PDH/PDL Sweep & Rejection - sudoPDH/PDL Sweep + Rejection
This indicator identifies classic liquidity sweeps of the previous day's high or low, then confirms whether price rejected that level with force. It is built to highlight moments when the market takes liquidity and immediately snaps back in the opposite direction, a behavior often linked to failed breakouts, engineered stops, or clean reversals. The tool marks these events directly on the chart so you can see them without manually watching the daily levels.
What it detects
The indicator focuses on two events:
PDH sweep and rejection
Price breaks above the previous day's high, overshoots the level by a meaningful amount, and then closes back below the high.
PDL sweep and rejection
Price breaks below the previous day's low, overshoots, and then closes back above the low.
These are structural liquidity events, not random wicks. The script checks for enough overshoot and strong bar range to confirm it was a genuine stop grab rather than noise.
How it works
The indicator evaluates each bar using the following logic:
1. Previous day levels
It pulls yesterday's high and low directly from the daily timeframe. These act as the PDH and PDL reference points for intraday trading.
2. Overshoot measurement
After breaking the level, price must push far enough beyond it to qualify as a sweep. Instead of using arbitrary pips, the required overshoot is scaled relative to ATR. This keeps the logic stable across different assets and volatility conditions.
3. Range confirmation
The bar must be larger than normal compared to ATR. This ensures the sweep happened with momentum and not because of small, choppy price movement.
4. Rejection close
A valid signal only prints if price closes back inside the previous day's range.
For a PDH sweep, the bar must close below PDH.
For a PDL sweep, the bar must close above PDL.
This confirms a failed breakout and a rejection.
What gets placed on the chart
Red downward triangle above the bar: Previous Day High sweep and rejection
Lime upward triangle below the bar: Previous Day Low sweep and rejection
The markers appear exactly on the bar where the sweep and rejection occurred.
How traders can use this
Identify potential reversals
Sweeps often occur when algorithms target liquidity pools. When followed by a strong rejection, the market may be preparing for a reversal or rotation.
Avoid chasing breakouts
A clear sweep warns that a breakout attempt failed. This can prevent traders from entering at the worst possible location.
Time entries at extremes
The markers help you see where the market grabbed stops and immediately turned. These areas can become high quality entry zones in both trend continuation and countertrend setups.
Support liquidity based models
The indicator aligns naturally with trading frameworks that consider liquidity, displacement, failed breaks, and microstructure shifts.
Add confidence to confluence-based setups
Combine sweeps with displacement, FVGs, or higher timeframe levels to refine entry timing.
Why this indicator is helpful
It automates a pattern that traders often identify manually. Sweeps are easy to miss in fast markets, and this tool eliminates the need to constantly monitor daily levels. By marking only the events that show overshoot plus rejection plus significant range, it filters out the weak or false signals and leaves only meaningful liquidity events.
インジケーターとストラテジー
NEXFEL - Adaptive MACD Flow PRONEXFEL – Adaptive MACD Flow PRO is a next-generation market analysis engine built on an enhanced Adaptive MACD core.
It combines R² correlation, multi-timeframe sentiment, volatility modeling, trend structure and regime detection to deliver highly refined BUY/SELL signals directly on the chart.
With dynamic target projection, confidence scoring, flow-based candle coloring and a real-time analytics panel, this tool provides a clear and intelligent read of momentum shifts before they fully develop — ideal for precision scalping and high-performance decision-making.
Optionsmith Daily SPX Direction ModelThis indicator, published by Optionsmith LLC, is used on the DAILY chart only, to gauge whether there is an edge to the bullish side or bearish side for the day. It uses multiple factors, such as where the price closed the previous day compared to the range for that day, as well as whether there is a large gap on open, and factoring in the general upward drift of SPX over time.
This indicator is published as is for educational use and with no guarantees on its reliability.
SuperTrend Fusion — Trend + Momentum + Volatility FilterSuperTrend Fusion — Trend + Momentum + Volatility Filter
SuperTrend Fusion — ATP is an original, multi-factor trend-filtering tool that enhances the classic SuperTrend by combining three market dimensions in one unified model:
1. Trend direction (SuperTrend)
Provides the base trend structure using ATR-based volatility bands.
2. Momentum confirmation (Average Force – adapted)
An adapted version of an open-source “Average Force” concept published on TradingView by racer8.
This component measures where closing price sits relative to recent highs/lows, smoothed to capture directional pressure.
3. Market condition filtering (Choppiness Index)
Filters out sideways, non-trending zones where SuperTrend alone typically produces false flips.
Together, these components create a cleaner, more selective system that focuses on higher-quality SuperTrend reversals, avoiding the most common whipsaws that occur during low-momentum or high-choppiness periods.
🔍 How it Works
A long signal occurs when:
- SuperTrend flips from downtrend to uptrend
- Momentum (AF) is positive (optional filter)
- The market is trending and not excessively choppy (optional filter)
A short signal triggers under the symmetrical conditions.
Filtered signals are visually marked with subtle “X” markers so traders can understand when a raw SuperTrend flip was rejected by the filters.
The indicator also includes:
Enhanced styling for better visibility
Colored bars during valid signals
Optional background highlight during choppy periods
🎯 What This Indicator Is Designed For
This tool aims to:
- Improve the quality of SuperTrend entries
- Remove many low-probability signals
- Help traders visually identify when the market has the momentum and structure required for cleaner trend continuation
It is not intended to predict markets or guarantee accuracy; rather, it provides structure and clarity for decision-making based on technical rules.
