CCI Level Zero Strategy (by Marcoweb) v1.0Hi guys,
My strategy is ready :)
Finally the zero level of the CCI gives the start and stop to my positions. As you could notice, setting up the CCI length to 340 area on 1 minute chart will let the profit factor go up to 20% from an already wonderful 16%. This is a great result cause will let profitable trades run while stopping the wrong ones with a very limited loss. What makes our profit are not several small little positions that are clearly unrepitable in real trade but few and very profitable positions in which jumping in will be easier due to their length (71 bars average).
Please share with me your impressions and suggestions.
Have a nice trade :)
Cari dalam skrip untuk "profitable"
I_Heikin Ashi CandleWhen apply a strategy to Heikin Ashi Candle chart (HA candle), the strategy will use the open/close/high/low values of the Heikin Ashi candle to calculate the Profit and Loss, hence also affecting the Percent Profitable, Profit Factor, etc., often resulting a unrealistic high Percent Profitable and Profit Factor, which is misleading. But if you want to use the HA candle's values to calculate your indicator / strategy, but pass the normal candle's open/close/high/low values to the strategy to calculate the Profit / Loss, you can do this:
1) set up the main chart to be a normal candle chart
2) use this indicator script to plot a secondary window with indicator looks exactly like a HA-chart
3) to use the HA-candle's open/close/high/low value to calculate whatever indicator you want (you may need to create a separate script if you want to plot this indicator in a separate indicator window)
MACDouble + RSI (rec. 15min-2hr intrv) Uses two sets of MACD plus an RSI to either long or short. All three indicators trigger buy/sell as one (ie it's not 'IF MACD1 OR MACD2 OR RSI > 1 = buy", its more like "IF 1 AND 2 AND RSI=buy", all 3 match required for trigger)
The MACD inputs should be tweaked depending on timeframe and what you are trading. If you are doing 1, 3, 5 min or real frequent trading then 21/44/20 and 32/66/29 or other high value MACDs should be considered. If you are doing longer intervals like 2, 3, 4hr then consider 9/19/9 and 21/44/20 for MACDs (experiment! I picked these example #s randomly).
Ideal usage for the MACD sets is to have MACD2 inputs at around 1.5x, 2x, or 3x MACD1's inputs.
Other settings to consider: try having fastlength1=macdlength1 and then (fastlength2 = macdlength2 - 2). Like 10/26/10 and 23/48/20. This seems to increase net profit since it is more likely to trigger before major price moves, but may decrease profitable trade %. Conversely, consider FL1=MCDL1 and FL2 = MCDL2 + (FL2 * 0.5). Example: 10/26/10 and 22/48/30 this can increase profitable trade %, though may cost some net profit.
Feel free to message me with suggestions or questions.
SPY Master v1.0This is a simple swing trading algorithm that uses a fast RSI-EMA to trigger buy/cover signals and a slow RSI-EMA to trigger sell/short signals for SPY, an xchange-traded fund for the S&P 500.
The idea behind this strategy follows the premise that most profitable momentum trades usually occur during periods when price is trending up or down. Periods of flat price actions are usually where most unprofitable trades occur. Because we cannot predict exactly when trending periods will occur, the algorithm basically bets money on all trade opportunities during all market conditions. Despite an accuracy rate of only 40%, the algorithm's asymmetric risk/reward profile allows the average winner to be 2x the average loser. The end result is a positive (profitable) net payout.
TRADING RULES:
Buy/Cover = EMA3(RSI2) cross> 50
Sell/Short = EMA5(RSI2) cross< 50
BACKTEST SETTINGS:
- Period = March 2011 - Present
- Initial capital = $10,000
- Dividends excluded
- Trading costs excluded
PERFORMANCE COMPARISON:
There are 657 trades, which means 1,314 orders. Assuming each order costs $2 (what I pay for at Interactive Brokers), total trading costs should be $2,628.
-SPY (buy & hold) = 132.73 ---> 193.22 = +45.57% (dividends excluded)
-SPY Master v1.0 = $12,649 - $2,628 = $10,021 = +100.21%
DISCLAIMER: None of my ideas and posts are investment advice. Past performance is not an indication of future results. This strategy was constructed with the benefit of hindsight and its future performance cannot be guaranteed.
Ichimoku EMA BandsSome find Ichimoku Clouds bit complicated. This simplified version is combined with EMA Bands may be profitable. Give a try!. I recommend hourly timeframe for good results. Aye! :D
yuthavithi volatility based force trade scalper strategyI have converted my volatility based force scalper into strategy. Nice to see it is so profitable. Work best with Heikin Ashi bar.
BACKTEST SCRIPT 0.999 ALPHATRADINGVIEW BACKTEST SCRIPT by Lionshare (c) 2015
THS IS A REAL ALTERNATIVE FOR LONG AWAITED TV NATIVE BACKTEST ENGINE.
READY FOR USE JUST RIGHT NOW.
For user provided trading strategy, executes the trades on pricedata history and continues to make it over live datafeed.
Calculates and (plots on premise) the next performance statistics:
profit - i.e. gross profit/loss.
profit_max - maximum value of gross profit/loss.
profit_per_trade - each trade's profit/loss.
profit_per_stop_trade - profit/loss per "stop order" trade.
profit_stop - gross profit/loss caused by stop orders.
profit_stop_p - percentage of "stop orders" profit/loss in gross profit/loss.
security_if_bought_back - size of security portfolio if bought back.
trades_count_conseq_profit - consecutive gain from profitable series.
trades_count_conseq_profit_max - maxmimum gain from consecutive profitable series achieved.
trades_count_conseq_loss - same as for profit, but for loss.
trades_count_conseq_loss_max - same as for profit, but for loss.
trades_count_conseq_won - number of trades, that were won consecutively.
trades_count_conseq_won_max - maximum number of trades, won consecutively.
trades_count_conseq_lost - same as for won trades, but for lost.
trades_count_conseq_lost_max - same as for won trades, but for lost.
drawdown - difference between local equity highs and lows.
profit_factor - profit-t-loss ratio.
profit_factor_r - profit(without biggest winning trade)-to-loss ratio.
recovery_factor - equity-to-drawdown ratio.
expected_value - median gain value of all wins and loss.
zscore - shows how much your seriality of consecutive wins/loss diverges from the one of normal distributed process. valued in sigmas. zscore of +3 or -3 sigmas means nonrandom realitonship of wins series-to-loss series.
confidence_limit - the limit of confidence in zscore result. values under 0.95 are considered inconclusive.
sharpe - sharpe ratio - shows the level of strategy stability. basically it is how the profit/loss is deviated around the expected value.
sortino - the same as sharpe, but is calculated over the negative gains.
k - Kelly criterion value, means the percentage of your portfolio, you can trade the scripted strategy for optimal risk management.
k_margin - Kelly criterion recalculated to be meant as optimal margin value.
