CM Indicator About Indicator:-
1) This is best Indicator for trend identification.
2) This is based on 42 EMA with Upper Band and Lower bands for trend identification.
3) This should be used for Line Bar chart only.
4) Line bar chart should be used at 1 hour for 15 line breaks.
How to Use:-
1) To go with trend is best use of this indicator.
2) This is for stocks and options not for index. Indicator used for Stocks at one hour and options for 10-15 minutes line break.
3) There will be 5% profitability defined for each entry, 3 entries with profit are best posible in same continuous trend 4 and 5th entry is in riskier zone in continuous trend.
4) Loss will only happen if there is trend reversal.
5) Loss could only be one trade of profit out of three profitable trades.
6) Back tested on 200 stocks and 100 options.
Indicatori e strategie
cd_RSI_Divergence_CxGeneral:
The Relative Strength Index (RSI) is a momentum oscillator widely used by traders in price analysis. In addition to showing overbought/oversold zones, divergences between RSI and price are also tracked to identify trading opportunities.
The general consensus is that oscillators alone are not sufficient for entries and should be evaluated together with multiple confirmations.
This oscillator is designed as an additional confirmation/compatible tool for strategies that already use higher time frame (HTF) sweeps and lower time frame (LTF) confirmations such as Change in State Delivery (CISD) or Change of Character (CHOCH).
Features:
While RSI oscillators are commonly displayed in line format (classic), this indicator also offers candlestick-style visualization.
Depending on the selected source, period length, and EMA length, RSI can be displayed as lines and/or candlesticks.
Divergence detection & tracking:
Price and RSI values are monitored on the chosen higher time frame (from the menu) to determine highs and lows. For divergence display, the user can choose between two modes:
1- Alignment with HTF Sweep
2- All
1 - Alignment with HTF Sweep:
First, the price must sweep the previous high/low of the candle on the HTF (i.e., break it) but fail to continue in that direction and return inside (sweep).
If this condition is met, RSI values are checked:
If price makes a high sweep but RSI fails to make a new high → divergence is confirmed.
If price makes a low sweep but RSI fails to make a new low → divergence is confirmed.
Divergence is then displayed on the chart.
2 - All:
In this mode, sweep conditions are ignored. Divergence is confirmed if:
Price makes a new high on HTF but RSI does not.
RSI makes a new high on HTF but price does not.
Price makes a new low on HTF but RSI does not.
RSI makes a new low on HTF but price does not.
Menu & Settings:
RSI visualization (source + period length + EMA period length)
Option to choose classic/candlestick style display
Color customization
Higher time frame selection
Adjustable HTF boxes and table display
Final notes:
This oscillator is designed as an additional confirmation tool for strategies based on HTF sweep + LTF CISD/CHOCH confirmation logic. The chosen HTF in the oscillator should match the time frame where sweeps are expected.
Divergence signals from this oscillator alone will not make you profitable.
For spot trades, monitoring sweeps and divergences on higher time frames is more suitable (e.g., Daily–H1 / Weekly–H4).
My personal usage preferences:
Entry TF: 3m
HTF bias: Daily + H1
Sweep + CISD: 30m / 3m
Market Structure: 3m
RSI divergence: HTF = 30m
If all of them align bullish or bearish ( timeframe alignment ), I try to take the trade.
I’d be glad to hear your feedback and suggestions for improvement.
Happy trading!
OMN Heikin Ashi Candle Direction Reversal AlertThis is a indicator to let you know once Heikin Ashi candle has changed direction compared to the candle before it. Set an alert on the indicator to get an audible alert.
Justin's Bitcoin Power Law PredictorJustin's MSTR Powerlaw Price Predictor is a Pine Script v6 indicator for TradingView that adapts Giovanni Santostasi’s Bitcoin power law model to forecast MicroStrategy (MSTR) stock prices. Using the formula Price = A * (daysSinceGenesis)^B, it calculates fair, upper, and floor prices with constants A_fair = 1.16e-17, A_floor = 0.42e-17, and B = 5.82, starting from Bitcoin’s genesis (January 3, 2009). The script plots these prices, displays values in a table.
