Earnings X-Ray and Fundamentals Data:VSMarketTrendThis indicator calculates essential financial metrics for stocks using TradingView's built-in functions and custom algorithms. The values are derived from fundamental data sources available on TradingView.
Key Output Metrics(YOY Basic Quaterly DATA)
MC (Market Cap): Company’s total market value (Price × Total Shares).
TS (Total Shares Outstanding): All shares (float + restricted) in circulation.
Sales: Annual revenue (TTM or latest fiscal year).
NETIn: Net income
P/E (Price-to-Earnings): Valuation ratio (Market Cap / Net Income or Price / EPS).
EPS (Earnings Per Share): Net income per share (Net Income / TS).
OPM (Operating Margin %): Core profitability (Operating Income / Revenue × 100).
Quick Ratio: Short-term liquidity ((Current Assets – Inventory) / Current Liabilities).
BVPS (Book Value Per Share): Equity per share (Shareholders’ Equity / TS).
PS (Price-to-Sales): Revenue-based valuation (Market Cap / Annual Revenue).
FCF (Free Cash Flow Per Share): Post-CapEx cash ((Operating Cash Flow – CapEx) / TS).
Data Sources & Methods
Uses TradingView’s request.financial() for income/balance sheet data (Revenue, EBITDA, etc.).
Fetches real-time metrics via request.security() (e.g., Shares Outstanding).
Normalizes data across timeframes (quarterly/annual).
Disclaimer
Not financial advice. Verify with official filings before trading.
Análise Fundamentalista
Chuan-事件合约专用指标-信号仅供参考This is a signal technical indicator developed by a technical analysis trader specifically for Binance event contracts. His name is ChuanCrypto
LevelUp^ Power Earnings Gap & EPS Acceleration ScreenerCustomizable Pine Screener to scan for stocks with a Power Earnings Gap as well as accelerating earnings and sales. Historical analysis shows that strong earnings often trigger institutional buying, pushing prices higher and increasing the likelihood of sustained price gains.
🔹 Power Earnings Gap (PEG)
A power earnings gap refers to a significant price gap up after an earnings report, reflecting a rapid shift in investor sentiment and perceived value. It’s called "power" because the move is often sharp, sustained, and accompanied by high trading volume, signaling a potential trend continuation or reversal.
A gap is the difference between the closing price of a stock on the day before an earnings report and the opening price the next trading day. A power earnings gap typically exceeds a certain threshold (e.g., 8-10% or more) and is driven by earnings surprises, guidance changes, or other significant news.
Strong earnings beats, misses, or forward-looking guidance can trigger these gaps. For example, a company reporting higher-than-expected profits or raising guidance might gap up, while a miss or weak outlook could cause a gap down.
The gap is often accompanied by above-average trading volume, confirming the move's strength. Power gaps often lead to sustained price movement in the direction of the gap (continuation) or signal a reversal if the gap fills quickly.
How Power Earnings Gap Be Helpful
▪ Power earnings gaps often indicate strong momentum. Traders can capitalize on this by entering trades in the direction of the gap (e.g., buying on a gap-up if the trend continues).
Example: If a stock gaps up 10% after a stellar earnings report and shows high volume, traders might buy, expecting further upside as momentum builds.
▪ Breakout Opportunities: A gap through key technical levels (e.g., resistance or support) can signal a breakout. Traders use these gaps to identify potential long-term trends.
Example: A stock breaking above a resistance level on a power earnings gap may continue to rally, offering a setup for swing or position traders.
▪ Volatility for Short-Term Trades: Earnings gaps create heightened volatility, ideal for day traders or scalpers. The large price swings allow for quick profits if timed correctly.
Example: A trader might use options (e.g., calls for a gap-up, puts for a gap-down) to leverage the volatility around earnings.
▪ Confirmation of Fundamental Strength/Weakness: A power earning gap often reflects a fundamental shift, e.g., strong earnings growth or a major business development. Traders can use this to align technical setups with fundamental catalysts.
Example: A gap-up after a company raises its full-year guidance might signal a long-term buying opportunity.