DISCLAIMER :
The SCRIPT is in ALPHA stage. So there could be some hidden bugs.
Though the basic functionality seems to work fine.
Initial documentation is not detailed. There could be english grammar mistakes also.
NOW Working hard on optimizing the script. Seems, some heavier strategies (especially those using the multiple SECURITY functions) call TV processing power limitation errors.
Docs are here:
docs.google.com
CM Stochastic POP Method 1 - Jake Bernstein_V1A good friend ucsgears recently published a Stochastic Pop Indicator designed by Jake Bernstein with a modified version he found.
I spoke to Jake this morning and asked if he had any updates to his Stochastic POP Trading Method. Attached is a PDF Jake published a while back (Please read for basic rules, which also Includes a New Method). I will release the Additional Method Tomorrow.
Jake asked me to share that he has Updated this Method Recently. Now across all symbols he has found the Stochastic Values of 60 and 30 to be the most profitable. NOTE - This can be Significantly Optimized for certain Symbols/Markets.
Jake Bernstein will be a contributor on TradingView when Backtesting/Strategies are released. Jake is one of the Top Trading System Developers in the world with 45+ years experience and he is going to teach how to create Trading Systems and how to Optimize the correct way.
Below are a few Strategy Results....Soon You Will Be Able To Find Results Like This Yourself on TradingView.com
BackTesting Results Example: EUR-USD Daily Chart Since 01/01/2005
Strategy 1:
Go Long When Stochastic Crosses Above 60. Go Short When Stochastic Crosses Below 30. Exit Long/Short When Stochastic has a Reverse Cross of Entry Value.
Results:
Total Trades = 164
Profit = 50, 126 Pips
Win% = 38.4%
Profit Factor = 1.35
Avg Trade = 306 Pips Profit
***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6
Strategy 2:
Rules - Proprietary Optimization Jake Will Teach. Only Added 1 Additional Exit Rule.
Results:
Total Trades = 164
Profit = 62, 876 Pips!!!
Win% = 38.4%
Profit Factor = 1.44
Avg Trade = 383 Pips Profit
***Most Consecutive Wins = 3 ... Most Consecutive Losses = 6
Strategy 3:
Rules - Proprietary Optimization Jake Will Teach. Only added 1 Additional Exit Rule.
Results:
Winning Percent Increases to 72.6%!!! , Same Amount of Trades.
***Most Consecutive Wins = 21 ...Most Consecutive Losses = 4
Indicator Includes:
-Ability to Color Candles (CheckBox In Inputs Tab)
Green = Long Trade
Blue = No Trade
Red = Short Trade
-Color Coded Stochastic Line based on being Above/Below or In Between Entry Lines.
Link To Jakes PDF with Rules
dl.dropboxusercontent.com
Vervoort Heiken Ashi Candlestick OscillatorHeiken-Ashi Candlestick Oscillator (HACO), by Sylvian Vervoort, is a digital oscillator version of the colored candlesticks.
Explanation from Vervoort:
"HACO is not meant to be an automatic trading system, so when there is a buy or sell signal from HACO, make sure it is confirmed by other TA techniques. HACO will certainly aid in signaling buy/sell opportunities and help you hold on to a trade, making it more profitable. The behavior of HACO is closely related to the level and speed of price change. It can be used on charts of any time frame ranging from intraday to monthly."
HACO has 2 configurable length parameters - "UP TEMA length" and "Down TEMA length". Vervoort suggests having them the same value.
I have also added an option to color the bars (overlay mode).
More info:
Trading with the Heiken-Ashi Candlestick Oscillator - Sylvian Vervoort
List of my other indicators:
- GDoc: docs.google.com
- Chart:
DEnvelope [Better Bollinger Bands]*** ***
Bollinger Bands (BB) usually expand quickly after a volatility increase but contract more slowly as volatility declines. This extended time it takes for BB to contract after a volatility drop can make trading some instruments using BB alone difficult or less profitable.
In the October 1998 issue of "Futures" there is an article written by Dennis McNicholl called "Better Bollinger Bands", in which the author recommends improving BB by modifying:
- the center line formula &
- different equations for calculating the bands.
These bands, called "DEnvelope", follow price more closely and respond faster to changes in volatility with these modifications.
Fore more indicators, check out my "Master Index of indicators" (Also check my published charts page for new ones I haven't added to that list):
More scripts related to DEnvelope:
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- DEnvelope Bandwidth: pastebin.com
- DEnvelope %B : pastebin.com
Sample chart with above indicators: www.tradingview.com
Multi Hourly ATP (Average Trade Price)"Multi-timeframe average trade price" analysis combines two concepts: using the Average Trade Price (ATP) as a benchmark and applying a multi-timeframe analysis (MTFA) trading strategy. The benefits stem from using the ATP for position management and MTFA for better-informed trading decisions.
Benefits of Averaging the Trade Price
Averaging the trade price (using methods like "averaging down" or "averaging up," or the Volume-Weighted Average Price - VWAP) helps investors manage their positions and costs.
Better Cost Basis Assessment: The ATP provides a clear benchmark for your overall cost per share, including fees. This helps you understand your true breakeven point and accurately assess whether a position is currently profitable or at a loss.
Risk Mitigation: In a falling market, buying more shares at a lower price (averaging down) reduces the average purchase price, which means the stock does not have to recover to its initial price for you to break even or make a profit.
Profit Accumulation: In a rising market, buying more shares as the price increases (averaging up or pyramiding) allows you to accumulate more profits if the upward trend continues, increasing your overall position size in a winning trade.
