These features enhance trade safety and let you tailor your risk management.
SL types available:
• Tick-based SL
• Percent-based SL
• ATR-based SL
Once you select your preferred SL type, you can fine-tune its distance using the offset field.
Trailing SL allows your stop to follow price as it moves in your favor — helping to lock in profits.
Multi-TP lets you take profits at two different levels, helping you secure gains while leaving room for extended moves.
Breakeven option is also available to automatically move your SL to entry after reaching a profit threshold.
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How to Build a Solid Strategy
Let’s break down a good setup into three key components:
1. Trend Filter
Avoid trading against the trend — that’s like swimming against the current.
Use a filter like:
• Supertrend
• Momentum indicators
• Candlestick bias, etc.
Example: In this case, I used Supertrend and filtered for trades only if the price is above the uptrend line.
2. Trigger Condition
Once we confirm the trend is on our side, we need a trigger to execute at the right moment. This can be:
• RSI cross
• Candlestick patterns
• Trendline breaks
• Moving average crossovers, etc.
Example: I used RSI crossing above 50 as the entry trigger.
3. Risk Management
Even in the right trend at the right time — anything can happen. That’s why you should always define Stop Loss and Take Profit levels.
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And there you have it! Your strategy is ready to backtest, refine, and deploy with alerts for live trading.
Questions or suggestions? Feel free to reach out
EWMA & EWVar + EWStd Expansion with MTF_V.5EWMA & EWVar + EWStd Expansion with MTF_V.5
This indicator combines adaptive trend smoothing (EWMA), variance estimation (EWVar) and dynamic volatility “bursts” (EWStd Expansion) with optional higher-timeframe confirmation. It’s designed both for visual chart analysis and for automated alerts on regime changes.
Key Features
EWMA (Exponential Smoothing):
• Computes an exponential moving average with either a custom α or a length-derived α = 2/(N+1).
• Option to recalculate only every N bars (reduces CPU load).
EWVar & EWStd (Variance & Standard Deviation):
• Exponentially weighted variance tracks recent price dispersion.
• EWStd (σ) is computed alongside the EWMA.
• Z-score (deviation in σ units) shows how far price has diverged from trend.
Multi-Timeframe Filter (MTF):
• Optionally require the same trend direction on a chosen higher timeframe (e.g. Daily, Weekly, H4).
• Real-time lookahead available (may repaint).
Gradient Around EWMA:
• A multi-layer “glow” zone of ±1σ, broken into up to 10 steps.
• Color interpolates between “upper” and “lower” shades for bullish, bearish and neutral regimes.
Instantaneous Trendline (ITL):
• Ultra-fast trend filter with slope-based coloring.
• Highlights micro-trends and short-lived accelerations.
Cross-Over Signals (ITL ↔ EWMA):
• Up/down triangles plotted when the ITL crosses the main EWMA.
EWStd Expansion (Volatility Bursts):
• Automatically detects σ expansions (σ growth above a set % threshold).
• Price filter: only when price moves beyond EWMA ± (multiplier·σ).
• Optional higher-timeframe confirmation.
Labels & Alerts:
• Text labels and circular markers on bars where a volatility burst occurs.
• Built-in alertcondition calls for both bullish and bearish expansions.
How to Use
Visual Analysis:
• The gradient around EWMA shows the width of the volatility channel expanding or contracting.
• ITL color changes instantly highlight short-term impulses.
• EWMA line color switches (bullish/bearish/neutral) indicate trend state.
Spotting Volatility Breakouts:
• “EWStd Expansion” labels and circles signal the onset of strong moves when σ spikes.
• Useful for entering at the start of new impulses.
Automated Alerts:
• Set alerts on the built-in conditions “Bullish EWStd Expansion Alert” or “Bearish EWStd Expansion Alert” to receive a popup or mobile push when a burst occurs.
This compact tool unifies trend, volatility and multi-timeframe analysis into a single indicator—ideal for traders who want to see trend direction, current dispersion, and timely volatility burst signals all at once.
Linear % ST | QuantEdgeB🚀 Introducing Linear Percentile SuperTrend (Linear % ST) by QuantEdgeB
🛠️ Overview
Linear % SuperTrend (Linear % ST) by QuantEdgeB is a hybrid trend-following indicator that combines Linear Regression, Percentile Filters, and Volatility-Based SuperTrend Logic into one dynamic tool. This system is designed to identify trend shifts early while filtering out noise during choppy market conditions.
By utilizing percentile-based median smoothing and customized ATR multipliers, this tool captures both breakout momentum and pullback opportunities with precision.
✨ Key Features
🔹 Percentile-Based Median Filtering
Removes outliers and normalizes price movement for cleaner trend detection using the 50th percentile (median) of recent price action.
🔹 Linear Regression Smoothing
A smoothed baseline is computed with Linear Regression to detect the underlying trend while minimizing lag.
🔹 SuperTrend Structure with Adaptive Bands
The indicator implements an enhanced SuperTrend engine with custom ATR bands that adapt to trend direction. Bands tighten or loosen based on volatility and trend strength.
🔹 Dynamic Long/Short Conditions
Long and short signals are derived from the relationship between price and the SuperTrend threshold zones, clearly showing trend direction with optional "Long"/"Short" labels on the chart.
🔹 Multiple Visual Themes
Select from 6 built-in color palettes including Strategy, Solar, Warm, Cool, Classic, and Magic to match your personal style or strategy layout.
📊 How It Works
1️⃣ Percentile Filtering
The source price (default: close) is filtered using a nearest-rank 50th percentile over a custom lookback. This normalizes data to reflect the central tendency and removes noisy extremes.
2️⃣ Linear Regression Trend Base
A Linear Regression Moving Average (LSMA) is applied to the filtered median, forming the core trend line. This dynamic trendline provides a low-lag yet smooth view of market direction.
3️⃣ SuperTrend Engine
ATR is applied with custom multipliers (different for long and short) to create dynamic bands. The bands react to price movement and only shift direction after confirmation, preventing false flips.
4️⃣ Trend Signal Logic
• When price stays above the dynamic lower band → Bullish trend
• When price breaks below the upper band → Bearish trend
• Trend direction remains stable until violated by price.
⚙️ Custom Settings
• Percentile Length → Lookback for percentile smoothing (default: 35)
• LSMA Length → Determines the base trend via linear regression (default: 24)
• ATR Length → ATR period used in dynamic bands (default: 14)
• Long Multiplier → ATR multiplier for bullish thresholds (default: 0.8)
• Short Multiplier → ATR multiplier for bearish thresholds (default: 1.9)
✅ How to Use
1️⃣ Trend-Following Strategy
✔️ Go Long when price breaks above the lower ATR band, initiating an upward trend
✔️ Go Short when price falls below the upper ATR band, confirming bearish conditions
✔️ Remain in trend direction until the SuperTrend flips
2️⃣ Visual Confirmation
✔️ Use bar coloring and the dynamic bands to stay aligned with trend direction
✔️ Optional Long/Short labels highlight key signal flips
👥 Who Should Use Linear % ST?
✅ Swing & Position Traders → To ride trends confidently
✅ Trend Followers → As a primary directional filter
✅ Breakout Traders → For clean signal generation post-range break
✅ Quant/Systematic Traders → Integrate clean trend logic into algorithmic setups
📌 Conclusion
Linear % ST by QuantEdgeB blends percentile smoothing with linear regression and volatility bands to deliver a powerful, adaptive trend-following engine. Whether you're a discretionary trader seeking cleaner entries or a systems-based trader building logic for automation, Linear % ST offers clarity, adaptability, and precision in trend detection.
🔹 Key Takeaways:
1️⃣ Percentile + Regression = Noise-Reduced Core Trend
2️⃣ ATR-Based SuperTrend = Reliable Breakout Confirmation
3️⃣ Flexible Parameters + Color Modes = Custom Fit for Any Strategy
📈 Use it to spot emerging trends, filter false signals, and stay confidently aligned with market momentum.
📌 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
📌 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
VIX bottom/top with color scale [Ox_kali]📊 Introduction
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The “VIX Bottom/Top with Color Scale” script is designed to provide an intuitive, color-coded visualization of the VIX (Volatility Index), helping traders interpret market sentiment and volatility extremes in real time.
It segments the VIX into clear threshold zones, each associated with a specific market condition—ranging from fear to calm—using a dynamic color-coded system.
This script offers significant value for the following reasons:
Intuitive Risk Interpretation: Color-coded zones make it easy to interpret market sentiment at a glance.
Dynamic Trend Detection: A 200-period SMA of the VIX is plotted and dynamically colored based on trend direction.
Customization and Flexibility: All colors are editable in the parameters panel, grouped under “## Color parameters ##”.
Visual Clarity: Key thresholds are marked with horizontal lines for quick reference.
Practical Trading Tool: Helps identify high-risk and low-risk environments based on volatility levels.
🔍 Key Indicators
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VIX (CBOE Volatility Index) : Measures market volatility and investor fear.
SMA 200 : Long-term trendline of the VIX, with color-coded direction (green = uptrend, red = downtrend).
