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CandelaCharts - Killzone Seasonality📝 Overview
The CandelaCharts - Killzone Seasonality indicator is a sophisticated statistical tool designed to help traders identify recurring price patterns. It provides a "Ghost Path" of average movement, individual session trails for variance analysis, and a directional bias heatmap for each day of the week.
📦 Features
Ghost Paths : Visualizes the mean price trajectory of historical sessions as a dynamic polyline.
Individual Trails : Overlays previous sessions as separate trails, allowing you to see how current price action deviates from historical norms.
DOW Directional Bias : A statistical dashboard (Mon-Fri) showing the percentage of times a specific killzone closed bullishly.
5 Standard Killzones : Pre-configured for Asia, London, NY AM, NY Lunch, and NY PM sessions.
Advanced Smoothing : Smooths the average trajectory to filter out noise and highlight the core trend.
Bottom Bars : Visualizes active sessions as horizontal color bars at the base of the chart window for quick identification.
High Performance : Built with Pine Script v6 matrices and polylines for maximum efficiency.
⚙️ Settings
Max History (Sessions) : Total number of historical sessions stored in memory (Max 50).
Ghost Lookback : Number of previous sessions used to calculate the Mean Path.
Trail Count : Number of previous session trails to display (Global limit).
Bar Size : Universal size setting (Tiny/Small/Normal) for all active bottom bars.
Path Smoothing : Adjusts the level of smoothing applied to the Ghost Path.
Timezone : Set the base timezone (default America/New_York).
Session Inputs : Configure start/end times, labels, and colors for all 5 killzones.
Ghost : Toggle the Mean Path prediction for this specific session.
Trails : Toggle individual historical trails for this specific session.
Bottom Bar : Toggle the horizontal session indicator bar at the base of the chart.
DOW Table : Toggle and position the statistical directional bias dashboard.
⚡️ Showcase
The Ghost Path
The Trail Lines
Statistical Heatmap
Killzone Bottom Bars
🚨 Alerts
Standard PulseWire alerts can be added for session transitions (implementation based on individual needs).
⚠️ Disclaimer
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
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Sentry Mode: Dynamic Trend & Exit SystemSentry Mode is designed for traders who prioritize risk management and structural trend alignment. It eliminates the guesswork of "How much should I buy?" by calculating your exact share count based on a live-tracking stop loss.
Core Features
1. The Sentry Position Manager (Quantitative Table)
The centerpiece of this script is a real-time data table that calculates:
Target vs. Actual Risk: Sees the gap between your desired equity risk and the actual dollar amount at stake after share rounding.
Dynamic Stop (Ribbon Top): The stop loss isn't a fixed percentage; it tracks the Low of the leading Moving Average in the ribbon, providing a "trailing floor."
Position Sizing: Automatically calculates shares based on your Account Size and Max Position % cap.
Invalid Price Filter: The Sentry will reject trade calculations (showing "PRICE BELOW STOP") if the asset is currently trading below the structural floor.
2. Structural Trend Ribbon
5-MA Cluster: Uses up to five user-selectable Moving Averages (SMA, EMA, WMA, etc.) to visualize trend strength.
Ribbon Top Analysis: Automatically identifies the "Fastest" MA to set the current trend boundary.
3rd MA Floor: Identifies the "meat" of the trend, serving as a secondary structural exit for trailing stops.
3. Multi-Timeframe Pivot Analysis
The script identifies and draws institutional-grade levels:
52-Week Highs: Tracks and extends 52-week highs with automated "Broken Line" logic when price clears the level.
Multi-Day Pivots: Visualizes 5-day, 9-day, 19-day, and 90-day pivot highs to identify supply zones and breakout entries.
Downtrend Resistance: Automatically plots 19-bar downward trendlines to identify "Cheat" entries and downtrend breaks.
4. SPY Market Context Filter
Broad Market Alignment: Includes a background color filter based on SPY (S&P 500) trend health.
ATR Volatility Scaling: The background changes intensity (L1, L2, L3) based on SPY’s ATR, warning you when the broad market is undergoing a "normal pullback" versus a "high-volatility breakdown."
4. How to Use
Define your Bankroll: In the settings, input your total Account Size and the percentage of equity you are willing to risk per trade (e.g., 0.25%).
Confirm the Trend: Look for price to be above the Ribbon Top. Ensure the SPY Context background is green.
Execute via Sentry Table: Read the "Shares" and "Pos Size" directly from the on-screen table.