Emotional Discipline: By following a predefined averaging strategy, traders can reduce the impact of emotional decisions like panic selling or holding onto losing trades for too long.
Managing Volatility: Averaging helps smooth out the impact of short-term price fluctuations on your overall portfolio performance, which is particularly useful in volatile markets.
Zero Lag MACD and EMA 200 with SignalsZero Lag MACD with EMA Filter and Smart Signals
This indicator is an enhanced version of the traditional MACD that uses Zero Lag EMA calculations to provide faster and more responsive signals for scalping and day trading.
Key Features:
🎯 Zero Lag Technology - Uses double-smoothed EMA calculations to eliminate lag and provide earlier signals compared to standard MACD
📊 Clean Visualization - Displays histogram with MACD and Signal lines for clear trend analysis
🔍 Smart Signal Logic - Only shows valid trading signals based on strict conditions:
Buy Signal (Green dot at bottom): Triggers when price is above 200 EMA AND MACD crosses Signal line from below AND crossover occurs below zero line
Sell Signal (Red dot at top): Triggers when price is below 200 EMA AND MACD crosses Signal line from above AND crossover occurs above zero line
🔔 Built-in Alerts - Easy alert setup for both buy and sell signals so you never miss a trading opportunity
📈 200 EMA Filter - Incorporates trend filter to avoid counter-trend trades and improve signal quality
⚙️ Fully Customizable - Adjust all parameters:
Fast EMA Length (default: 12)
Slow EMA Length (default: 26)
Signal Length (default: 9)
EMA Filter Length (default: 200)
How to Use:
-Add the indicator to your chart
-Look for green dots (buy signals) when price is in an uptrend above 200 EMA
-Look for red dots (sell signals) when price is in a downtrend below 200 EMA
-Set up alerts by clicking "Create Alert" and selecting "Buy Signal" or "Sell Signal"
-Use signals in conjunction with your trading strategy and risk management
Best Practices:
-Works best on 1-15 minute timeframes for scalping
-Combine with support/resistance levels for confirmation
-Use proper stop-loss and take-profit levels
-Not all signals will be profitable - use proper risk management
-Signals are filtered to reduce noise and false entries
Color Scheme:
Histogram: Red (bearish) / Cyan (bullish)
MACD Line: Fuchsia/Pink
Signal Line: Lime/Green
Buy Signal: Green dot (bottom)
Sell Signal: Red dot (top)
This indicator is perfect for traders who want a cleaner, faster-responding MACD with built-in trend filtering and clear entry signals. Free to use and customize!
Dynamic MAs Zscore | Lyro RSThe Dynamic MAs Zscore is an adaptive momentum and valuation oscillator built around advanced moving averages and statistical Z-Score normalization. By combining a wide selection of moving average types with dynamic deviation bands, this indicator delivers clear insights into trend strength , directional bias , and relative valuation — all in a clean, visually intuitive format.
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Key Features
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Dynamic Moving Average Engine
Applies one of 12 selectable moving average types (SMA, EMA, WMA, VWMA, HMA, ALMA, TEMA, etc.) to the chosen source. This allows fine-tuning between responsiveness and smoothness depending on market conditions.
Z-Score Normalization
Transforms the selected moving average into a standardized Z-Score:
(MA − mean) / standard deviation
This normalization makes momentum strength comparable across assets and timeframes.
Adaptive Deviation Bands
Upper and lower bands are derived from the rolling standard deviation of the Z-Score:
Custom band length
Independent positive and negative multipliers
These bands dynamically expand and contract with volatility.
Dual Signal Modes
Trend Mode – Focuses on directional continuation. Color changes and signals occur when Z-Score breaks above or below deviation bands.
Valuation Mode – Highlights relative overvaluation and undervaluation using a gradient color scale and predefined value zones.
Advanced Visual System
Includes bold layered plots, gradient fills, background shading, and candle/bar coloring to clearly reflect current market state.
Custom Color Palettes
Choose from multiple preset themes (Classic, Mystic, Accented, Royal) or define your own bullish and bearish colors.
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How It Works
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MA Calculation – The selected moving average type is applied to the chosen price source.
Z-Score Computation – The MA is normalized over a user-defined lookback period to quantify deviation from its mean.
Band Construction – Standard deviation of the Z-Score is calculated over the band length and scaled by positive/negative multipliers.
Mode-Dependent Logic
Trend Mode – Breaks above the upper band signal bullish momentum; breaks below the lower band signal bearish momentum.
Valuation Mode – A gradient reflects relative valuation from undervalued to overvalued, with background highlights at extreme Z-Score levels.
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Signal Interpretation
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Trend Confirmation
In Trend Mode, sustained moves beyond deviation bands indicate strong directional bias.
Momentum Strength
The distance of the Z-Score from zero reflects the intensity of trend momentum.
Relative Valuation
In Valuation Mode, deep negative Z-Scores suggest undervaluation, while high positive Z-Scores suggest overvaluation.
Visual Clarity
Bar and candle coloring aligned with oscillator state allows for rapid assessment of market conditions.
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Customization
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Adjust MA type and length to balance speed vs. smoothness.
Modify Z-Score length to control sensitivity.
Tune band length and multipliers for volatility adaptation.
Switch between Trend and Valuation modes depending on strategy.
Personalize visuals using preset or custom color palettes.
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Alerts
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Bullish condition when Z-Score > 0
Bearish condition when Z-Score < 0
Overvalued and undervalued valuation alerts
⚠️ Disclaimer
This indicator is intended for technical analysis and educational purposes only. It does not guarantee profitable outcomes and should be used alongside other tools, confirmation methods, and sound risk management. The author is not responsible for any financial decisions made using this indicator.
Quality Detector (Buffett Style) + Beta [Solid]This indicator acts as an on-chart fundamental screener, designed to instantly evaluate the quality and financial health of a company directly on your price chart.
The concept is inspired by "Buffettology" principles: looking for large, profitable companies with low debt. Additionally, it includes a Beta calculation to assess market volatility risk.
The tool displays a panel in the bottom-right corner featuring four key metrics and a final verdict.
How it Works & Metrics Used
The script retrieves quarterly fundamental data ("FQ") and performs calculations to verify if the asset meets specific criteria.