Color-coded VIX Levels:
🔴 33+ → Something bad just happened
🟠 23–33 → Something bad is happening
🟡 17–23 → Something bad might happen
🟢 14–17 → Nothing bad is happening
✅ 12–14 → Nothing bad will ever happen
🔵 <12 → Something bad is going to happen
🧠 Originality and Purpose
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Unlike traditional VIX indicators that only plot a line, this script enhances interpretation through visual segmentation and dynamic trend tracking.
It serves as a risk-awareness tool that transforms the VIX into a simple, emotional market map.
This is the first version of the script, and future updates may include alerts, background fills, and more advanced features.
⚙️ How It Works
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The script maps the current VIX value to a range and applies the corresponding color.
It calculates a SMA 200 and colors it green or red depending on its slope.
It displays horizontal dotted lines at key thresholds (12, 14, 17, 23, 33).
All colors are configurable via input parameters under the group: "## Color parameters ##".
🧭 Indicator Visualization and Interpretation
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The VIX line changes color based on market condition zones.
The SMA line shows long-term direction with dynamic color.
Horizontal threshold lines visually mark the transitions between volatility zones.
Ideal for quickly identifying periods of fear, caution, or stability.
🛠️ Script Parameters
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Grouped under “## Color parameters ##”, the following elements are customizable:
🎨 VIX Zone Colors:
33+ → Red
23–33 → Orange
17–23 → Yellow
14–17 → Light Green
12–14 → Dark Green
<12 → Blue
📈 SMA Colors:
Uptrend → Green
Downtrend → Red
These settings allow users to match the script’s visuals to their preferred chart style or theme.
✅ Conclusion
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The “VIX Bottom/Top with Color Scale” is a clean, powerful script designed to simplify how traders view volatility.
By combining long-term trend data with real-time color-coded sentiment analysis, this script becomes a go-to reference for managing risk, timing trades, or simply staying in tune with market mood.
🧪 Notes
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This is version 1 of the script. More features such as alert conditions, background fill, and dashboard elements may be added soon. Feedback is welcome!
💡 Color code concept inspired by the original VIX interpretation chart by @nsquaredvalue on Twitter. Big thanks for the visual clarity! 💡
⚠️ Disclaimer
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This script is a visual tool designed to assist in market analysis. It does not guarantee future performance and should be used in conjunction with proper risk management. Past performance is not indicative of future results.
Multi-Fibonacci Trend Average[FibonacciFlux]Multi-Fibonacci Trend Average (MFTA): An Institutional-Grade Trend Confluence Indicator for Discerning Market Participants
My original indicator/Strategy:
Engineered for the sophisticated demands of institutional and advanced traders, the Multi-Fibonacci Trend Average (MFTA) indicator represents a paradigm shift in technical analysis. This meticulously crafted tool is designed to furnish high-definition trend signals within the complexities of modern financial markets. Anchored in the rigorous principles of Fibonacci ratios and augmented by advanced averaging methodologies, MFTA delivers a granular perspective on trend dynamics. Its integration of Multi-Timeframe (MTF) filters provides unparalleled signal robustness, empowering strategic decision-making with a heightened degree of confidence.
MFTA indicator on BTCUSDT 15min chart with 1min RSI and MACD filters enabled. Note the refined signal generation with reduced noise.
MFTA indicator on BTCUSDT 15min chart without MTF filters. While capturing more potential trading opportunities, it also generates a higher frequency of signals, including potential false positives.
Core Innovation: Proprietary Fibonacci-Enhanced Supertrend Averaging Engine
The MFTA indicator’s core innovation lies in its proprietary implementation of Supertrend analysis, strategically fortified by Fibonacci ratios to construct a truly dynamic volatility envelope. Departing from conventional Supertrend methodologies, MFTA autonomously computes not one, but three distinct Supertrend lines. Each of these lines is uniquely parameterized by a specific Fibonacci factor: 0.618 (Weak), 1.618 (Medium/Golden Ratio), and 2.618 (Strong/Extended Fibonacci).
// Fibonacci-based factors for multiple Supertrend calculations
factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval=0.01, step=0.01, tooltip='Factor 1 (Weak/Fibonacci)', group="Fibonacci Supertrend")
factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval=0.01, step=0.01, tooltip='Factor 2 (Medium/Golden Ratio)', group="Fibonacci Supertrend")
factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval=0.01, step=0.01, tooltip='Factor 3 (Strong/Extended Fib)', group="Fibonacci Supertrend")
This multi-faceted architecture adeptly captures a spectrum of market volatility sensitivities, ensuring a comprehensive assessment of prevailing conditions. Subsequently, the indicator algorithmically synthesizes these disparate Supertrend lines through arithmetic averaging. To achieve optimal signal fidelity and mitigate inherent market noise, this composite average is further refined utilizing an Exponential Moving Average (EMA).
// Calculate average of the three supertends and a smoothed version
superlength = input.int(21, 'Smoothing Length', tooltip='Smoothing Length for Average Supertrend', group="Fibonacci Supertrend")
average_trend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_trend = ta.ema(average_trend, superlength)
The resultant ‘Smoothed Trend’ line emerges as a remarkably responsive yet stable trend demarcation, offering demonstrably superior clarity and precision compared to singular Supertrend implementations, particularly within the turbulent dynamics of high-volatility markets.
Elevated Signal Confluence: Integrated Multi-Timeframe (MTF) Validation Suite
MFTA transcends the limitations of conventional trend indicators by incorporating an advanced suite of three independent MTF filters: RSI, MACD, and Volume. These filters function as sophisticated validation protocols, rigorously ensuring that only signals exhibiting a confluence of high-probability factors are brought to the forefront.
1. Granular Lower Timeframe RSI Momentum Filter
The Relative Strength Index (RSI) filter, computed from a user-defined lower timeframe, furnishes critical momentum-based signal validation. By meticulously monitoring RSI dynamics on an accelerated timeframe, traders gain the capacity to evaluate underlying momentum strength with precision, prior to committing to signal execution on the primary chart timeframe.
// --- Lower Timeframe RSI Filter ---
ltf_rsi_filter_enable = input.bool(false, title="Enable RSI Filter", group="MTF Filters", tooltip="Use RSI from lower timeframe as a filter")
ltf_rsi_timeframe = input.timeframe("1", title="RSI Timeframe", group="MTF Filters", tooltip="Timeframe for RSI calculation")
ltf_rsi_length = input.int(14, title="RSI Length", minval=1, group="MTF Filters", tooltip="Length for RSI calculation")
ltf_rsi_threshold = input.int(30, title="RSI Threshold", minval=0, maxval=100, group="MTF Filters", tooltip="RSI value threshold for filtering signals")
2. Convergent Lower Timeframe MACD Trend-Momentum Filter
The Moving Average Convergence Divergence (MACD) filter, also calculated on a lower timeframe basis, introduces a critical layer of trend-momentum convergence confirmation. The bullish signal configuration rigorously mandates that the MACD line be definitively positioned above the Signal line on the designated lower timeframe. This stringent condition ensures a robust indication of converging momentum that aligns synergistically with the prevailing trend identified on the primary timeframe.
// --- Lower Timeframe MACD Filter ---
ltf_macd_filter_enable = input.bool(false, title="Enable MACD Filter", group="MTF Filters", tooltip="Use MACD from lower timeframe as a filter")
ltf_macd_timeframe = input.timeframe("1", title="MACD Timeframe", group="MTF Filters", tooltip="Timeframe for MACD calculation")
ltf_macd_fast_length = input.int(12, title="MACD Fast Length", minval=1, group="MTF Filters", tooltip="Fast EMA length for MACD")
ltf_macd_slow_length = input.int(26, title="MACD Slow Length", minval=1, group="MTF Filters", tooltip="Slow EMA length for MACD")
ltf_macd_signal_length = input.int(9, title="MACD Signal Length", minval=1, group="MTF Filters", tooltip="Signal SMA length for MACD")
3. Definitive Volume Confirmation Filter
The Volume Filter functions as an indispensable arbiter of trade conviction. By establishing a dynamic volume threshold, defined as a percentage relative to the average volume over a user-specified lookback period, traders can effectively ensure that all generated signals are rigorously validated by demonstrably increased trading activity. This pivotal validation step signifies robust market participation, substantially diminishing the potential for spurious or false breakout signals.
// --- Volume Filter ---
volume_filter_enable = input.bool(false, title="Enable Volume Filter", group="MTF Filters", tooltip="Use volume level as a filter")
volume_threshold_percent = input.int(title="Volume Threshold (%)", defval=150, minval=100, group="MTF Filters", tooltip="Minimum volume percentage compared to average volume to allow signal (100% = average)")
These meticulously engineered filters operate in synergistic confluence, requiring all enabled filters to definitively satisfy their pre-defined conditions before a Buy or Sell signal is generated. This stringent multi-layered validation process drastically minimizes the incidence of false positive signals, thereby significantly enhancing entry precision and overall signal reliability.
Intuitive Visual Architecture & Actionable Intelligence
MFTA provides a demonstrably intuitive and visually rich charting environment, meticulously delineating trend direction and momentum through precisely color-coded plots:
Average Supertrend: Thin line, green/red for uptrend/downtrend, immediate directional bias.
Smoothed Supertrend: Bold line, teal/purple for uptrend/downtrend, cleaner, institutionally robust trend.