⚙️ Inputs
- ATR Length & Factor (SuperTrend)
- Average Force Period & Smoothing
- Choppiness Length & Threshold
- Option to enable/disable each filter individually
📘 Credits
This script includes an adapted version of an open-source “Average Force” function originally published on TradingView by its author, racer8.
SuperTrend and Choppiness Index components are derived from classical, public-domain formulas.
📌 Important Notes
This indicator is not a strategy and does not guarantee performance.
Signals are based on historical calculations only and do not use lookahead.
Past performance does not guarantee future results.
Always test different assets and timeframes before using in live conditions.
👍 Recommended Usage
For a clean experience:
- Use on standard candlestick charts
- Avoid non-standard chart types (Renko, Heikin Ashi, Kagi, Range)
- Combine with your own risk management and trade planning
Z-score RegimeThis indicator compares equity behaviour and credit behaviour by converting both into z-scores. It calculates the z-score of SPX and the z-score of a credit proxy based on the HYG divided by LQD ratio.
SPX z-score shows how far the S&P 500 is from its rolling average.
Credit z-score shows how risk-seeking or risk-averse credit markets are by comparing high-yield bonds to investment-grade bonds.
When both z-scores move together, the market is aligned in either risk-on or risk-off conditions.
When SPX z-score is strong but credit z-score is weak, this may signal equity strength that is not supported by credit markets.
When credit z-score is stronger than SPX z-score, credit markets may be leading risk appetite.
The indicator plots the two z-scores as simple lines for clear regime comparison.
Algoticks.in: RSI StrategyRSI Strategy - User Guide
Overview
This is a Relative Strength Index (RSI) strategy that generates trading signals based on overbought and oversold levels. It integrates with Algoticks.in API for automated trading on Delta Exchange.
Strategy Logic
Long Signal: When RSI crosses above the Oversold level (Mean Reversion / Dip Buy)
Short Signal: When RSI crosses below the Overbought level (Mean Reversion / Top Sell)
Automatically closes opposite positions before entering new ones
Quick Setup
1. Add to TradingView
Open TradingView and go to the chart
Click "Pine Editor" at the bottom
Paste the script code
Click "Add to Chart"
2. Configure Strategy Parameters
Strategy Settings
RSI Length (default: 14): The lookback period for RSI calculation
Overbought Level (default: 70): Level above which the asset is considered overbought
Oversold Level (default: 30): Level below which the asset is considered oversold
General API Settings
Paper Trading : Enable for testing without real money
Signal Type : Choose "Trading Signal" (default) for tracking
Exchange : DELTA (Delta Exchange)
Segment :
futures - Perpetual contracts
options - Call/Put options
spot - Spot trading
Order Settings: Basic
Quantity : Number of contracts (e.g., 1, 0.5, 2)
Validity :
GTC - Good Till Cancelled
IOC - Immediate or Cancel
FOK - Fill or Kill
DAY - Day order
Product : cross_margin or isolated_margin
Order Settings: Entry Type
Choose how orders are executed:
Market Order : Immediate fill at best price
Limit Order : Fill at specified price or better
Stop Market : Triggers at stop price, then market order
Stop Limit : Triggers at stop price, then limit order
Entry Prices (for Limit/Stop orders)
Limit Price:
Price : The value to use
Type : Last Price / Mark Price / Index Price
Mode :
Absolute - Exact price (e.g., 65000)
Relative - Offset from entry price
% Checkbox : If checked, relative uses percentage; if unchecked, uses points
Example:
Absolute: 65000 → Order at exactly 65000
Relative 1% (checked): Entry ± 1% of entry price
Relative 100 (unchecked): Entry ± 100 points
Trigger Price: Same logic as Limit Price, used for Stop orders
Exit / Bracket Prices (SL/TP)
Stop Loss (SL):
Type : Price type to monitor (Mark Price recommended)
Mode : Absolute or Relative
% : Percentage or points
SL : Stop loss value (e.g., 2 for 2%)
Trig : Optional trigger price (creates Stop-Limit SL)
Take Profit (TP): Same structure as SL
Example:
Long entry at 65000, SL = 2% → Exit at 63700 (65000 - 2%)
Short entry at 65000, TP = 3% → Exit at 63050 (65000 - 3%)
3. Options Trading Setup (Only if Segment = Options)
Strike Selection Method
User Defined Mode:
Manually specify exact strike and option type
Best for: Trading specific levels
Required fields:
Strike Price : e.g., "65000"
Option Type : Call or Put
Dynamic Mode:
System calculates strike based on ATM price
Best for: Automated strategies
Required fields:
Algo Type : Options Buying or Selling
Strike Offset : 0 (ATM), +1 (above ATM), -1 (below ATM)
Strike Interval : Gap between strikes (e.g., BTC: 500, ETH: 50)
Expiry Date Formats:
T+0 - Today
T+1 - Tomorrow
current week - This Friday
next week - Next Friday
current month - Last Friday of month
131125 - Specific date (13 Nov 2025)
4. Create Alert for Automation
Right-click on chart → "Add Alert"
Condition : Select your strategy name
Alert Actions : Webhook URL
Webhook URL : Your Algoticks.in API endpoint
Message : Leave as {{strategy.order.alert_message}} (contains JSON)
Click "Create"
The alert will automatically send JSON payloads to your API when signals occur.
