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Educational
Cost Basis of DCA Strategy (Enhanced)“Cost Basis of DCA Strategy (Enhanced): An Analytical Tool for Smarter DCA Investing”
The indicator designed here serves as a comprehensive analytical tool for evaluating a Dollar-Cost Averaging (DCA) strategy. Instead of merely recording scattered buy transactions, it integrates all purchases into a clear framework that reveals the real cost basis, portfolio performance, and capital allocation. Its primary function is to transform the concept of DCA from a mechanical process into a measurable and strategic decision-making system.
At the foundation of its operation, the user provides essential inputs such as the initial capital, the price and size of each buy transaction, and an optional sell price for hypothetical exit scenarios. With these inputs, the indicator calculates how many units were acquired in total, how much money was spent, and what the average cost per unit—the cost basis—truly is. This cost basis acts as the anchor for evaluating whether the market price has moved in favor or against the investor’s average entry point.
Beyond this, the indicator goes further by calculating both realized and unrealized dimensions of performance. It presents the current market value of holdings based on live price data and contrasts it with the total cost to derive unrealized profit or loss in both absolute terms and percentages. If the user sets a sell price, the tool simulates a full liquidation scenario, displaying the expected profit or loss should all holdings be sold at that level. This dual perspective enables the user to examine their strategy both from a present-value standpoint and a forward-looking one.
In addition, the indicator keeps track of remaining capital—the portion of initial funds not yet deployed into purchases—thus bridging the gap between portfolio construction and financial planning. It also reports the number of buy transactions, reinforcing awareness of execution discipline in DCA.
For visualization, the system is not confined to numbers alone. It marks each buy price directly on the price chart with distinct horizontal lines, labeled for clarity. This allows the trader to see not just statistics in a table but also the spatial relationship between historical entry points and ongoing market dynamics.
In essence, this indicator reframes the practice of DCA into a structured analytical exercise. It empowers investors to understand the true average entry cost, evaluate ongoing performance, and simulate future outcomes under different price scenarios. By doing so, it elevates DCA from a passive habit into an active, data-driven investment methodology, allowing users to make more informed, confident, and strategically grounded decisions.
RSI: alternative derivationMost traders accept the Relative Strength Index (RSI) as a standard tool for measuring momentum. But what if RSI is actually a position indicator?
This script introduces an alternative derivation of RSI, offering a fresh perspective on its true nature. Instead of relying on the traditional calculation of average gains and losses, this approach directly considers the price's position relative to its equilibrium (moving average), adjusted for volatility.
While the final value remains identical to the standard RSI, this alternative derivation offers a completely new understanding of the indicator.
Key components:
Price (Close)
Utilizes the closing price, consistent with the original RSI formula.
normalization factor
Transforms raw calculations into a fixed range between -1 and +1.
normalization_factor = 1 / (Length - 1)
EMA of Price
Applies Wilder’s Exponential Moving Average (EMA) to the price, serving as the anchor point for measuring price position, similar to the traditional RSI formula.
myEMA = ta.rma(close,Length)
EMA of close-to-close absolute changes (unit of volatility)
Adjusts for market differences by applying a Wilder’s EMA to absolute price changes (volatility), ensuring consistency across various assets.
CC_vol = ta.rma(math.abs(close - close ),Length)
Calculation Breakdown
DISTANCE:
Calculate the difference between the closing price and its Wilder's EMA. A positive value indicates the price is above the EMA; a negative value indicates it is below.
distance = close - myEMA
STANDARDIZED DISTANCE
Divide the distance by the unit of volatility to standardize the measurement across different markets.
S_distance = distance / CC_vol
NORMALIZED DISTANCE
Normalize the standardized distance using the normalization factor (n-1) to adjust for the lookback period.
N_distance = S_distance * normalization_factor
RSI
Finally, scale the normalized distance to fit within the standard RSI range of 0 to 100.
myRSI = 50 * (1 + N_distance)
The final equation:
RSI = 50 ×
What This Means for RSI
Same RSI Values, Different Interpretation
The standard RSI formula may obscure its true measurement, whereas this approach offers clarity.
RSI primarily indicates the price's position relative to its equilibrium, rather than directly measuring momentum.
RSI can still be used to analyze momentum, but in a more intuitive and well-informed way.