Dynamic Trend Fill: Green/red fill between Supertrends quantifies trend strength and momentum.
Adaptive Background Coloring: Light green/red background mirrors Smoothed Supertrend direction, holistic trend perspective.
Precision Buy/Sell Signals: ‘BUY’/‘SELL’ labels appear on chart when trend touch and MTF filter confluence are satisfied, facilitating high-conviction trade action.
MFTA indicator applied to BTCUSDT 4-hour chart, showcasing its effectiveness on higher timeframes. The Smoothed Length parameter is increased to 200 for enhanced smoothness on this timeframe, coupled with 1min RSI and Volume filters for signal refinement. This illustrates the indicator's adaptability across different timeframes and market conditions.
Strategic Applications for Institutional Mandates
MFTA’s sophisticated design provides distinct advantages for advanced trading operations and institutional investment mandates. Key strategic applications include:
High-Probability Trend Identification: Fibonacci-averaged Supertrend with MTF filters robustly identifies high-probability trend continuations and reversals, enhancing alpha generation.
Precision Entry/Exit Signals: Volume and momentum-filtered signals enable institutional-grade precision for optimized risk-adjusted returns.
Algorithmic Trading Integration: Clear signal logic facilitates seamless integration into automated trading systems for scalable strategy deployment.
Multi-Asset/Timeframe Versatility: Adaptable parameters ensure applicability across diverse asset classes and timeframes, catering to varied trading mandates.
Enhanced Risk Management: Superior signal fidelity from MTF filters inherently reduces false signals, supporting robust risk management protocols.
Granular Customization and Parameterized Control
MFTA offers unparalleled customization, empowering users to fine-tune parameters for precise alignment with specific trading styles and market conditions. Key adjustable parameters include:
Fibonacci Factors: Adjust Supertrend sensitivity to volatility regimes.
ATR Length: Control volatility responsiveness in Supertrend calculations.
Smoothing Length: Refine Smoothed Trend line responsiveness and noise reduction.
MTF Filter Parameters: Independently configure timeframes, lookback periods, and thresholds for RSI, MACD, and Volume filters for optimal signal filtering.
Disclaimer
MFTA is meticulously engineered for high-quality trend signals; however, no indicator guarantees profit. Market conditions are unpredictable, and trading involves substantial risk. Rigorous backtesting and forward testing across diverse datasets, alongside a comprehensive understanding of the indicator's logic, are essential before live deployment. Past performance is not indicative of future results. MFTA is for informational and analytical purposes only and is not financial or investment advice.
Lowess Channel + (RSI) [ChartPrime]The Lowess Channel + (RSI) indicator applies the LOWESS (Locally Weighted Scatterplot Smoothing) algorithm to filter price fluctuations and construct a dynamic channel. LOWESS is a non-parametric regression method that smooths noisy data by fitting weighted linear regressions at localized segments. This technique is widely used in statistical analysis to reveal trends while preserving data structure.
In this indicator, the LOWESS algorithm is used to create a central trend line and deviation-based bands. The midline changes color based on trend direction, and diamonds are plotted when a trend shift occurs. Additionally, an RSI gauge is positioned at the end of the channel to display the current RSI level in relation to the price bands.
lowess_smooth(src, length, bandwidth) =>
sum_weights = 0.0
sum_weighted_y = 0.0
sum_weighted_xy = 0.0
sum_weighted_x2 = 0.0
sum_weighted_x = 0.0
for i = 0 to length - 1
x = float(i)
weight = math.exp(-0.5 * (x / bandwidth) * (x / bandwidth))
y = nz(src , 0)
sum_weights := sum_weights + weight
sum_weighted_x := sum_weighted_x + weight * x
sum_weighted_y := sum_weighted_y + weight * y
sum_weighted_xy := sum_weighted_xy + weight * x * y
sum_weighted_x2 := sum_weighted_x2 + weight * x * x
mean_x = sum_weighted_x / sum_weights
mean_y = sum_weighted_y / sum_weights
beta = (sum_weighted_xy - mean_x * mean_y * sum_weights) / (sum_weighted_x2 - mean_x * mean_x * sum_weights)
alpha = mean_y - beta * mean_x
alpha + beta * float(length / 2) // Centered smoothing
⯁ KEY FEATURES
LOWESS Price Filtering – Smooths price fluctuations to reveal the underlying trend with minimal lag.
Dynamic Trend Coloring – The midline changes color based on trend direction (e.g., bullish or bearish).
Trend Shift Diamonds – Marks points where the midline color changes, indicating a possible trend shift.
Deviation-Based Bands – Expands above and below the midline using ATR-based multipliers for volatility tracking.
RSI Gauge Display – A vertical gauge at the right side of the chart shows the current RSI level relative to the price channel.
Fully Customizable – Users can adjust LOWESS length, band width, colors, and enable or disable the RSI gauge and adjust RSIlength.
⯁ HOW TO USE
Use the LOWESS midline as a trend filter —bullish when green, bearish when purple.
Watch for trend shift diamonds as potential entry or exit signals.
Utilize the price bands to gauge overbought and oversold zones based on volatility.
Monitor the RSI gauge to confirm trend strength—high RSI near upper bands suggests overbought conditions, while low RSI near lower bands indicates oversold conditions.
⯁ CONCLUSION
The Lowess Channel + (RSI) indicator offers a powerful way to analyze market trends by applying a statistically robust smoothing algorithm. Unlike traditional moving averages, LOWESS filtering provides a flexible, responsive trendline that adapts to price movements. The integrated RSI gauge enhances decision-making by displaying momentum conditions alongside trend dynamics. Whether used for trend-following or mean reversion strategies, this indicator provides traders with a well-rounded perspective on market behavior.
Ethereum Logarithmic Regression Bands (Fine-Tuned)This indicator, "Ethereum Logarithmic Regression Bands (Fine-Tuned)," is my attempt to create a tool for estimating long-term trends in Ethereum (ETH/USD) price action using logarithmic regression bands. Please note that I am not an expert in financial modeling or coding—I developed this as a personal project to serve as a rough estimation rather than a precise or professional trading tool. The data was fitted to non-bubble periods of Ethereum's history to provide a general trendline, but it’s far from perfect.
I’m sharing this because I couldn’t find a similar indicator available, and I thought it might be useful for others who are also exploring ETH’s long-term behavior. The bands start from Ethereum’s launch price and are adjustable via input parameters, but they are based on my best effort to align with historical data. With some decent coding experience, I’m sure someone could refine this further—perhaps by optimizing the coefficients or incorporating more advanced fitting techniques. Feel free to tweak the code, suggest improvements, or use it as a starting point for your own projects!
How to Use:
** THIS CHART IS SPECIFICALLY CODED FOR ETH/USD (KRAKEN) ON THE WEEKLY TIMEFRAME IN LOG VIEW**
The main band (blue) represents the logarithmic regression line.
The upper (red) and lower (green) bands provide a range around the main trend, adjustable with multipliers.
Adjust the "Launch Price," "Base Coefficient," "Growth Coefficient," and other inputs to experiment with different fits.
Disclaimer:
This is not financial advice. Use at your own risk, and always conduct your own research before making trading decisions.
Chaikin Money Flow with EnhancementsThis enhanced version of the Chaikin Money Flow (CMF) indicator is designed to help traders better understand market sentiment by visualizing momentum shifts and trends based on volume-weighted accumulation and distribution.
CMF Calculation: The CMF line is calculated using the typical CMF formula, which compares the close price to the high/low range, weighted by volume.
Fading Color Zones: Green and red fading zones are added between the CMF line and the zero line. Green represents bullish momentum (CMF above zero), and red represents bearish momentum (CMF below zero). These zones highlight key shifts in market sentiment.
Cross Detection: The indicator detects when the CMF crosses above or below the zero line, signaling potential trend changes. The price and CMF values at the time of the cross are stored and can be used for further analysis.
Average Line: A configurable moving average of the CMF is plotted to provide a smoothed trendline, helping traders identify the overall direction of market sentiment.
This indicator is ideal for traders who want to enhance their technical analysis by incorporating volume-weighted momentum indicators and identifying trend reversals more clearly.
CAD CHF JPY (Index) vs USDDescription:
Analyze the combined performance of CAD, CHF, and JPY against the USD with this customized Forex currency index. This tool enables traders to gain a broader perspective of how these three currencies behave relative to the US Dollar by aggregating their movements into a single index. It’s a versatile tool designed for traders seeking actionable insights and trend identification.
Core Features:
Flexible Display Options:
Choose between Line Mode for a simplified view of the index trend or Candlestick Mode for detailed analysis of price action.
Custom Weight Adjustments:
Fine-tune the weight of each currency pair (USD/CAD, USD/CHF, USD/JPY) to better reflect your trading priorities or market expectations.
Moving Average Integration:
Add a moving average to smooth the data and identify trends more effectively. Choose your preferred type: SMA, EMA, WMA, or VWMA, and configure the number of periods to suit your strategy.
Streamlined Calculation:
The index aggregates data from USD/CAD, USD/CHF, and USD/JPY using a weighted average of their OHLC (Open, High, Low, Close) values, ensuring accuracy and adaptability to different market conditions.