▪ Risk Management and Stop Losses: Gaps provide clear levels for setting stop-loss orders. For instance, traders might place stops at or below the gap up bar low to protect against a potential reversal.
Example: If a stock gaps up from $100 to $110 and intraday hits a low of $105, a trader might set a stop at $105 or lower to limit downside risk.
▪ Gap Fill Strategies:Some traders bet on gaps filling, i.e., the stock returning to its pre-gap price. If a power earnings gap seems overextended (e.g., due to market overreaction), contrarian traders might short a gap-up or buy a gap-down, anticipating a pullback.
Example: A stock gaps up 15% but lacks volume or follow-through; a trader might short it, expecting the price to retreat.
🔹 Earnings and Sales Acceleration
Earnings and sales acceleration refers to the rate of growth in a company's earnings over consecutive quarters. It highlights companies that are not only growing but doing so at an accelerating pace, signaling improving financial health and operational momentum. This metric is derived from earnings reports, which detail a company’s financial performance.
Key Concepts
▪ Earnings Acceleration: When a company’s earnings per share (EPS) growth rate increases over time (e.g., EPS growth of 10% in Q1, 15% in Q2, 20% in Q3). It indicates improving profitability, often due to cost efficiencies, margin expansion and strong demand.
▪ Sales Acceleration: When revenue growth rates increase over time (e.g., revenue growth of 5% in Q1, 8% in Q2, 12% in Q3). This reflects rising demand for products/services and operational efficiency.
▪ Relation to Earnings Reports: Acceleration is calculated by comparing sequential quarter-over-year growth rates in earnings and sales, often highlighted in earnings reports or analyst commentary. It’s a sign of fundamental strength when both metrics accelerate together.
How It’s Helpful to Traders
▪ Identify High-Potential Stocks: Stocks with accelerating earnings and sales often attract investor attention, as they signal a company is outperforming expectations and gaining market share. This can lead to sustained price appreciation.
Example: A tech company reporting 20% EPS growth and 15% sales growth quarter-over-quarter may see bullish price action as investors bet on continued momentum.
▪ Momentum Trading Opportunities: Acceleration often fuels stock price momentum, especially post-earnings. Traders can ride these trends using technical setups like breakouts or pullbacks.
Example: A stock breaking above a key resistance level after reporting accelerating growth may be a buy signal for swing traders.
▪ Early Indicator of Breakouts: Companies with accelerating fundamentals are more likely to experience price breakouts, as institutional investors (e.g., hedge funds, mutual funds) pile in. Traders can use this to position early.
Example: A retailer with accelerating sales due to strong holiday demand might gap up post-earnings, offering a breakout trade.
▪ Confirmation of Fundamental Strength: Acceleration validates a company’s growth story, reducing the risk of investing in stocks with inconsistent performance. Traders can align technical trades with strong fundamentals.
Example: A biotech with accelerating sales from a new drug launch may sustain a rally, giving traders confidence in long positions.
▪ Volatility for Short-Term Trades: Earnings reports showing acceleration often lead to significant price gaps or volatility, creating opportunities for day traders or options traders.
Example: A trader might buy call options on a stock expected to report accelerating earnings, anticipating a sharp post-earnings move.
🔹 Power Earnings Gaps - Examples
🔹 Screening Features - Setting Your Search Criteria
Power Earnings Gap
▪ Search Range
How many bars back to search for Power Earnings Gaps, anywhere between 1 and 90 bars.
▪ Last Bar Only
Look only at the last bar for Power Earnings Gaps. This is useful when looking for PEGs when screening at the end of a trading day. Choosing this option, the Search Range will be ignored.
▪ Minimum Price % Gap Up From Prior Close
This is the minimum gap up percent change to be considered a Power Earnings Gap.
▪ Minimum Volume % Change Over Average
This is the minimum volume percent change, over the 50-day average volume, to be considered a Power Earnings Gap.
▪ Require Positive Surprise
Require a positive earnings surprise and the minimum percent change.
