Williams Alligator Price vs Jaw StrategyWilliams Alligator using Price crossing over Jaw to go long and Price crossing under Jaw to close
Indicators and strategies
Swing High & Low MarkerMarks swing high and low candles
Swing high candle:
A candle whose high is higher than the highs of the candles immediately before and after it.
Swing low candle:
A candle whose low is lower than the lows of the candles immediately before and after it.
VWMA + ML RSI StrategyVWMA + ML RSI Strategy
This strategy combines the power of Volume-Weighted Moving Average (VWMA) with a Machine Learning-enhanced RSI to generate high-probability long entries.
✅ Buy Logic:
A buy signal is triggered when:
The candle closes above the VWMA
The ML RSI (smoothed using advanced moving averages) is above 60
If only one of the above conditions is met, the strategy waits for the second to confirm before entering.
❌ Sell Logic:
The position is closed when:
The candle closes below the VWMA, and
The ML RSI falls below 40
🎯 Risk Management:
Take Profit: 1.5% above entry
Stop Loss: 1.5% below entry
🤖 ML RSI Explanation:
The ML RSI is a refined version of the traditional RSI using smoothing techniques (like ALMA, EMA, etc.) to reduce noise and enhance responsiveness to price action. It helps filter out weak signals and improves trend confirmation.
🔧 Customization:
Adjustable VWMA length
Configurable ML RSI smoothing method, length, and ALMA sigma
Thresholds for entry/exit RSI levels
ATR Trend Color📌 ATR Trend Color — Visually clean trend-following tool based on adaptive ATR trailing stop
► Description
ATR Trend Color is a simple yet powerful indicator designed to visually identify and follow the market trend using an adaptive ATR-based trailing stop. Its main advantage lies in clarity — it uses just a single line that dynamically changes color based on trend direction:
✅ Blue line indicates price is above the trailing stop (bullish trend).
🔻 Black line indicates price is below the trailing stop (bearish trend).
This clean display allows for instant trend recognition and potential exit or reversal zones.
► How it works
The indicator uses the Average True Range (ATR) to calculate a dynamic trailing stop level. ATR measures volatility and adjusts the trailing line to match current market conditions:
When the price rises, the line moves up and acts as dynamic support.
When the price drops, the line moves down and acts as resistance.
This behavior makes it ideal for trend following and volatility-adjusted stop-loss placement.
► Key Features:
✅ Clean chart with just one ATR trailing line
✅ Dynamic color changes in real-time
✅ Great for trend confirmation and management
✅ Customizable ATR period and multiplier
✅ Step line with diamonds for high visual clarity
► How to use
Add the indicator to your chart.
Adjust ATR period and multiplier to your strategy (default: ATR 7 / multiplier 3.1).
Follow the line color:
Blue: Bullish trend — may signal to stay in long positions.
Black: Bearish trend — may suggest exit or short entries.
► Originality
Unlike typical ATR trailing stop indicators that display two lines or static colors, ATR Trend Color simplifies visualization by using a single smart line with real-time visual feedback on trend direction.
Additionally, it uses the “Step line with diamonds” display mode to enhance readability in fast or noisy markets.
DAX Setup ScreenerPine Script – Setup Screener
This code detects:
Range trading zone
Breakout long & breakdown short signals
With visual overlay
Use it like this:
Adjust rangeHigh, rangeLow, and breakoutBuffer
Enabled: Draws signals on the live chart
Candle Color Based on 12 month SMAThis indicator is designed to be used on a 1M (monthly) chart. It:
• Calculates the 12-month Simple Moving Average (SMA).
• Colors candles green if the monthly close is above the SMA.
• Colors candles red if the monthly close is below the SMA.
• Plots the 12-month SMA as a cyan stair-step line for clear visual tracking.
Renko UT Bot Strategy v6 - ADX FilterDescription:
This script implements a Renko-based trailing stop strategy using the UT Bot method, now enhanced with an optional ADX and DI+/- filter to help avoid choppy, low-momentum market conditions. Trades are triggered only when price and EMA cross the adaptive trailing stop and ADX/DI conditions are also met.