Practical Applications:
Trend Identification:
Use the Line Mode with a moving average to confirm whether CAD, CHF, and JPY collectively show strength or weakness against the USD. A rising trendline signals currency strength, while a declining line suggests USD dominance.
Weight-Based Analysis:
If CAD is expected to lead, adjust its weight higher relative to CHF and JPY to emphasize its influence in the index. This customization makes the indicator adaptable to your market outlook.
Actionable Insights:
Identify key reversal points or breakout opportunities by analyzing the interaction of the index with its moving average. Combined with other technical tools, this indicator becomes a robust addition to any trader’s toolkit.
Additional Notes:
This indicator is a valuable resource for comparing the collective behavior of CAD, CHF, and JPY against the USD. Pair it with additional oscillators or divergence tools for a comprehensive market overview.
Perfect for both intraday analysis and swing trading strategies. Combine it with EUR GPB AUD (Index) indicator.
Good Profits!
MTF RSI CandlesThis Pine Script indicator is designed to provide a visual representation of Relative Strength Index (RSI) values across multiple timeframes. It enhances traditional candlestick charts by color-coding candles based on RSI levels, offering a clearer picture of overbought, oversold, and sideways market conditions. Additionally, it displays a hoverable table with RSI values for multiple predefined timeframes.
Key Features
1. Candle Coloring Based on RSI Levels:
Candles are color-coded based on predefined RSI ranges for easy interpretation of market conditions.
RSI Levels:
75-100: Strongest Overbought (Green)
65-75: Stronger Overbought (Dark Green)
55-65: Overbought (Teal)
45-55: Sideways (Gray)
35-45: Oversold (Light Red)
25-35: Stronger Oversold (Dark Red)
0-25: Strongest Oversold (Bright Red)
2. Multi-Timeframe RSI Table:
Displays RSI values for the following timeframes:
1 Min, 2 Min, 3 Min, 4 Min, 5 Min
10 Min, 15 Min, 30 Min, 1 Hour, 1 Day, 1 Week
Helps traders identify RSI trends across different time horizons.
3. Hoverable RSI Values:
Displays the RSI value of any candle when hovering over it, providing additional insights for analysis.
Inputs
1. RSI Length:
Default: 14
Determines the calculation period for the RSI indicator.
2. RSI Levels:
Configurable thresholds for RSI zones:
75-100: Strongest Overbought
65-75: Stronger Overbought
55-65: Overbought
45-55: Sideways
35-45: Oversold
25-35: Stronger Oversold
0-25: Strongest Oversold
How It Works:
1. RSI Calculation:
The RSI is calculated for the current timeframe using the input RSI Length.
It is also computed for 11 additional predefined timeframes using request.security.
2. Candle Coloring:
Candles are colored based on their RSI values and the specified RSI levels.
3. Hoverable RSI Values:
Each candle displays its RSI value when hovered over, via a dynamically created label.
Multi-Timeframe Table:
A table at the bottom-left of the chart displays RSI values for all predefined timeframes, making it easy to compare trends.
Usage:
1. Trend Identification:
Use candle colors to quickly assess market conditions (overbought, oversold, or sideways).
2. Timeframe Analysis:
Compare RSI values across different timeframes to determine long-term and short-term momentum.
3. Signal Confirmation:
Combine RSI signals with other indicators or patterns for higher-confidence trades.
Best Practices
Use this indicator in conjunction with volume analysis, support/resistance levels, or trendline strategies for better results.
Customize RSI levels and timeframes based on your trading strategy or market conditions.
Limitations
RSI is a lagging indicator and may not always predict immediate market reversals.
Multi-timeframe analysis can lead to conflicting signals; consider your trading horizon.
MEMEQUANTMEMEQUANT
This script is a comprehensive and specialized tool designed for tracking trends and money flow within meme coins and DEX tokens. By combining various features such as trend lines, Fibonacci levels, and category-based indices, it helps traders make informed decisions in highly volatile markets.
Key Features:
1. Category-Based Indices:
• Tracks the performance of token categories like:
• AI Agent Tokens
• AI Tokens
• Animal Tokens
• Murad Picks
• Each category consists of leader tokens, which are selected based on their higher market cap and trading volume. These tokens act as benchmarks for their respective categories.
• Visualizes category indices in a line chart to identify trends and compare money flow between categories.
2. Fibonacci Correction Zones:
• Highlights key retracement levels (e.g., 60%, 70%, 80%).
• These levels are crucial for identifying potential reversal zones, commonly observed in meme coin trading patterns.
• Fully customizable to match individual trading strategies.
3. Trend Lines:
• Automatically detects major support and resistance levels.
• Separates long-term and short-term trend lines, allowing traders to focus on significant price movements.
4. Enhanced Info Table:
• Provides real-time insights, including:
• % Distance from All-Time High (ATH)
• Current Trading Volume
• 50-bar Average Volume
• Volume Change Percentage
• Displays information in an easy-to-read table on the chart.
5. Customizable Settings:
• Users can adjust transparency, colors, and ranges for Fibonacci zones, trend lines, and the table.
• Enables or disables individual features (e.g., Fibonacci, trend lines, table) based on preferences.
How It Works:
1. Tracking Money Flow Across Categories:
• The script calculates the market cap to volume ratio for each category of tokens to help identify the dominant trend.
• A higher ratio indicates greater liquidity and stability, while a lower ratio suggests higher volatility or price manipulation.
2. Identifying Retracement Patterns:
• Leverages common retracement behaviors (e.g., 70% correction levels) observed in meme coins to detect potential reversal zones.
• Combines this with trend line analysis for additional confirmation.
3. Leader Tokens as Indicators:
• Each category is represented by its leader tokens, which have historically higher liquidity and market cap. This allows the script to accurately reflect the overall trend in each category.
When to Use:
• Trend Analysis: To identify which category (e.g., AI Tokens or Animal Tokens) is leading the market.
• Reversal Zones: To spot potential support or resistance levels using Fibonacci zones.
• Money Flow: To understand how capital is moving across different token categories in real time.
Who Is This For?
This script is tailored for:
• Traders specializing in meme coins and DEX tokens.
• Those looking for an edge in trend-based trading by analyzing market cap, volume, and retracement levels.
• Anyone aiming to track money flow dynamics between different token categories.
Future Updates:
This is the initial version of the script. Future updates may include:
• Support for additional token categories and DEX data.
• More advanced pattern recognition and alerts for volume and price anomalies.
• Enhanced visualization for historical data trends.
With this tool, traders can combine money flow analysis with the 60-70% retracement strategy, turning it into a powerful assistant for navigating the fast-paced world of meme coins and DEX tokens.
This script is designed to provide meaningful insights and practical utility for traders, adhering to TradingView’s standards for originality, clarity, and user value.
VWAP Fibonacci Bands (Zeiierman)█ Overview
The VWAP Fibonacci Bands is a sophisticated yet user-friendly indicator designed to assist traders in visualizing market trends, volatility, and potential support/resistance levels. Developed by Zeiierman, this tool integrates the MIDAS (Market Interpretation Data Analysis System) methodology with Standard Deviation Bands and user-defined Fibonacci levels to provide a comprehensive market analysis framework.
This indicator is built for traders who want a dynamic and customizable approach to understanding market movements, offering features that adapt to varying market conditions. Whether you're a scalper, swing trader, or long-term investor.
█ How It Works
⚪ Anchor Point System
The indicator begins its calculations based on an anchor point, which can be set to:
A specific date for historical analysis or alignment with significant market events.
A timeframe-based reset, dynamically restarting calculations at the beginning of each selected period (e.g., daily, weekly, or monthly).
This dual-anchor method ensures flexibility, allowing the indicator to align with various trading strategies.
⚪ MIDAS Calculation
The MIDAS calculation is central to this indicator. It uses cumulative price and volume data to compute a volume-weighted average price (VWAP), offering a trendline that reflects the true value weighted by trading activity.
⚪ Standard Deviation Bands
The upper and lower bands are calculated using the standard deviation of price movements around the MIDAS line.
⚪ Fibonacci Levels
User-defined Fibonacci ratios are used to plot additional support and resistance levels between the bands. These levels provide visual cues for potential price reversals or trend continuations.
█ How to Use
⚪ Trend Identification
Uptrend: The price remains above the MIDAS line.
Downtrend: The price stays below the MIDAS line and aligns with the lower bands.
⚪ Support and Resistance
The upper and lower bands act as support and resistance levels.
Fibonacci levels provide intermediate zones for potential price reversals.
⚪ Volatility Analysis
Wider bands indicate periods of high volatility.
Narrower bands suggest low-volatility conditions, often preceding breakouts.
⚪ Overbought/Oversold Conditions
Look for the price beyond the upper or lower bands to identify extreme conditions.
█ Settings
Set Anchor Method
Anchor Method: Choose between Timeframe or Date to define the starting point of calculations.
Anchor Timeframe: For Timeframe mode, specify the interval (e.g., Daily, Weekly).
Anchor Date: For Date mode, set the exact starting date for historical alignment.
Set Std Dev Multiplier
Controls the width of the bands:
Higher values widen the bands, filtering out minor fluctuations.