Manage the Exit: The red dashed Sentry Line shows your floor. If price closes below this line (or the 3rd MA), the trend structure is broken.
5. Technical Details (For the Sidebar)
Signal Type: Trend-Following / Momentum.
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FC Footprint HeatmapFC Footprint Profiles Heatmap is a professional-grade order flow analysis tool that combines four live data layers into a single unified overlay: a session footprint-based Volume Profile, a real-time 1D heatmap sidebar, raw footprint row text, and bar-level signal detection — all built from request.footprint() data streaming at the tick level.
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Unlike standard volume profile indicators that use OHLCV data, this script reads true footprint data — per-row buy and sell volume for every bar — and aggregates it in real time across the session. Every visual element updates live as price moves.
Features
Session Heatmap Blocks (Volume Profile)
Draws session profile blocks built from running intraday footprint rows
Color-coded by Cumulative Delta by Row (CVD), Sell-Buy, Sum, Bar Sell-Buy, or Bar Sum
Value Area (VAH / VAL) and POC computed using a canonical single-step expansion algorithm starting at the highest-volume row
VA rows rendered with full opacity; outside-VA rows with reduced transparency
POC row highlighted with a distinct border color
Three text display modes: All Boxes, Last Box Per Row (cleanest, recommended), or Off
Compact mode skips low-importance rows on lower timeframes, keeping the chart readable
Configurable box width, max row count, text size, and text alignment
Running Session VA / POC Lines
Dotted VAH, VAL, and POC lines extend in real time as session volume develops
Lines are trimmed and extended automatically across bars
Optional right-side POC and VAH/VAL labels
VA algorithm uses the immediate-neighbor single-row expansion method — at each step the adjacent row with higher volume is added, matching standard Market Profile convention
1D Heatmap Sidebar
Live session volume profile heatmap rendered as a sidebar to the right of the current bar
Row height matches the footprint tick-per-row setting exactly
Three gradient modes:
Dominant Side — binary buy/sell color
Buy/Sell % — continuous gradient by buy percentage
Recent Bias — smoothed short-lookback gradient using nearby rows
Two row width modes: Full Width or Volume Width (row width scales proportionally to row volume, similar to a Bookmap-style density view)
Value Area and POC rows distinctly colored
Optional row text showing: Dominant Volume, Total Volume, Delta, Buy Volume, or Sell Volume
Optional dominant-side percentage text (up/down arrow with %)
Panel background, gap, width, and text offset are all configurable
Zero stale labels: full delete-and-rebuild on every barstate.islast tick — no duplicate or overlapping row labels
Raw Footprint Row Text
Displays per-row footprint data beside the actual candles for the most recent N bars
Three display modes: DELTA (+/- buy minus sell), BUY-SELL (sell-buy pair), SUM (total)
Row colors differentiate POC, VA, zero-print, positive delta, negative delta, and neutral
Zero Print highlighting — rows where either buy or sell is zero are flagged in a distinct color
X offset adjustable to avoid overlapping candles
Bar Signals and Bubbles
High Delta Detection — bubble appears when absolute bar delta exceeds recent average by a configurable multiplier
High Volume Detection — bubble appears when bar volume exceeds recent average by a configurable multiplier
Bubble size scales with the multiplier: tiny, small, normal, or large
Bubble text shows the exact multiple (e.g. 3.2x delta or 4.7x volume)
When both conditions fire simultaneously, the dominant signal is shown
Simple Absorption Detection — flags bars where delta direction opposes price direction, body is small, and the opposing wick dominates
All signal history is capped at a user-defined max (default 8 recent bubbles)
Bar Delta / Bar Sum label — persistent tiny label below the current bar showing live delta and/or total volume
Settings Reference
Core — Footprint Engine
Ticks Per Row (default 4)
Primary row height for request.footprint(). Controls the granularity of all volume rows.
Larger values reduce row count and noise. Smaller values increase precision and detail.
Value Area % (default 70)
Session VA target as a percentage of total session volume. 70% is the standard Market Profile convention.
Imbalance % (default 300)
Threshold passed directly to the footprint engine for imbalance marking.
TPO Timeframe (default 30)
Aggregation timeframe for TPO column logic.