USE:
Start the indicator on a Renko chart and optimize settings for prefered choosen chart
Key Features:
Adaptive ATR trailing stop based on Renko logic
EMA/Trailing Stop crossovers for entries
Adjustable ADX and DI+/- filter (no signals if conditions aren’t met)
Visual stop line and trade labels on the chart
Customizable inputs for ATR, EMA, and filter levels
Disclaimer:
This strategy is provided for educational and research purposes only. It has not been tested in live trading or with real money. The past performance of this script does not guarantee future results. Trading involves substantial risk, and you can lose all or more of your investment.
Before considering any real-money use, please test the strategy thoroughly on a demo account or in TradingView’s paper trading environment.
This script is not financial advice. Consult with a licensed financial advisor before making trading decisions.
Author PDK1977
Candlesticks MTF + Prev Daily RangeCandlesticks MTF + Previous Daily Range
This TradingView script displays higher timeframe candlesticks on a lower timeframe chart and optionally projects the previous day's high, low, and close levels. The user can define the timeframe from which the candles are taken, typically a higher timeframe like daily. A specified number of historical candles are drawn on the chart using boxes for candle bodies and lines for wicks. The color of each candle indicates its direction: bullish candles use a "long" color (default teal), and bearish candles use a "short" color (default red).
An optional feature allows the projection of the previous daily range. When enabled, the script draws horizontal lines extending across the chart to mark the high, low, and close of the second most recent higher timeframe candle. These lines are color-coded for easy visual identification and can help identify potential support and resistance zones.
All visual elements, including the number of candles, their width, and the colors of candles and projection lines, can be customized through the settings. The script dynamically updates in real time, clearing outdated boxes and lines to avoid visual clutter. This makes it a useful tool for traders who want to incorporate multi-timeframe analysis and key price levels directly into their intraday charting.
trade bang mongIndicator Name:
🔺 Key Swing Zones Based on Breakouts (Line-Based)
Short Description:
This indicator automatically detects and visualizes key swing highs and lows based on the principle of candle close breaking the wick of the previous candle, then classifies the current market trend as uptrend, downtrend, or neutral. It draws horizontal lines representing key zones and adds visual labels to help traders analyze market structure more clearly.
Dynamic Gap Probability ToolDynamic Gap Probability Tool measures the percentage gap between price and a chosen moving average, then analyzes your chart history to estimate the likelihood of the next candle moving up or down. It dynamically adjusts its sample size to ensure statistical robustness while focusing on the exact deviation level.
Originality and Value:
• Combines gap-based analysis with dynamic sample aggregation to balance precision and reliability.
• Automatically extends the sample when exact matches are scarce, avoiding misleading signals on rare extreme moves.
• Provides real “next-candle” probabilities based on historical occurrences rather than fixed thresholds or untested heuristics.
• Adds value by giving traders an evidence-based edge: you see how similar past deviations actually played out.
How It Works:
1. Calculate gap = (close – moving average) / moving average * 100.
2. Round the absolute gap to nearest percent (X%).
3. Count historical bars where gap ≥ X% above or ≤ –X% below.
4. If exact X% count is below the minimum occurrences threshold, include gaps at X+1%, X+2%, etc., until threshold is reached.
5. Compute “next-candle” green vs. red probabilities from the aggregated sample.
6. Display current gap, sample size, green probability, and red probability in a table.
Inputs:
• Moving Average Type (SMA, EMA, WMA, VWMA, HMA, SMMA, TMA)
• Moving Average Period (default 200)
• Minimum Occurrences Threshold (default 50)
• Table position and styling options
Examples:
• If price is 3% above the 200-period SMA and 120 occurrences ≥3% are found, with 84 green next candles (70%) and 36 red (30%), the script displays “3% | 120 | 70% green | 30% red.”
