[Algoros] Bitcoin Risk Heat MapBitcoin Risk Heat Map v2.0 — How to use
Purpose: A BTC daily risk “temperature” overlay that colors price from colder blue (lower risk) to hotter red (higher risk), plus an optional on-chart thermometer barometer.
1) Required setup (important)
Symbol : Best results on BITSTAMP:BTCUSD . Also supports BTCUSD, BTCEUR, BTCCHF, BTCGBP, BTCAUD, BTCJPY.
Timeframe : 1D (Daily) .
Chart type : Standard candles or line (avoid non-standard chart types).
If you pick the wrong symbol/timeframe/type, the script can show an on-chart warning message.
2) What the colors mean
Colder (blue/aqua/teal) : lower risk conditions (cooler market “temperature”).
Neutral (lime) : mid / balanced conditions.
Hotter (yellow/orange/red/maroon) : higher risk conditions (hot market “temperature”).
3) Visuals
Colored BTC price overlay : the BTC price line is colored by the current risk level.
Heat band : a colored band around price. Control thickness via Heatmap width .
Thermometer / Barometer table : enable/disable via Show Heatmap Barometer .
4) Settings
Heatmap width : controls how wide the colored band is drawn around price.
Show Heatmap Barometer : toggles the thermometer-style table at the bottom.
Component weights : you can change the weight of each sub-component to adjust the risk model emphasis.
5) Using it together with Bitcoin Profit Scout (recommended)
This combination makes perfect sense:
- Buy signals from Bitcoin Profit Scout in red/hot areas of the Bitcoin Risk Heat Map may be riskier than buy signals in colder blue areas.
- Vice versa, sell signals in red/hot areas might be stronger than sell signals in colder blue areas.
Example screenshot (Bitcoin Profit Scout + Bitcoin Risk Heat Map)
Free video walkthrough + deeper explanations
If you want a step-by-step video walkthrough and additional explanations/examples for Bitcoin Risk Heat Map, you can access them on our website (free): algoros.ai
Notes / expectations
This is not financial advice; always use risk management and position sizing.
The heat map is designed for daily BTC charts . Other symbols/timeframes will degrade results.
Sentiment
[Algoros] Altcoin Profit ScoutAltcoin Profit Scout — How to use
Purpose: A daily guide for managing altcoin pumps and taking profits. APS combines (1) Bitcoin Profit Scout (BPS) style BTC signals projected onto your altcoin chart for market context, and (2) altcoin-specific Sell Areas + Sell signals (yellow/orange/red) to help manage altcoin tops.
1) Required setup (important)
Symbol : Use this on the altcoin chart you want to manage (spot or perp). Best results on liquid pairs.
Timeframe : 1D (Daily) .
Chart type : Standard candles or line (avoid non-standard chart types).
If you use a non-daily timeframe or a non-standard chart type, APS shows an on-chart error message and signals may be missing.
2) What the lines mean (Sell Areas)
Yellow Sell Area : Early take-profit / first “overextended” zone.
Orange Sell Area : Stronger overextension; typically more aggressive profit-taking zone.
Red Sell Area : Extreme overextension / euphoria zone.
Important: The areas are zones , not instant “sell now” commands. Price entering an area is context; the sell triangle is the confirmation.
3) Signals (shapes) and how to act
Altcoin sell signals (above candles)
Yellow Sell (yellow triangle): First take-profit style signal (milder extension).
Orange Sell (orange triangle): Stronger take-profit signal (higher extension).
Red Sell (red triangle): Strongest take-profit signal (highest extension).
Optional: Bitcoin context signals
Larger, more “BTC-linked” altcoins (e.g., ETH, SOL, XRP) often follow Bitcoin’s broader swings. For that reason APS can display the Bitcoin Profit Scout BTC signal set (Small Buy / Buy / Strong Buy / Golden Buy / Blow-Off Buy and Sell / Sell (Blow-Off) / BM Sell) on your altcoin chart .
These are the same BTC signals from the BPS algorithm — they are not computed from the altcoin . Think of them as a “BTC backdrop” so you can time dip-buys and risk-off phases while watching an altcoin chart.
Why APS exists: Altcoins can sometimes keep accelerating even when BTC starts fading or turning down. APS therefore adds altcoin-specific sell signals on top of the BTC backdrop to help you manage those late-stage altcoin tops.
Practical usage idea (simple and robust)
Context first : Watch whether the altcoin price is entering the yellow/orange/red areas.
Wait for confirmation : Use the sell triangles as confirmation (not just touching an area line).
Scale out : Consider partial exits on yellow/orange and bigger reductions on red instead of all-in/all-out.
Use BTC context (optional): If the projected BTC context is flashing risk-off sells, be more selective with holding altcoin tops (altcoins can still run, but risk usually rises).
4) “Show Signals…” (reducing repaint surprises)
when they appear : Signals can appear intraday and may vanish before the daily candle closes.
on the day of action : Signals are shown after the daily candle closes (confirmed; plotted 1 day later).
Tip: If you want the cleanest, least-surprising signals, use on the day of action .
5) Inputs you’ll likely adjust
Show Sell Trigger Lines : Show/hide the yellow/orange/red Sell Area lines.
Show Altcoin Sell Signals : Show/hide the yellow/orange/red sell triangles.
Show Bitcoin Signals : Show/hide the BTC context signal set.
MA Short Term Trend and MA Height : Shape how quickly the sell areas track price.
Sell area length : Affects the ATR-based expansion for the higher sell areas.
BTC dominance period and BTC dominance divergence : Controls how strict the BTC.D divergence filter is for altcoin sell signals (more strict = fewer signals).