Example Configurations
Standard RSI Reversal
Strategy: RSI Length = 14, OB = 70, OS = 30
Segment: futures
Order Type: market_order
Quantity: 1
SL: 1.5% (Relative)
TP: 3% (Relative)
Aggressive Scalping
Strategy: RSI Length = 7, OB = 80, OS = 20
Segment: futures
Order Type: market_order
Quantity: 0.5
SL: 0.5% (Relative)
TP: 1% (Relative)
Important Notes
Paper Trading First : Always test with paper trading enabled before live trading
Order Tags : Automatically generated for tracking (max 18 chars)
Position Management : Strategy closes opposite positions automatically
Signal Confirmation : Uses barstate.isconfirmed to prevent repainting
JSON Payload : All settings are converted to JSON and sent via webhook
Troubleshooting
No signals : Check if RSI is actually reaching your OB/OS levels
Orders not executing : Verify webhook URL and API credentials
Wrong strikes : Double-check Strike Interval for your asset
SL/TP not working : Ensure values are non-zero and mode is correct
Support
For API setup and connector configuration, visit Algoticks.in documentation.
AlphaStrike: Zen ModeDescription:
The Problem most of us lose money because we try to do two opposing things at once: we chase trends when they are already overextended, and we try to catch falling knives before they are ready to bounce. We get chopped up in the middle.
The Solution AlphaStrike is a "Hybrid" system designed to separate these two battlefields. It combines a Trend Following engine (to keep you in big moves) with a Momentum Reversion engine (to spot exhaustion).
It essentially answers two questions:
"Is the trend my friend?" (Trend Filter)
"Is the rubber band about to snap?" (Reversal Signal)
How It Works (The "Zen" Logic) I stripped away the noise. No clouds, no confusing lines—just the signals that matter.
The Trend Line (Red/Green): This is your bias.
Green: Only look for buys.
Red: Only look for sells (or cash).
Rule: Never trade against the line color unless you are scalping a confirmed Reversal Signal.
The Circles (Reversals):
🔵 Blue Dot: "Oversold Rejection." Price stretched below the bands and wicked back up. This is a high-reward entry for dips.
🟠 Orange Dot: "Overbought Exhaustion." Price stretched too high and was rejected. This is your warning to take profits or tighten stops.
The Triangles (Breakouts):
Green/Red Triangles: These confirm the trend has officially flipped. This is the safer entry for conservative traders.
Risk Management (The Built-in Calculator) Trading is math, not magic. This indicator includes a "Smart Risk Table" in the bottom right corner.
It calculates the distance to the structural Stop Loss (invisible support/resistance swings).
It tells you exactly how much to buy to risk only 1% of your account.
Note: You must go to Settings and enter your actual Account Size for this to work.
Best Settings
Crypto (BTC/ETH): Use the default settings (Factor 3.5).
Forex/Stocks: Lower the Factor to 3.0 for more sensitivity.
Disclaimer: No indicator is perfect. This tool is designed to manage risk and identify probability, not to predict the future. Always use a stop loss.
Position Size Calculator + Live R/R Panel — SMC/ICT (@PueblaATH)Position Size + Live R/R Panel — SMC/ICT (@PueblaATH)
Position Size + Live R/R Panel — SMC/ICT (@PueblaATH) is a professional-grade risk management and execution module built for Smart Money Concepts (SMC) and ICT Traders who require accurate, repeatable, institution-style trade planning.
This tool delivers precise position sizing, R:R modeling, leverage and margin projections, fee-adjusted PnL outcomes, and real-time execution metrics—all directly on the chart. Optimized for crypto, forex, and futures, it provides scalpers, day traders, and swing traders with the clarity needed to execute high-quality trades with confidence and consistency.
What the Indicator Does
Institutional Position Sizing Engine
Calculates position size based on account balance, % risk, and SL distance.
Supports custom minimum lot size rounding across crypto, FX, indices, and derivatives.
Intelligent direction logic (Auto / Long / Short) based on SMC/ICT structure.
Advanced Risk/Reward & Profit Modeling
Real-time R:R ratio using actual rounded position size.
Live PnL readout that updates with price movements.
Gross & net profit projections with full fee deduction.
Execution Planning with Draggable Levels
Entry, SL, and TP levels fully draggable for fast scenario modeling.
Automatic projected lines backward/forward with clean label alignment.
TP and SL tags include % movement from Entry, ideal for SMC/ICT journaling.
Precise modeling of real exchange fee structures
Maker fee per side
Taker fee per side
Mixed fee modes (Maker entry, Taker exit, Average, etc.)
Leverage & Margin Forecasting
Margin requirements displayed for 3 customizable leverage settings.
Helps traders understand capital commitment before executing the trade.
Useful for futures, crypto perps, and CFD setups.
Clean HUD Panel for Rapid Decision-Making
A full professional trading panel displays:
Target & actual risk
Position size
Entry / SL / TP
TP/SL percentage distance
Gross profit
Net profit (after fees)
Fees @ TP and @ SL
Live PnL
Margin requirements
Optimized for SMC & ICT Workflows
Perfect for traders using:
Breakers, FVGs, OBs
Liquidity sweeps
Session models
Precision entries (OTE, Displacement, Rebalancing)
Leverage-based execution (crypto perps, futures)
How to Use It
Attach the indicator to your chart.
Set account balance, risk %, fee model, and leverage presets.
Drag Entry, SL, and TP to shape the setup.