Source: www.ccn.com
Justin's MSTR Powerlaw Price PredictorJustin's MSTR Powerlaw Price Predictor is a Pine Script v6 indicator for TradingView that adapts Giovanni Santostasi’s Bitcoin power law model to forecast MicroStrategy (MSTR) stock prices. The price prediction is based on the the formula published in this article:
www.ccn.com
Setup Cripto EMA + Volume//@version=5 indicator("Sinais Multi-Cripto – EMA+Volume (BTC/ETH/BNB/SOL/XRP)", overlay=false)
// Inputs emaFast = input.int(50, "EMA Curta") emaSlow = input.int(200, "EMA Longa") emaPull = input.int(20, "EMA Pullback") volLen = input.int(20, "Média Volume")
symBTC = input.symbol(defval="BINANCE:BTCUSDT", title="BTC") symETH = input.symbol(defval="BINANCE:ETHUSDT", title="ETH") symBNB = input.symbol(defval="BINANCE:BNBUSDT", title="BNB") symSOL = input.symbol(defval="BINANCE:SOLUSDT", title="SOL") symXRP = input.symbol(defval="BINANCE:XRPUSDT", title="XRP")
f_sig(sym) => c = request.security(sym, timeframe.period, close) v = request.security(sym, timeframe.period, volume) e50 = ta.ema(c, emaFast) e200 = ta.ema(c, emaSlow) e20 = ta.ema(c, emaPull) vma = ta.sma(v, volLen) long = (e50 > e200) and (c > e20) and (v > vma) short = (e50 < e200) and (c < e20) and (v > vma)
= f_sig(symBTC) = f_sig(symETH) = f_sig(symBNB) = f_sig(symSOL) = f_sig(symXRP)
// Exibição plotchar(btcL, title="BTC Long", char="▲", location=location.top) plotchar(btcS, title="BTC Short", char="▼", location=location.bottom) plotchar(ethL, title="ETH Long", char="▲", location=location.top) plotchar(ethS, title="ETH Short", char="▼", location=location.bottom) plotchar(bnbL, title="BNB Long", char="▲", location=location.top) plotchar(bnbS, title="BNB Short", char="▼", location=location.bottom) plotchar(solL, title="SOL Long", char="▲", location=location.top) plotchar(solS, title="SOL Short", char="▼", location=location.bottom) plotchar(xrpL, title="XRP Long", char="▲", location=location.top) plotchar(xrpS, title="XRP Short", char="▼", location=location.bottom)
AltCoin & MemeCoin Index Correlation [Eddie_Bitcoin]🧠 Philosophy of the Strategy
The AltCoin & MemeCoin Index Correlation Strategy by Eddie_Bitcoin is a carefully engineered trend-following system built specifically for the highly volatile and sentiment-driven world of altcoins and memecoins.
This strategy recognizes that crypto markets—especially niche sectors like memecoins—are not only influenced by individual price action but also by the relative strength or weakness of their broader sector. Hence, it attempts to improve the reliability of trading signals by requiring alignment between a specific coin’s trend and its sector-wide index trend.
Rather than treating each crypto asset in isolation, this strategy dynamically incorporates real-time dominance metrics from custom indices (OTHERS.D and MEME.D) and combines them with local price action through dual exponential moving average (EMA) crossovers. Only when both the asset and its sector are moving in the same direction does it allow for trade entries—making it a confluence-based system rather than a single-signal strategy.
It supports risk-aware capital allocation, partial exits, configurable stop loss and take profit levels, and a scalable equity-compounding model.
✅ Why did I choose OTHERS.D and MEME.D as reference indices?
I selected OTHERS.D and MEME.D because they offer a sector-focused view of crypto market dynamics, especially relevant when trading altcoins and memecoins.
🔹 OTHERS.D tracks the market dominance of all cryptocurrencies outside the top 10 by market cap.
This excludes not only BTC and ETH, but also major stablecoins like USDT and USDC, making it a cleaner indicator of risk appetite across true altcoins.
🔹 This is particularly useful for detecting "Altcoin Season"—periods where capital rotates away from Bitcoin and flows into smaller-cap coins.
A rising OTHERS.D often signals the start of broader altcoin rallies.
🔹 MEME.D, on the other hand, captures the speculative behavior of memecoin segments, which are often driven by retail hype and social media activity.
It's perfect for timing momentum shifts in high-risk, high-reward tokens.
By using these indices, the strategy aligns entries with broader sector trends, filtering out noise and increasing the probability of catching true directional moves, especially in phases of capital rotation and altcoin risk-on behavior.
📐 How It Works — Core Logic and Execution Model
At its heart, this strategy employs dual EMA crossover detection—one pair for the asset being traded and one pair for the selected market index.
A trade is only executed when both EMA crossovers agree on the direction. For example:
Long Entry: Coin's fast EMA > slow EMA and Index's fast EMA > slow EMA
Short Entry: Coin's fast EMA < slow EMA and Index's fast EMA < slow EMA
You can disable the index filter and trade solely based on the asset’s trend just to make a comparison and see if improves a classic EMA crossover strategy.
Additionally, the strategy includes:
- Adaptive position sizing, based on fixed capital or current equity (compound mode)
- Take Profit and Stop Loss in percentage terms
- Smart partial exits when trend momentum fades
- Date filtering for precise backtesting over specific timeframes
- Real-time performance stats, equity tracking, and visual cues on chart
⚙️ Parameters & Customization
🔁 EMA Settings
Each EMA pair is customizable:
Coin Fast EMA: Default = 47
Coin Slow EMA: Default = 50
Index Fast EMA: Default = 47
Index Slow EMA: Default = 50
These control the sensitivity of the trend detection. A wider spread gives smoother, slower entries; a narrower spread makes it more responsive.
🧭 Index Reference
The correlation mechanism uses CryptoCap sector dominance indexes:
OTHERS.D: Dominance of all coins EXCLUDING Top 10 ones
MEME.D: Dominance of all Meme coins
These are dynamically calculated using:
OTHERS_D = OTHERS_cap / TOTAL_cap * 100
MEME_D = MEME_cap / TOTAL_cap * 100
You can select:
Reference Index: OTHERS.D or MEME.D
Or disable the index reference completely (Don't Use Index Reference)
💰 Position Sizing & Risk Management
Two capital allocation models are supported:
- Fixed % of initial capital (default)
- Compound profits, which scales positions as equity grows
Settings:
- Compound profits?: true/false
- % of equity: Between 1% and 200% (default = 10%)
This is critical for users who want to balance growth with risk.