6) Alerts (TradingView)
Yellow Sell
Orange Sell
Red Sell
Price > Yellow Sell Area
Price > Orange Sell Area
Price > Red Sell Area
Free video walkthrough + deeper explanations
If you want a step-by-step video walkthrough and additional explanations/examples for Altcoin Profit Scout, you can access them on our website (free): algoros.ai
Notes / expectations
APS is designed for daily altcoin charts . Other timeframes will degrade results.
Altcoin sell signals use BTC-based context/filters (e.g., BTC trend and BTC dominance divergence). This can intentionally suppress signals during certain market regimes.
This is not financial advice; use risk management and position sizing.
[Algoros] Bitcoin Profit ScoutBitcoin Profit Scout v4.3.1 — How to use
Purpose: a BTC daily “buy the dips / sell the rips” guide using Buy/Sell Trigger Lines + confirmed signal shapes + optional Signal Barometer.
1) Required setup (important)
Symbol : Best results on BITSTAMP:BTCUSD . Also supports BTCUSD, BTCEUR, BTCCHF, BTCGBP, BTCAUD, BTCJPY.
Timeframe : 1D (Daily) .
Chart type : Standard candles or line (avoid non-standard chart types).
If you pick the wrong symbol/timeframe/type, BPS will show an on-chart error message and hide signals/lines.
2) What the lines mean
Buy Trigger Line : prices below this line are the “Buy Zone”.
Sell Trigger Line : prices above this line are the “Sell Zone”.
3) Market modes (visual cues)
Bull Market Mode (green emphasis): “Buy Zone” is less strict.
Bear Market Mode (teal/aqua emphasis): “Buy Zone” is stricter (deeper downside needed).
Hype Market Mode (red emphasis): sell logic can become stricter; special “blow-off” logic can apply.
4) Signals (shapes) and how to act
Buy signals (below candles)
Small Buy (green triangle, tiny): early/smaller dip buy.
Buy (green triangle, small): stronger dip buy.
Strong Buy (aqua/teal triangle): bear-market style buy (typically deeper undervaluation).
Golden Buy (yellow triangle): rare, deep-cycle accumulation style signal.
Blow-Off Buy (green diamond): buy signal during hype/blow-off conditions when a dip is attractive.
Sell signals (above candles)
Sell (red triangle, tiny): regular sell / take-profit signal.
Sell (Blow-Off) (red triangle, larger): blow-off top style sell signal.
BM Sell (red X-cross): bear-market “soft sell” / risk-off sell signal.
Practical usage idea (simple and robust)
Context first : use the trigger lines to see whether price is in Buy Zone or Sell Zone.
Wait for confirmation : act on the signal shapes (not just touching a line).
Scale in/out : consider multiple entries on buy signals and partial exits on sell signals (instead of all-in/all-out).
5) “Show Signals…” (reducing repaint surprises)
when they appear : signals can appear intraday and may vanish before the daily candle closes.
on the day of action : signals are shown after the daily candle closes (confirmed; plotted 1 day later).
Tip: If you want the cleanest, least-surprising signals, use on the day of action .
6) Signal Barometer (optional)
Show Signal Barometer : displays Buy and Sell likelihood for the current daily candle from 0–10.
How to interpret : 0 = unlikely, 10 = very likely / a signal is present.
Highlight historical barometer : visually highlights candles when the barometer is above your chosen threshold (commonly 8–10).
7) Alerts (TradingView)
Buy
Strong Buy
Golden Buy
Sell (includes bull sells, blow-off sells, and BM sells)
Altcoins
BPS is BTC-focused. If you want similar signal-style analysis on altcoin charts, use the separate Altcoin Profit Scout indicator (where available to you).
Free video walkthrough + deeper explanations
If you want a step-by-step video walkthrough and additional explanations/examples for Bitcoin Profit Scout, you can access them on our website (free): algoros.ai
Notes / expectations
BPS is designed for daily BTC charts . Using other timeframes or non-BTC symbols will degrade results and may hide signals.
Signals are based on multiple data sources (e.g., funding proxies and on-chain SOPR). Occasional data delays from providers can shift timing.
This is not financial advice; use risk management and position sizing.
Signal Quality Score (SQS) 🔹 Short Public Description
Anti Trap Confirmation is a non-directional market filter designed to identify higher-quality trading conditions.
It does not provide buy or sell signals and does not predict market direction.
The indicator helps traders avoid low-quality and trap-prone environments by analyzing price acceptance, volume behavior, and VWAP context.
Use this tool only as a confirmation layer alongside your own trading strategy and risk management.
🔹 Optimized Declaration (TradingView-Safe)
Anti Trap Confirmation evaluates market conditions to determine whether trading activity is statistically favorable.
It focuses on acceptance versus rejection behavior rather than signal generation or forecasting.
A visual marker appears only when multiple quality conditions align.
This script is not a trading system and does not guarantee performance or profitability.
All trading involves risk, and users are responsible for their own decisions.
Created by: Tarun Jangid
If you find this script useful, you may support the author by donating to encourage further development and research.
NYC ORB Multi-Symbol Scanner
**ORB Multi-Symbol Scanner**
Track Opening Range Breakouts across multiple symbols simultaneously with this comprehensive scanner designed for day traders.