• If price is 8% below the SMA but only 20 exact matches exist, the script will include 9% and 10% gaps until it reaches 50 samples, then calculate probabilities from that broader set.
Why It’s Useful:
• Mean-reversion traders see green-probability signals at extreme overbought or oversold levels.
• Trend-followers identify continuation likelihood when red probability is high.
• Risk managers gauge reliability by inspecting sample size before acting on any signal.
Limitations:
• Historical probabilities do not guarantee future performance.
• Results depend on timeframe and symbol, backtest with your data before trading.
• Use realistic slippage and commission when overlaying on strategy scripts.
Gold_Bulls | TP1+TP2 + Trailing SL + Clean Entry//@version=5
indicator("Gold_Bulls | TP1+TP2 + Trailing SL + Clean Entry", overlay=true)
// === INPUTS ===
lookbackDays = input.int(4, "Lookback Days (5m candles)")
pivotLen = input.int(5, "Pivot Strength")
rr1 = input.float(1.0, "TP1 Risk:Reward")
rr2 = input.float(1.5, "TP2 Risk:Reward")
trailATRmult = input.float(1.2, "Trailing SL ATR Multiplier")
// === TIME FILTER ===
inLastDays = time > (timenow - lookbackDays * 24 * 60 * 60 * 1000)
// === PIVOT S/R ===
pivotHigh = ta.pivothigh(high, pivotLen, pivotLen)
pivotLow = ta.pivotlow(low, pivotLen, pivotLen)
resistance = not na(pivotHigh) and inLastDays ? pivotHigh : na
support = not na(pivotLow) and inLastDays ? pivotLow : na
plotshape(resistance, location=location.abovebar, style=shape.triangledown, color=color.purple, size=size.tiny)
plotshape(support, location=location.belowbar, style=shape.triangleup, color=color.blue, size=size.tiny)
// === TRACK LAST LEVEL ===
var float lastSupport = na
var float lastResistance = na
if not na(support)
lastSupport := support
if not na(resistance)
lastResistance := resistance
// === ATR for Trailing SL ===
atr = ta.atr(14)
// === VARIABLES ===
var float entryBuy = na
var float slBuy = na
var float tp1Buy = na
var float tp2Buy = na
var float trailBuy = na
var float entrySell = na
var float slSell = na
var float tp1Sell = na
var float tp2Sell = na
var float trailSell = na
// === CONDITIONAL ENTRY ===
buyCond = na(entryBuy) and close > lastResistance and ta.barssince(close > lastResistance) == 0
sellCond = na(entrySell) and close < lastSupport and ta.barssince(close < lastSupport) == 0
// === BUY ENTRY ===
if buyCond
entryBuy := close
slBuy := ta.lowest(low, 6)
risk = entryBuy - slBuy
tp1Buy := entryBuy + risk * rr1
tp2Buy := entryBuy + risk * rr2
trailBuy := entryBuy - atr * trailATRmult
if not na(entryBuy)
trailBuy := math.max(trailBuy, close - atr * trailATRmult)
if close < trailBuy or close > tp2Buy
entryBuy := na
slBuy := na
tp1Buy := na
tp2Buy := na
trailBuy := na
// === SELL ENTRY ===
if sellCond
entrySell := close
slSell := ta.lowest(low, 6) // as per your request
risk = entrySell - slSell
tp1Sell := entrySell - risk * rr1
tp2Sell := entrySell - risk * rr2
trailSell := entrySell + atr * trailATRmult
if not na(entrySell)
trailSell := math.min(trailSell, close + atr * trailATRmult)
if close > trailSell or close < tp2Sell
entrySell := na
slSell := na
tp1Sell := na
tp2Sell := na
trailSell := na
// === PLOTS ===
plotshape(buyCond, location=location.belowbar, style=shape.labelup, color=color.green, text="BUY")
plot(entryBuy, title="Buy Entry", color=color.green)
plot(slBuy, title="Buy SL", color=color.orange)
plot(tp1Buy, title="Buy TP1", color=color.lime)
plot(tp2Buy, title="Buy TP2", color=color.teal)
plot(trailBuy, title="Buy Trailing SL", color=color.yellow)
plotshape(sellCond, location=location.abovebar, style=shape.labeldown, color=color.red, text="SELL")
plot(entrySell, title="Sell Entry", color=color.red)
plot(slSell, title="Sell SL", color=color.orange)
plot(tp1Sell, title="Sell TP1", color=color.green)
plot(tp2Sell, title="Sell TP2", color=color.teal)
plot(trailSell, title="Sell Trailing SL", color=color.yellow)
// === ALERTS ===
alertcondition(buyCond, title="BUY Signal", message="📈 BUY Signal Triggered!")