1. Market Cap (Size)
What it is: The total market value of the company's outstanding shares.
Goal: To identify established, large-cap companies.
Default Threshold: Must be greater than $10 Billion.
2. ROE - Return on Equity (Quality)
What it is: A measure of financial performance calculated by dividing net income by shareholders' equity.
Goal: To find companies that are efficient at generating profits from shareholders' capital.
Default Threshold: Must be higher than 15%.
3. Total Debt to Equity (Health)
What it is: A ratio indicating the relative proportion of shareholders' equity and debt used to finance a company's assets.
Calculation: This script manually calculates this ratio by fetching TOTAL_DEBT and dividing it by TOTAL_EQUITY from fundamental data to ensure robustness across different symbols.
Goal: To ensure the company is not overly leveraged.
Default Threshold: Must be lower than 1.5.
4. Beta (Risk/Volatility)
What it is: A measure of a stock's volatility in relation to the overall market (S&P 500).
Calculation: It is calculated by comparing the asset's returns against SPY (S&P 500 ETF) returns over a 252-day period (approx. 1 trading year).
Goal: To understand if the stock is more volatile (Beta > 1) or less volatile (Beta < 1) than the market.
Note: Beta does not affect the final "Quality" score but serves as an extra risk indicator, highlighting in orange if Beta > 1.
The Verdict (Scoring System)
The indicator assigns a score from 0 to 3 based on the first three fundamental metrics (Size, ROE, and Debt/Equity).
If a metric passes the threshold, it gets a green background and +1 point.
If it fails, it gets a red background.
Final Verdict:
💎 QUALITY GEM: The company passed all 3 fundamental checks (Score = 3/3).
⚠️ DISCARD: The company failed one or more fundamental checks.
Settings
You can customize the thresholds to fit your own investment strategy in the indicator settings:
Minimum Market Cap (in Billions).
Minimum ROE (%).
Maximum Debt/Equity Ratio.
Disclaimer: This tool is for informational and educational purposes only. It relies on third-party fundamental data which may sometimes be delayed or unavailable. Do not base investment decisions solely on this indicator.
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure.
To use this engine successfully, you must adopt a specific optimization mindset:
Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless.
Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the trade is rejected.
This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal.
Module 2: Correlation Trend Indicator (CTI)
Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend).
Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise).
Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts).
Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support.
Module 6: Crypto Market Breadth (CMB)
Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges.
Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data.
Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart.
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen.
Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up.
Module 11: HSRS Compression / Super AO
Logic: Two options in one.
HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands.
Super AO: A combination of the Awesome Oscillator and SuperTrend logic.
Function: Great for catching explosive moves that result from periods of low volatility (consolidation).
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked.
Bitcoin Halving Logic:
Hardcoded dates for past and projected future Bitcoin halvings (up to 2040).
Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes.
Miner Capitulation:
Uses Hash Rate Ribbons (Moving averages of Hash Rate).
If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat.
ADX Filter (Flat Market Protocol):
If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market.
CryptoCap Trend:
Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins.
6. Risk Management & The Dump Protection Team (DPT)
Gypsy Bot separates "Entry Logic" from "Risk Management Logic."
Dump Protection Team (DPT)
This is a specialized logic branch designed to save the account during Black Swan events.
Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit.
Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction.
Advanced Adaptive Trailing Stop (AATS)
Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic.
Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks.
Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital.
Staged Take Profits
TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win.
TP2: Take the bulk of profit.
TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance.
Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative).
Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals).
Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Bayesian Liquidity Pain & Gain [Instit. Vol Weighted]Bayesian Liquidity Pain & Gain Indicator
Stop guessing where support and resistance are.
The Bayesian Liquidity Pain & Gain indicator moves beyond arbitrary lines and raw price action. It quantifies Institutional Intent by calculating the exact price levels where large volume has been accumulated and visualizes the "Pain" (stress) those participants feel when the market moves against them.
The Logic: Quantified Institutional Stress
Institutions don't trade single candles; they accumulate positions over time. This indicator tracks their Volume-Weighted Average Cost Basis to answer two critical questions:
Where did they enter? (The Cost Basis Lines)
Are they underwater? (The Pain Clouds)
By normalizing price distance using volatility (ATR) and statistical deviation (Z-Score), we filter out noise and only highlight zones where "Smart Money" is statistically forced to defend their positions or capitulate.
How to Read the Chart
1. The Cost Basis Lines (Anchors)
• 🟢 Green Line (Buyer Cost Basis): The average price where institutions accumulated long positions. This acts as dynamic Support.
• 🔴 Red Line (Seller Cost Basis): The average price where institutions accumulated short positions. This acts as dynamic Resistance.
2. The Pain Clouds (Signals)
When price moves significantly away from the cost basis (Z-Score > 2.0), "Clouds" appear to visualize the PnL status of the participants:
• 🔴 Red Cloud (Buyer Pain): Price is below the buyer's entry. Buyers are losing money (in the red). This creates a "Discount" zone where they may defend support.
• 🟢 Green Cloud (Seller Pain): Price is above the seller's entry. Sellers are losing money (shorts are squeezed). This indicates strong bullish momentum.
3. The Multi-Timeframe Dashboard
A real-time HUD showing the Z-Score status across 4 timeframes (1m, 5m, 15m, 1h):
• 🟢 Green: Profitable/Neutral (Trend Continuation)
• 🟠 Orange: Warning (Pressure Building)
• 🔴 Red: Critical Pain (High Probability Reversal)
Trading Strategies
Setup 1: The Defensive Bounce (Long)
• Context: Price drops into a 🔴 Red Cloud (Buyer Pain).
• Trigger: Price touches the 🟢 Green Line (Buyer Cost Basis) and shows a rejection wick.
• Logic: Institutional buyers defend their cost basis to avoid realizing losses.
Setup 2: The Short Squeeze (Momentum)
• Context: Price rallies into a 🟢 Green Cloud (Seller Pain).
• Trigger: Price holds above the 🔴 Red Line (Seller Cost Basis).
• Logic: Short sellers are trapped and forced to buy back (cover), fueling the rally.
Fractal Alignment:
For high-conviction trades, wait for the Dashboard to show "Pain" signals on both the 1h (Anchor) and 5m (Trigger) timeframes simultaneously.