**Features:**
✓ **6 Symbol Support**: ES, NQ, YM, GC, BTC, and RTY (Russell 2000)
✓ **Real-Time ORB Status**: ACTIVE (forming), READY (complete), or WAITING (pre-market)
✓ **Breakout Detection**: Instant LONG/SHORT signals when price breaks ORB levels
✓ **Near-Level Warnings**: "NEAR HIGH" or "NEAR LOW" alerts when price approaches breakout
✓ **ORB Range Display**: Shows the high-low range for each symbol
✓ **Live Price Feed**: Current price for each tracked symbol
✓ **Customizable Table**: Position, size, and symbol selection all adjustable
✓ **Individual & Combined Alerts**: Get notified for specific symbols or any breakout
20-Week SMA + Weekly RSI SignalWeekly Momentum Indicator
The 20-Week SMA + Weekly RSI Signals are used to track weekly momentum. The 20-Week SMA (Simple Moving Average) is used to track the general momentum, while the weekly RSI signals indicate the direction which the momentum is moving.
Flag signals are created once both the SMA and the RSI show clear signs of momentum.
Please note that the signals are not always correct. So it is typically best to wait for confirmation candles in order to confirm bias.
20 Week SMA
14 RSI
Gold Premium Histogram
Compares Altins1 to gram gold in turkish lira to see the deviation and suggesting when to arbitrage
Sri - MACD with Smoothed EMA Sri – MACD with Smoothed EMA (Auto-TF, Offset, Sensitivity Engine)
This indicator is an enhanced and more flexible version of the classic MACD, redesigned for traders who want higher-level control, smoother trend detection, and improved readability across different chart timeframes.
Unlike the standard MACD, this version introduces Auto-Timeframe Logic, Sensitivity Scaling, and a Smoothed EMA Envelope around the MACD line, giving traders a more consistent and stable momentum view across intraday and higher-timeframe environments.
✨ What Makes This MACD Unique
This script is not a simple recreation of the open-source MACD.
It adds multiple proprietary layers that change the underlying behaviour:
1. Auto-Timeframe Engine
The indicator automatically switches the MACD timeframe depending on chart conditions:
If the chart is ≤ 15 minutes, the MACD calculation automatically uses 1-Hour (60-min) data.
Otherwise, it uses the chart’s native timeframe.
This makes the signal more stable on low-timeframe charts and reduces noise.
This feature is not available in standard MACD implementations.
2. Sensitivity-Based Scaling (Trend Zoom)
The script includes a Zoom engine that “amplifies or compresses” MACD and Signal values:
Higher sensitivity highlights micro-swings
Lower sensitivity smooths out noise for cleaner macro-signals
This custom scaling approach provides a different look & feel than standard MACD outputs.
3. Hi-Line Offset (Vertical Shift Controller)
Traders can vertically shift the MACD cluster up or down using an offset value.
This is extremely useful when:
Combining multiple oscillators in the same pane
Wanting more visual space
Aligning the indicator with multi-indicator layouts
This is also not found in the standard MACD.
4. Smoothed MACD EMA Overlay (50-EMA Cloud)
The script optionally adds a Smoothed MACD EMA, forming a type of momentum envelope:
Helps track longer-term MACD momentum
Filters fake crossovers
Highlights periods where MACD momentum is flattening or accelerating
This extra smoothed layer provides a proprietary visual trend-tracking component.
5. Color-Coded MACD–Signal Fill
Areas between MACD & signal are shaded:
Blue when MACD is above Signal (bull momentum)
Orange when MACD is below Signal (bear momentum)
This makes momentum direction instantly visible at a glance.
📌 How the Indicator Works (Conceptual Explanation)
Without revealing proprietary code, here is the conceptual flow:
Determine the operative timeframe
A custom auto-TF engine selects a 60-minute MACD for smaller charts or remains native on higher charts.
Compute the MACD and Signal lines
Using user-selected MA types (EMA or SMA).
Apply Sensitivity Scaling
Both MACD and Signal values are zoomed or compressed using a sensitivity factor.
Apply Vertical Offset
The entire MACD structure is shifted up or down using a Hi-Line Offset.
Smooth the MACD using a 50-period EMA
This forms a momentum backbone that helps identify trend continuation vs exhaustion.
Plot MACD, Signal, Smoothed EMA, and Color-Fill
The indicator visually represents trend health, crossovers, divergence behavior, and momentum cycles.
📊 How to Use the Indicator
Trend Direction
MACD > Signal → Bullish momentum
MACD < Signal → Bearish momentum
Trend Strength
Large separation between MACD & Signal → Strong push
Tight clustering → Consolidation or transition zone
Smoothed EMA Interpretation
MACD above Smoothed EMA → Uptrend bias
MACD below Smoothed EMA → Downtrend bias
When Smoothed EMA flattens → Upcoming trend pause or reversal
Sensitivity Settings
Scalpers use higher sensitivity
Swing traders use lower sensitivity
Position traders use default or minimal sensitivity
Offset Use-Cases
Combine with RSI / PMO in the same pane
Manage layout when using multi-oscillator templates
Improve clarity on smaller monitors or laptop screens
Buy / Sell Volume LabelsINDICATOR NAME:
Buy/Sell Volume Labels
DESCRIPTION:
Buy/Sell Volume Labels displays real-time buying and selling volume with dynamic color-coded labels that highlight market dominance. The indicator automatically emphasizes the dominant side (buy or sell) with bright green or red backgrounds, while the non-dominant side fades to gray for instant visual clarity.