🎯 Take Profit / Stop Loss
Customizable thresholds determine automatic exits:
- TakeProfit: Default = 99999 (disabled)
- StopLoss: Default = 5 (%)
These exits are percentage-based and operate off the entry price vs. current close.
📉 Trend Weakening Exit (Scale Out)
If the position is in profit but the trend weakens (e.g., EMA color signals trend loss), the strategy can partially close a configurable portion of the position:
- Scale Position on Weak Trend?: true/false
- Scaled Percentage: % to close (default = 65%)
This feature is useful for preserving profits without exiting completely.
📆 Date Filter
Useful for segmenting performance over specific timeframes (e.g., bull vs bear markets):
- Filter Date Range of Backtest: ON/OFF
- Start Date and End Date: Custom time range
OTHER PARAMETERS EXPLANATION (Strategy "Properties" Tab):
- Initial Capital is set to 100 USD
- Commission is set to 0.055% (The ones I have on Bybit)
- Slippage is set to 3 ticks
- Margin (short and long) are set to 0.001% to avoid "overspending" your initial capital allocation
📊 Visual Feedback and Debug Tools
📈 EMA Trend Visualization
The slow EMA line is dynamically color-coded to visually display the alignment between the asset trend and the index trend:
Lime: Coin and index both bullish
Teal: Only coin bullish
Maroon: Only index bullish
Red: Both bearish
This allows for immediate visual confirmation of current trend strength.
💬 Real-Time PnL Labels
When a trade closes, a label shows:
Previous trade return in % (first value is the effective PL)
Green background for profit, Red for losses.
📑 Summary Table Overlay
This table appears in a corner of the chart (user-defined) and shows live performance data including:
Trade direction (yellow long, purple short)
Emojis: 💚 for current profit, 😡 for current loss
Total number of trades
Win rate
Max drawdown
Duration in days
Current trade profit/loss (absolute and %)
Cumulative PnL (absolute and %)
APR (Annualized Percentage Return)
Each metric is color-coded:
Green for strong results
Yellow/orange for average
Red/maroon for poor performance
You can select where this appears:
Top Left
Top Right
Bottom Left
Bottom Right (default)
📚 Interpretation of Key Metrics
Equity Multiplier: How many times initial capital has grown (e.g., “1.75x”)
Net Profit: Total gains including open positions
Max Drawdown: Largest peak-to-valley drop in strategy equity
APR: Annualized return calculated based on equity growth and days elapsed
Win Rate: % of profitable trades
PnL %: Percentage profit on the most recent trade
🧠 Advanced Logic & Safety Features
🛑 “Don’t Re-Enter” Filter
If a trade is closed due to StopLoss without a confirmed reversal, the strategy avoids re-entering in that same direction until conditions improve. This prevents false reversals and repetitive losses in sideways markets.
🧷 Equity Protection
No new trades are initiated if equity falls below initial_capital / 30. This avoids overleveraging or continuing to trade when capital preservation is critical.
Keep in mind that past results in no way guarantee future performance.
Eddie Bitcoin
BTC CME Gap – detector & single signals# BTC CME Gap — Detector & Single Signals (Pine v5)
**What it does**
This indicator finds the **weekend gap** on **CME Bitcoin futures** and turns it into a clean, tradable object:
* Draws a **gap zone** (Friday close ↔ Monday open) as a right-extending box.
* Fires **one-time signals** per gap:
* **ENTER** – first touch of the gap zone by price.
* **FILL** – gap is considered filled when price tags **Friday’s close**.
It works on any BTC chart (spot or futures). The gap itself is calculated from **CME\:BTC1!** daily data.
---
## How it works
1. Pulls **daily** `open`/`close` from `CME:BTC1!` (`request.security`, no lookahead).
2. On **Monday**, compares Monday **open** with previous **Friday close**:
* If different → a **gap** exists.
3. Defines the zone:
* `gapTop = max(MonOpen, FriClose)`
* `gapBot = min(MonOpen, FriClose)`
4. Renders a box + boundary lines, **extending right** until price action resolves it.
5. Signals:
* **ENTER**: the first bar that **enters** the gap zone.
* **FILL**: first bar that **touches Friday close** (gap completion).
6. Each new Monday gap **replaces** the previous box and signals.
---
## Inputs
* **CME symbol** (default `CME:BTC1!`)
* **Gap timeframe** (default `D`)
* **Colors** for the box and edges
---
## Plot & Signals
* **Box** = visual gap zone (transparent fill, outlined).
* **ENTER** = triangle up below bar.
* **FILL** = triangle down above bar.
* Optional label prints **Top / Bottom / Fill** levels.
---
## Notes on behavior
* Uses `barmerge.lookahead_off` and daily aggregation, so the gap definition **does not repaint** once Monday’s daily bar is confirmed.
* Signals are **single-shot** per gap (no clutter).
* Works on any chart timeframe; the gap logic always references **CME daily**.
---
## Practical use
* Track obvious **“magnets”** for mean-reversion, stop-runs, or liquidity grabs.
* Combine with your higher-timeframe bias (e.g., **1D trend filter**) and execution on **4H/1H**.