▪ Require Closing Range
To ensure the price action closed strong on the day, specify a preferred closing range as a percentage of the bar's daily range.
▪ Gap Up Bar
The gap up bar can be configured to require one of the following:
- Open Above Prior High - Ensures there is visible gap up from the prior bar.
- Low Above Prior High - Allows for intraday price action to go below the prior bar high.
- No Requirement
Earnings And Sales Acceleration
▪ Quarters of Acceleration
You can specify between 1 and 4 quarters of earnings and/or sales acceleration.
🔹 Installation And Usage
▪ Mark this indicator as a Favorite.
▪ Use the Pine Screener to search for stocks.
▪ Save the search results to a watchlist.
▪ View the watchlist in TradingView.
🔹 Note
▪ Risk of Reversals: Not all gaps sustain their direction. Over reactions can lead to gap fills.
▪ High Volatility: Earnings gaps can be unpredictable, requiring quick decision-making & discipline.
Ai buy and sell fundamental the Gk fundamental is a precision built market analysis tool designed yto help traders identify high probability
it uses a combination of market structure analysis, volatility tracking, and multi time frame confirmation to highlight possible trade opportunities
HOW IT WORKS
analyses momentum shift and structure breaks on the 2h chart for clearer direction
confirms potential entries by filtering market noise and using volatility directional filters
HOW TO USE apply 2h chart for primary direction
when signal appears allow 1 candle to close for confirmation
drop to lower time frame to lower time frame to refine entry if desired
always use proper risk management - no tool guarantees results
Comparaison DXY, VIX, SPX, DJI, GVZPine Script indicator compares the normalized values of DXY, VIX, SPX, DJI, and GVZ indices on a single scale from 0 to 100. Here's a breakdown of what it does:
Data Requests: Gets closing prices for:
US Dollar Index (DXY)
VIX Volatility Index
S&P 500 (SPX)
Dow Jones Industrial Average (DJI)
Gold Volatility Index (GVZ)
Normalization: Each index is normalized using a 500-period lookback to scale values between 0-100, making them comparable despite different price scales.
Visualization:
Plots each normalized index with distinct colors
Adds a dotted midline at 50 for reference
Uses thicker linewidth (2) for better visibility
Timeframe Flexibility: Works on any chart timeframe since it uses timeframe.period
This is useful for:
Comparing relative strength/weakness between these key market indicators
Identifying divergences or convergences in their movements
Seeing how different asset classes (currencies, equities, volatility) relate
You could enhance this by:
Adding correlation calculations between pairs
Including options to adjust the normalization period
Adding alerts when instruments diverge beyond certain thresholds
Including volume or other metrics alongside price
AI BUY AND SELL BGThe Gk fundamental is a next gen level ai powered BUY and SELL system engineered for big market moves, it runs an embedded algorithm within a algorithm to detect breakout points before they happen giving traders insane results
works best and only 2h and 4h
Minimal S/R Zones with Volume StrengthHow it works
Pivot Detection
A pivot high is a candle whose high is greater than the highs of a certain number of candles before and after it.
A pivot low is a candle whose low is lower than the lows of a certain number of candles before and after it.
Parameters like Pivot Left Bars and Pivot Right Bars control how sensitive the pivots are.
Zone Creation
Pivot High → creates a Resistance zone.
Pivot Low → creates a Support zone.
Each zone is defined as a price range (top and bottom) and drawn horizontally for a given lookback length.
Volume Strength Filter
Volume Strength (%) = (Volume at Pivot / Volume SMA) × 100.
If the strength is below the minimum threshold (Min Strength %), the zone is ignored.
This ensures only pivots with significant trading activity create zones.
Zone Management
The indicator stores zones in arrays.
Max Zones per side prevents too many zones from being displayed at once.
Older zones are removed when new ones are added beyond the limit.
Visuals
Support zones → green label with Volume Strength %.
Resistance zones → red label with Volume Strength %.
Zones have semi-transparent boxes so price action remains visible.