Settings
• Memory Length (Default 144): The lookback period for the institutional cost basis. Increase for swing trading, decrease for scalping.
• Sigma Threshold (Default 2.0): The statistical confidence level for "Pain". Higher values = fewer, stronger signals.
• Volume Amp: When enabled, high volume amplifies the pain signal, giving more weight to institutional footprints.
FTPM - Institutional Trend Pressure Suite @darshaksscThis indicator provides an informational view of market trend pressure using fractal-based momentum events, smoothed pressure calculations, higher timeframe confirmation, and divergence analysis. It does not produce buy or sell signals. Instead, it presents market context to help traders interpret trend conditions in a structured and data-driven way.
The indicator includes the following components:
1). Non-repainting Trend Pressure Engine
The pressure line is derived from confirmed fractal events, body-to-range ratios, displacement strength, and a controlled decay factor. The value is normalized to a 0 to 100 scale. A rising pressure value suggests increasing trend strength, while a declining value indicates weakening strength. This is informational only.
2). Pressure Shifts
The tool highlights transitions where pressure crosses above or below key thresholds. These labels do not represent entries or exits, but simply indicate contextual changes in momentum.
3). Higher Timeframe Pressure Confirmation
Users can compare current timeframe pressure to a selected higher timeframe. When both pressures align in similar regions, it may indicate agreement in broader market structure. This feature is informational only and does not generate trading signals.
4). Divergence Detection
Identifies confirmed bullish or bearish divergences between price pivots and pressure pivots. Divergences are simply analytical tools and should not be interpreted as actionable trading signals.
5). Institutional Dashboard
A multi-line dashboard summarizes current pressure, regime classification, higher timeframe regime, pressure direction, divergence status, and alignment conditions. The dashboard is informational only. No part of the dashboard should be interpreted as a trade instruction.
6). Dashboard Size Selector
Users may switch between Full, Medium, or Thin dashboard layouts to match their screen preferences. This affects only display, not indicator logic.
Important Notes
This indicator does not forecast future price movement.
It does not generate buy, sell, long, or short signals.
It does not guarantee profitable outcomes.
It is intended purely for visual analysis and market context.
All information is derived from confirmed historical data.
No part of this script is designed to automate trading decisions.
This tool is suitable for traders who want a clear, non-repainting visualization of pressure conditions and structural behavior without violating TradingView House Rules.
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HOW TO USE
The indicator helps traders observe whether pressure is increasing or decreasing, whether higher timeframe conditions agree with the current chart, and whether divergences are present. All outputs are informational and should be combined with the user's preferred strategy or manual analysis. The indicator is not intended to signal trades or provide recommendations.
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DISCLAIMERS
This indicator is for educational and informational purposes only.
It does not constitute financial advice.
It does not provide buy, sell, long, or short signals.
It does not predict future price movement.
Past performance does not guarantee future results.
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Smart Christmas Tree Overlay with Live Market StatusGet into the holiday spirit while you trade! 🎅📈
This script adds a festive, animated Christmas tree overlay to your chart that reacts to live market conditions in real-time. It is designed with a "Slim Fit" ratio to minimize screen real estate while maximizing the holiday vibe.
Key Features:
🎄 Trend-Reactive Lighting:
Bullish (Up): The tree lights sparkle in Green tones, and a special Blue Diamond (🔷) shines to indicate upward momentum.
Bearish (Down): The tree lights turn Red, and a Red Diamond (♦️) blinks to warn of downward movement.
✨ Real-Time Animation: The lights and star blink dynamically based on price updates, making the chart feel alive.
📊 Mini Market HUD: Displays the current Ticker, Last Price, Price Change, and Change % neatly below the tree.
📐 Fully Customizable: You can easily change the tree's Position (Corners/Middle) and Size (Small to Large) via the settings menu.
🖼️ "Always On" Overlay: Uses the TradingView table function to stay fixed on your screen, regardless of zoom or scroll.
How to use: Simply add it to your chart, select your preferred corner in the settings, and enjoy the show!
Happy Holidays and Profitable Trading! 🎁
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트레이딩을 하면서 연말 분위기를 느껴보세요! 🎅📈
이 스크립트는 실시간 시장 상황에 반응하는 애니메이션 크리스마스 트리 오버레이를 차트에 추가합니다. 화면 공간을 최소한으로 차지하도록 "슬림 핏" 비율로 디자인되었습니다.
주요 기능:
🎄 추세 반응형 조명:
상승장 (Bullish): 트리 조명이 녹색 톤으로 반짝이며, 상승 모멘텀을 나타내는 특별한 **파란색 다이아몬드(🔷)**가 빛납니다.
하락장 (Bearish): 트리 조명이 빨간색으로 변하고, **빨간색 다이아몬드(♦️)**가 깜빡이며 하락을 경고합니다.
✨ 실시간 애니메이션: 가격 업데이트에 따라 조명과 별이 역동적으로 깜빡여 차트에 생동감을 줍니다.
📊 미니 시세판 (HUD): 트리 바로 아래에 현재 종목명, 현재가, 가격 변동폭, 변동률(%)을 깔끔하게 표시합니다.
📐 완벽한 커스터마이징: 설정 메뉴를 통해 트리의 위치(모서리/중간)와 크기(작게~크게)를 쉽게 변경할 수 있습니다.
🖼️ "Always On" 오버레이: TradingView의 table 기능을 사용하여 줌이나 스크롤에 관계없이 화면에 고정됩니다.
사용 방법: 차트에 추가하고 설정에서 원하는 위치를 선택하기만 하면 됩니다!
행복한 연말 보내시고 성투하세요! 🎁
양키트레이더 from PropKorea.com
BTC Mon 8am Buy / Wed 2pm Sell (NY Time, Daily + Intraday)This strategy implements a fixed weekly time-based trading schedule for Bitcoin, using New York market hours as the reference clock. It is designed to test whether a consistent pattern exists between early-week accumulation and mid-week distribution in BTC price behavior.
Entry Rule — Monday 8:00 AM (NY Time)
The strategy enters a long position every Monday at exactly 08:00 AM Eastern Time, one hour after the U.S. equities market pre-open activity begins influencing global liquidity.