* Typical outcomes: quick Monday fill, staged fill after partial rejection, or delayed fill during later consolidation.
---
## Customization ideas
* Add `alertcondition(enterSignal, …)` / `alertcondition(fillSignal, …)` for automation.
* Gate trades with trend filters (EMA/SMA, Kernel regression, ADX) or session tools (VWAP/POC).
* Persist multiple historical gap boxes if you want to track **unfilled** gaps.
---
**Credits**: Built for BTC CME weekend gaps; minimal, publication-ready visualization with single-event signals to keep charts clean.
Price Heat Meter [ChartPrime]⯁ OVERVIEW
Price Heat Meter visualizes where price sits inside its recent range and turns that into an intuitive “temperature” read. Using rolling extremes, candles fade from ❄️ aqua (cold) near the lower bound to 🔥 red (hot) near the upper bound. The tool also trails recent extreme levels, tags unusually persistent extremes with a % “heat” label, and shows a bottom gauge (0–100%) with a live arrow so you can read market heat at a glance.
⯁ KEY FEATURES
Rolling Heat Map (0–100%):
The script measures where the close sits between the current Lowest Low and Highest High over the chosen Length (default 50).
Candles use a two-stage gradient: aqua → yellow (0–50%), then yellow → red (50–100%). This makes “how stretched are we?” instantly visible.
Dynamic Extremes with Time Decay:
When a new rolling High or Low is set, the script starts a faint horizontal trail at that price. Each bar that passes without a new extreme increases a counter; the line’s color gradually fades over time and fully disappears after ~100 bars, keeping the chart clean.
Persistent-Extreme Tags (Reversal Hints):
If an extreme persists for 40 bars (i.e., price hasn’t reclaimed or surpassed it), the tool stamps the original extreme pivot with its recorded Heat% at the moment the extreme formed.
• Upper extremes print a red % label (possible exhaustion/resistance context).
• Lower extremes print an aqua % label (possible exhaustion/support context).
Bottom Heat Gauge (0–100% Scale):
A compact, gradient bar renders at the bottom center showing the current Heat% with an arrow/label. ❄️ anchors the left (0%), 🔥 anchors the right (100%). The arrow adopts the same candle heat color for consistency.
Minimal Inputs, Clear Theme:
• Length (lookback window for H/L)
• Heat Color set (Cold / Mid / Hot)
The defaults give a balanced, legible gradient on most assets/timeframes.
Signal Hygiene by Design:
The meter doesn’t “call” reversals. Instead, it contextualizes price within its range and highlights the aging of extremes. That keeps it robust across regimes and assets, and ideal as a confluence layer with your existing triggers.
⯁ HOW IT WORKS (UNDER THE HOOD)
Range Model:
H = Highest(High, Length), L = Lowest(Low, Length). Heat% = 100 × (Close − L) / (H − L).
Extreme Tracking & Fade:
When High == H , we record/update the current upper extreme; same for Low == L on the lower side. If the extreme doesn’t change on the next bar, a counter increments and the plotted line’s opacity shifts along a 0→100 fade scale (visual decay).
40-Bar Persistence Labels:
On the bar after the extreme forms, the code stores the bar_index and the contemporaneous Heat% . If the extreme survives 40 bars, it places a % label at the original pivot price and index—flagging levels that were meaningfully “tested by time.”
Unified Color Logic:
Both candles and the gauge use the same two-stage gradient (Cold→Mid, then Mid→Hot), so your eye reads “heat” consistently across all elements.
⯁ USAGE
Treat >80% as “hot” and <20% as “cold” context; combine with your trigger (e.g., structure, OB, div, breakouts) instead of acting on heat alone.
Watch persistent extreme labels (40-bar marks) as reference zones for reaction or liquidity grabs.
Use the fading extreme lines as a memory map of where price last stretched—levels that slowly matter less as they decay.
Tighten Length for intraday sensitivity or increase it for swing stability.
⯁ WHY IT’S UNIQUE
Rather than another oscillator, Price Heat Meter translates simple market geometry (rolling extremes) into a readable temperature layer with time-aware extremes and a synchronized gauge . You get a continuously updated sense of stretch, persistence, and potential reversal context—without clutter or overfitting.
VWMA MACD AmanitaVWMA MACD (Volume-Weighted MACD)
This indicator modifies the standard MACD by replacing EMAs with VWMAs
(Volume-Weighted Moving Averages).
- Fast VWMA (default 12 bars)
- Slow VWMA (default 26 bars)
- MACD Line = Fast VWMA - Slow VWMA
- Signal Line = EMA of MACD (default 9 bars)
- Histogram = MACD - Signal
Compared to the standard MACD, this version emphasizes price moves that
are backed by higher trading volume, helping to filter out weak signals.
The script also lets you choose the price source (Close, HL2, HLC3, OHLC4).
Trading Advice By RajTrading Advice Strategy
This strategy is based on a simple moving average crossover system using the 50 EMA and the 200 EMA.
Buy Signal (Long): When the 50 EMA crosses above the 200 EMA, a bullish trend is detected and a BUY signal is generated.
Sell Signal (Short): When the 200 EMA crosses above the 50 EMA, a bearish trend is detected and a SELL signal is generated.