alertcondition(sellCond, title="SELL Signal", message="📉 SELL Signal Triggered!")
TFlab Trailing Stop StrategyThe trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward.
Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision.
SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading.
The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management.
A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making.
Micro Trend Start Signal (Up & Down)To compliment fast trends in the market, this strategy should be tried and tested on the 1 minute strategy. The 2nd alerts work also very well.
User-Defined Volume Average ComparisonThe User-Defined Volume Average Comparison indicator empowers traders to analyze volume trends by comparing short-term and long-term volume moving averages. With customizable periods, visual cues, and built-in alerts, it’s a versatile tool for identifying volume-driven market shifts across any timeframe, ideal for stocks, forex, crypto, and more.Key Features: Customizable Periods: Set short and long periods (in bars) to match your trading strategy.
Conditional Highlighting:
Green Background: Short-period volume average ≥ long-period volume average, signaling strong short-term volume.
Red Background: Short-period volume average < long-period volume average / 2, indicating low short-term volume.
Optional Labels: Toggle labels to display conditions on the chart (default: off).
Alerts: Receive notifications for key conditions: “Short ≥ Long Alert” for high volume periods.
“Short < Long/2 Alert” for low volume periods.
Visualized Averages: Plots short-period (blue) and long-period (red) volume moving averages for easy analysis.
How It Works:
The indicator calculates the simple moving average (SMA) of volume over user-defined short and long periods, then compares them: A green background and alert trigger when the short-period average meets or exceeds the long-period average, suggesting increased volume activity.
A red background and alert trigger when the short-period average falls below half of the long-period average, indicating reduced volume.
Labels (if enabled) display “Short ≥ Long” or “Short < Long/2” for clarity.
Settings: Short Period (Bars): Number of bars for the short-term volume average (default: 3).
Long Period (Bars): Number of bars for the long-term volume average (default: 50).
Show Labels: Enable or disable condition labels (default: off).
Use Cases: Trend Confirmation: Use green alerts to confirm high volume during breakouts or trend continuations.
Divergence Detection: Identify low volume periods with red alerts to spot potential reversals or weak trends.
Multi-Timeframe Analysis: Apply on any timeframe (e.g., 4H, 1D), with periods based on bars (e.g., 3 bars on 4H = 12 hours).
Notes: Periods are based on the chart’s timeframe (bars). For shorter timeframes, consider increasing period values for more significant results.
Set alerts to “Once Per Bar Close” for reliable notifications.
Combine with price-based indicators to enhance trading decisions.
Why Use This Indicator?
This indicator offers a flexible, alert-driven approach to volume analysis, helping traders of all levels make informed decisions. Its intuitive design and customizable settings make it a valuable addition to any trading setup.
Sanuja nuwanThe Zero Fear Indicator is a custom-built trading tool designed for confident and precise entries. Powered by real-time market structure, volume pressure, and volatility logic, it filters out noise and shows clear buy/sell signals with zero hesitation. Perfect for both beginners and experienced traders looking to trade without fear.
Swing Structure [HH HL LH LL + 😎 + 👻]Tracks real-time swing structure (HH, HL, LH, LL) using confirmed pivot points. Shows ghost 👻 and cool 😎 emojis at key higher low setups. Great for identifying breakout retests and trend continuation zones. No repaint.