Key Features:
- Dynamic Color Coding: Dominant volume side displays in bright green (buy) or red (sell), non-dominant side in gray
- Trend Indicator: Optional "Bullish Trend", "Bearish Trend", or "Neutral" label shows current market bias
- Flexible Display Options: Choose to show percentages only, volume only, or both
- Customizable Position: Place labels anywhere on chart (top, center, bottom; left, center, right)
- Adjustable Size: Six size options from Tiny to Huge, including Auto
- Lookback Period: Calculate volume for current bar or sum across multiple bars
- Neutral Threshold: Define when market is considered neutral vs. trending
How It Works:
- The indicator calculates buying and selling volume based on where price closes within each bar's range. When buying volume dominates, the Buy label turns bright green with black text while the Sell label turns gray. When selling dominates, the Sell label turns bright red with white text while the Buy label turns gray. This makes it immediately obvious which side controls the market.
Perfect For:
- Day traders and scalpers on futures (/MNQ, /ES, /NQ)
- Identifying accumulation vs. distribution phases
- Confirming trend strength and reversals
- Quick visual assessment of market pressure
- All timeframes from tick charts to daily
Settings:
- Header location (9 positions)
- Display mode (Volume, Percent- age, or Both)
- Table size (Tiny to Huge + Auto)
- Lookback period (bars)
- Trend label toggle
- Neutral threshold percentage
Created by NPR21 for the TradingView community.
Elliott Wave Risk MetricThis indicator combines two complementary risk engines into a single framework. Engine A (the BTC Risk Metric) produces a normalized 0–1 risk line by measuring Bitcoin’s logarithmic distance from a long-term trend (a 377-day simple moving average), scaled by time to account for Bitcoin’s exponential growth. This core line is excellent at identifying low-risk accumulation zones near major cycle bottoms and provides a consistent, regime-aware baseline that allows different market cycles to be compared on the same scale.
Engine B evolves the model by adding an Elliott Wave– and Fibonacci-based extension framework. Instead of relying on momentum or trend deviation, it measures how far price has extended from meaningful local and macro anchor lows, using prior impulse lengths as the projection unit. These extensions are mapped into Fibonacci risk zones and converted into a 0–1 extension risk score. The plotted line remains Engine A’s core risk, but its colour is driven by a weighted blend of Engine A and Engine B (default 30% / 70%), allowing late-cycle price peaks—especially fifth waves—to correctly display elevated risk even when momentum is fading.
Why the Bitcoin Risk Metric needed to evolve
The original Bitcoin Risk Metric is structurally biased toward momentum and trend deviation, which makes it very effective at identifying cycle lows but less effective at distinguishing relative risk between late-cycle highs. In strong bull markets, third waves often produce the highest momentum and the greatest distance from the long-term average, causing the metric to peak early. As the market transitions into later fifth-wave advances, price may reach higher levels, but with weaker momentum and slower rate-of-change, leading the metric to print lower highs despite price being objectively riskier.
In other words, the original metric answers the question “How stretched is price relative to its long-term trend?” rather than “How extended is price within its current market structure?” This results in under-warning near late-cycle tops and blow-off phases, particularly in assets that move in clear impulsive waves like Bitcoin. By adding Engine B, the model now incorporates structural extension risk, ensuring that risk remains elevated when price is far advanced from meaningful cycle lows—even if momentum has already rolled over. The result is an evolved risk framework that preserves the strengths of the original metric while correcting its primary blind spot at major and late-stage market tops.
Crypto Exhange Rank BTC/ETHShows the rank from 1-5 between the main spot pairs of crypto exchanges. Works for BTC and ETH.
Coinbase PremiumShows the Coinbase Premium over Binance adjusted for USDT peg. Works for ETH and BTC.
Best RSI Unified (SIIT) By Nagaraj HiremathShows RSI with Divergence and RSI Trend in current Time Frame and Next TF and shows Trend direction when to Buy and sell . AllInOne RSI Unified - SIIT By Nagaraj Hiremath
FOMO/PANIC - TheTechnicalTraders.comTheTechnicalTraders.com Exclusive Extreme Sentiment Indicator.
Shows a real-time level of FOMO buying and Panic selling.
When the indicator is 3 or higher, the market is reaching an extreme.
Only to be used on the 30-minute regular hours trading chart.
Volume Pulse Dots Relative Volume at a Glance
Volume Pulse Dots is a lightweight, price-overlay indicator designed to highlight unusual volume activity directly on the chart, without adding clutter or a separate volume pane.
Instead of raw volume bars, this script uses relative volume (rVol) — current volume compared to a moving average of recent volume — to visually flag moments when participation meaningfully deviates from normal.
How It Works
Relative volume is calculated as:
Current volume ÷ Volume moving average (user-defined length)
Based on this ratio, small dots are plotted on the chart:
• High relative volume (green dot below bar)
Signals increased participation compared to recent activity. Often appears during momentum moves, breakouts, or strong continuation candles.
• Very high relative volume (larger cyan dot below bar)
Indicates extreme participation. Common near major breakouts, capitulation candles, or key inflection points.
• Low relative volume (gray dot above bar)
Highlights weak participation. These candles often represent fake moves, fading momentum, or price drifting without conviction.
Dots are intentionally subtle and plotted directly on price to keep context clear while staying out of the way.
How to Use It
This indicator is not a standalone signal generator. It works best when combined with:
• VWAP and EMA structure
• Key support and resistance levels
• Candlestick context (range, wicks, follow-through)
• Price location relative to the open, highs, or prior day levels
Examples:
• High rVol dots near VWAP can confirm real participation
• Very high rVol dots at extended levels may signal exhaustion
• Low rVol dots during breakouts often warn of weak follow-through
Customization
You can adjust:
• Volume moving average length
• Thresholds for high, very high, and low relative volume
• Optional display of the rVol value in the status line (no extra pane)
Design Philosophy
• No separate volume pane
• No alerts or signals
• No repainting
• Minimal visual footprint
This tool is meant to quietly surface information that experienced traders already look for, without distracting from price.