EMA lines are hidden on the chart for a clean look. Only BUY and SELL signals are shown as labels.
Suitable for trend-following traders who want clear entry signals without noise.
Can be combined with risk management tools like Stop Loss & Take Profit for better results. youtube.com BINANCE:BTCUSDT
Pasrsifal.RegressionTrendStateSummary
The Parsifal.Regression.Trend.State Indicator analyzes the leading coefficients of linear and quadratic regressions of price (against time). It also considers their first- and second-order changes. These features are aggregated into a Trend-State background, shown as a gradient color. In addition, the indicator generates fast and slow signals that can be used as potential entry- or exit triggers.
This tool is designed for advanced trend-following strategies, leveraging information from multiple trendline features.
Background
Trendlines provide insight into the state of a trend or the “trendiness” of a price process. While moving averages or pivot-based lines can serve as envelopes and breakout levels, they are often too lagging for swing traders, who need tools that adapt more closely to price swings, ideally using trendlines, around which the price process swings continuously.
Regression lines address this by cutting directly through the data, making them a natural anchor for observing how price winds around a central trendline within a chosen lookback period.
Regression Trendlines
• Linear Regression:
o Minimizes distance to all closing values over the lookback period.
o The slope represents the short-term linear trend.
o The change of slope indicates trend acceleration or deceleration.
o Linear regression lags during phases of rapid market shifts.
• Quadratic Regression:
o Fits a second-degree polynomial to minimize deviation from closing prices.
o The convexity term (leading coefficient) reflects curvature:
Positive convexity → accelerating uptrend or fading downtrend.
Negative convexity → accelerating downtrend or fading uptrend.
o The change of convexity detects early shifts in momentum and often reacts faster than slope features.
Features Extracted
The indicator evaluates six features:
• Linear features: slope, first derivative of slope, second derivative of slope.
• Quadratic features: convexity term, first derivative of the convexity term, second derivative of the convexity term.
• Linear features: capture broad, background trend behavior.
• Quadratic features: detect deviations, accelerations, and smaller-scale dynamics.
Quadratic terms generally react first to market changes, while linear terms provide stability and context.
Dynamics of Market Moves as seen by linear and quadratic regressions
• At the start of a rapid move:
The change of convexity reacts first, capturing the shift in dynamics before other features. The convexity term then follows, while linear slope features lag further behind. Because convexity measures deviation from linearity, it reflects accelerating momentum more effectively than slope.
• At the end of a rapid move:
Again, the change of convexity responds first to fading momentum, signaling the transition from above-linear to below-linear dynamics. Even while a strong trend persists, the change of convexity may flip sign early, offering a warning of weakening strength. The convexity term itself adjusts more slowly but may still turn before the price process does. Linear features lag the most, typically only flipping after price has already reversed, thereby smoothing out the rapid, more sensitive reactions of quadratic terms.
________________________________________
Parsifal Regression.Trend.State Method
1. Feature Mapping:
Each feature is mapped to a range between -1 and 1, preserving zero-crossings (critical for sign interpretation).
2. Aggregation:
A heuristic linear combination*) produces a background information value, visualized as a gradient color scale:
o Deep green → strong positive trend.
o Deep red → strong negative trend.
o Yellow → neutral or transitional states.
3. Signals:
o Fast signal (oscillator): ranges from -1 to 1, reflecting short-term trend state.
o Slow signal (smoothed): moving average of the fast signal.
o Their interactions (crossovers, zero-crossings) provide actionable trading triggers.
How to Use
The Trend-State background gradient provides intuitive visual feedback on the aggregated regression features (slope, convexity, and their changes). Because these features reflect not only current trend strength but also their acceleration or deceleration, the color transitions help anticipate evolving market states:
• Solid Green: All features near their highs. Indicates a strong, accelerating uptrend. May also reflect explosive or hyperbolic upside moves (including gaps).
• Fading Solid Green: A recently strong uptrend is losing momentum. Price may shift into a slower uptrend, consolidation, or even a reversal.
• Fading Green → Yellow: Often appears as a dirty yellow or a rapidly mixing pattern of green and red. Signals that the uptrend is weakening toward neutrality or beginning to turn negative.
• Yellow → Deepening Red: Two possible scenarios:
o Coming from a strong uptrend → suggests a sharp fade, though the trend may still technically be up.
o Coming from a weaker uptrend or sideways market → suggests the start of an accelerating downtrend.
• Solid Red: All features near their lows. Indicates a strong, accelerating downtrend. May also reflect crash-type conditions or downside gaps.
• Fading Solid Red: A recently strong downtrend is losing strength. Market may move into a slower decline, consolidation, or early reversal upward.
• Fading Red → Yellow : The downtrend is weakening toward neutral, with potential for a bullish shift.
• Yellow → Increasing Green: Two possible scenarios:
o Coming from a strong downtrend, it reflects a sharp fade of bearish momentum, though the market may still technically be trending down.
o Coming from a weaker downtrend or sideways movement, it suggests the start of an accelerating uptrend.
Note: Market evolution does not always follow this neat “color cycle.” It may jump between states, skip stages, or reverse abruptly depending on market conditions. This makes the background coloring particularly valuable as a contextual map of current and evolving price dynamics.