Heatmap Blocks
Show Heatmap Blocks — enables the session profile block overlay
Heatmap Value Mode — CVD / Sell-Buy / Sum / Bar Sell-Buy / Bar Sum
Heatmap Text Display — All Boxes / Last Box Per Row / Off
Heatmap Box Width — manual width in bars when compact mode is active
Max Heatmap Rows — safety cap for visible profile rows (default 24)
Compact Mode — skip low-importance rows on lower timeframes
Show VA Lines — draw live VAH / VAL dotted lines
1D Heatmap Sidebar
Show Heatmap — enables the sidebar panel
Width — max panel width in bars (default 16)
Gap — distance from price to panel in bars (default 8)
Row Width Mode — Full Width or volume-proportional width
Gradient Mode — Dominant Side / Buy/Sell % / Recent Bias
Show Value Text — prints row volume beside each row
Show Dominant % — prints directional percentage beside each row
Bar Signals
High Delta Threshold — minimum multiple of average delta to trigger bubble (default 1.8x)
High Volume Threshold — minimum multiple of average volume to trigger bubble (default 1.8x)
Absorption Body % — max body/range ratio for absorption detection (default 0.35)
Recent Bubbles — max signal labels kept on chart (default 8)
How the Value Area Is Calculated
The VA expansion starts at the POC (highest total-volume row). At each step it compares the immediate next row above vs. the immediate next row below, and adds the one with higher volume. This repeats until cumulative volume reaches the target percentage. Ties expand both sides. This matches the standard Market Profile VA construction method and avoids the lookahead bias common in two-row heuristic approaches.
Target = Total Session Volume x VA%
Each step:
hiVol = volume at next row above current top
loVol = volume at next row below current bottom
hiVol > loVol → expand up
loVol > hiVol → expand down
tie → expand both until target is reached
Requirements and Notes
Requires PulseWire Premium or Ultimate — request.footprint() is not available on lower plans
Works on all instruments that support footprint data (futures, crypto, forex)
All visuals are session-scoped and reset at each daily session boundary
Object limits: 500 lines / 500 boxes / 500 labels — managed with automatic cleanup
max_bars_back = 1500 for replay compatibility
Includes a replay fix so isLastDay resolves correctly during historical replay sessions
Recommended Starting Settings
NQ / ES Futures
Ticks Per Row: 4 to 12 | Heatmap Mode: CVD | Gradient: Buy/Sell % | Text: Last Box Per Row
Gold (GC)
Ticks Per Row: 2 to 4 | Heatmap Mode: CVD | Gradient: Dominant Side | Text: Off
BTC Crypto
Ticks Per Row: 100 to 200 | Heatmap Mode: CVD | Gradient: Recent Bias | Text: Off
Heatmap only (clean view)
Heatmap Blocks: Off | Gradient: Buy/Sell % | Text: Off
Deep order flow read
Ticks Per Row: 2 to 4 | TPO Mode: Sell-Buy | Gradient: Buy/Sell % | Text: All Boxes
Note:
Requires PulseWire Premium or Ultimate — request.footprint() is not available on lower plans
PulseWire enforces a hard limit of 500 boxes, 500 lines, and 500 labels per indicator
The heatmap sidebar uses boxes and labels for every visible price row — on instruments with many active rows (e.g. NQ on a 1-tick or 2-tick setting), the heatmap alone can consume a large share of the box budget
If Heatmap blocks stop drawing or appear incomplete, the box limit has been reached — turn off the Heatmap VP Sidebar first to free up object
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Stacked OLS Ribbon [SS]Hey everyone,
This is my Stacked OLS Ribbon indicator I have been working on for some time. So let's get into the details!
Understanding the Core: What is Stacked OLS?
OLS stands for Ordinary Least Squares. It is a standard statistical method used to find the "line of best fit" by minimizing the sum of the squares of the vertical deviations between each data point and the line.
Stacked OLS refers to the recursive process of "stacking" multiple regression calculations on top of one another. Instead of simply calculating the trend of price versus time once, this indicator takes the Standard Error (the leftover noise) from the first calculation and runs a second regression on that error. It repeats this process through six layers. By stacking these calculations, the indicator systematically peels away layers of market noise to isolate the most significant statistical boundaries. This is actually identical to gradient boosting. If you are a quantitative minded trader and/or familiar with things such as XG Boost or GBM, the premise is actually the same.
The Mechanics: How the Ribbon is Built
The Recursive Engine
The indicator executes six simultaneous passes using the f_linear_regression function. The first pass calculates the relationship between the current and previous price. Each subsequent pass uses the results of the previous one as its starting point. This creates a "multi-filter" effect where the final output is based on the consensus of six different statistical perspectives.
Dynamic Volatility Mapping
Rather than using a fixed width, the ribbon identifies the maximum standard error produced across all six passes. This ensures the boundaries of the ribbon expand and contract based on the actual complexity of recent price action. If the market is chaotic, the "Stack" produces a wider error, which naturally widens the ribbon.