View instant calculations of: Position size; R:R; Net PnL after fees; Margin required
Use it as your pre-trade checklist & execution model.
Originality & Credits
This script is an original creation by @PueblaATH, released under the MPL 2.0 license.
It does not copy, modify, or repackage any existing TradingView code.
All logic—including the fee engine, margin calculator, responsive HUD, dynamic risk model, and visual execution system—is authored specifically for this indicator.
First Session Candle (Transparent Label) Change timezone & more"Global First Candle Rule: Session Refinement Tool"
"This tool/template is designed to apply the First Candle Rule across the world's three major trading sessions: New York (NYO), Asia (AO), and London (LO).
It uses New York Time (NY) as the default reference, but the timezone can be easily adjusted to UTC or UTC+7 (Vietnam Time).
🎁 Free for the community!"
Double candle engulfing (Optimized)Double Engulfing Pattern Detector (DELO)
This indicator identifies strong trend reversal signals by detecting the confirmation of two consecutive Engulfing Candlestick Patterns.
✨ Key Features:
Bullish Engulfing: Triggers a Buy Signal when two consecutive bullish engulfing patterns are confirmed.
Bearish Engulfing: Triggers a Sell Signal when two consecutive bearish engulfing patterns are confirmed.
Probability Cone█ Overview:
Probability Cone is based on the Expected Move . While Expected Move only shows the historical value band on every bar, probability panel extend the period in the future and plot a cone or curve shape of the probable range. It plots the range from bar 1 all the way to bar 31.
In this model, we assume asset price follows a log-normal distribution and the log return follows a normal distribution.
Note: Normal distribution is just an assumption; it's not the real distribution of return.
The area of probability range is based on an inverse normal cumulative distribution function. The inverse cumulative distribution gives the range of price for given input probability. People can adjust the range by adjusting the standard deviation in the settings. The probability of the entered standard deviation will be shown at the edges of the probability cone.
The shown 68% and 95% probabilities correspond to the full range between the two blue lines of the cone (68%) and the two purple lines of the cone (95%). The probabilities suggest the % of outcomes or data that are expected to lie within this range. It does not suggest the probability of reaching those price levels.
Note: All these probabilities are based on the normal distribution assumption for returns. It's the estimated probability, not the actual probability.
█ Volatility Models :
Sample SD : traditional sample standard deviation, most commonly used, use (n-1) period to adjust the bias
Parkinson : Uses High/ Low to estimate volatility, assumes continuous no gap, zero mean no drift, 5 times more efficient than Close to Close
Garman Klass : Uses OHLC volatility, zero drift, no jumps, about 7 times more efficient
Yangzhang Garman Klass Extension : Added jump calculation in Garman Klass, has the same value as Garman Klass on markets with no gaps.
about 8 x efficient
Rogers : Uses OHLC, Assume non-zero mean volatility, handles drift, does not handle jump 8 x efficient.
EWMA : Exponentially Weighted Volatility. Weight recently volatility more, more reactive volatility better in taking account of volatility autocorrelation and cluster.
YangZhang : Uses OHLC, combines Rogers and Garmand Klass, handles both drift and jump, 14 times efficient, alpha is the constant to weight rogers volatility to minimize variance.
Median absolute deviation : It's a more direct way of measuring volatility. It measures volatility without using Standard deviation. The MAD used here is adjusted to be an unbiased estimator.
You can learn more about each of the volatility models in out Historical Volatility Estimators indicator.
█ How to use
Volatility Period is the sample size for variance estimation. A longer period makes the estimation range more stable less reactive to recent price. Distribution is more significant on larger sample size. A short period makes the range more responsive to recent price. Might be better for high volatility clusters.
People usually assume the mean of returns to be zero. To be more accurate, we can consider the drift in price from calculating the geometric mean of returns. Drift happens in the long run, so short lookback periods are not recommended.
The shape of the cone will be skewed and have a directional bias when the length of mean is short. It might be more adaptive to the current price or trend, but more accurate estimation should use a longer period for the mean.
Using a short look back for mean will make the cone having a directional bias.
When we are estimating the future range for time > 1, we typically assume constant volatility and the returns to be independent and identically distributed. We scale the volatility in term of time to get future range. However, when there's autocorrelation in returns( when returns are not independent), the assumption fails to take account of this effect. Volatility scaled with autocorrelation is required when returns are not iid. We use an AR(1) model to scale the first-order autocorrelation to adjust the effect. Returns typically don't have significant autocorrelation. Adjustment for autocorrelation is not usually needed. A long length is recommended in Autocorrelation calculation.
Note: The significance of autocorrelation can be checked on an ACF indicator.
ACF
Time back settings shift the estimation period back by the input number. It's the origin of when the probability cone start to estimation it's range.
E.g., When time back = 5, the probability cone start its prediction interval estimation from 5 bars ago. So for time back = 5 , it estimates the probability range from 5 bars ago to X number of bars in the future, specified by the Forecast Period (max 1000).
█ Warnings:
People should not blindly trust the probability. They should be aware of the risk evolves by using the normal distribution assumption. The real return has skewness and high kurtosis. While skewness is not very significant, the high kurtosis should be noticed. The Real returns have much fatter tails than the normal distribution, which also makes the peak higher. This property makes the tail ranges such as range more than 2SD highly underestimate the actual range and the body such as 1 SD slightly overestimate the actual range. For ranges more than 2SD, people shouldn't trust them. They should beware of extreme events in the tails.