Adaptive Causal Wavelet Trend FilterThe Adaptive Causal Wavelet Trend Filter is a technical indicator implementing causal approximations of wavelet transform properties for better trend detection with adaptive volatility response.
The Adaptive Causal Wavelet Trend Filter (ACWTF) applies mathematical principles derived from wavelet analysis to financial time series, providing robust trend identification with minimal lag. Unlike conventional moving averages, it preserves significant price movements while filtering market noise through signal processing that i describe below.
I was inspired to build this indicator after reading " Wavelet-Based Trend Identification in Financial Time Series " by In, F., & Kim, S. 2013 and reading about Mexican Hat wavelet filters.
The ACWTF maintains optimal performance across varying market regimes without requiring parameter adjustments by adapting filter characteristics to current volatility conditions.
Mathematical Foundation
Inspired by the Mexican Hat wavelet (Ricker wavelet), this indicator implements causal approximations of wavelet filters optimized for real-time financial analysis. The multi-resolution approach identifies features at different scales and the adaptive component dynamically adjusts filtering characteristics based on local volatility measurements.
Key mathematical properties include:
Non-linear frequency response adaptation
Edge-preserving signal extraction
Scale-space analysis through dual filter implementation
Volatility-dependent coefficient adjustment, which I love
Filter Methods
Adaptive: Implements a volatility-weighted combination of multiple filter types to optimize the time-frequency resolution trade-off
Hull: Provides a causal approximation of wavelet edge detection properties with forward-projection characteristics
VWMA: Incorporates volume information into the filtering process for enhanced signal detection
EMA Cascade: Creates a multi-pole filter structure that approximates certain wavelet scaling properties
Suggestion: try all as they will provide slightly different signals. Try also different time-frames.
Practical Applications
Trend Direction Identification: Clear visual trend direction with reduced noise and lag
Regime Change Detection: Early identification of significant trend reversals
Market Condition Analysis: Integrated volatility metrics provide context for current market behavior
Multi-timeframe Confirmation: Alignment between primary and secondary filters offers additional confirmation
Entry/Exit Timing: Filter crossovers and trend changes provide potential trading signals
The comprehensive information panel provides:
Current filter method and trend state
Trend alignment between timeframes
Real-time volatility assessment
Price position relative to filter
Overall trading bias based on multiple factors
Implementation Notes
Log returns option provides improved statistical properties for financial time series
Primary and secondary filter lengths can be adjusted to optimize for specific instruments and timeframes
The indicator performs particularly well during trend transitions and regime changes
The indicator reduces the need for using additional indicators to check trend reversion
Market Structure by HorizonAImarket structure with BOS and CHOCH. It has full accuracy. Identify structure and trade accordingly.
Vùng đỉnh đáy chính theo phá vỡ (dùng line)Indicator Name:
🔺 Key Swing Zones Based on Breakouts (Line-Based)
Short Description:
This indicator automatically detects and visualizes key swing highs and lows based on the principle of candle close breaking the wick of the previous candle, then classifies the current market trend as uptrend, downtrend, or neutral. It draws horizontal lines representing key zones and adds visual labels to help traders analyze market structure more clearly.
How It Works:
🔹 Reversal Signal Logic:
In an uptrend, if a candle closes below the previous candle's low, it marks a swing low.
In a downtrend, if a candle closes above the previous candle's high, it marks a swing high.
🔹 Structure Break Detection:
Price breaking above a key high → confirms an uptrend.
Price breaking below a key low → confirms a downtrend.
If price breaks a zone but doesn't form a new high/low → switches to neutral.
🔹 Visual Display:
Draws two horizontal lines: one at the key high, one at the key low.
Adds labels "Key High" or "Key Low" at the breakout points.
Zone color representation:
🟢 Green = Uptrend
🔴 Red = Downtrend
⚪ White = Neutral
BullFinder_15M_OBV_RSI_MFI📊 BullFinder_15M_OBV_RSI_MFI
15-Minute BTC/USDT Long-Only Strategy Powered by OBV, NetVolume, RSI and MFI
Designed for high-frequency bullish opportunities, this strategy combines volume-confirmed momentum with dynamic trailing stop exits. Ideal for breakout traders seeking consistency over noise.