Historical Outlier Memory
The script utilizes a 500-bar lookback array to track every instance where price moved outside the expected range. It specifically looks for the absolute maximum "excursion" or distance that price has traveled away from the mean. When current price exceeds this 500-bar historical record, it triggers the exhaustion labels.
Comparative Context: Stacked OLS vs. Other Bands
Against Bollinger Bands
Bollinger Bands rely on a Simple Moving Average and a standard deviation calculation that assumes a "normal distribution" of data. Stacked OLS is a "slope-aware" model. Because it is based on regression, it accounts for the angle and velocity of the trend, allowing the ribbon to lean into the move and provide more accurate support and resistance levels during aggressive trending phases.
Against Nadaraya-Watson Estimators
Nadaraya-Watson indicators use kernel smoothing to create a non-parametric line. While visually smooth, these can be prone to repainting or over-fitting to local noise. Stacked OLS remains mathematically anchored to the OLS framework, providing a more rigid and reliable statistical "ceiling" and "floor" that does not shift as drastically when new data arrives.
Practical Trading and MTF Strategy
The Power of Higher Timeframes (HTF)
The tf input allows you to project higher-order statistics onto your current chart. For example, if you are trading on a 5-minute timeframe but set the indicator to the 1-hour or Daily timeframe, the ribbon will show you the institutional-grade volatility boundaries.
Trend Alignment: When the higher timeframe ribbon is sloping upward, the most reliable setups are the exhaustion signals (Lime Circles) at the bottom of the ribbon.
Mean Reversion: The neon circles represent a "500-bar record" in price deviation. When these appear, price has reached a statistical extreme. This is often the signal for a high-probability reversal back toward the r4 midline.
The Volatility Squeeze: When the Green and Red fills compress and become very narrow, it indicates that the market has reached a point of statistical equilibrium. This "tightness" is almost always the precursor to a violent breakout in volatility.
Summary of Use
Signals: Look for the stacked circle labels to identify historical exhaustion points.
Targets: The center line of the ribbon serves as the primary target for mean reversion trades.
Context: Use the higher timeframe input to filter out local noise and stay aligned with the broader market structure.
My Suggestions
After having spent time using and refining this script, here are my general suggestions:
Leave it on your selected timeframe for short term scalping.
For longer trades or if you are planning on swing trading, increase the timeframe to hourly or even 4 hours.
If it exceeds the range, wait for a signal (the green and red dot) before fomoing in for a reversal!
That's the indicator!
Hope you all enjoy it and as always, safe trades to all!
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0000 Season Quarter Month 48xHORIZ v2.29Overview
The "Season Quarter Month 48xHORIZ v2.29" script is an advanced, seasonality-based backtesting indicator and dashboard designed for PulseWire. It strictly requires a Daily timeframe and analyzes historical price action by slicing the trading year into 48 "Quarter-Months" (roughly 7-day increments) or 24 "Half-Months."
Core Mechanics & Scoring
Seasonal Scoring System: For every segment of the year, the script calculates a proprietary "Score." This score rewards periods with high average returns and a high percentage of positive historical outcomes (win rate), while penalizing volatility (standard deviation).
Risk Aversion: A customizable RiskAversion input acts as an exponent to punish highly volatile periods—the higher the value, the safer the seasonal period must be to trigger a trade.
Time Shifting: An offset feature (offsetDays) allows the user to shift the start of a "seasonal month" forward or backward by a few days to anticipate seasonal trends earlier.
Trend Filter: An optional Exponential Moving Average (EMA) filter ensures that new seasonal buy signals are only executed if the asset is in an active macro uptrend.
Simulation & Backtesting
"Glaskugel" (Crystal Ball) Mode: This is an in-sample simulation that uses the entirety of the loaded historical data to generate an equity curve. By acting with "hindsight," it shows the theoretical maximum performance of the seasonal pattern.
Performance Tracking: The script simulates a trading strategy (buying when the seasonal score exceeds a threshold) and compares it against a Buy & Hold (B&H) baseline. It calculates metrics like Compound Annual Growth Rate (CAGR), Maximum Drawdown (Max DD), Win Rate, and Profit Factor.
Equity Polyline: It visually plots the simulated portfolio's growth directly on the chart using colored polylines.
UI & Dashboards
Stats Table: Displays high-level strategy performance, Buy & Hold comparisons, the asset's Market Cap, the distance from the EMA, and exactly when the next seasonal phase shift will occur.