Risk Appetite IndexWhat This Indicator Does
The Risk Appetite Index measures market participants' willingness to take risk by analyzing multiple market factors. This indicator attempts to provide insights into overall market sentiment by combining information from different market segments into a single composite measure.
How It Works
The indicator uses a multi-factor approach that examines various aspects of market behavior including equity market conditions, interest rate environments, credit markets, volatility patterns, and other relevant market data. These factors are processed and combined to create a composite reading on a 0-100 scale.
Theoretical Foundation
The methodology is grounded in established financial theories including Modern Portfolio Theory principles for risk assessment, behavioral finance concepts regarding market sentiment cycles, and factor investing approaches for multi-dimensional market analysis. The indicator incorporates insights from academic research on market microstructure, volatility clustering phenomena, and cross-asset correlation patterns during different market regimes.
The approach draws from research on fear and greed cycles in financial markets, term structure modeling, and credit risk assessment methodologies. Statistical techniques employed include robust normalization methods and composite index construction principles established in econometric literature.
The methodology employs statistical techniques to normalize the different market inputs and reduce the impact of extreme values. The final output aims to reflect the general level of risk appetite present in financial markets.
Signal Interpretation
Values above 60 may suggest higher risk appetite conditions in markets. Values below 30 may indicate lower risk appetite environments. The 30-60 range represents neutral or mixed conditions where market sentiment may be unclear.
The indicator includes threshold levels that may help identify potential changes in market conditions. However, like all technical indicators, these levels should be considered as potential reference points rather than definitive signals.
Research Context
The approach builds upon established sentiment measurement methodologies documented in financial literature, including studies on VIX-based fear indicators, credit spread analysis, yield curve interpretation, and cross-asset momentum research. The multi-factor design reflects principles from academic research on composite economic indicators and systematic risk assessment frameworks used by central banks and institutional investors.
The threshold-based signal generation follows established precedents in quantitative finance research regarding regime detection and market state classification methodologies documented in institutional portfolio management literature.
Key Features
Analytics Dashboard: Displays real-time information about current readings, market regime assessment, and signal quality indicators.
Visual Tools: Multiple color schemes and background options to help visualize current market conditions and trends.
Alert System: Optional alerts for threshold crossings and regime changes to help monitor market conditions.
Quality Assessment: Built-in filters attempt to distinguish between higher and lower confidence readings based on data quality and market conditions.
How to Use
This indicator is designed to be used on daily timeframes and displays in a separate panel below the main chart. It works best when used as part of a comprehensive market analysis approach rather than as a standalone trading tool.
The dashboard provides additional context about current readings and may help users understand the quality and reliability of current signals. Users should consider multiple factors and conduct their own analysis when making trading decisions.
Important Considerations
This indicator is designed for educational and analytical purposes. It does not guarantee profitable trading results and should not be used as the sole basis for trading decisions.
Market conditions can change rapidly and unpredictably. Past behavior of any indicator does not predict future market movements. All trading involves substantial risk and may not be suitable for all investors.
The indicator's effectiveness may vary across different market environments and conditions. Users should consider their own risk tolerance and investment objectives when using any analytical tool.
Data Limitations
The indicator relies on multiple external data sources and may be affected by data quality, market holidays, or limited trading hours. Performance may vary during unusual market conditions or structural changes in financial markets.
Like all quantitative models, this indicator has inherent limitations and may not capture all relevant market factors or unprecedented market events.
Intended Use
This indicator may be useful for traders and analysts seeking additional tools for market sentiment analysis. It is designed for those who want to incorporate multiple market factors into their decision-making process.
Academic Research Foundation
The development approach incorporates established research methodologies from quantitative finance literature. Key theoretical frameworks include:
Factor Models: Based on research into multi-factor asset pricing models and their application to portfolio construction and risk management practices developed in academic finance literature.
Behavioral Finance: Incorporates findings from behavioral economics research on market anomalies, investor psychology, and sentiment-driven market movements as documented in financial psychology studies.
Market Microstructure: Utilizes principles from market microstructure research regarding information flow, price discovery mechanisms, and cross-market relationships established in institutional finance literature.