🔍 Indicators Used:
OBV + Net Volume: Volume divergence & pressure detection
RSI + MFI: Momentum and liquidity filters
EMA21: Baseline trend confirmation
Advanced Trailing Stop: Dynamic trigger + offset + hard loss control
📅 Backtest Summary (Last 12 Months | BTC/USDT | 15m TF):
Total Trades: 381
Win Rate: 83.20%
Avg. PnL per Trade: +746.18 USDT
Avg. Winner: 7,097 USDT
Avg. Loser: -30,713 USDT
Best Trade: 65,654 USDT
Profit Factor: 0.231
✅ Alerts Available
To automate entries or get Telegram alerts, set an alarm with the message:
📢 "BullFinder: Long Entry Triggered"
K Bands v2.2K Bands v2 - Settings Breakdown (Timeframe Agnostic)
K Bands v2 is an adaptive volatility envelope tool designed for flexibility across different trading
styles and timeframes.
The settings below allow complete control over how the bands are constructed, smoothed, and how
they respond to market volatility.
1. Upstream MA Type
Controls the core smoothing applied to price before calculating the bands.
Options:
- EMA: Fast, responsive, reacts quickly to price changes.
- SMA: Classic moving average, slower but provides stability.
- Hull: Ultra smooth, reduces noise significantly but may react differently to choppy conditions.
- GeoMean: Geometric mean smoothing, creates a unique, slightly smoother line.
- SMMA: Wilder-style smoothing, balances noise reduction and responsiveness.
- WMA: Weighted Moving Average, emphasizes recent price action for sharper responsiveness.
2. Smoothing Length
Lookback period for the upstream moving average.
- Lower values: Faster reaction, captures short-term shifts.
- Higher values: Smoother trend depiction, filters out noise.
3. Multiplier
Determines the width of the bands relative to calculated volatility.
- Lower multiplier: Tighter bands, more signals, but increased false breakouts.
- Higher multiplier: Wider bands, fewer false signals, more conservative.
4. Downstream MA Type
Applies final smoothing to the band plots after initial calculation.
Same options as Upstream MA.
5. Downstream Smoothing Length
Lookback period for downstream smoothing.
- Lower: More responsive bands.
- Higher: Smoother, visually cleaner bands.
6. Band Width Source
Selects the method used to calculate band width based on market volatility.
Options:
- ATR (Average True Range): Smooth, stable bands based on price range expansion.
- Stdev (Standard Deviation): More reactive bands highlighting short-term volatility spikes.
7. ATR Smoothing Type
Controls how the ATR or Stdev value is smoothed before applying to band width.
Options:
- Wilder: Classic, stable smoothing.
- SMA: Simple moving average smoothing.
- EMA: Faster, more reactive smoothing.
- Hull: Ultra-smooth, noise-reducing smoothing.
- GeoMean: Geometric mean smoothing.
8. ATR Length
Lookback period for smoothing the volatility measurement (ATR or Stdev).
- Lower: More reactive bands, captures quick shifts.
- Higher: Smoother, more stable bands.
9. Dynamic Multiplier Based on Volatility
Allows the band multiplier to adapt automatically to changes in market volatility.
- ON: Bands expand during high volatility and contract during low volatility.
- OFF: Bands remain fixed based on the set multiplier.
10. Dynamic Multiplier Sensitivity
Controls how aggressively the dynamic multiplier responds to volatility changes.
- Lower values: Subtle adjustments.
- Higher values: More aggressive band expansion/contraction.
K Bands v2 is designed to be adaptable across any market or timeframe, helping visualize price
structure, trend, and volatility behavior.
Buy/Sell Volume + Avg LinesBuy/Sell volume + avg line = avg line * n
set n value
you can set alert by using avg line * n to find pumping coins