Trend Signal Pro v2.1Trend Signal Pro is a technical analysis indicator designed to help traders
identify market trend direction and potential entry points.
The indicator analyzes price behavior using standard candlestick data
and applies trend-filtering logic to reduce false signals during
sideways market conditions.
Signals are generated only when multiple internal conditions align,
making it suitable for intraday and swing trading across different markets.
This indicator does not repaint and should be used as a decision-support tool,
not as a standalone trading system. Proper risk management is advised.
Institutional Frontrunner w/ PCR & VIX - Fixed Distance LabelsUse this script to evaluate if buying or selling is indicated based on a variety of metrics surrounding momentum and volume or institutional traders.
JMMF3 PANTOKRATOR V1.5.4 [update]This script implements an advanced market reading and diagnostic system based on a deterministic state architecture. Its design follows formal systems engineering principles and structural evaluation criteria, with the purpose of identifying valid operational contexts and vetoing those that do not meet the required conditions.
The system does not perform predictions and does not provide investment recommendations. Its function is strictly analytical and intended to support user decision making by offering an objective framework for market assessment across different operational states.
The script evaluates multiple market dimensions in a synchronized manner and only recognizes states that are fully validated by its internal architecture. There is no automated discretion and no trade execution. The user retains full responsibility for any operational decision at all times.
Access to this script is private and granted exclusively by invitation. Its use is limited to personal purposes and is non transferable. Any form of reproduction, redistribution, or reverse engineering is strictly prohibited.
This development does not constitute financial advice nor an automated trading system.
This script is available in both Spanish and English versions.
DLR - Daily Liquidity Range Framework (v1.3)Daily Level Ranges
This strategy targets discounted premiums for buying Call/Put Options in discounted areas based on liquidity levels that form ranges.
Opening Range creates the strongest liquidity for the day.
Premarket Highs/Lows are strong liquidity points.
Previous Day Highs/Lows are reliable liquidity points.
PMH/PML and PDH/PDL may alternate positions relative to OR.
* Discounted Calls are taken under the OR in Bullish conditions
* Discounted Puts are taken above the OR in bearish conditions.
- Momentum Calls are taken at the OR in Bullish Conditions
- Momentum Puts are taken at the OR in Bearish Conditions
Time Pressure ZonesTime Pressure Zones is a multi‑purpose candle and volume‑based indicator that highlights moments when markets are likely being driven by urgency rather than routine trading flow.
**Overview**
Detects sequences of strong, one‑directional candles accompanied by volume spikes to approximate institutional time pressure (forced buying or selling).
Paints subtle background zones, labels, and a net‑pressure histogram so you can see when aggressive flow is building or exhausting across any instrument and timeframe.
**Core Logic**
A bar is tagged “strong” when its real body occupies at least a user‑defined percentage of the full high‑low range, filtering out indecision candles and long‑wick noise.
Volume is compared to a rolling 20‑bar average; only bars with volume above a configurable multiple are treated as meaningful participation, which makes the tool adapt to different symbols and sessions.
The script counts consecutive bars that are both strong and high‑volume in the same direction, then flags a time‑pressure event once a set fraction of the lookback has been reached (e.g., 2 out of 3, 3 out of 5).
**Visual Outputs**
Background shading: green or red bands mark active bullish or bearish time‑pressure windows without overpowering other tools on the chart.
On‑chart labels: “↑ Time Pressure” and “↓ Time Pressure” appear only on the first bar of a new pressure sequence, ideal for alerts and discretionary entries.
Net Pressure histogram: plots the difference between bullish and bearish streak counts, giving a quick at‑a‑glance sense of which side currently dominates.
**Sessions and News**
Uses UTC‑based logic to highlight London and New York open and close windows, where institutional flows and intraday “deadline” behavior tend to cluster.
Includes a manual News Window toggle so you can mark high‑impact event periods (CPI, FOMC, NFP, etc.), aligning tape‑based urgency with scheduled catalysts.
**How To Use**
Look to join moves when fresh time‑pressure labels print into session opens, breakouts, or key levels, rather than fading them.
Tune the three main inputs per market and timeframe: lower thresholds for choppy or thin markets, and higher body/volume requirements for very liquid symbols like major indices or BTC pairs.
Aggregate Bull & Bear IndexAggregate Bull and Bear Index
The Aggregate Bull and Bear Index represents a systematic approach to measuring market sentiment through the aggregation of multiple fundamental market factors. This indicator draws conceptual inspiration from the Bank of America Bull and Bear Indicator, a widely followed institutional sentiment gauge that has demonstrated significant predictive value for market turning points over multiple market cycles (Hartnett, 2019). While the original Bank of America indicator relies on proprietary institutional data flows and internal metrics that remain inaccessible to individual investors, the Aggregate Bull and Bear Index provides a methodologically similar framework using publicly available market data, thereby democratizing access to sentiment analysis previously reserved for institutional participants.
The theoretical foundation of sentiment based investing rests on decades of behavioral finance research demonstrating that market participants systematically exhibit predictable psychological biases during periods of extreme optimism and pessimism. Shiller (2000) documented how irrational exuberance manifests in asset prices through feedback loops of investor enthusiasm, while Kahneman and Tversky (1979) established that human decision making under uncertainty deviates substantially from rational expectations. These behavioral patterns create opportunities for contrarian strategies that exploit the tendency of crowds to overreact at market extremes. The Aggregate Bull and Bear Index quantifies these psychological states by synthesizing information from diverse market segments into a unified scale ranging from zero to ten, where readings below two indicate extreme fear and readings above eight signal extreme greed.