Risk Management: Built upon established risk measurement frameworks including Value at Risk methodologies, stress testing approaches, and systematic risk assessment techniques documented in risk management research.
Econometric Methods: Employs statistical techniques based on time series analysis, robust estimation methods, and composite index construction principles established in econometric literature and central bank research methodologies.
The proprietary methodology combines various market inputs in an attempt to provide insights into overall risk appetite trends, though results may vary and should always be considered alongside other forms of analysis.
Risk Warnings
Past performance does not guarantee future results. All trading involves substantial risk of loss. This indicator does not eliminate market risk and should be used as part of a comprehensive trading plan. Market conditions can change rapidly and unexpectedly. No indicator is accurate in all market conditions.
Technical Requirements
Optimal use on daily charts with TradingView Pro or higher for real-time data access. Designed primarily for US equity market analysis during regular trading hours.
Note: This is a closed-source indicator with proprietary calculation methods designed to maintain effectiveness and provide users with a unique analytical tool.
TSI Indicator with Trailing StopAuthor: ProfitGang
Type: Indicator (visual + alerts). No orders are executed.
What it does
This tool combines the True Strength Index (TSI) with a simple tick-based trailing stop visualizer.
It plots buy/sell markers from a TSI cross with momentum confirmation and, if enabled, draws a trailing stop line that “ratchets” in your favor. It also shows a compact info table (position state, entry price, trailing status, and unrealized ticks).
Signal logic (summary)
TSI is computed with double EMA smoothing (user lengths).
Signals:
Buy when TSI crosses above its signal line and momentum (TSI–Signal histogram) improves, with TSI above your Buy Threshold.
Sell when TSI crosses below its signal line and momentum weakens, with TSI below your Sell Threshold.
Confirmation: Optional “Confirm on bar close” setting evaluates signals on closed bars to reduce repaint risk.
Trailing stop (visual only)
Units are ticks (uses the symbol’s min tick).
Start Trailing After (ticks): activates the trail only once price has moved in your favor by the set amount.
Trailing Stop (ticks): distance from price once active.
For longs: stop = close - trail; it never moves down.
For shorts: stop = close + trail; it never moves up.
Exits shown on chart when the trailing line is touched or an opposite signal occurs.
Note: This is a simulation for visualization and does not place, manage, or guarantee broker orders.
Inputs you can tune
TSI Settings: Long Length, Short Length, Signal Length, Buy/Sell thresholds, Confirm on Close.
Trailing Stop: Start Trailing After (ticks), Trailing Stop (ticks), Show/Hide trailing lines.
Display: Toggle chart signals, info table, and (optionally) TSI plots on the price chart.
Alerts included
TSI Buy / TSI Sell
Long/Short Trailing Activated
Long/Short Trail Exit
Tips for use
Timeframes/markets: Works on any symbol/timeframe that reports a valid min tick. If your market has large ticks, adjust the tick inputs accordingly.
TSI view: By default, TSI lines are hidden to avoid rescaling the price chart. Enable “Show TSI plots on price chart” if you want to see the oscillator inline.
Non-repainting note: With Confirm on bar close enabled, signals are evaluated on closed bars. Intrabar previews can change until the bar closes—this is expected behavior in TradingView.
Limitations
This is an indicator for education/research. It does not execute trades, and visuals may differ from actual broker fills.
Performance varies by market conditions; thresholds and trail settings should be tested by the user.
Disclaimer
Nothing here is financial advice. Markets involve risk, including possible loss of capital. Always do your own research and test on a demo before using any tool in live trading.
— ProfitGang
Financial Change % Table - ToluFinancial Change % Table which includes revenue , operating profit and earning per share . compares the financial data with previous quarter QoQ and previous year YoY . and shows the change in %.
Institutional level Indicator V5Smart money concept indicator with added VWAP for better understanding for fair price with relation to movement of price.
PFA_Earnings Surprise %📌 Indicator Name: Earnings Surprise %
📖 Description:
The Earnings Surprise % indicator calculates and plots the difference between reported EPS (Earnings Per Share) and analyst consensus estimates, expressed as a percentage of the estimate. It helps traders and investors quickly gauge how much a company’s earnings have deviated from expectations on each earnings release date.