The uncertainty in future bars makes the range wider. The overestimate effect of the body is partly neutralized when it's extended to future bars. We encourage people who use this indicator to further investigate the Historical Volatility Estimators , Fast Autocorrelation Estimator , Expected Move and especially the Linear Moments Indicator .
The probability is only for the closing price, not wicks. It only estimates the probability of the price closing at this level, not in between.
CCI TIME COUNT//@version=6
indicator("CCI Multi‑TF", overlay=true)
// === Inputs ===
// CCI Inputs
cciLength = input.int(20, "CCI Length", minval=1)
src = input.source(hlc3, "Source")
// Timeframes
timeframes = array.from("1", "3", "5", "10", "15", "30", "60", "1D", "1W")
labels = array.from("1m", "3m", "5m", "10m", "15m", "30m", "60m", "Daily", "Weekly")
// === Table Settings ===
tblPos = input.string('Top Right', 'Table Position', options = , group = 'Table Settings')
i_textSize = input.string('Small', 'Text Size', options = , group = 'Table Settings')
textSize = i_textSize == 'Small' ? size.small : i_textSize == 'Normal' ? size.normal : i_textSize == 'Large' ? size.large : size.tiny
textColor = color.white
// Resolve table position
var pos = switch tblPos
'Top Left' => position.top_left
'Top Right' => position.top_right
'Bottom Left' => position.bottom_left
'Bottom Right' => position.bottom_right
'Middle Left' => position.middle_left
'Middle Right' => position.middle_right
=> position.top_right
// === Custom CCI Function ===
customCCI(source, length) =>
sma = ta.sma(source, length)
dev = ta.dev(source, length)
(source - sma) / (0.015 * dev)
// === CCI Values for All Timeframes ===
var float cciVals = array.new_float(array.size(timeframes))
for i = 0 to array.size(timeframes) - 1
tf = array.get(timeframes, i)
cciVal = request.security(syminfo.tickerid, tf, customCCI(src, cciLength))
array.set(cciVals, i, cciVal)
// === Countdown Timers ===
var string countdowns = array.new_string(array.size(timeframes))
for i = 0 to array.size(timeframes) - 1
tf = array.get(timeframes, i)
closeTime = request.security(syminfo.tickerid, tf, time_close)
sec_left = barstate.isrealtime and not na(closeTime) ? math.max(0, (closeTime - timenow) / 1000) : na
min_left = sec_left >= 0 ? math.floor(sec_left / 60) : na
sec_mod = sec_left >= 0 ? math.floor(sec_left % 60) : na
timer_text = barstate.isrealtime and not na(sec_left) ? str.format("{0,number,00}:{1,number,00}", min_left, sec_mod) : "–"
array.set(countdowns, i, timer_text)
// === Build Table ===
if barstate.islast
rows = array.size(timeframes) + 1
var table t = table.new(pos, 3, rows, frame_color=color.rgb(252, 250, 250), border_color=color.rgb(243, 243, 243))
// Headers
table.cell(t, 0, 0, "Timeframe", text_color=textColor, bgcolor=color.rgb(238, 240, 242), text_size=textSize)
table.cell(t, 1, 0, "CCI (" + str.tostring(cciLength) + ")", text_color=textColor, bgcolor=color.rgb(239, 243, 246), text_size=textSize)
table.cell(t, 2, 0, "Time to Close", text_color=textColor, bgcolor=color.rgb(239, 244, 248), text_size=textSize)
// Data Rows
for i = 0 to array.size(timeframes) - 1
row = i + 1
label = array.get(labels, i)
cciVal = array.get(cciVals, i)
countdown = array.get(countdowns, i)
// Color CCI: Green if < -100, Red if > 100
cciColor = cciVal < -100 ? color.green : cciVal > 100 ? color.red : color.rgb(236, 237, 240)
// Background warning if <60 seconds to close
tf = array.get(timeframes, i)
closeTime = request.security(syminfo.tickerid, tf, time_close)
sec_left = barstate.isrealtime and not na(closeTime) ? math.max(0, (closeTime - timenow) / 1000) : na
countdownBg = sec_left < 60 ? color.rgb(255, 220, 220, 90) : na
// Table cells
table.cell(t, 0, row, label, text_color=color.rgb(239, 240, 244), text_size=textSize)
table.cell(t, 1, row, str.tostring(cciVal, "#.##"), text_color=cciColor, text_size=textSize)
table.cell(t, 2, row, countdown, text_color=color.rgb(232, 235, 243), bgcolor=countdownBg, text_size=textSize)
VWAP + RSI Bounce Strategy Hariss 369VWAP + RSI Bounce Strategy
This strategy combines VWAP (Volume-Weighted Average Price) and RSI momentum shift to capture high-probability reversal bounces. The idea is simple: price often reacts strongly around VWAP, which represents the true intraday fair value. When price pulls back towards VWAP and then bounces away with strength, it often marks a continuation move.
A long signal forms when:
Price touches or slightly dips below VWAP, showing a pullback
Candle closes back above VWAP, confirming a strong bullish bounce
RSI turns bullish (crosses 50 or crosses above its smoothing)
A sell signal forms in the opposite conditions with a bearish bounce below VWAP.
This combination filters out weak reactions and focuses only on momentum-backed bounces. Trend-colored VWAP helps visualize directional bias more clearly—green when VWAP is rising and red when falling. This approach is best used in trending markets and works well across intraday timeframes.