Methodology and Calculation Framework
The methodology underlying the Aggregate Bull and Bear Index incorporates statistical normalization techniques that transform raw market data into comparable standardized scores. Each component factor is processed through a calculation that measures how far current values deviate from historical norms, effectively capturing whether specific market metrics exhibit unusual readings relative to their own history. These normalized components are then aggregated using a weighting scheme designed to balance information from different market segments while minimizing noise and false signals. The final composite undergoes percentile ranking over a trailing lookback period to produce the familiar zero to ten scale that facilitates intuitive interpretation.
The indicator incorporates several important features designed to enhance signal quality and reduce the probability of acting on spurious readings. A consensus filter examines whether multiple underlying components align in the same direction, adding weight to signals when broad agreement exists across different market factors and discounting readings that rest on narrow evidence. Dynamic threshold adjustment allows the extreme zones to adapt to changing market volatility regimes, recognizing that the appropriate definition of extreme varies depending on ambient market conditions. These refinements reflect lessons learned from decades of quantitative finance research on signal processing and regime detection.
Professional Application and Portfolio Integration
Professional portfolio managers have long recognized the value of sentiment indicators as a complementary tool to fundamental and technical analysis. The fundamental insight underlying sentiment based strategies is elegantly simple yet empirically robust. When market participants become uniformly bullish, marginal buyers become exhausted and the probability of price declines increases substantially. Conversely, when pessimism reaches extreme levels, forced selling creates attractive entry points for patient capital. Bank of America research found that their Bull and Bear Indicator generated a remarkable track record when deployed as a contrarian signal, with extreme fear readings historically preceding positive forward returns in equity markets (Bank of America Global Research, 2020). The Aggregate Bull and Bear Index applies this same contrarian logic while adapting the methodology to accommodate the data constraints facing individual investors.
For institutional investors operating with fiduciary responsibilities and substantial capital, the Aggregate Bull and Bear Index serves as one input among many in comprehensive risk management frameworks. Large asset managers might use extreme readings to trigger portfolio review processes, stress testing exercises, or adjustments to tactical allocation overlays. The indicator proves particularly valuable when it diverges from consensus expectations, as such divergences often precede meaningful market inflections. Hedge fund managers implementing systematic strategies can incorporate the index as a conditioning variable that adjusts position sizing or strategy weights based on the prevailing sentiment environment.
The integration of sentiment analysis into investment practice finds support in the concept of informational efficiency and the limits thereof. While efficient market hypothesis suggests that prices reflect all available information, the behavioral finance literature demonstrates that information processing by market participants exhibits systematic biases that create temporary mispricings (Barberis and Thaler, 2003). Sentiment indicators capture the psychological dimension of this information processing, providing insight into how market participants collectively interpret and react to fundamental developments. Extreme sentiment readings often indicate that psychological factors have pushed prices away from levels justified by fundamentals alone, creating opportunities for those willing to act against prevailing market opinion.
Practical Implementation for Individual Investors
The practical implementation of the indicator follows straightforward principles that both sophisticated institutions and individual retail traders can apply within their existing investment frameworks. When the index falls into the extreme fear zone below a reading of two, this suggests that market participants have become excessively pessimistic and that risk assets may offer favorable risk reward characteristics. Traders might consider this an opportune moment to increase equity exposure or reduce hedging positions. When the index rises into the extreme greed zone above eight, the opposite dynamic applies and a defensive posture becomes prudent. This could manifest as reducing equity allocations, increasing cash reserves, or implementing protective hedging strategies. The neutral zone between these extremes suggests no strong directional bias from a sentiment perspective, during which time other analytical frameworks should take precedence in decision making.
Individual retail investors can derive substantial benefit from the indicator even without sophisticated infrastructure or large capital bases. The most straightforward application involves treating extreme readings as alerts that warrant careful examination of existing portfolio positioning. A reading in the extreme fear zone might prompt consideration of whether recent market declines have created opportunities to deploy excess cash or rebalance toward equities. A reading in the extreme greed zone could trigger review of whether current equity exposure exceeds target allocations and whether risk reduction measures merit consideration. Importantly, the indicator should inform rather than dictate investment decisions, serving as one valuable perspective within a broader analytical framework.
Retail investors frequently find themselves at a psychological disadvantage during market extremes because emotional responses to portfolio losses or gains often prompt actions contrary to long term wealth accumulation. The academic literature on investor behavior consistently documents that individual investors tend to buy near market peaks when confidence runs highest and sell near market bottoms when fear dominates (Barber and Odean, 2000). A systematic sentiment indicator provides an objective framework for recognizing these emotional extremes and consciously acting against natural psychological impulses. By externalizing the assessment of market mood into a quantifiable metric, investors create psychological distance from their own emotional state and gain perspective on the collective sentiment environment.
The decision to implement a sentiment indicator within an investment process requires thoughtful consideration of how it complements existing analytical approaches. Technical analysts may find that sentiment readings help contextualize chart patterns and momentum signals, with extreme fear adding conviction to bullish technical setups and extreme greed warranting caution even when price trends appear strong. Fundamental investors can use sentiment as a timing tool that helps avoid the common mistake of being right on valuation but wrong on timing. Quantitative investors might incorporate sentiment factors into multi factor models or use them to adjust position sizing across strategies.
Trading Behavior and Strategy Characteristics
The Aggregate Bull and Bear Index employs a contrarian investment methodology that fundamentally diverges from trend following approaches prevalent in systematic trading. The trading logic rests upon the principle of accumulating positions when collective fear pervades market sentiment and liquidating those positions when greed dominates investor psychology. This approach stands in direct opposition to momentum strategies that amplify existing market movements rather than positioning against them.