Earnings Surprise % — See how earnings stack up against expectations!
This simple yet powerful tool shows the percentage difference between reported EPS and analyst estimates directly on your chart. Positive surprises are plotted in green, negative surprises in red, so you can instantly spot earnings beats and misses. Great for combining with gap analysis, volume spikes, or technical setups around earnings dates. Works best on daily charts of stocks and ETFs with regular earnings reports.
Fair Value Gap with Swing PointsFair Value Gaps occur when there's a significant price difference between the close of one period and the opening of the next, signaling market inefficiencies. Bullish gaps indicate potential upward momentum, while bearish gaps suggest potential downward pressure.
⚡ AbyssX Dip Hunter ⚡SP_Quant⚡AbyssX Dip Hunter ⚡ by SP_Quant
AbyssX Dip Hunter is a clean and effective indicator designed to help you identify potential dip-buying opportunities using Z-Score analysis and an optional RSI filter.
🔍 How It Works:
Z-Score Logic: Detects statistical price dips when the Z-Score drops below your set threshold.
Optional RSI Filter: Filters signals only when RSI is under a specified level — useful for avoiding false positives in strong trends.
Custom Color Mode: Choose your preferred signal color (Purple, Cyan, Green, or Orange).
Chart Visuals: Dip signals are shown with triangle markers and soft background highlights.
Live Info Panel: Displays real-time RSI, Z-Score, and signal status in a table on your chart.
⚙️ Settings:
Z-Score Length & Threshold
RSI Filter ON/OFF with custom RSI Length and Threshold
Visual Style (Color Mode)
✅ Best for traders who use oversold/mean-reversion strategies or look for extreme pullbacks.
⚠️ Disclaimer:
This indicator is for educational and informational purposes only and does not constitute financial advice, trading advice, or investment recommendations. Use it at your own risk. Always perform your own analysis before making any trading decisions. The author is not liable for any losses or damages resulting from the use of this script.
MK SpreadCalculates the spread between two instruments, with a primary use case of tracking the differential between real (inflation-adjusted) and nominal yields.
ZoneShift+StochZ+LRO + AI Breakout Bands [Combined]This composite Pine Script brings together four powerful trend and momentum tools into a single, easy-to-read overlay:
ZoneShift
Computes a dynamic “zone” around price via an EMA/HMA midpoint ± average high-low range.
Flags flips when price closes convincingly above or below that zone, coloring candles and drawing the zone lines in bullish or bearish hues.
Stochastic Z-Score
Converts your chosen price series into a statistical Z-score, then runs a Stochastic oscillator on it and HMA-smooths the result.
Marks momentum flips in extreme over-sold (below –2) or over-bought (above +2) territory.
Linear Regression Oscillator (LRO)
Builds a bar-indexed linear regression, normalizes it to standard deviations, and shows area-style up/down coloring.
Highlights local reversals when the oscillator crosses its own look-back values, and optionally plots LRO-colored candles on price.
AI Breakout Bands (Kalman + KNN)
Applies a Kalman filter to price, smooths it further with a KNN-weighted average, then measures mean-absolute-error bands around that smoothed line.
Colors the Kalman trend line and bands for bullish/bearish breaks, giving you a data-driven channel to trade.
Composite Signals & Alerts
Whenever the ZoneShift flip, Stoch Z-Score flip, and LRO reversal all agree and price breaks the AI bands in the same direction, the script plots a clear ▲ (bull) or ▼ (bear) on the chart and fires an alert. This triple-confirmation approach helps you zero in on high-probability reversal points, filtering out noise and combining trend, momentum, and statistical breakout criteria into one unified signal.