Kalman Ema Crosses - [JTCAPITAL]Kalman EMA Crosses - is a modified way to use Kalman Filters applied on Exponential Moving Averages (EMA Crosses) for Trend-Following.
Credits for the kalman function itself goes to @BackQuant
The Kalman filter is a recursive smoothing algorithm that reduces noise from raw price or indicator data, and in this script it is applied both directly to price and on top of EMA calculations. The goal is to create cleaner, more reliable crossover signals between two EMAs that are less prone to false triggers caused by volatility or market noise.
The indicator works by calculating in the following steps:
Source Selection
The script starts by selecting the price input (default is Close, but can be adjusted). This chosen source is the foundation for all further smoothing and EMA calculations.
Kalman Filtering on Price
Depending on user settings, the selected source is passed through one of two independent Kalman filters. The filter takes into account process noise (representing expected market randomness) and measurement noise (representing uncertainty in the price data). The Kalman filter outputs a smoothed version of price that minimizes noise and preserves underlying trend structure.
EMA Calculation
Two exponential moving averages (EMA 1 and EMA 2) are then computed on the Kalman-smoothed price. The lengths of these EMAs are fully customizable (default 15 and 25).
Kalman Filtering on EMA Values
Instead of directly using raw EMA curves, the script applies a second layer of Kalman filtering to the EMA values themselves. This step significantly reduces whipsaw behavior, creating smoother crossovers that emphasize real momentum shifts rather than temporary volatility spikes.
Trend Detection via EMA Crossovers
-A bullish trend is detected when EMA 1 (fast) crosses above EMA 2 (slow).
-A bearish trend is detected when EMA 1 crosses below EMA 2.
The detected trend state is stored and used to dynamically color the plots.
Visual Representation
Both EMAs are plotted on the chart. Their colors shift to blue during bullish phases and purple during bearish phases. The area between the two EMAs is filled with a shaded region to clearly highlight trending conditions.
Buy and Sell Conditions:
-Buy Condition: When the Kalman-smoothed EMA 1 crosses above the Kalman-smoothed EMA 2, a bullish crossover is confirmed.
-Sell Condition: When EMA 1 crosses below EMA 2, a bearish crossover is confirmed.
Users may enhance the robustness of these signals by adjusting process noise, measurement noise, or EMA lengths. Lower measurement noise values make the filter react faster (but potentially noisier), while higher values make it smoother (but slower).
Features and Parameters:
-Source: Selectable price input (Close, Open, High, Low, etc.).
-EMA 1 Length: Defines the fast EMA period.
-EMA 2 Length: Defines the slow EMA period.
-Process Noise: Controls how much randomness the Kalman filter assumes in price dynamics.
-Measurement Noise: Controls how much uncertainty is assumed in raw input data.
-Kalman Usage: Option to apply Kalman filtering either before EMA calculation (on price) or after (on EMA values).
Specifications:
Kalman Filter
The Kalman filter is an optimal recursive algorithm that estimates the state of a system from noisy measurements. In trading, it is used to smooth prices or indicator values. By balancing process noise (expected volatility) with measurement noise (data uncertainty), it generates a smoothed signal that reacts adaptively to market conditions.
Exponential Moving Average (EMA)
An EMA is a weighted moving average that emphasizes recent data more heavily than older data. This makes it more responsive than a simple moving average (SMA). EMAs are widely used to identify trends and momentum shifts.
EMA Crossovers
The crossing of a fast EMA above a slow EMA suggests bullish momentum, while the opposite suggests bearish momentum. This is a cornerstone technique in trend-following systems.
Dual Kalman Filtering
Applying Kalman both to raw price and to the EMAs themselves reduces whipsaws further. It creates crossover signals that are not only smoothed but also validated across two levels of noise reduction. This significantly enhances signal reliability compared to traditional EMA crossovers.
Process Noise
Represents the filter’s assumption about how much the underlying market can randomly change between steps. Higher values make the filter adapt faster to sudden changes, while lower values make it more stable.
Measurement Noise
Represents uncertainty in price data. A higher measurement noise value means the filter trusts the model more than the observed data, leading to smoother results. A lower value makes the filter more reactive to observed price fluctuations.
Trend Coloring & Fill
The use of dynamic colors and filled regions provides immediate visual recognition of trend states, helping traders act faster and with greater clarity.
Enjoy!
Trend Target
Determines the trend direction based on the last 3 candles.
Provides a target (dotted line) and a stop loss (solid line) derived from the price action over the last 3 candles.
Green dotted target is for a bullish position, red dotted target is for a bearish position and gray solid lines are for range-bound sideways movement amongst the last 3 candles.
EMA + Sessions + RSI Strategy v1.0A professional trading strategy that combines multiple technical indicators for high-probability entries. This system uses EMA crossovers, RSI zone filtering, and trend confirmation to identify optimal trading opportunities while managing risk with advanced position management tools.
Key Features:
✅ Dual Entry Signals (EMA21 + EMA100 crossover conditions)
✅ Trend Filter EMA750 (trade only with the major trend)
✅ Complete Risk Management (SL 1%, TP 3% default)
✅ Trailing Stop & Breakeven (maximize profits, protect capital)
✅ Compact Statistics Table (real-time performance metrics)
✅ RSI & Session Filters (avoid low-probability setups)
✅ Optional Pyramiding (scale into winning positions)
Perfect for swing trading and trend-following on any timeframe. Fully customizable to match your trading style.