This timing attempts to capture early-week directional moves in Bitcoin, which sometimes occur as traditional markets come online.
Exit Rule — Wednesday 2:00 PM (NY Time)
The strategy closes the position every Wednesday at 2:00 PM Eastern Time, a point in the week where:
U.S. equity markets are still open
BTC often experiences mid-week volatility rotations
Liquidity is generally high
This exit removes exposure before later-week uncertainty and gives a consistent, measurable time window for each trade.
Timeframe Compatibility
Works on intraday charts (recommended 1h or lower) using precise time-based triggers.
Also runs on daily charts, where entries and exits occur on the Monday and Wednesday bars respectively (daily charts cannot show intraday timestamps).
All timestamps are synced to America/New_York regardless of the exchange’s native timezone.
Trading Frequency
Exactly one trade per week, preventing overtrading and allowing comparison of weekly performance across years of historical BTC price data.
Purpose of the Strategy
This is not a value-based or trend-following system, but a behavioral/time-cycle analysis tool.
It helps evaluate whether a repeating short-term edge exists based solely on:
Weekday timing
Liquidity cycles
Institutional market influence
BTC’s habitual early-week momentum patterns
It is ideal for:
Backtesting weekly BTC behavior
Studying time-based edges
Comparing alternative weekday/time combinations
Visualizing weekly P&L structure
Risk Notes
This strategy does not attempt to predict price direction and should not be assumed profitable without robust backtesting.
Time-based edges can appear, disappear, or invert depending on macro conditions.
There is no stop loss or risk management included by default, so the strategy reflects raw timing-based performance.
VB-MainLiteVB-MainLite – v1.0 Initial Release
Overview
VB-MainLite is a consolidated market-structure and execution framework designed to streamline decision-making into a single chart-level view. The script combines multi-timeframe trend, volatility, volume, and liquidity signals into one cohesive visual layer, reducing indicator clutter while preserving depth of information for active traders.
Core Architecture
Trend Backbone – EMA 200
Dedicated EMA 200 acts as the primary trend filter and higher-timeframe bias reference.
Serves as the “spine” of the system for contextualizing all secondary signals (swings, reversals, volume events, etc.).
Custom MA Suite (Envelope Ready)
Four configurable moving averages with flexible source, length, and smoothing.
Default configuration (preset idea: “8/89 Envelope”):
MA #1: EMA 8 on high
MA #2: EMA 8 on low
MA #3: EMA 89 on high
MA #4: EMA 89 on low
All four are disabled by default to keep the chart minimal. Users can toggle them on from the Custom MAs group for envelope or cloud-style configurations.
Nadaraya–Watson Smoother (Swing Framework)
Gaussian-kernel Nadaraya–Watson regression applied to price (hl2) to build a smooth synthetic curve.
Two layers of functionality:
Swing labels (▲ / ▼) at inflection points in the smoothed curve.
Optional curve line that visually tracks the turning structure over the last ~500 bars.
Designed to surface early swing potential before standard MAs react.
Hull Moving Average (Trend Overlay)
Optional Hull MA (HMA) for faster trend visualization.
Color-coded by slope (buy/sell bias).
Default: off to prevent overloading the chart; can be enabled under Hull MA settings.
Momentum, Exhaustion & Pattern Engine
CCI-Based Bar Coloring
CCI applied to close with configurable thresholds.
Overbought / oversold CCI zones map directly into candle coloring to visually highlight short-term momentum extremes.
RSI Top / Bottom Exhaustion Finder
RSI logic applied separately to high-driven (tops) and low-driven (bottoms) sequences.
Plots:
Top arrows where high-side RSI stretches into high-risk territory.
Bottom arrows where low-side RSI indicates exhaustion on the downside.
Useful as confluence around the Nadaraya swing turns and EMA 200 regime.
Engulfing + MA Trend Engine (“Fat Bull / Fat Bear”)
Detects bullish and bearish engulfing patterns, then combines them with MA trend cross logic.
Only when both pattern and MA regime align does the engine flag:
Fat Bull (Engulf + MA aligned long)
Fat Bear (Engulf + MA aligned short)
Candles are marked via conditional barcolor to highlight strong, structured shifts in control.
Fat Finger Detection (Wick Spikes / Stop Runs)
Identifies abnormal wick extensions relative to the prior bar’s body range with configurable tolerance.
Supports detection of potential liquidity grabs, stop runs, or “excess” that may precede reversals or mean-reversion behavior.
Volume & Liquidity Intelligence
Bull Snort (Aggressive Buy Spikes)
Flags events where:
Volume is significantly above the 50-period average, and
Price closes in the upper portion of the bar and above prior close.
Plots a labeled marker below the bar to indicate aggressive upside initiative by buyers.
Pocket Pivots (Accumulation Flags)
Compares current volume vs prior 10 sessions with a filter on prior “up” days.
Highlights pocket pivot days where current green candle volume outclasses recent down-day volumes, suggesting stealth accumulation.
Delta Volume Core (Directional Volume by Price)
Internal volume-by-price style engine over a user-defined lookback.
Splits volume into up-close and down-close buckets across dynamic price bins.
Feeds into S&R and ICT zone logic to quantify where buying vs selling pressure built up.
Structural Context: S&R and ICT Zones
S&R Power Channel
Computes local high/low band over a configurable lookback window.
Renders:
Upper and lower S&R channel lines.
Shaded support / resistance zones using boxes.
Adds Buy Power / Sell Power metrics based on the ratio of up vs down bars inside the window, displayed directly in the zone overlays.
Drops ◈ markers where price interacts dynamically with the top or bottom band, highlighting reaction points.
ICT-Style Premium / Discount & Macro Zones
Two tiered structures:
Local Premium / Discount zones over a shorter SR window.
Macro Premium / Discount zones over a longer macro window.
Each zone:
Uses underlying directional volume to annotate accumulation vs distribution bias.
Provides Delta Volume Bias shading in the mid-band region, visually encoding whether local power flows are net-buying or net-selling.
Enables traders to quickly see whether current trade location is in a local/macro discount or premium context while still respecting volume profile.
Positioning Intelligence: PCD (Stocks)
Position Cost Distribution (PCD) – Stocks Only
Available for stock symbols on intraday up to daily timeframe (≤ 1D).