Lower values tighten the bands for more responsive analysis.
Set Fibonacci Levels
Define custom Fibonacci ratios (e.g., 0.236, 0.382) to plot intermediate levels between the bands.
█ Tips for Fine-Tuning
⚪ For Trend Trading:
Use higher Std Dev Multipliers to focus on long-term trends and avoid noise. Adjust Anchor Timeframe to Weekly or Monthly for broader trend analysis.
⚪ For Reversal Trading:
Tighten the bands with a lower Std Dev Multiplier.
Use shorter anchor timeframes for intraday reversals (e.g., Hourly).
⚪ For Volatile Markets:
Increase the Std Dev Multiplier to accommodate wider price swings.
⚪ For Quiet Markets:
Decrease the Std Dev Multiplier to highlight smaller fluctuations.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Regime Classifier Oscillator (AiBitcoinTrend)The Regime Classifier Oscillator (AiBitcoinTrend) is an advanced tool for understanding market structure and detecting dynamic price regimes. By combining filtered price trends, clustering algorithms, and an adaptive oscillator, it provides traders with detailed insights into market phases, including accumulation, distribution, advancement, and decline.
This innovative tool simplifies market regime classification, enabling traders to align their strategies with evolving market conditions effectively.
👽 What is a Regime Classifier, and Why is it Useful?
A Regime Classifier is a concept in financial analysis that identifies distinct market conditions or "regimes" based on price behavior and volatility. These regimes often correspond to specific phases of the market, such as trends, consolidations, or periods of high or low volatility. By classifying these regimes, traders and analysts can better understand the underlying market dynamics, allowing them to adapt their strategies to suit prevailing conditions.
👽 Common Uses in Finance
Risk Management: Identifying high-volatility regimes helps traders adjust position sizes or hedge risks.
Strategy Optimization: Traders tailor their approaches—trend-following strategies in trending regimes, mean-reversion strategies in consolidations.
Forecasting: Understanding the current regime aids in predicting potential transitions, such as a shift from accumulation to an upward breakout.
Portfolio Allocation: Investors allocate assets differently based on market regimes, such as increasing cash positions in high-volatility environments.
👽 Why It’s Important
Markets behave differently under varying conditions. A regime classifier provides a structured way to analyze these changes, offering a systematic approach to decision-making. This improves both accuracy and confidence in navigating diverse market scenarios.
👽 How We Implemented the Regime Classifier in This Indicator
The Regime Classifier Oscillator takes the foundational concept of market regime classification and enhances it with advanced computational techniques, making it highly adaptive.
👾 Median Filtering: We smooth price data using a custom median filter to identify significant trends while eliminating noise. This establishes a baseline for price movement analysis.
👾 Clustering Model: Using clustering techniques, the indicator classifies volatility and price trends into distinct regimes:
Advance: Strong upward trends with low volatility.
Decline: Downward trends marked by high volatility.
Accumulation: Consolidation phases with subdued volatility.
Distribution: Topping or bottoming patterns with elevated volatility.
This classification leverages historical price data to refine cluster boundaries dynamically, ensuring adaptive and accurate detection of market states.
Volatility Classification: Price volatility is analyzed through rolling windows, separating data into high and low volatility clusters using distance-based assignments.
Price Trends: The interaction of price levels with the filtered trendline and volatility clusters determines whether the market is advancing, declining, accumulating, or distributing.
👽 Dynamic Cycle Oscillator (DCO):
Captures cyclic behavior and overlays it with smoothed oscillations, providing real-time feedback on price momentum and potential reversals.
Regime Visualization:
Regimes are displayed with intuitive labels and background colors, offering clear, actionable insights directly on the chart.
👽 Why This Implementation Stands Out
Dynamic and Adaptive: The clustering and refit mechanisms adapt to changing market conditions, ensuring relevance across different asset classes and timeframes.
Comprehensive Insights: By combining price trends, volatility, and cyclic behaviors, the indicator provides a holistic view of the market.
This implementation bridges the gap between theoretical regime classification and practical trading needs, making it a powerful tool for both novice and experienced traders.
👽 Applications
👾 Regime-Based Trading Strategies
Traders can use the regime classifications to adapt their strategies effectively:
Advance & Accumulation: Favorable for entering or holding long positions.
Decline & Distribution: Opportunities for short positions or risk management.
👾 Oscillator Insights for Trend Analysis
Overbought/oversold conditions: Early warning of potential reversals.
Dynamic trends: Highlights the strength of price momentum.
👽 Indicator Settings
👾 Filter and Classification Settings
Filter Window Size: Controls trend detection sensitivity.
ATR Lookback: Adjusts the threshold for regime classification.
Clustering Window & Refit Interval: Fine-tunes regime accuracy.
👾 Oscillator Settings
Dynamic Cycle Oscillator Lookback: Defines the sensitivity of cycle detection.
Smoothing Factor: Balances responsiveness and stability.
Disclaimer: This information is for entertainment purposes only and does not constitute financial advice. Please consult with a qualified financial advisor before making any investment decisions.
Rolling Window Geometric Brownian Motion Projections📊 Rolling GBM Projections + EV & Adjustable Confidence Bands
Overview
The Rolling GBM Projections + EV & Adjustable Confidence Bands indicator provides traders with a robust, dynamic tool to model and project future price movements using Geometric Brownian Motion (GBM). By combining GBM-based simulations, expected value (EV) calculations, and customizable confidence bands, this indicator offers valuable insights for decision-making and risk management.
Key Features
Rolling GBM Projections: Simulate potential future price paths based on drift (μμ) and volatility (σσ).
Expected Value (EV) Line: Represents the average projection of simulated price paths.
Confidence Bands: Define ranges where the price is expected to remain, adjustable from 51% to 99%.
Simulation Lines: Visualize individual GBM paths for detailed analysis.
EV of EV Line: A smoothed trend of the EV, offering additional clarity on price dynamics.
Customizable Lookback Periods: Adjust the rolling lookback periods for drift and volatility calculations.
Mathematical Foundation
1. Geometric Brownian Motion (GBM)
GBM is a mathematical model used to simulate the random movement of asset prices, described by the following stochastic differential equation:
dSt=μStdt+σStdWt
dSt=μStdt+σStdWt
Where:
StSt: Price at time tt
μμ: Drift term (expected return)
σσ: Volatility (standard deviation of returns)
dWtdWt: Wiener process (standard Brownian motion)
2. Drift (μμ) and Volatility (σσ)
Drift (μμ): Represents the average logarithmic return of the asset. Calculated using a simple moving average (SMA) over a rolling lookback period.
μ=SMA(ln(St/St−1),Lookback Drift)
μ=SMA(ln(St/St−1),Lookback Drift)
Volatility (σσ): Measures the standard deviation of logarithmic returns over a rolling lookback period.
σ=STD(ln(St/St−1),Lookback Volatility)
σ=STD(ln(St/St−1),Lookback Volatility)
3. Price Simulation Using GBM
The GBM formula for simulating future prices is:
St+Δt=St×e(μ−12σ2)Δt+σϵΔt
St+Δt=St×e(μ−21σ2)Δt+σϵΔt
Where:
ϵϵ: Random variable from a standard normal distribution (N(0,1)N(0,1)).
4. Confidence Bands
Confidence bands are determined using the Z-score corresponding to a user-defined confidence percentage (CC):
Upper Band=EV+Z⋅σ
Upper Band=EV+Z⋅σ
Lower Band=EV−Z⋅σ
Lower Band=EV−Z⋅σ
The Z-score is computed using an inverse normal distribution function, approximating the relationship between confidence and standard deviations.
Methodology
Rolling Drift and Volatility:
Drift and volatility are calculated using logarithmic returns over user-defined rolling lookback periods (default: μ=20μ=20, σ=16σ=16).
Drift defines the overall directional tendency, while volatility determines the randomness and variability of price movements.
Simulations:
Multiple GBM paths (default: 30) are generated for a specified number of projection candles (default: 12).
Each path is influenced by the current drift and volatility, incorporating random shocks to simulate real-world price dynamics.
Expected Value (EV):
The EV is calculated as the average of all simulated paths for each projection step, offering a statistical mean of potential price outcomes.
Confidence Bands:
The upper and lower bounds of the confidence bands are derived using the Z-score corresponding to the selected confidence percentage (e.g., 68%, 95%).
EV of EV:
A running average of the EV values, providing a smoothed perspective of price trends over the projection horizon.
Indicator Functionality
User Inputs:
Drift Lookback (Bars): Define the number of bars for rolling drift calculation (default: 20).
Volatility Lookback (Bars): Define the number of bars for rolling volatility calculation (default: 16).
Projection Candles (Bars): Set the number of bars to project future prices (default: 12).
Number of Simulations: Specify the number of GBM paths to simulate (default: 30).
Confidence Percentage: Input the desired confidence level for bands (default: 68%, adjustable from 51% to 99%).
Visualization Components:
Simulation Lines (Blue): Display individual GBM paths to visualize potential price scenarios.
Expected Value (EV) Line (Orange): Highlight the mean projection of all simulated paths.
Confidence Bands (Green & Red): Show the upper and lower confidence limits.