CVDD Z-ScoreCumulative Value Days Destroyed (CVDD) - The CVDD was created by Willy Woo and is the ratio of the cumulative value of Coin Days Destroyed in USD and the market age (in days). While this indicator is used to detect bottoms normally, an extension is used to allow detection of BTC tops. When the BTC price goes above the CVDD extension, BTC is generally considered to be overvalued. Because the "strength" of the BTC tops has decreased over the cycles, a logarithmic function for the extension was created by fitting past cycles as log extension = slope * time + intercept. This indicator is triggered for a top when the BTC price is above the CVDD extension. For the bottoms, the CVDD is shifted upwards at a default value of 120%. The slope, intercept, and CVDD bottom shift can all be modified in the script.
Now with the automatic Z-Score calculation for ease of classification of Bitcoin's valuation according to this metric.
Created for TRW.
Leader-Lagger DashboardSummary:
The ultimate frustration for a trader: being right on the idea, but wrong on the asset.
You correctly predict a market move, develop a solid bullish or bearish thesis, but the instrument you choose fails to follow through. Meanwhile, a correlated asset makes the exact move you anticipated, leaving you with a losing trade or a missed opportunity.
This common pitfall is precisely what the Leader/Lagger Dashboard is designed to solve.
The Solution: Instant Clarity on Relative Strength
The Leader/Lagger Dashboard provides a clear, real-time verdict on the relative strength between two correlated assets, such as ES (S&P 500 futures) and NQ (Nasdaq 100 futures).
By instantly identifying the Leader (the stronger asset) and the Lagger (the weaker asset), it empowers you to focus your capital on the instrument with the highest probability of performing in line with your market view.
As shown in the example image, if your idea is to short the market, choosing the "Weak" asset (ES) results in a winning trade, while shorting the "Strong" asset (NQ) would have failed. This tool helps you make that critical distinction before you enter.
How It Works
The engine at the core of this dashboard analyzes the price action of two assets on a higher timeframe (defaulting to 90 minutes). It measures how the current bar's high and low are performing relative to the previous bar's range for each asset. By comparing these normalized values, it generates a score to determine which asset is exhibiting stronger momentum (the Leader) and which is showing weakness (the Lagger).
A tie-breaking mechanism using a lower timeframe ensures you always have a decisive verdict.
How to Use It
The principle is simple: Go long the leader, and short the lagger.
If you are Bullish: Look for the asset marked "Strong." This is the instrument most likely to lead the upward move.
If you are Bearish: Look for the asset marked "Weak." This is the instrument most likely to lead the downward move.
By aligning your trade execution with the market's internal momentum, you dramatically increase your odds of success and avoid the frustration of trading against underlying strength or weakness.
Key Features
Instant Verdict: A simple on-chart table displays a "Strong" or "Weak" verdict for each asset.
Focus on the Leader: Easily identify which asset is leading the move to align your trades with momentum.
Avoid the Lagger: Steer clear of the weaker asset that might chop around or reverse, even if your directional bias is correct.
Fully Customizable: Change the two assets to any symbols you trade (e.g., GOLD vs. SILVER, EURUSD vs. GBPUSD).
Adjustable Display: Control the table's position and font size to perfectly fit your chart layout. The table is designed to be visible on lower timeframes (5-minutes and under) to assist with day trading execution.
This tool is designed to be a crucial part of your decision-making process, providing an objective layer of confirmation for your trading ideas. so Stop guessing and start trading the right asset.
As always, use this indicator in conjunction with your own complete analysis and risk management strategy.
Bitcoin Logarithmic Growth Curve 2025 Z-Score"The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
snapshot
snapshot
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns."
Now with Z-Score calculation for easy and constant valuation classification of Bitcoin according to this metric.
Created for TRW
Regime Reaper | QuantEdgeB📊 Regime Reaper | QuantEdgeB
🔍 What is Regime Reaper?
Regime Reaper is QuantEdgeB’s premier regime detection engine, designed to quantify market behavior through a scientific blend of stationarity tests, trend diagnostics, and reversion signals.
Rather than guessing if a market is trending or mean-reverting, Regime Reaper mathematically determines it—blending econometrics with market momentum, volatility texture, and predictive correlation.
💡 Think of Regime Reaper as a financial MRI — probing deep statistical layers to tell you what kind of environment you're in before you make a move.