Signal Crossovers:
Although the fast signal is very similar (but not identical) to the background coloring, it provides a numerical representation indicating a bullish interpretation for rising values and bearish for falling.
o High-confidence entries:
Fast signal rising from < -0.7 and crossing above the slow signal → potential long entry.
Fast signal falling from > +0.7 and crossing below the slow signal → potential short entry.
o Low-confidence entries:
Crossovers near zero may still provide a valid trigger but may be noisy and should be confirmed with other signals.
o Zero-crossings:
Indicate broader state changes, useful for conservative positioning or option strategies. For confirmation of a Fast signal 0-crossing, wait for the Slow signal to cross as well.
________________________________________
*) Note on Aggregation
While the indicator currently uses a heuristic linear combination of features, alternatives such as Principal Component Analysis (PCA) could provide a more formal aggregation. However, while in the absence of matrix algebra, the required eigenvalue decomposition can be approximated, its computational expense does not justify the marginal higher insight in this case. The current heuristic approach offers a practical balance of clarity, speed, and accuracy.
OHLC Horizontal Compact + Volume + Buy/SellA compact, single-row horizontal table for TradingView displaying Open, High, Low, Close (OHLC), net change, percentage change, volume, and buy/sell pressure percentages. The table is fully color-coded for easy interpretation: green for positive values, red for negative, and yellow for neutral. Table position is fully customizable (top, middle, bottom / left, center, right). Ideal for traders who want a concise, real-time snapshot of price action and market sentiment in a single row.
Features:
OHLC values in one horizontal row
Net change (Δ) and % change with directional arrows
Real-time volume display
Buy/Sell pressure % with dynamic coloring
Fully customizable table placement
Works on all timeframes
Signal Validator - Signal Validator with Volume and IV ProxySignal Validator - Signal Validator with Volume and IV Proxy
Advanced Ghost Volume DetectorAdvanced Ghost Volume DetectorAdvanced Ghost Volume DetectorAdvanced Ghost Volume DetectorAdvanced Ghost Volume Detector
Polynomial Regression HeatmapPolynomial Regression Heatmap – Advanced Trend & Volatility Visualizer
Overview
The Polynomial Regression Heatmap is a sophisticated trading tool designed for traders who require a clear and precise understanding of market trends and volatility. By applying a second-degree polynomial regression to price data, the indicator generates a smooth trend curve, augmented with adaptive volatility bands and a dynamic heatmap. This framework allows users to instantly recognize trend direction, potential reversals, and areas of market strength or weakness, translating complex price action into a visually intuitive map.
Unlike static trend indicators, the Polynomial Regression Heatmap adapts to changing market conditions. Its visual design—including color-coded candles, regression bands, optional polynomial channels, and breakout markers—ensures that price behavior is easy to interpret. This makes it suitable for scalping, swing trading, and longer-term strategies across multiple asset classes.
How It Works
The core of the indicator relies on fitting a second-degree polynomial to a defined lookback period of price data. This regression curve captures the non-linear nature of market movements, revealing the true trajectory of price beyond the distortions of noise or short-term volatility.
Adaptive upper and lower bands are constructed using ATR-based scaling, surrounding the regression line to reflect periods of high and low volatility. When price moves toward or beyond these bands, it signals areas of potential overextension or support/resistance.
The heatmap colors each candle based on its relative position within the bands. Green shades indicate proximity to the upper band, red shades indicate proximity to the lower band, and neutral tones represent mid-range positioning. This continuous gradient visualization provides immediate feedback on trend strength, market balance, and potential turning points.
Optional polynomial channels can be overlaid around the regression curve. These three-line channels are based on regression residuals and a fixed width multiplier, offering additional reference points for analyzing price deviations, trend continuation, and reversion zones.
Signals and Breakouts
The Polynomial Regression Heatmap includes statistical pivot-based signals to highlight actionable price movements:
Buy Signals – A triangular marker appears below the candle when a pivot low occurs below the lower regression band.
Sell Signals – A triangular marker appears above the candle when a pivot high occurs above the upper regression band.
These markers identify significant deviations from the regression curve while accounting for volatility, providing high-quality visual cues for potential entry points.
The indicator ensures clarity by spacing markers vertically using ATR-based calculations, preventing overlap during periods of high volatility. Users can rely on these signals in combination with heatmap intensity and regression slope for contextual confirmation.
Interpretation
Trend Analysis :
The slope of the polynomial regression line represents trend direction. A rising curve indicates bullish bias, a falling curve indicates bearish bias, and a flat curve indicates consolidation.
Steeper slopes suggest stronger momentum, while gradual slopes indicate more moderate trend conditions.
Volatility Assessment :
Band width provides an instant visual measure of market volatility. Narrow bands correspond to low volatility and potential consolidation, whereas wide bands indicate higher volatility and significant price swings.
Heatmap Coloring :
Candle colors visually represent price position within the bands. This allows traders to quickly identify zones of bullish or bearish pressure without performing complex calculations.
Channel Analysis (Optional) :
The polynomial channel defines zones for evaluating potential overextensions or retracements. Price interacting with these lines may suggest areas where mean-reversion or trend continuation is likely.
Breakout Signals :
Buy and Sell markers highlight pivot points relative to the regression and volatility bands. These are statistical signals, not arbitrary triggers, and should be interpreted in context with trend slope, band width, and heatmap intensity.