EV of EV Line (Orange Dashed): Provide a smoothed trendline of the EV values.
Current Price (White): Overlay the real-time price for context.
Display Toggles:
Enable or disable components (e.g., simulation lines, EV line, confidence bands) based on preference.
Practical Applications
Risk Management:
Utilize confidence bands to set stop-loss levels and manage trade risk effectively.
Use narrower confidence intervals (e.g., 50%) for aggressive strategies or wider intervals (e.g., 95%) for conservative approaches.
Trend Analysis:
Observe the EV and EV of EV lines to identify overarching trends and potential reversals.
Scenario Planning:
Analyze simulation lines to explore potential outcomes under varying market conditions.
Statistical Insights:
Leverage confidence bands to understand the statistical likelihood of price movements.
How to Use
Add the Indicator:
Copy the script into the TradingView Pine Editor, save it, and apply it to your chart.
Customize Settings:
Adjust the lookback periods for drift and volatility.
Define the number of projection candles and simulations.
Set the confidence percentage to tailor the bands to your strategy.
Interpret the Visualization:
Use the EV and confidence bands to guide trade entry, exit, and position sizing decisions.
Combine with other indicators for a holistic trading strategy.
Disclaimer
This indicator is a mathematical and statistical tool. It does not guarantee future performance.
Use it in conjunction with other forms of analysis and always trade responsibly.
Happy Trading! 🚀
Anchored Geometric Brownian Motion Projections w/EVAnchored GBM (Geometric Brownian Motion) Projections + EV & Confidence Bands
Version: Pine Script v6
Overlay: Yes
Author:
Published On:
Overview
The Anchored GBM Projections + EV & Confidence Bands indicator leverages the Geometric Brownian Motion (GBM) model to project future price movements based on historical data. By simulating multiple potential future price paths, it provides traders with insights into possible price trajectories, their expected values, and confidence intervals. Additionally, it offers a "Mean of EV" (EV of EV) line, representing the running average of expected values across the projection period.
Key Features
Anchor Time Setup:
Define a specific point in time from which the projections commence.
By default, it uses the current bar's timestamp but can be customized.
Projection Parameters:
Projection Candles (Bars): Determines the number of future bars (time periods) to project.
Number of Simulations: Specifies how many GBM paths to simulate, ensuring statistical relevance via the Central Limit Theorem (CLT).
Display Toggles:
Simulation Lines: Visual representation of individual GBM simulation paths.
Expected Value (EV) Line: The average price across all simulations at each projection bar.
Upper & Lower Confidence Bands: 95% confidence intervals indicating potential price boundaries.
EV of EV Line: Running average of EV values, providing a smoothed central tendency across the projection period. Additionally, this line often acts as an indicator of trend direction.
Visualization:
Clear and distinguishable lines with customizable colors and styles.
Overlayed on the price chart for direct comparison with actual price movements.
Mathematical Foundation
Geometric Brownian Motion (GBM):
Definition: GBM is a continuous-time stochastic process used to model stock prices. It assumes that the logarithm of the stock price follows a Brownian motion with drift.
Equation:
S(t)=S0⋅e(μ−12σ2)t+σW(t)
S(t)=S0⋅e(μ−21σ2)t+σW(t) Where:
S(t)S(t) = Stock price at time tt
S0S0 = Initial stock price
μμ = Drift coefficient (average return)
σσ = Volatility coefficient (standard deviation of returns)
W(t)W(t) = Wiener process (standard Brownian motion)
Drift (μμ) and Volatility (σσ):
Drift (μμ) represents the expected return of the stock.
Volatility (σσ) measures the stock's price fluctuation intensity.
Central Limit Theorem (CLT):
Principle: With a sufficiently large number of independent simulations, the distribution of the sample mean (EV) approaches a normal distribution, regardless of the underlying distribution.
Application: Ensures that the EV and confidence bands are statistically reliable.
Expected Value (EV) and Confidence Bands:
EV: The mean price across all simulations at each projection bar.
Confidence Bands: Range within which the actual price is expected to lie with a specified probability (e.g., 95%).
EV of EV (Mean of Sample Means):
Definition: Represents the running average of EV values across the projection period, offering a smoothed central tendency.
Methodology
Anchor Time Setup:
The indicator starts projecting from a user-defined Anchor Time. If not customized, it defaults to the current bar's timestamp.
Purpose: Allows users to analyze projections from a specific historical point or the latest market data.
Calculating Drift and Volatility:
Returns Calculation: Computes the logarithmic returns from the Anchor Time to the current bar.
returns=ln(StSt−1)
returns=ln(St−1St)
Drift (μμ): Calculated as the simple moving average (SMA) of returns over the period since the Anchor Time.
Volatility (σσ): Determined using the standard deviation (stdev) of returns over the same period.
Simulation Generation:
Number of Simulations: The user defines how many GBM paths to simulate (e.g., 30).
Projection Candles: Determines the number of future bars to project (e.g., 12).
Process:
For each simulation:
Start from the current close price.
For each projection bar:
Generate a random number zz from a standard normal distribution.
Calculate the next price using the GBM formula:
St+1=St⋅e(μ−12σ2)+σz
St+1=St⋅e(μ−21σ2)+σz
Store the projected price in an array.
Expected Value (EV) and Confidence Bands Calculation:
EV Path: At each projection bar, compute the mean of all simulated prices.
Variance and Standard Deviation: Calculate the variance and standard deviation of simulated prices to determine the confidence intervals.
Confidence Bands: Using the standard normal z-score (1.96 for 95% confidence), establish upper and lower bounds:
Upper Band=EV+z⋅σEV
Upper Band=EV+z⋅σEV
Lower Band=EV−z⋅σEV
Lower Band=EV−z⋅σEV
EV of EV (Running Average of EV Values):
Calculation: For each projection bar, compute the average of all EV values up to that bar.
EV of EV =1j+1∑k=0jEV
EV of EV =j+11k=0∑jEV
Visualization: Plotted as a dynamic line reflecting the evolving average EV across the projection period.
Visualization Elements
Simulation Lines:
Appearance: Semi-transparent blue lines representing individual GBM simulation paths.
Purpose: Illustrate a range of possible future price trajectories based on current drift and volatility.
Expected Value (EV) Line:
Appearance: Solid orange line.
Purpose: Shows the average projected price at each future bar across all simulations.
Confidence Bands:
Upper Band: Dashed green line indicating the upper 95% confidence boundary.
Lower Band: Dashed red line indicating the lower 95% confidence boundary.
Purpose: Highlight the range within which the price is statistically expected to remain with 95% confidence.
EV of EV Line:
Appearance: Dashed purple line.
Purpose: Displays the running average of EV values, providing a smoothed trend of the central tendency across the projection period. As the mean of sample means it approximates the population mean (i.e. the trend since the anchor point.)
Current Price:
Appearance: Semi-transparent white line.
Purpose: Serves as a reference point for comparing actual price movements against projected paths.
Usage Instructions
Configuring User Inputs:
Anchor Time:
Set to a specific timestamp to start projections from a historical point or leave it as default to use the current bar's time.
Projection Candles (Bars):
Define the number of future bars to project (e.g., 12). Adjust based on your trading timeframe and analysis needs.
Number of Simulations:
Specify the number of GBM paths to simulate (e.g., 30). Higher numbers yield more accurate EV and confidence bands but may impact performance.
Display Toggles:
Show Simulation Lines: Toggle to display or hide individual GBM simulation paths.
Show Expected Value Line: Toggle to display or hide the EV path.
Show Upper Confidence Band: Toggle to display or hide the upper confidence boundary.
Show Lower Confidence Band: Toggle to display or hide the lower confidence boundary.
Show EV of EV Line: Toggle to display or hide the running average of EV values.
Managing TradingView's Object Limits:
Understanding Limits:
TradingView imposes a limit on the number of graphical objects (e.g., lines) that can be rendered. High values for projection candles and simulations can quickly consume these limits. TradingView appears to only allow a total of 55 candles to be projected, so if you want to see two complete lines, you would have to set the projection length to 27: since 27 * 2 = 54 and 54 < 55.
Optimizing Performance:
Use Toggles: Enable only the necessary visual elements. For instance, disable simulation lines and confidence bands when focusing on the EV and EV of EV lines. You can also use the maximum projection length of 55 with the lower limit confidence band as the only line, visualizing a long horizon for your risk.
Adjust Parameters: Lower the number of projection candles or simulations to stay within object limits without compromising essential insights.
Interpreting the Indicator:
Simulation Lines (Blue):
Represent individual potential future price paths based on GBM. A wider spread indicates higher volatility.
Expected Value (EV) Line (Goldenrod):
Shows the mean projected price at each future bar, providing a central trend.
Confidence Bands (Green & Red):
Indicate the statistical range (95% confidence) within which the price is expected to remain.
EV of EV Line (Dotted Line - Goldenrod):
Reflects the running average of EV values, offering a smoothed perspective of expected price trends over the projection period.
Current Price (White):
Serves as a benchmark for assessing how actual prices compare to projected paths.
Practical Applications
Risk Management:
Confidence Bands: Help in identifying potential support and resistance levels based on statistical confidence intervals.
EV Path: Assists in setting realistic target prices and stop-loss levels aligned with projected expectations.