Multi Timeframe Trend IndicatorDiscreet visual display across 4 timeframes (adjustable). If you trade on a 5-minute timeframe, for example, you have an all-in-one visual display across the 4 higher timeframes (e.g., m15, m30, h1 and h4) for better decision-making.
Impulse Trend Suite (LITE) — v1.4 source🚀 Impulse Trend Suite (LITE) — v1.4
Smart trend visualization with precise flip arrows. A lightweight, momentum-filtered trend tool designed to stay clean, avoid repeated signals, and keep you focused only on real market direction.
✨ What’s New in v1.4
Minor upgrades mostly visual
Added Blue fill between MA lines
clearer labels
📌 Core Features
Trend flip arrows (no spam, 1 signal per turn)
Continuous background zones (gap-free trend shading)
Adaptive Baseline + ATR structure channel
RSI + MACD momentum filter (suppresses weak signals)
Trend Status Panel (UP, DOWN, NEUTRAL)
🔍 Quick Guide
BUY setup = green arrow + green background
SELL setup = red arrow + red background
Stay in the move while color doesn’t change
ATR channel helps avoid chasing overextended candles
🆚 LITE vs PRO
Feature LITE PRO
--------------------- -------- ------------------------------
Trend shading + arrows ✔ ✔ + confirmations
Neutral trend state ✔ ✔ enhanced
Alerts ✖ ✔ full suite
Reversal Zones ✖ ✔ predictive boxes
HTF Filter ✖ ✔ smarter trend bias
Included strategies ✖ ✔ + PDF training
========================================================
🔓 Upgrade to PRO
Reversal Zones • Alerts • HTF Filter • Trend Continuation Strategy
👉 fxsharerobots.com/impulse-trend-pro/
📈 Works on Forex, Stocks, Crypto, Indices, Metals
⌚ Scalping • Intraday • Swing • Long-term
==========================================================
⚠️ LITE - Educational tool. Backtest before trading live.
Visit us for Full Trading Tools Collection here:
fxsharerobots.com/downloads/
Happy trading! — FxShareRobots Team
SKeTCHeX - Enhanced 20SMA Cloud
// ║
// ║ Enhanced 20SMA Cloud with Trend Colors
// ║ Developer: SKeTCHeX Institutional Algorithmic Systems
// ║
// ║ DESCRIPTION:
// ║ Professional-grade moving average indicator featuring dynamic cloud
// ║ visualization with intelligent trend-based coloring. The SMA automatically
// ║ changes color based on price position (green when bullish, red when
// ║ bearish), while the surrounding cloud provides dynamic support/resistance
// ║ zones using either ATR volatility measurement or percentage-based width.
// ║
// ║ FEATURES:
// ║ • Real-time trend detection with color-coded SMA
// ║ • Dynamic cloud bands (ATR-based or percentage-based)
// ║ • Multiple price source options (Close, Open, High, Low, HL2, HLC3, OHLC4)
// ║ • Customizable shift for forward/backward projection
// ║ • Institutional-grade visual clarity for multi-timeframe analysis
// ║
// ║ USAGE:
// ║ Green SMA/Cloud = Bullish bias (price above SMA)
// ║ Red SMA/Cloud = Bearish bias (price below SMA)
// ║ Cloud bands act as dynamic support/resistance zones
TQQQ Vibha Strategy – Auto Ranges + Rally Days1. Buy only after an intermediate bottom
A 20-day lowest low becomes the potential bottom.
2. Wait 3–4 days of higher highs & higher lows
higherSeq logic enforces that.
3. Avoid buying when too extended from the 200-day
Enforced with:
close <= ma200 * (1 + maxExtension) (default 10%)
4. Must close back above 200-day
Needed for “change of character”
5. Sell immediately if price breaks the Day-1 rally low (“line in the sand”)
Script sets lineInSand = bottom low
If price undercuts → close position immediately
6. Range-top rejection
Track touches of range top (highest high since bottom)
Three failures = sell (“3 strikes rule”)
1.1 SMF LONG: Sweep → BOS → OB → BOS break SMF LONG Strategy (Sweep → BOS → Order Block → BOS) — Summary
The strategy looks for a moment when the market takes liquidity to the downside through a sweep (breaking previous lows), followed by the formation of the first BOS, indicating that sellers have lost control. After that, the strategy waits for the creation of an Order Block (OB) — the last bearish candle before the upward impulse — which highlights the zone where large players entered positions. When price returns to the OB, the entry (TVH) is placed at the top of the OB, the stop-loss at the bottom of the OB, and the take-profit is always set to 3× the stop size, regardless of the OB width.
In a one-year backtest from December 2024 to December 2025, the strategy and indicator showed a win rate of 30.85%:
65 stop-losses,
29 take-profits,
and 15 missed trades where the take-profit was hit before price could return to the entry zone.
Price Channel Breakout Strategy — Long & ShortThis strategy is a dual-direction Price Channel breakout system designed for high-volatility indices such as US30, NAS100, and XAUUSD.
It enters long when price breaks above the highest high of the past N bars, and enters short when price breaks below the lowest low.
A key feature is the use of fixed dollar-based take-profit and stop-loss, making the strategy adaptive across symbols with different tick values.
Core Logic
Long entry when price breaks the N-bar high
Short entry when price breaks the N-bar low
Dollar-based TP and SL (converted to ticks automatically)
Suitable for trending and breakout-friendly markets
Backtest Notes (US30 Example)
Sharpe Ratio: 2.7
Profit Factor: 2.111
Total Return (12-month backtest): +46.89%
Max Drawdown: 0.26%
Trades: 3,666
This strategy performs well in sustained volatility environments and is particularly effective for intraday momentum bursts on US30.