RK Scalper V1.0Version 1.0
Scalper Indicator
Use multiple options to decide the best possible scalping possibilities on 1, 3, 5 and 15 min timeframes
1. 3 different EMA trend lines to decide direction and reversal; option to include EMA crossover to take entry and exit positions
2. Show signal when price cross VWAP with huge volume
3. Show SuperTrend and identify possible reversal when price touches the SuperTrend line
4. Show VWAP line
5. Show SuperTrend VWAP crossover with an option to either include volume spike or not
6. Show VWMA line to decide exit points when price moves below at buy and above at sell positions
7. Show Open=High / Open-Low to see the buy and sell pressure and buyer seller dominance
8. Show Volume spike indication on Volume for NIFTY, BANK NIFTY and MIDCAP NIFTY futures volume on their respective underlying asset
9.
Note: It is batter to use scalp indicator along with trend and momentum indicators to have better results.
RK CPR Buy/Sell Setup Ver1.0Version 1.0
CPR based Buy and Sell Indicator
First option is to show the Buy and Sell indicators, in which multiple options given to users to adjust the buy and sell setup.
1. Include Trend direction
2. Include candlestick touching the EMA 20 / EMA 50 / EMA 100 / VWAP trend lines
3. Include Momentum check
4. Include candlestick patterns to decide buy or sell
5. Exclude Wide CPR day for trading
Second option is the identify the different possible reversal indicators and same are as follows
1. Extreme Reversal
2. Outside Reversal
3. Doji Reversal
4. Triple/Double wick Reversal
5. Pulllback Reversal
Note: It is batter to use reversal indicator along with trend and momentum to have better results.
Global M2 Money SupplyThis indicator calculates and plots an aggregated estimate of the Global M2 money supply, expressed in U.S. dollar terms. It combines M2 data from major economies and regions—including the U.S., Eurozone, Canada, the U.K., Switzerland, China, Japan, India, Brazil, and others—and adjusts each by its respective FX rate to USD. By summing these series, the script provides a broad view of worldwide liquidity conditions in one line.
A user-defined offset in days allows you to shift the global M2 line forward or backward, making it easier to visually compare liquidity trends against asset prices such as Bitcoin, gold, or equities. This tool is designed for traders and macro observers who want to study how global money supply growth or contraction correlates with financial markets over time.
이 지표는 전 세계 주요 국가와 지역의 M2 통화량을 달러 기준으로 합산하여 글로벌 유동성 지표로 보여줍니다. 미국, 유로존, 캐나다, 영국, 스위스, 중국, 일본, 인도, 브라질 등 여러 지역의 M2 데이터를 각 통화의 환율(USD 환산)로 조정한 뒤 합산해 하나의 흐름으로 표현합니다. 이를 통해 글로벌 차원의 통화 공급 변화를 한눈에 파악할 수 있습니다.
또한 사용자가 지정한 일 단위 오프셋 기능을 통해 글로벌 M2 라인을 앞뒤로 이동시켜, 비트코인·금·주식 등 다양한 자산 가격과의 시차적 관계를 직관적으로 비교할 수 있습니다. 거시경제 환경과 자산시장 간의 상관성을 연구하거나 시장 유동성 추이를 모니터링하려는 투자자에게 유용한 도구입니다.
Gold Lagging (N days)This indicator overlays the price of gold (XAUUSD) on any chart with a customizable lag in days. You can choose the price source (open, high, low, close, hlc3, ohlc4), shift the series by a set number of daily bars, and optionally normalize the values so that the first visible bar equals 100. The original gold line can also be displayed alongside the lagged series for direct comparison.
It is especially useful for analyzing delayed correlations between gold and other assets, observing shifts in safe-haven demand, or testing hypotheses about lagging market reactions. Since the lag is calculated on daily data, it remains consistent even if applied on intraday charts, while the indicator itself can be plotted on a separate price scale for clarity.
이 지표는 금(XAUUSD) 가격을 원하는 차트 위에 N일 지연된 형태로 표시합니다. 가격 소스(시가, 고가, 저가, 종가, hlc3, ohlc4)를 선택할 수 있으며, 지정한 일 수만큼 시리즈를 뒤로 이동시킬 수 있습니다. 또한 첫 값 기준으로 100에 맞춰 정규화하거나, 원래 금 가격선을 함께 표시해 비교할 수도 있습니다.