The observation that the indicator frequently initiates long positions despite subsequent downward price movement represents not a flaw but an inherent characteristic of contrarian strategies. When the indicator signals extreme fear, this indicates that market participants have already engaged in substantial selling and pessimistic expectations have become embedded in asset prices. However, this emphatically does not guarantee that the ultimate trough has been reached. Fear can intensify, panic selling can escalate, and fundamental deterioration can trigger additional price declines before stabilization occurs. The indicator identifies phases where the statistical probability distribution of future returns appears favorable rather than pinpointing exact inflection points. Academic research by De Bondt and Thaler (1985) demonstrated that markets systematically overreact to both positive and negative information, creating opportunities for patient contrarian investors willing to endure interim volatility.
Risk Profile and Investment Considerations
This characteristic produces a distinctive risk profile that investors must thoroughly comprehend before implementation. The primary danger manifests in what practitioners colloquially term catching a falling knife. Purchasing assets during declining markets exposes capital to potentially severe interim drawdowns even when the ultimate investment thesis proves correct. The backtest evidence reveals numerous instances where positions experienced double digit percentage declines before eventually generating positive returns or triggering exit signals. Investors lacking the psychological fortitude to maintain positions through such adversity will inevitably abandon the strategy at precisely the wrong moment, crystallizing losses that patient adherents would have recovered. Behavioral research by Odean (1998) documented that individual investors exhibit a strong disposition effect, holding losing positions too long in some contexts while selling winners prematurely, yet paradoxically abandoning systematic strategies during drawdowns when discipline matters most.
The temporal dimension of contrarian investing demands particular attention. Unlike trend following strategies that can generate returns relatively quickly by riding established momentum, contrarian approaches often require extended holding periods before mean reversion materializes. The indicator may signal fear and initiate positions that subsequently experience weeks or months of continued decline before sentiment shifts and prices recover. This extended timeline conflicts with human psychological preferences for immediate gratification and creates substantial opportunity for doubt and strategy abandonment. Investors must recognize that the strategy optimizes for terminal wealth accumulation over extended horizons rather than minimizing short term discomfort.
A critical risk factor involves the possibility of genuine regime changes that invalidate historical relationships. While extreme fear readings have historically preceded favorable forward returns, this pattern assumes that pessimism eventually proves excessive and fundamentals stabilize or improve. In scenarios involving structural economic transformation, permanent impairment of earnings power, or systemic financial crisis, fear may prove entirely justified rather than excessive. The indicator cannot distinguish between irrational panic creating buying opportunities and rational recognition of deteriorating fundamentals. This limitation underscores the importance of using the indicator as one input among many rather than as a standalone decision mechanism.
Risk management applications deserve particular attention given the indicator's historical tendency to signal market stress before price declines fully materialize. Portfolio managers charged with protecting capital during drawdowns can use rising greed readings as an early warning system that justifies defensive measures such as reducing beta exposure, increasing cash allocations, or purchasing portfolio protection through options strategies. The contrarian nature of the indicator means that protective action occurs when markets appear strongest rather than weakest, avoiding the common trap of implementing risk reduction after substantial losses have already occurred.
Opportunity Set and Compounding Benefits
The opportunity set presented by contrarian sentiment investing derives from persistent behavioral biases that academic research has extensively documented. Extrapolation bias leads investors to assume recent trends will continue indefinitely, causing excessive optimism after gains and excessive pessimism after losses (Greenwood and Shleifer, 2014). Herding behavior amplifies these tendencies as investors observe and mimic the actions of others, creating self reinforcing cycles of buying or selling that push prices away from fundamental values. The Aggregate Bull and Bear Index systematically exploits these patterns by positioning against the prevailing emotional consensus.
The compounding benefits of buying during fear merit emphasis. When the indicator signals extreme pessimism, asset prices by definition trade at depressed levels relative to recent history. Investors who accumulate positions at these reduced valuations capture not only potential price recovery but also enhanced long term compound returns from reinvesting dividends and earnings at favorable prices. This mathematical advantage compounds over decades, explaining why legendary investors from Benjamin Graham to Warren Buffett have emphasized the importance of purchasing during periods of market distress despite the psychological difficulty such actions entail.
Investor Suitability and Implementation Requirements
Regarding suitability, the Aggregate Bull and Bear Index aligns most appropriately with investors possessing specific characteristics. First, a genuinely long term investment horizon measured in years rather than months proves essential. The strategy will underperform during extended bull markets when momentum approaches dominate and will experience painful interim drawdowns during crisis periods. Only investors capable of maintaining positions through these challenging phases will capture the strategy's full return potential. Second, psychological resilience to act against consensus and tolerate portfolio volatility represents a prerequisite. Research by Goetzmann and Kumar (2008) demonstrated that most individual investors lack the temperament for contrarian strategies despite their theoretical appeal. Third, sufficient financial reserves to avoid forced liquidation during drawdowns ensures that temporary price declines do not become permanent capital impairment.
The indicator proves less suitable for investors seeking steady returns with minimal volatility, those with short investment horizons or imminent liquidity needs, and individuals whose emotional responses to portfolio fluctuations compromise rational decision making. Institutional investors with quarterly performance pressures may find the strategy incompatible with their governance constraints despite its long term merits. Retirees depending on portfolio withdrawals must carefully consider whether interim drawdowns could force disadvantageous liquidations.