Uses:
TOTAL_SHARES_OUTSTANDING fundamentals,
Daily OHLCV snapshot, and
A bucketed distribution engine
to approximate cost basis distribution across price.
Outputs:
Horizontal “PCD bars” to the right of current price, density-scaled by estimated share concentration.
Color-coding by profitability relative to current price (profitable vs unprofitable positions).
Labels for:
Current price
Average cost
Profit ratio (share % below current price)
90% cost range
70% cost range
Range overlap as a measure of clustering / concentration.
Multi-Timeframe Trend: Two-Pole Gaussian Dashboard
Two-Pole Gaussian Filter (Line + Cloud)
Smooths a user-selected source (default: close) using a two-pole Gaussian filter with tunable alpha.
Plots:
A thin Gaussian trend line, and
A thick Gaussian “cloud” line with transparency, colored by slope vs past (offsetG).
Functions as a responsive trend backbone that is more sensitive than EMA 200 but less noisy than raw price.
Multi-Timeframe Gaussian Dashboard
Evaluates Gaussian trend direction across up to six timeframes (e.g., 1H / 2H / 4H / Daily / Weekly).
Renders a compact bottom-right table:
Header: symbol + overall bias arrow (up / down) based on average trend alignment.
Row of colored cells per timeframe (green for uptrend, magenta for downtrend) with human-readable TF labels (e.g., “60M”, “4H”, “1D”).
Gives an immediate read on whether intraday, swing, and higher-timeframe flows are aligned or fragmented.
Default Configuration & Usage Guidance
Default state after adding the script:
Enabled by default:
EMA 200 trend backbone
Nadaraya–Watson swing labels and curve
CCI bar coloring
RSI top/bottom arrows
Fat Bull / Fat Bear engine
Bull Snort & Pocket Pivots
S&R Power Channel
ICT Local + Macro zones
Two-pole Gaussian line + cloud + dashboard
PCD engine for stocks (auto-active where data is available)
Disabled by default (opt-in):
Custom MA suite (4x MAs, preset as EMA 8/8/89/89)
Hull MA overlay
How traders can use VB-MainLite in practice:
Use EMA 200 + Gaussian dashboard to define top-down directional bias and avoid trading directly against multi-TF trend.
Use Nadaraya swing labels, RSI exhaustion arrows, and CCI bar colors to time entries within that higher-timeframe bias.
Use Fat Bull / Fat Bear events as structured confirmation that both pattern and MA regime have flipped in the same direction.
Use Bull Snort, Pocket Pivots, and S&R / ICT zones to align execution with liquidity, volume, and location (premium vs discount).
On stocks, use PCD as a positioning map to understand trapped supply, support zones near crowded cost basis, and where profit-taking is likely.
EMA Market Structure [BOSWaves]EMA Market Structure - Trend-Driven Structural Mapping with Adaptive Swing Detection
Overview
The EMA Market Structure indicator provides an advanced framework for visualizing market structure through dynamically filtered trend and swing analysis.
Unlike conventional EMA overlays, which merely indicate average price direction, this model integrates trend acceleration, swing highs/lows, and break-of-structure (BOS) logic into a unified, visually intuitive display.
Each element adapts in real time to price movement, offering traders a living map of support, resistance, and trend bias that reacts fluidly to market momentum.
The result is a comprehensive, trend-aware representation of price structure.
EMA slope and acceleration guide trend perception, while swing points identify key inflection zones.
Breaks of prior highs or lows are highlighted with visual BOS labels and stop-loss projections, giving traders actionable context for continuation or reversal setups.
Unlike static lines or simple moving averages, the EMA Market Structure indicator fuses dynamic trend analysis with structural awareness to provide a clear picture of market bias and potential turning points.
Theoretical Foundation
The EMA Market Structure builds on principles of momentum filtering and structural analysis.
Standard moving averages track average price but ignore acceleration and context; this indicator captures both the directional slope of the EMA and its rate of change, providing a proxy for trend strength.
Simultaneously, swing detection identifies statistically significant highs and lows, while BOS logic flags decisive breaks in structure, aligned with trend direction.
At its core are three interacting components:
EMA Trend & Acceleration : Smooths price data while highlighting acceleration changes, producing gradient-driven color cues for trend momentum.
Swing Detection Engine : Identifies swing highs and lows over configurable bar lengths, ensuring key turning points are captured with minimal clutter.
Break-of-Structure Logic : Detects price breaches of previous swings and aligns them with EMA trend for actionable BOS signals, including projected stop-loss levels for tactical decision-making.
By integrating these elements, the system scales effectively across timeframes and assets, maintaining structural clarity while visualizing trend dynamics in real time. Traders receive both macro and micro perspectives of market movement, with clear cues for trend continuation or reversal.
How It Works
The EMA Market Structure indicator operates through layered processing stages:
EMA Slope & Acceleration : Calculates the EMA and its rate of change, normalizing via ATR and a smoothing function to produce gradient color coding. This allows instant visual identification of bullish or bearish momentum.
Swing Identification : Swing highs and lows are computed using configurable left/right bar lengths, filtered through a cool-off mechanism to prevent redundant signals and maintain chart clarity.
Structural Lines & Zones : Swing points are connected with lines, and shaded zones are drawn between successive highs/lows to highlight key support and resistance regions.
Break-of-Structure Detection : BOS events occur when price breaches a prior swing in alignment with the EMA trend. Bullish and bearish BOS signals include enhanced label effects and projected stop-loss lines and zones, providing immediate tactical reference.
Dynamic Background Mapping : The chart background adapts to EMA trend direction, reinforcing trend context with subtle visual cues.
Through these processes, the indicator creates a living, adaptive map of market structure that reflects both trend strength and swing-based inflection points.
Interpretation
The EMA Market Structure reframes market reading from simple trend following to structured awareness of price behavior:
Uptrend Phases : EMA is rising with positive acceleration, swings confirm higher lows, and BOS events occur above prior highs, signaling trend continuation.
Downtrend Phases : EMA slope is negative, swings form lower highs, and BOS events occur below prior lows, confirming bearish bias.
Trend Reversals : Flat or decelerating EMA with BOS failures may indicate impending structural change.