Trend Analysis:
EV of EV Line: Offers a smoothed trendline, aiding in identifying overarching market directions amidst price volatility. Indicative of the population mean/overall trend of the data since your anchor point.
Scenario Planning:
Simulation Lines: Enable traders to visualize multiple potential outcomes, fostering better decision-making under uncertainty.
Performance Evaluation:
Comparing Actual vs. Projected Prices: Assess how actual price movements align with projected scenarios, refining trading strategies over time.
Mathematical and Statistical Insights
Simulation Integrity:
Independence: Each simulation path is generated independently, ensuring unbiased and diverse projections.
Randomness: Utilizes a Gaussian random number generator to introduce variability in diffusion terms, mimicking real market randomness.
Statistical Reliability:
Central Limit Theorem (CLT): By simulating a sufficient number of paths (e.g., 30), the sample mean (EV) converges to the population mean, ensuring reliable EV and confidence band calculations.
Variance Calculation: Accurate computation of variance from simulation data ensures precise confidence intervals.
Dynamic Projections:
Running Average (EV of EV): Provides a cumulative perspective, allowing traders to observe how the average expectation evolves as the projection progresses.
Customization and Enhancements
Adjustable Parameters:
Tailor the projection length and simulation count to match your trading style and analysis depth.
Visual Customization:
Modify line colors, styles, and transparency to enhance clarity and fit chart aesthetics.
Extended Statistical Metrics:
Future iterations can incorporate additional metrics like median projections, skewness, or alternative confidence intervals.
Dynamic Recalculation:
Implement logic to automatically update projections as new data becomes available, ensuring real-time relevance.
Performance Considerations
Object Count Management:
High simulation counts and extended projection periods can lead to a significant number of graphical objects, potentially slowing down chart performance.
Solution: Utilize display toggles effectively and optimize projection parameters to balance detail with performance.
Computational Efficiency:
The script employs efficient array handling and conditional plotting to minimize unnecessary computations and object creation.
Conclusion
The Anchored GBM Projections + EV & Confidence Bands indicator is a robust tool for traders seeking to forecast potential future price movements using statistical models. By integrating Geometric Brownian Motion simulations with expected value calculations and confidence intervals, it offers a comprehensive view of possible market scenarios. The addition of the "EV of EV" line further enhances analytical depth by providing a running average of expected values, aiding in trend identification and strategic decision-making.
Hope it helps!
OBV Divergence Indicator [TradingFinder] On-Balance Vol Reversal🔵 Introduction
The On-Balance Volume (OBV) indicator, introduced by Joe Granville in 1963, is a powerful technical analysis tool used to measure buying and selling pressure based on trading volume and price.
By aggregating trading volume—adding it on positive days and subtracting it on negative days—OBV creates a cumulative line that reflects market volume pressure, making it valuable for confirming trends, identifying entry and exit points, and forecasting potential price movements.
Divergences between price and OBV often provide significant signals. A bearish divergence occurs when the price forms higher highs while the OBV line forms lower highs. This discrepancy indicates that upward momentum is weakening, increasing the likelihood of a downward trend.
In contrast, a bullish divergence happens when the price makes lower lows, but the OBV line forms higher lows. This suggests increasing buying pressure and the potential for an upward trend reversal.
For instance, if the price is rising but the OBV trendline is falling, it may signal a bearish divergence, warning of a possible price decline. Conversely, if the price is falling while the OBV line is rising, this could signal a bullish divergence, indicating a possible price recovery. These signals are particularly useful for identifying market turning points.
OBV often acts as a leading indicator, moving ahead of price changes. For example, a rising OBV alongside stable or declining prices can signal an impending upward breakout.
Conversely, a declining OBV with rising prices may indicate that the current uptrend is losing strength. Traders using this strategy often consider entering positions at breakout levels while setting stop losses near recent swing highs or lows to manage risk effectively.
This integration highlights how OBV divergences can provide actionable insights for predicting price movements and managing trades efficiently.
Bullish Divergence :
Bearish Divergence :
🔵 How to Use
The OBV indicator, as a cumulative tool, assists analysts in comparing volume and price changes to identify new trends and key levels for entering or exiting trades. Beyond confirming existing trends, it is particularly effective in analyzing positive and negative divergences between price and volume, providing valuable signals for trading decisions.
🟣 Bullish Divergence
A bullish divergence occurs when the price continues its downward or stable trend, but the OBV line starts rising, forming a higher low compared to its previous low. This suggests increasing volume on up days relative to down days and often signals a reversal to the upside.
For instance, if an asset's price stabilizes near a support level but the OBV line shows an upward trend, this divergence could present an opportunity to enter a long position.
🟣 Bearish Divergence
A bearish divergence occurs when the price forms higher highs, but the OBV line declines, creating lower highs compared to previous peaks. This indicates decreasing volume on up days relative to down days and often acts as a warning for a reversal to the downside.
For example, if an asset’s price approaches a resistance level while OBV starts declining, this divergence may signal the beginning of a downtrend and could indicate a good time to exit long trades or enter short positions.
🔵 Setting
Period : The "Period" setting allows you to define the number of bars or intervals for "Periodic" and "EMA" modes. A shorter period captures more short-term movements, while a longer period smooths out the fluctuations and provides a broader view of market trends.
You can enable or disable labels to highlight key levels or divergences and tables to show numerical details like values and divergence types. These options allow for a customized chart display.
🔵 Table
The following table breaks down the main features of the oscillator. It covers four critical categories: Exist, Consecutive, Divergence Quality, and Change Phase Indicator.
Exist : If divergence is detected, a "+" will appear in this row.
Consecutive: Shows the number of consecutive divergences that have formed in a short period.
Divergence Quality : Evaluates the quality of the divergence based on the number of occurrences. One is labeled "Normal," two are "Good," and three or more are considered "Strong."
Change Phase Indicator : If a phase change is detected between two oscillation peaks, this is marked in the table.
🔵 Conclusion
The OBV (On Balance Volume) indicator is a simple yet effective tool in technical analysis that combines volume and price changes to provide a comprehensive view of market buying and selling pressure. By identifying positive and negative divergences, OBV enables analysts to detect early signs of trend reversals and refine their trading strategies.
Divergences in OBV often precede price changes, making it a leading indicator for predicting market movements. Using OBV alongside other technical tools can enhance decision-making accuracy and help traders identify better entry and exit points. However, it is essential to consider the limitations of OBV, such as the potential for signal errors and the impact of sudden news events.
Ultimately, OBV serves as a complementary tool in technical analysis, aiding in trend identification, signal confirmation, and risk management. A thoughtful application of this indicator, in combination with other analytical tools, can create valuable opportunities for profiting in financial markets.
Stoch RSI and RSI Buy/Sell Signals with MACD Trend FilterDescription of the Indicator
This Pine Script is designed to provide traders with buy and sell signals based on the combination of Stochastic RSI, RSI, and MACD indicators, enhanced by the confirmation of candle colors. The primary goal is to facilitate informed trading decisions in various market conditions by utilizing different indicators and their interactions. The script allows customization of various parameters, providing flexibility for traders to adapt it to their specific trading styles.
Usefulness
This indicator is not just a mashup of existing indicators; it integrates the functionality of multiple momentum and trend-detection methods into a cohesive trading tool. The combination of Stochastic RSI, RSI, and MACD offers a well-rounded approach to analyzing market conditions, allowing traders to identify entry and exit points effectively. The inclusion of color-coded signals (strong vs. weak) further enhances its utility by providing visual cues about the strength of the signals.
How to Use This Indicator
Input Settings: Adjust the parameters for the Stochastic RSI, RSI, and MACD to fit your trading style. Set the overbought/oversold levels according to your risk tolerance.
Signal Colors:
Strong Buy Signal: Indicated by a green label and confirmed by a green candle (close > open).
Weak Buy Signal: Indicated by a blue label and confirmed by a green candle (close > open).
Strong Sell Signal: Indicated by a red label and confirmed by a red candle (close < open).
Weak Sell Signal: Indicated by an orange label and confirmed by a red candle (close < open).
Example Trading Strategy Using This Indicator
To effectively use this indicator as part of your trading strategy, follow these detailed steps:
Setup:
Timeframe : Select a timeframe that aligns with your trading style (e.g., 15-minute for intraday, 1-hour for swing trading, or daily for longer-term positions).
Indicator Settings : Customize the Stochastic RSI, RSI, and MACD parameters to suit your trading approach. Adjust overbought/oversold levels to match your risk tolerance.
Strategy:
1. Strong Buy Entry Criteria :
Wait for a strong buy signal (green label) when the RSI is at or below the oversold level (e.g., ≤ 35), indicating a deeply oversold market. Confirm that the MACD shows a decreasing trend (bearish momentum weakening) to validate a potential reversal. Ensure the current candle is green (close > open) if candle color confirmation is enabled.
Example Use : On a 1-hour chart, if the RSI drops below 35, MACD shows three consecutive bars of decreasing negative momentum, and a green candle forms, enter a buy position. This setup signals a robust entry with strong momentum backing it.