For appropriate investors, the Aggregate Bull and Bear Index offers a systematic framework for implementing time tested contrarian principles that have generated superior long term returns across multiple market cycles. By externalizing sentiment assessment into an objective metric, the indicator helps investors overcome the natural human tendency to capitulate at market bottoms and chase performance at market tops. The strategy demands patience, discipline, and genuine long term orientation, but rewards those characteristics with the potential for meaningful wealth accumulation over extended investment horizons.
Proprietary Elements and Limitations
The proprietary aspects of the indicator's construction reflect both practical and theoretical considerations. From a practical standpoint, maintaining certain methodological details as proprietary preserves the informational advantage that the indicator provides and prevents degradation of signal quality that might occur if widespread adoption prompted market participants to trade directly against the underlying components. From a theoretical perspective, the specific parameter choices and weighting schemes represent empirical findings from extensive research that constitute intellectual property developed through substantial effort.
Academic research on sentiment indicators provides encouraging evidence regarding their predictive value while appropriately acknowledging limitations. Baker and Wurgler (2006) demonstrated that investor sentiment predicts the cross section of stock returns, with high sentiment periods followed by lower returns for speculative stocks prone to overvaluation during euphoric conditions. Brown and Cliff (2005) found that sentiment measures contain information about near term market returns beyond that captured by traditional risk factors. However, the same literature cautions that sentiment signals exhibit variable lead times and occasional false positives, reinforcing the importance of using such indicators as part of comprehensive analytical frameworks rather than standalone trading systems.
The Aggregate Bull and Bear Index ultimately represents an attempt to bridge the gap between institutional grade sentiment analysis and the tools available to broader investor populations. By providing a systematic framework for assessing collective market psychology, the indicator empowers users to recognize emotional extremes and consider contrarian positioning when conditions warrant. The historical tendency of markets to reverse from extreme sentiment readings creates opportunities for those willing to act against crowd psychology, while the indicator's multi factor construction and quality filters help distinguish genuine extremes from temporary fluctuations. Whether deployed by professional money managers seeking to refine risk management practices or individual investors striving to overcome behavioral biases, the Aggregate Bull and Bear Index offers a valuable perspective on the eternal struggle between fear and greed that drives financial markets.
References
Baker, M. and Wurgler, J. (2006) Investor sentiment and the cross section of stock returns. The Journal of Finance, 61(4), pp. 1645 to 1680.
Bank of America Global Research (2020) The Bull and Bear Indicator: A contrarian timing tool. Bank of America Securities Research Report.
Barber, B.M. and Odean, T. (2000) Trading is hazardous to your wealth: The common stock investment performance of individual investors. The Journal of Finance, 55(2), pp. 773 to 806.
Barberis, N. and Thaler, R. (2003) A survey of behavioral finance. Handbook of the Economics of Finance, 1, pp. 1053 to 1128.
Brown, G.W. and Cliff, M.T. (2005) Investor sentiment and asset valuation. The Journal of Business, 78(2), pp. 405 to 440.
De Bondt, W.F.M. and Thaler, R. (1985) Does the stock market overreact? The Journal of Finance, 40(3), pp. 793 to 805.
Goetzmann, W.N. and Kumar, A. (2008) Equity portfolio diversification. Review of Finance, 12(3), pp. 433 to 463.
Greenwood, R. and Shleifer, A. (2014) Expectations of returns and expected returns. The Review of Financial Studies, 27(3), pp. 714 to 746.
Hartnett, M. (2019) Flow Show: Bull and Bear Indicator methodology and applications. Bank of America Merrill Lynch Investment Strategy.
Kahneman, D. and Tversky, A. (1979) Prospect theory: An analysis of decision under risk. Econometrica, 47(2), pp. 263 to 291.
Odean, T. (1998) Are investors reluctant to realize their losses? The Journal of Finance, 53(5), pp. 1775 to 1798.
Shiller, R.J. (2000) Irrational Exuberance. Princeton University Press.
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Delta Hedging Pressure📊 COT Delta Hedging Pressure – Institutional Sentiment Indicator
This indicator visualizes institutional hedging pressure by aggregating delta-style positioning into a clean, session-aware sentiment framework.
Instead of guessing direction, it shows who is likely hedging vs. pressing, helping traders align intraday execution with higher-timeframe positioning.
🔍 What This Indicator Does
Calculates cumulative hedging pressure using price-based delta logic
Classifies market state into:
Bullish (positive hedge pressure)
Bearish (negative hedge pressure)
Neutral (balanced flow)
Resets cleanly by session or user-defined period
Visualizes sentiment using:
Background shading
Labels
Cumulative plots
🧠 How Traders Use It
Directional bias filter (trade only with sentiment)
Context for FVGs, liquidity raids, and pullbacks
Avoids chop by identifying neutral hedge conditions
Pairs especially well with:
XAUUSD
Index CFDs
Futures / CFD hybrids
⚙️ Key Features
Session-aware cumulative logic
Adjustable sensitivity and lookback
Clean visual design (no clutter)
Non-repainting calculations
Works on 1m → HTF
⚠️ Important Notes
This is a context tool, not a signal generator
Best used alongside price structure and risk management
Designed for discipline and alignment, not overtrading
🎯 Ideal For
Scalpers & intraday traders
Traders using:
Fair Value Gaps (FVG)
Liquidity sweeps
Session-based models
Traders transitioning from prop logic to personal capital
🧩 Final Thought
This indicator answers one question:
“Is the market hedging or pressing — and should I be aggressive or patient?”
If you trade with structure, this keeps you on the right side.






