⚙️ Core Components
✅ Z-Blend Framework
At its core, Regime Reaper combines up to 15 independent signals, each normalized via Z-Scores, including:
• 🧪 Stationarity Tests: ADF, KPSS, PP Test — detecting mean-reverting pressure or randomness
• 🌀 Cycle Predictors: Hurst exponent, Fourier approximation
• 🔥 Trend Strength: ADX, Price Momentum Correlation (PMC), Relative Price Change
• 💣 Volatility Analysis: GARCH, BBW, VAM
• ⚡ Behavioral Texture: Choppiness Index, Wavelet Energy, Half-Life
Each signal is optionally enabled/disabled — allowing surgical custom blends tailored to your asset or timeframe.
✅ Z-Avg Value Engine
• All active signals are aggregated into a composite Z-Score (Z-Avg)
• This value forms the backbone of regime classification logic
• Combined with adaptive percentile thresholds for precision detection
🎯 Regime Classification Logic
🧭 Z-Avg-Based Threshold Model
Regime Reaper classifies markets into three states:
Z-Avg Score Market Regime
≥ Threshold + Percentile 🔺 Trending
≥ Threshold Only ⚖️ Neutral / Weak Trend
≤ Reversion Threshold 🔻 Mean-Reverting
These scores are colored, plotted, and displayed in a histogram view to make regime transitions immediately visible.
✅ Custom threshold values via:
• Trending Threshold
• Reverting Threshold
• Percentile Rank Comparison
📊 Dashboard Overlay (Optional)
Regime Reaper includes three live tables:
1. Metrics Panel (𝓡𝓮𝓰𝓲𝓶𝓮 𝓡𝓮𝓪𝓹𝓮𝓻)
o Displays the Z-Score of each active metric
o Highlights total Z-Blend Score
o Shows current regime stage (Trending, Reverting, Neutral)
2. Signal Scanner Table
o Explains current Z-Avg score & decision logic
o Displays thresholds for trend/revert neutrality
o Delivers a stage verdict with live updates
3. Info Panel
o Visual color-coded regime bars
o Snapshot of all 3 possible states
🎨 Visual Signal System
• Z-Avg Histogram — core value colored by regime state
• Background Coloring — lightly shades trending vs reverting periods
• Table Text Coloring — shows metric strength in live table updates
• User-Specified Color Themes — switch between Magic, Strategy, Cool, etc.
🧠 Why Use Regime Reaper?
Because knowing the market’s regime changes everything:
• Reversion strategies fail in strong trends
• Trend systems bleed during choppy reverts
• Random walks are dangerous to both
With Regime Reaper, you no longer have to guess — you measure.
💼 Ideal Use Cases
• Trend vs Mean-Reversion Filters
• System Mode Switching (Auto Toggle)
• Volatility Regime Adaptation
• Signal Confidence Boosting (by regime match)
• Portfolio Allocation Strategy Filters
🧬 Default Config
• Composite Model: All 15 metrics ON
• Trending Threshold: +0.15
• Reversion Threshold: −0.15
• Adaptive Filtering via Percentile Ranks
🧬 In Summary
Regime Reaper | QuantEdgeB is more than a filter — it's a regime recognition system built on powerful statistical indicators and dynamic Z-Score fusion. It doesn’t just observe behavior; it categorizes it.
Use it to confirm entries, time exits, suppress signals in bad regimes, or dynamically change your system logic.
📌 Trade the Right Logic in the Right Market | Powered by QuantEdgeB
🔹 Disclaimer: No indicator guarantees future performance.
🔹 Tip: Tune metric
15-Min ORB Box x SmartBlackGirlThe 15-Minute ORB (Opening Range Breakout) Box plots the first 15-minute high and low after the market opens, giving you a visual reference for potential breakout zones and **direction
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The indicator is designed to enable high profitability by combining various established technical analysis approaches into one tool, facilitating decision-making regarding entry and exit points.
The script can be integrated and used directly in TradingView by creating a new indicator script and pasting the code there.