Critical Zones : Swing-based lines and shaded zones highlight areas where price may pause, reverse, or accelerate, providing high-probability decision points.
Visually, EMA color gradients, structural lines, and BOS labels combine to provide both statistical trend confirmation and actionable structural cues.
Strategy Integration
EMA Market Structure integrates seamlessly into trend-following and swing-based trading systems:
Trend Alignment : Confirm higher-timeframe EMA slope before entering continuation trades.
BOS Entry Triggers : Use BOS events aligned with EMA trend for tactical entries and stop placement.
Support/Resistance Mapping : Swing lines and zones help define areas for scaling, exits, or reversals.
Volatility Context : ATR-based smoothing and stop-loss buffers accommodate varying market volatility, ensuring robustness across conditions.
Multi-Timeframe Coordination : Combine higher-timeframe EMA trend and swings with lower-timeframe structural events for precision entries.
Technical Implementation Details
Core Engine : EMA slope and ATR-normalized acceleration for gradient-driven trend visualization.
Swing Framework : Pivot-based high/low detection with configurable bar lengths and cool-off intervals.
Structural Visualization : Lines, zones, and labels for high-fidelity mapping of support/resistance and BOS events.
BOS Engine : Detects structural breaks aligned with EMA trend, automatically plotting stop-loss lines and visual cues.
Performance Profile : Lightweight, optimized for real-time responsiveness across multiple timeframes.
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Ideal for intraday swing spotting and microstructure trend tracking.
15 - 60 min : Medium-range structural analysis and BOS-driven entries.
4H - Daily : Macro trend mapping and key swing-based support/resistance identification.
Suggested Configuration:
EMA Length : 50
Swing Length : 5
Swing Cooloff : 10 bars
BOS Cooloff : 15 bars
SL Buffer : 0.1%
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Performance Characteristics
High Effectiveness:
Trending markets with defined swings and structural consistency.
Markets where EMA slope and acceleration reliably indicate momentum changes.
Reduced Effectiveness:
Choppy or sideways markets with minimal swing definition.
Random walk assets lacking clear structural anchors.
Integration Guidelines
Confluence Framework : Combine with volume, momentum, or BOSWaves structural indicators
to validate entries.
Directional Control: Follow EMA slope and BOS alignment for high-conviction trades.
Risk Calibration: Use SL projections for disciplined exposure management.
Multi-Timeframe Synergy: Confirm higher-timeframe trend before executing lower-timeframe structural trades.
Disclaimer
The EMA Market Structure is a professional-grade trend and structure visualization tool. It is not predictive or guaranteed profitable; performance depends on parameter tuning, market regime, and disciplined execution. BOSWaves recommends using it as part of a comprehensive analytical stack integrating trend, liquidity, and structural context.
VB Sigma Smart Momentum IndicatorVB Sigma Smart Momentum Indicator (VBSSMI)
The VBSSMI provides a consolidated decision-support framework that surfaces market participation, trend integrity, and liquidity conditions in a single visual environment. The tool integrates four analytical modules: MCDX Flow Mapping, Donchian Regime Layers, Banker Flow Modeling, and Chop Zone Trend Classification. Together, these components convert raw price movement into an actionable interpretation of who is in control, whether momentum is durable, and what phase the instrument is currently cycling through.
How to Use the Indicator (Practical Workflow)
1. Start with Institutional / Banker Flow (Pink/Red/Yellow/Green Candles)
This is the primary signal layer. It tells you when high-capacity participants are increasing, reducing, or reversing risk.
Yellow Candle — Entry Bias
Indicates a potential institutional initiation when their trend metric crosses above their accumulation threshold.
Operational signal: instrument enters “monitor for entry” state.
Green Candle — Accumulation State
Fund-trend > bullbearline.
Operational signal: trend integrity improving; pullbacks are generally buyable.
White Candle — Distribution / Cooling
Fund-trend weakening but not broken.
Operational signal: tighten stops; momentum deteriorating.
Red Candle — Exit / Trend Failure
Fund-trend < bullbearline.
Operational signal: momentum regime invalidated; avoid long risk.
Blue Candle — Weak Rebound
A temporary uptick within broader weakness.
Operational signal: do not mistake this for a durable reversal.
2. Validate alignment with Flow Chips (Retail / Trader / Institutional)
These three flow columns (MCDX layers) answer: who is actually participating?
Retailer Flow (Locked Chips – Green)
High values imply retail conviction, often late-cycle.
Good for confirming trend strength, not timing entries.
Trader Zone Flow (Float Chips – Yellow)
When this spikes, volatility and tactical positioning increase.
Signal: strong short-term engagement, supports breakout/trend continuation.
Institutional Flow (Profitable Chips – Red/Pink)
This is the “true north” of momentum.
Rising values = institutions controlling price discovery.
Signal: long setups have statistical tailwind.
The operational guidance is straightforward:
Institutional Flow > Trader Flow > Retail Flow
is the healthiest configuration for sustainable upside momentum.
3. Confirm Breakout / Breakdown Conditions with Donchian Regime Columns
The vertical Donchian stack illustrates trend regime in a time-compressed format.
Bright Blue/Cyan
Structure expanding upward (breakout cluster).
Dark Purple/Red
Structure breaking downward (breakdown cluster).
Mixed Columns
Transitional or indecisive conditions.
Interpret it as a “momentum backdrop”:
If Donchian columns and Banker Flow candles disagree, avoid entries.
4. Consult the Chop Zone Strip Before Committing Capital
The Chop Zone uses EMA angle to determine whether the market is trending or congested.
Greens/Blues → Trend phase (favorable environment for continuation trades).
Yellows/Oranges/Reds → High noise probability; expect false signals.
Operationally:
Never enter breakout setups during yellow/orange/red chop.
5. Final Decision Framework (Checklist)
A long setup typically requires:
Green or Yellow Banker Flow Candle
Institutional Flow rising
Donchian columns in bullish regime colors
Chop Zone in a trend color (not red/yellow/orange)
A short setup is the exact inverse.
Recommended Use Cases
Momentum trading
Swing position building
Institutional-flow confirmation
Trend-filtering before deploying breakout systems
Screening for strong/weak symbols in multi-asset rotation strategies