Bifurcation Early WarningBifurcation Early Warning (BEW) — Chaos Theory Regime Detection
OVERVIEW
The Bifurcation Early Warning indicator applies principles from chaos theory and complex systems research to detect when markets are approaching critical transition points — moments where the current regime is likely to break down and shift to a new state.
Unlike momentum or trend indicators that tell you what is happening, BEW tells you when something is about to change. It provides early warning of regime shifts before they occur, giving traders time to prepare for increased volatility or trend reversals.
THE SCIENCE BEHIND IT
In complex systems (weather, ecosystems, financial markets), major transitions don't happen randomly. Research has identified three universal warning signals that precede critical transitions:
1. Critical Slowing Down
As a system approaches a tipping point, it becomes "sluggish" — small perturbations take longer to decay. In markets, this manifests as rising autocorrelation in returns.
2. Variance Amplification
Short-term volatility begins expanding relative to longer-term baselines as the system destabilizes.
3. Flickering
The system oscillates between two potential states before committing to one — visible as increased crossing of mean levels.
BEW combines all three signals into a single composite score.
COMPONENTS
AR(1) Coefficient — Critical Slowing Down (Blue)
Measures lag-1 autocorrelation of returns over a rolling window.
• Rising toward 1.0: Market becoming "sticky," slow to mean-revert — transition approaching
• Low values (<0.3): Normal mean-reverting behavior, stable regime
Variance Ratio (Purple)
Compares short-term variance to long-term variance.
• Above 1.5: Short-term volatility expanding — energy building before a move
• Near 1.0: Volatility stable, no unusual pressure
Flicker Count (Yellow/Teal)
Counts state changes (crossings of the dynamic mean) within the lookback period.
• High count: Market oscillating between states — indecision before commitment
• Low count: Price firmly in one regime
INTERPRETING THE BEW SCORE
0–50 (STABLE): Normal market conditions. Existing strategies should perform as expected.
50–70 (WARNING): Elevated instability detected. Consider reducing exposure or tightening risk parameters.
70–85 (DANGER): High probability of regime change. Avoid initiating new positions; widen stops on existing ones.
85+ (CRITICAL): Bifurcation likely imminent or in progress. Expect large, potentially unpredictable moves.
HOW TO USE
As a Regime Filter
• BEW < 50: Normal trading conditions — apply your standard strategies
• BEW > 60: Elevated caution — reduce position sizes, avoid mean-reversion plays
• BEW > 80: High alert — consider staying flat or hedging existing positions
As a Preparation Signal
BEW tells you when to pay attention, not which direction. When readings elevate:
• Watch for confirmation from volume, order flow, or other directional indicators
• Prepare for breakout scenarios in either direction
• Adjust take-profit and stop-loss distances for larger moves
For Volatility Adjustment
High BEW periods correlate with larger candles. Use this to:
• Widen stops during elevated readings
• Adjust position sizing inversely to BEW score
• Set more ambitious profit targets when entering during high-BEW breakouts
Divergence Analysis
• Price making new highs/lows while BEW stays low: Trend likely to continue smoothly
• Price consolidating while BEW rises: Breakout incoming — direction uncertain but move will be significant
SETTINGS GUIDE
Core Settings
• Lookback Period: General reference period (default: 50)
• Source: Price source for calculations (default: close)
Critical Slowing Down (AR1)
• AR(1) Calculation Period: Bars used for autocorrelation (default: 100). Higher = smoother, slower.
• AR(1) Warning Threshold: Level at which AR(1) is considered elevated (default: 0.85)
Variance Growth
• Variance Short Period: Fast variance window (default: 20)
• Variance Long Period: Slow variance window (default: 100)
• Variance Ratio Threshold: Level for maximum score contribution (default: 1.5)
Regime Flickering
• Flicker Detection Period: Window for counting state changes (default: 20)
• Flicker Bandwidth: ATR multiplier for state detection — lower = more sensitive (default: 0.5)
• Flicker Count Threshold: Number of crossings for maximum score (default: 4)
TIMEFRAME RECOMMENDATIONS
• 5m–15m: Use shorter periods (AR: 30–50, Var: 10/50). Expect more noise.
• 1H: Balanced performance with default or slightly extended settings (AR: 100, Var: 20/100).
• 4H–Daily: Extend periods further (AR: 100–150, Var: 30/150). Cleaner signals, less frequent.
ALERTS
Three alert conditions are included:
• BEW Warning: Score crosses above 50
• BEW Danger: Score crosses above 70
• BEW Critical: Score crosses above 85
LIMITATIONS
• No directional bias: BEW detects instability, not direction. Combine with trend or momentum indicators.
• Not a timing tool: Elevated readings may persist for several bars before the actual move.
• Parameter sensitive: Optimal settings vary by asset and timeframe. Backtest before live use.
• Leading indicator trade-off: Early warning means some false positives are inevitable.
CREDITS
Inspired by research on early warning signals in complex systems:
• Dakos et al. (2012) — "Methods for detecting early warnings of critical transitions"
DISCLAIMER
This indicator is for educational and informational purposes only. It does not constitute financial advice. Past performance is not indicative of future results. Always conduct your own analysis and risk management. Use at your own risk.