Strategy Integration
The Polynomial Regression Heatmap supports multiple trading approaches:
Trend Following – Enter trades in the direction of the regression slope while using the heatmap for momentum confirmation.
Pullback Entries – Use breakouts or deviations from the regression bands as low-risk entry points during trend continuation.
Mean Reversion – Price reaching outer channel boundaries can indicate potential reversal or retracement opportunities.
Multi-Timeframe Alignment – Overlay on higher and lower timeframes to filter noise and improve entry timing.
Stop-loss levels can be set just beyond the opposing regression band, while take-profit targets can be informed by the distance between the bands or the curvature of the polynomial line.
Advanced Techniques
For traders seeking greater precision:
Combine the Polynomial Regression Heatmap with volume, momentum, or volatility indicators to validate signals.
Observe the width and slope of the regression bands over time to anticipate expanding or contracting volatility.
Track sequences of breakout signals in conjunction with heatmap intensity for systematic trade management.
Adjusting regression length allows customization for different assets or timeframes, balancing responsiveness and smoothing. The combination of polynomial curve, adaptive bands, heatmap, and optional channels provides a comprehensive statistical framework for informed decision-making.
Inputs and Customization
Regression Length – Determines the number of bars used for polynomial fitting. Shorter lengths increase responsiveness; longer lengths improve smoothing.
Show Bands – Toggle visibility of the ATR-based regression bands.
Show Channel – Enable or disable the polynomial channel overlay.
Color Settings – Customize bullish, bearish, neutral, and accent colors for clarity and visual preference.
All other internal parameters are fixed to ensure consistent statistical behavior and minimize potential misconfiguration.
Why Use Polynomial Regression Heatmap
The Polynomial Regression Heatmap transforms complex price action into a clear, actionable visual framework. By combining non-linear trend mapping, adaptive volatility bands, heatmap visualization, and breakout signals, it provides a multi-dimensional perspective that is both quantitative and intuitive.
This indicator allows traders to focus on execution, interpret market structure at a glance, and evaluate trend strength, overextensions, and potential reversals in real time. Its design is compatible with scalping, swing trading, and long-term strategies, providing a robust tool for disciplined, data-driven trading.
Low Volatility Breakout in Trend
█ OVERVIEW
"Low Volatility Breakout in Trend" is a technical analysis tool that identifies periods of low-volatility consolidation within an ongoing trend and signals potential breakouts aligned with the trend's direction. The indicator detects trends using a simple moving average (SMA) of price, identifies consolidation zones based on the size of candle bodies, and displays the percentage change in volume (volume delta) at the breakout moment.
█ CONCEPTS
The core idea of the indicator is to pinpoint moments where traders can join an ongoing trend by capitalizing on breakouts from consolidation zones, supported by additional information such as volume delta. It provides clear visualizations of trends, consolidation zones, and breakout signals to facilitate trading decisions.
Why Use It?
* Breakout Identification: The indicator locates low-volatility consolidation zones (measured by the size of individual candle bodies, not the price range of the consolidation) and signals breakouts, enabling traders to join the trend at key moments.
* Volume Analysis: Displays the percentage change in volume (delta) relative to its simple moving average, providing insight into market activity rather than acting as a signal filter.
* Visual Clarity: Colored trend lines, consolidation boxes (drawn only after the breakout candle closes, not on subsequent candles), and volume delta labels enable quick chart analysis.
* Flexibility: Adjustable parameters, such as the volatility window length or SMA period, allow customization for various trading strategies and markets.
How It Works
* Trend Detection: The indicator calculates a simple moving average (SMA) of price (default: based on the midpoint of high/low) and creates dynamic trend bands, offset by a percentage of the average candle height (band scaling). A price above the upper band signals an uptrend, while a price below the lower band indicates a downtrend. Trend changes occur not when the price crosses the SMA but when it crosses above the upper band or below the lower band (offset by the average candle height multiplied by the scaling factor).
* Consolidation Identification: Identifies low-volatility zones when the candle body size is smaller than the average body size over a specified period (default: 20 candles) multiplied by a volatility threshold — the maximum allowable body size as a percentage of the average body (e.g., 2 means the candle body must be less than twice the average body to be considered low-volatility).
* Breakout Signals: A breakout occurs when the candle body exceeds the volatility threshold, is larger than the maximum body in the consolidation, and aligns with the trend direction (bullish in an uptrend, bearish in a downtrend).
* Visualization: Draws a trend line with a gradient, consolidation boxes (appearing only after the breakout candle closes, marking the consolidation zone), and volume delta labels. Optionally displays breakout signal arrows.
* Signals and Alerts: The indicator generates signals for bullish and bearish breakouts, including the volume delta percentage. Alerts are an additional feature that can be enabled for notifications.
Settings and Customization
* Volatility Window: Length of the period for calculating the average candle body size (default: 20).
* Volatility Threshold: Maximum candle body size as a percentage of the average body (default: 2).
* Minimum Consolidation Bars: Number of candles required for a consolidation (default: 10).
* SMA Length for Trend: Period of the SMA for trend detection (default: 100).
* Band Scaling: Offset of trend bands as a percentage of the average candle height (default: 250%), determining the distance from the SMA.