2. Weak Buy Entry Criteria :
Monitor for weak buy signals (blue label) when RSI is above the oversold level but still below the neutral (e.g., between 36 and 50). This indicates a market recovering from an oversold state but not fully reversing yet. These signals can be used for early entries with additional confirmations, such as support levels or higher timeframe trends.
Example Use : On the same 1-hour chart, if RSI is at 45, the MACD shows momentum stabilizing (not necessarily negative), and a green candle appears, consider a partial or cautious entry. Use this as an early warning for a potential bullish move, especially when higher timeframe indicators align.
3. Strong Sell Entry Criteria :
Look for a strong sell signal (red label) when RSI is at or above the overbought level (e.g., ≥ 65), signaling a strong overbought condition. The MACD should show three consecutive bars of increasing positive momentum to indicate that the bullish trend is weakening. Ensure the current candle is red (close < open) if candle color confirmation is enabled.
Example Use : If RSI reaches 70, MACD shows increasing momentum that starts to level off, and a red candle forms on a 1-hour chart, initiate a short position with a stop loss set above recent resistance. This is a high-confidence signal for potential price reversal or pullback.
4. Weak Sell Entry Criteria :
Use weak sell signals (orange label) when RSI is between the neutral and overbought levels (e.g., between 50 and 64). These can indicate potential short opportunities that might not yet be fully mature but are worth monitoring. Look for other confirmations like resistance levels or trendline touches to strengthen the signal.
Example Use : If RSI reads 60 on a 1-hour chart, and the MACD shows slight positive momentum with signs of slowing down, place a cautious sell position or scale out of existing long positions. This setup allows you to prepare for a possible downtrend.
Trade Management:
Stop Loss : For buy trades, place stop losses below recent swing lows. For sell trades, set stops above recent swing highs to manage risk effectively.
Take Profit : Target nearby resistance or support levels, apply risk-to-reward ratios (e.g., 1:2), or use trailing stops to lock in profits as price moves in your favor.
Confirmation : Align these signals with broader trends on higher timeframes. For example, if you receive a weak buy signal on a 15-minute chart, check the 1-hour or daily chart to ensure the overall trend is not bearish.
Real-World Example: Imagine trading on a 15-minute chart :
For a buy:
A strong buy signal (green) appears when the RSI dips to 32, MACD shows declining bearish momentum, and a green candle forms. Enter a buy position with a stop loss below the most recent support level.
Alternatively, a weak buy signal (blue) appears when RSI is at 47. Use this as a signal to start monitoring the market closely or enter a smaller position if other indicators (like support and volume analysis) align.
For a sell:
A strong sell signal (red) with RSI at 72 and a red candle signals to short with conviction. Place your stop loss just above the last peak.
A weak sell signal (orange) with RSI at 62 might prompt caution but can still be acted on if confirmed by declining volume or touching a resistance level.
These strategies show how to blend both strong and weak signals into your trading for more nuanced decision-making.
Technical Analysis of the Code
1. Stochastic RSI Calculation:
The script calculates the Stochastic RSI (stochRsiK) using the RSI as input and smooths it with a moving average (stochRsiD).
Code Explanation : ta.stoch(rsi, rsi, rsi, stochLength) computes the Stochastic RSI, and ta.sma(stochRsiK, stochSmoothing) applies smoothing.
2. RSI Calculation :
The RSI is computed over a user-defined period and checks for overbought or oversold conditions.
Code Explanation : rsi = ta.rsi(close, rsiLength) calculates RSI values.
3. MACD Trend Filter :
MACD is calculated with fast, slow, and signal lengths, identifying trends via three consecutive bars moving in the same direction.
Code Explanation : = ta.macd(close, macdLengthFast, macdLengthSlow, macdSignalLength) sets MACD values. Conditions like macdLine < macdLine confirm trends.
4. Buy and Sell Conditions :
The script checks Stochastic RSI, RSI, and MACD values to set buy/sell flags. Candle color filters further confirm valid entries.
Code Explanation : buyConditionMet and sellConditionMet logically check all conditions and toggles (enableStochCondition, enableRSICondition, etc.).
5. Signal Flags and Confirmation :
Flags track when conditions are met and ensure signals only appear on appropriate candle colors.
Code Explanation : Conditional blocks (if statements) update buyFlag and sellFlag.
6. Labels and Alerts :
The indicator plots "BUY" or "SELL" labels with the RSI value when signals trigger and sets alerts through alertcondition().
Code Explanation : label.new() displays the signal, color-coded for strength based on RSI.
NOTE : All strategies can be enabled or disabled in the settings, allowing traders to customize the indicator to their preferences and trading styles.
RSI/MFI Divergence Finder [idahodev]Monitoring RSI (Relative Strength Index) and MFI (Money Flow Index) divergences on a stock or index chart offers several benefits to traders and analysts. Let's break down the advantages:
Comprehensive Market View: Combining both indicators provides a more complete picture of market conditions, as they measure different aspects of price movement. RSI focuses on recent gains/losses relative to price change, while MFI incorporates volume data to assess money flow in and out of a security.
Enhanced Signal Accuracy: When divergences occur simultaneously in both RSI and MFI, it may be considered a stronger signal than if only one indicator showed divergence. This can potentially lead to more reliable trading decisions.
Identification of False Breakouts: Divergences between these indicators and price action can help identify false breakouts or misleading price movements that are not supported by underlying market strength or volume.
More Nuanced Market Understanding: By examining divergent behavior between money flow (MFI) and momentum (RSI), traders gain a more detailed comprehension of the interplay between these factors in shaping market trends.
Early Warning Signs: These divergences can act as early warning signs for potential trend reversals or changes in market sentiment, allowing traders to adjust their strategies proactively.
It's important to note that RSI/MFI divergences should be used as part of a broader trading strategy rather than solely relying on them for buy/sell signals. They can serve as valuable tools for confirming trends, identifying potential turning points, or warning against overbought/oversold conditions.
When using these indicators together, traders must be cautious of false signals, especially in choppy markets or during periods of high volatility. It's crucial to combine this analysis with other technical and fundamental factors before making trading decisions.
In summary, monitoring RSI/MFI divergences may offer a way to gain insights into the underlying strengths and weaknesses of market movements.
This utility differs from other in that it allows for a choke/threshold/sensitivity setting to help weed out noisy signals. This needs to be carefully adjusted per chart.
It also allows for tuning of the MFI smoothing length (number of bars on the current chart) as well as how many previous bars it will take into consideration when calculating RSI and MFI divergences. It will signal when it sees alignment forming between RSI and MFI divergences in a direction. You will likely need to tune this script's settings every few days or at least anytime there is a change in overall market behavior or sustained volatility.
Ultimately, the goal with this script is to provide an additional level of confirmation of weakness or strength. It should be combined with other indicators such as exhaustion, pivots, supply/demand, trendline breaks or tests, and structure changes, to name a few complementary tools or strategies. It's not meant to be a standalone buy/sell signal indicator!
Here are some settings for futures that may help you get started:
ES (4m chart)
RSI Length: 26
MFI Length: 8
MFI Smoothing Length: 32
Divergence Sensitivity: 124
Left Bars for Pivot: 10
Right Bars for Pivot: 1
NQ (4m chart)
RSI Length: 14
MFI Length: 14
MFI Smoothing Length: 21
Divergence Sensitivity: 400
Left Bars for Pivot: 21
Right Bars for Pivot: 1
YM (4m chart)
RSI Length: 14
MFI Length: 14
MFI Smoothing Length: 21
Divergence Sensitivity: 810
Left Bars for Pivot: 33
Right Bars for Pivot: 1
Leading Indicator by Parag RautBreakdown of the Leading Indicator:
Linear Regression (LRC):
A linear regression line is used to estimate the current trend direction. When the price is above or below the regression line, it indicates whether the price is deviating from its mean, signaling potential reversals.
Rate of Change (ROC):
ROC measures the momentum of the price over a set period. By using thresholds (positive or negative), we predict that the price will continue in the same direction if momentum is strong enough.
Leading Indicator Calculation:
We calculate the difference between the price and the linear regression line. This is normalized using the standard deviation of price over the same period, giving us a leading signal based on price divergence from the mean trend.
The leading indicator is used to forecast changes in price behavior by identifying when the price is either stretched too far from the mean (indicating a potential reversal) or showing strong momentum in a particular direction (predicting trend continuation).
Buy and Sell Signals:
Buy Signal: Generated when ROC is above a threshold and the leading indicator shows the price is above the regression line.
Sell Signal: Generated when ROC is below a negative threshold and the leading indicator shows the price is below the regression line.
Visual Representation:
The indicator oscillates around zero. Values above zero signal potential upward price movements, while values below zero signal potential downward movements.
Background colors highlight potential buy (green) and sell (red) areas based on our conditions.
How It Works as a Leading Indicator:
This indicator attempts to predict price movements before they happen by combining the trend (via linear regression) and momentum (via ROC).
When the price significantly diverges from the trendline and momentum supports a continuation, it signals a potential entry point (either buy or sell).
It is leading in that it anticipates price movement before it becomes fully apparent in the market.
Next Steps:
You can adjust the length of the linear regression and ROC to fine-tune the indicator’s sensitivity to your trading style.
This can be combined with other indicators or used as part of a larger strategy