H1 & H2 Seasonality Heatmaps: Two massive, highly detailed tables showing the historical performance of the First Half (H1) and Second Half (H2) of the year. They break down average returns, win rates, and scores for every Quarter-Month, Half-Month, Month, and Quarter, complete with historical year-by-year data.
Debug Table: A diagnostic tool that isolates a user-defined "Debug Year" and prints a t-log of every simulated trade (Entry Date, Exit Date, and Return) to verify the strategy's logic. Indicator
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Regime Correlation MatrixRegime Correlation Matrix — PulseWire Indicator
This indicator displays a real-time rolling Pearson correlation table between NQ (or any base chart symbol) and seven macro instruments: ES, CL (Crude Oil), 6C (Canadian Dollar), HG (Copper), GC (Gold), ZN (10-Year Treasury), and USD/CNH (Offshore Chinese Yuan). Each row shows the correlation coefficient, a dot-strength rating, and an auto-generated regime interpretation label.
Designed for intraday regime diagnosis. The default length of 78 bars covers one full RTH session on a 5-minute chart. Reducing to 20 bars produces a responsive rolling 2-hour window for real-time session reads. Increasing to 390 bars covers a full trading week for macro regime-level analysis.
Color coding: Bright green = strong positive correlation (r ≥ 0.6). Faded green = weak positive (r ≥ 0.2). Bright red = strong negative (r ≤ -0.6). Faded red = weak negative (r ≤ -0.2). Gray = neutral / no meaningful correlation.
Regime interpretation logic is instrument-specific:
CL: positive correlation = risk-on or geopolitical supply bid. Negative = stagflation regime, CL is the headwind.
6C: positive = tariff relief being priced. Negative = tariff fear active.
HG (Copper): positive = global growth and trade normalization. Negative = demand destruction.
GC (Gold): negative correlation to equities = uncertainty bid active, market does not trust the rally.
ZN (Bonds): negative = inflation/risk-on. Positive = deflation/risk-off flight to safety.
USD/CNH: this row is inverse — USD/CNH rising means CNH is weakening, meaning tariff fear is active. A negative correlation between NQ and USD/CNH therefore signals tariff relief. The regime label accounts for this inversion automatically.
ES: correlation to NQ reads index cohesion. Below 0.6 flags potential decoupling. Readings below 0.2 trigger a DECOUPLED label — the primary signal that session precision will be degraded and size should be reduced.
Primary use cases: Pre-session regime check, intraday regime shift detection, confirmation before adding size to a directional position, and identification of decoupled sessions where full-size trading is inappropriate. The footer row displays the current bar length, timeframe, and base symbol so the context is always visible at a glance. Indicator
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Simple Trend & Breakout System v6Key Features of the Strategy:
Multi-Timeframe (MTF) Trend Filter: The strategy uses a 240-period Exponential Moving Average (EMA) to determine the overall trend. Thanks to the MTF feature, the EMA is always anchored to the Daily (1D) chart by default, even if you switch your viewing chart to a Weekly timeframe. You can easily adjust the EMA length in steps of 5 within the settings.
Breakout Entry Logic: Instead of buying blindly, the script waits for bullish or bearish momentum (consecutive higher/lower closes). It then places a stop order 0.1% above the high (for longs) or below the low (for shorts) of the signal candle to catch the actual breakout.
Dynamic Percentage Trailing Stop: Exits are handled by a dynamic trailing stop set to 2.5% by default. It trails your position automatically, locking in profits and cutting losses, and is visualized directly on the chart (green line for longs, red line for shorts).
Realistic Backtesting Conditions: It includes a realistic trading commission of 0.01% per trade and allows you to set a custom Backtest Date Range (defaulting to 1998 - 2099).
Smart Data Handling (No Empty Drag): If you set the start year to 1922, but the asset data only begins in 1973, the script automatically detects the real start date. It calculates the CAGR accurately based only on the available data, preventing distorted, watered-down performance metrics.
Comprehensive StatTab: A dashboard in the bottom right corner gives you a direct comparison between your Strategy's performance and a pure Buy & Hold approach. It tracks Win Rate, Profit Factor, CAGR, Maximum Drawdowns, and the exact dates those drawdowns occurred.
Relative Equity Curve: An optional purple line that plots your strategy's equity growth directly onto the price chart. It anchors your starting capital to the asset's initial opening price, allowing you to visually see if your strategy is outperforming the underlying asset in real-time. Strategy