* Visualization Options: Enable/disable consolidation boxes (Show Consolidation Boxes, drawn after the breakout candle closes), volume delta labels (Show Volume Delta Labels), and breakout signals (Show Breakout Signals, e.g., triangles).
* Colors: Customize colors for the trend line, consolidation boxes, and volume delta labels.
█ OTHER SECTIONS
Usage Examples
* Joining an Uptrend: When the price breaks out of a consolidation in an uptrend with a volume delta of +50%, open a long position; the signal is stronger if the breakout candle surpasses a local high.
* Avoiding False Breakouts: Ignore breakout signals with low volume delta (e.g., below 0%) and combine the indicator with other tools (e.g., support/resistance levels or oscillators) to confirm moves in low-activity zones.
Notes for Users
* On markets that do not provide volume data, the indicator will not display volume delta — disable volume labels and enable breakout signals (e.g., triangles) instead.
* Adjust parameters to suit the market's characteristics to minimize noise.
* Combine with other tools, such as Fibonacci levels or oscillators, for greater precision.
India Nifty Index Performances DashboardSelf explanatory tabular view of Nifty sector performance ranked top & bottom across calendar year vs. financial year — a clear view of market leaders and laggards.
Options available: Day, Week, Month, Quarter, Calendar Year, (India) Financial Year p
performances. Included Gold (from Mcx), Sme (from Bse), 10Y Gsec for comparison.
Fibonacci Sequence Circles [BigBeluga]🔵 Overview
The Fibonacci Sequence Circles is a unique and visually intuitive indicator designed for the TradingView platform. It combines the principles of the Fibonacci sequence with geometric circles to help traders identify potential support and resistance levels, as well as price expansion zones. The indicator dynamically anchors to key price points, such as pivot highs, pivot lows, or timeframe changes (daily, weekly, monthly), and generates Fibonacci-based circles around these anchor points.
⚠️For proper indicators visualization use simple not logarithmic chart
🔵 Key Features
Customizable Anchor Points : The indicator can be anchored to Pivot Highs , Pivot Lows , or timeframe changes ( Daily, Weekly, Monthly ), making it adaptable to various trading strategies.
Fibonacci Sequence Logic : The circles are generated using the Fibonacci sequence, where the diameter of each circle is the sum of the diameters of the two preceding circles.
first = start_val
secon = start_val + int(start_val/2)
three = first + secon
four = secon + three
five = three + four
six = four + five
seven = five + six
eight = six + seven
nine = seven + eight
ten = eight + nine
Adjustable Start Value : Traders can modify the starting value of the sequence to scale the circles larger or smaller, ensuring they fit the current price action.
Color Customization : Each circle can be individually enabled or disabled, and its color can be customized for better visual clarity.
Visual Labels : The diameter of each circle (in bars) is displayed next to the circle, providing additional context for analysis.
🔵 Usage
Step 1: Set the Anchor Point - Choose the anchor type ( Pivot High, Pivot Low, Daily, Weekly, Monthly ) to define the center of the Fibonacci circles.
Step 2: Adjust the Start Value - Modify the starting value of the Fibonacci sequence to scale the circles according to the price action.
Step 3: Customize Circle Colors - Enable or disable specific circles and adjust their colors for better visualization.
Step 4: Analyze Price Action - Use the circles to identify potential support/resistance levels, price expansion zones, or trend continuation areas.
Step 5: Combine with Other Tools - Enhance your analysis by combining the indicator with other technical tools like trendlines, moving averages, or volume indicators.
The Fibonacci Sequence Circles is a powerful and flexible tool for traders who rely on Fibonacci principles and geometric patterns. Its ability to anchor to key price points and dynamically scale based on market conditions makes it suitable for various trading styles and timeframes. Whether you're a day trader or a long-term investor, this indicator can help you visualize and anticipate price movements with greater precision.
NYSE Advancing Issues & Volume RatiosOverview
This comprehensive market breadth indicator tracks two essential NYSE ratios that provide deep insights into market sentiment and internal strength:
NYSE Advancing Issues Ratio
NYSE Advancing Volume Ratio
Dual Ratio Analysis
Issues Ratio: Measures the percentage of NYSE stocks advancing vs. total issues
Volume Ratio: Measures the percentage of NYSE volume flowing into advancing stocks
Both ratios displayed as easy-to-read percentages (0-100%)
Customizable Display Options
Toggle each ratio on/off independently
Choose from multiple moving average types (SMA, EMA, WMA)
Adjustable moving average periods
Custom color schemes for better visualization
Reference Levels
50% Line: Market neutral point (gray dashed)
10% Line: Extremely bearish breadth (red dotted)
90% Line: Extremely bullish breadth (green dotted)
Optional background highlighting for extreme readings
Smart Alerts
Cross above/below 50% (neutral) for both ratios
Extreme readings: Above 90% (strong bullish) and below 10% (strong bearish)
Real-time notifications for key market breadth shifts
📈 How to Interpret
Bullish Signals
Above 50%: More stocks/volume advancing than declining
Above 90%: Extremely strong market breadth (rare occurrence)
Divergence: Price making new highs while breadth weakens (potential warning)
Market Timing
Extreme readings (10%/90%) often coincide with market turning points
Breadth thrusts from extreme levels can signal powerful moves
Use with other technical indicators for enhanced timing