금과 다른 자산 간의 지연 상관관계를 분석하거나 안전자산 수요 변화를 관찰할 때 유용하며, 시장 반응의 시차 효과를 검증하는 데에도 활용할 수 있습니다. 지연은 일봉 데이터 기준으로 계산되므로 단기 차트에 적용해도 일 단위 기준이 유지되며, 별도의 가격 스케일에 표시되어 가독성을 높일 수 있습니다.
Bitcoin Lagging (N Days)This indicator overlays Bitcoin’s price on any chart with a user-defined N-day lag. You can select the BTC symbol and timeframe (daily recommended), choose which price source to use (open, high, low, close, hlc3, ohlc4), and shift the series by a chosen number of days. An option to normalize the series to 100 at the first visible value is also available, along with the ability to display the original BTC line for comparison.
It is designed for traders and researchers who want to test lagging relationships between Bitcoin and other assets, observe correlation changes, or visualize how BTC’s past prices might align with current market movements. The lagging is calculated based on daily candles, so even if applied on intraday charts, the shift remains in daily units.
이 지표는 비트코인 가격을 원하는 차트 위에 N일 지연된 상태로 표시해 줍니다. 심볼과 타임프레임(일봉 권장)을 선택할 수 있으며, 가격 소스(시가, 고가, 저가, 종가, hlc3, ohlc4)도 설정 가능합니다. 또한 시리즈를 첫 값 기준으로 100에 맞춰 정규화하거나, 원래의 비트코인 가격선을 함께 표시할 수도 있습니다.
비트코인과 다른 자산 간의 시차 효과를 분석하거나 상관관계 변화를 관찰할 때 유용하게 활용할 수 있습니다. 지연은 일봉 기준으로 계산되므로, 분·시간 차트에 적용해도 항상 일 단위로 반영됩니다.
Nick2k Trend Tracker MT botNick2k Trend Tracker MT bot
Type: Indicator (signals + PineConnector alerts for EAs)
Markets: Designed for XAUUSD (gold), adaptable to other symbols
Timeframes: Optimized for M5/M15
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What it does
Nick2k Trend Tracker MT bot identifies trend flips using a percentile-normalized SMA slope with hysteresis, then applies a multi-layer filter suite to avoid false signals in low-quality conditions.
It can optionally auto-manage trades via PineConnector:
Send open orders with SL/TP (ATR- or pip-based)
Breakeven activation
Dual trailing stops (pip-based or ATR-based)
Staged partial closes (up to 3 levels)
The indicator also:
Highlights chop zones in the background
Provides diagnostic labels showing which filters passed/failed
Lets you disable all alerts with one checkbox (visual testing mode)
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Core logic (simplified)
Trend Engine: SMA slope normalized by a rolling percentile; flips with hysteresis at +0.1/–0.1.
Filters: optional checks for slope strength, ADX, narrow range ratio, ATR squeeze, higher-timeframe slope.
Sessions: entry/management can be gated to London, NY, Tokyo, Sydney sessions and weekdays.
Chop highlight: background shading when ranges/low-volatility are detected for consecutive bars.
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Visuals
Colored SMA line (gradient by slope)
BUY/SELL labels at valid flip bars
Chop background (yellow overlay)
Filter score/diagnostic label (optional)
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Alerts & PineConnector integration
Open orders: sent at valid BUY/SELL flips with embedded SL/TP + BE/trailing if enabled
Partial closes: 3 configurable milestones (ATR or pip based, % or fixed lots)
Master toggle: switch all alerts ON/OFF instantly
Alerts are formatted in PineConnector EA syntax for compatibility with MetaTrader auto-trading.
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Inputs (organized by group)
SMA & Theme (length, colors)
Auto Trading (license, symbol, lots, master toggle)
SL/TP Target Type (prices vs pips)
ATR SL/TP (length, multipliers, rounding)
Breakeven (trigger/offset)
Pip Trailing (trigger/dist/step)
ATR Trailing (TF, period, multiplier, trigger)
Partial Closes (mode, lots or %)
Time Filters (sessions, weekdays)
Filters (Slope, ADX, NRR, ATR squeeze, HTF confirm)
Chop Zone Highlight (on/off, hold bars, color)
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Why this script is unique (and closed-source)
This is not a simple moving-average crossover. It combines several custom-built methods that are rarely seen in public scripts:
Normalized SMA slope with hysteresis: avoids whipsaws, adapts to volatility regimes.
Multi-filter confirmation: ADX, NRR, ATR squeeze, HTF slope — stacked to improve quality.
Chop detection with persistence: custom counter/hold logic to highlight ranging markets.
Integrated trade management: PineConnector-ready messages with SL/TP, breakeven, dual trailing stops, staged partial closes.
EA-compatible syntax: formatted exactly for PineConnector EAs, including safety toggles.
This represents a full trading framework designed for semi-automated gold scalping, not just a “signal indicator.”
The source is protected to prevent clones and preserve development effort invested in unique logic and PineConnector integration.
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Recommended starting settings (XAUUSD M5/M15)
Pip size: 0.10
Slope threshold: 0.20 (M5), 0.16–0.20 (M15)
ADX min: 18–22
NRR floor: 2.0–2.4
ATR ratio: 0.65–0.75
ATR SL/TP: SL = 1.5×ATR, TP = 2.5×ATR
Sessions: London & NY
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Limitations & disclaimer
Not financial advice. Test on demo before live trading.
Performance depends on broker symbols, spread, and volatility regime.
Auto-trading requires PineConnector EA set up correctly.
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Changelog
v1.0 – Initial release (trend engine, filters, sessions, chop highlight, PineConnector alerts, BE/trailing, partial closes, diagnostics)
CAD DataThis indicator provides all of the data required to use the Context Analysis Dashboard (CAD) for live trading.
G. Santostasi Bitcoin Power Law Monte Carlo IndicatorOverview:
The "G. Santostasi Bitcoin Power Law Monte Carlo" is a sophisticated TradingView indicator inspired by the Bitcoin Power Law Theory developed by physicist Giovanni Santostasi.
This theory posits that Bitcoin's price follows a power-law relationship with time, measured in days since the Bitcoin Genesis Block (January 3, 2009). The indicator leverages this framework to analyze Bitcoin's price dynamics through a normalized metric called "Daily Slopes," which captures local deviations from the long-term power-law trend. By fitting these Daily Slopes to a t-location scale distribution on a moving window, the indicator computes key parameters (mu, sigma, and nu) and plots them along with deviation bands. This allows traders to identify local minima and maxima in price action relative to the global power-law slope of approximately 5.9.Additionally, the indicator incorporates Monte Carlo simulations to project potential future price paths up to 100 days ahead, generating up to 500 randomized trajectories based on the statistical properties of the Daily Slopes. This tool is particularly useful for understanding Bitcoin's inherent diminishing returns, assessing market stability, and forecasting short-term scenarios while emphasizing the asset's long-term predictability as a self-organizing network akin to natural systems.
The indicator does not predict exponential growth but instead highlights Bitcoin's scale-invariant behavior, where returns diminish predictably over time—a feature, not a bug, of its design. It has been observed that the core metric (mu) remains stable across Bitcoin's entire history, reinforcing the power law as Bitcoin's "DNA."
Core Concept: Daily Slopes:
At the heart of the indicator is the "Daily Slopes" metric, which normalizes daily logarithmic returns to account for the diminishing nature predicted by the power-law model. This normalization reveals a stable "local slope" (n) that oscillates around a fixed global value, providing insight into Bitcoin's consistent behavior over time.
Definition and Calculation:
Daily logarithmic returns are calculated as log(P2/P1)\log(P_2 / P_1)\log(P_2 / P_1), where P2P_2P_2 is the current day's closing price and P1P_1P_1 is the previous day's closing price.
According to the power-law model, if Bitcoin's price ( P(t) ) follows P(t)=c⋅tnP(t) = c \cdot t^nP(t) = c \cdot t^n
(where ( t ) is days since the Genesis Block, ( c ) is a constant, and n≈5.9n \approx 5.9n \approx 5.9
is the global slope from log-log regression), then the expected daily log return is n⋅log((t+1)/t)n \cdot \log((t+1)/t)n \cdot \log((t+1)/t)
.
The Daily Slope is thus the normalized value:
Daily Slope=log(P2/P1)log((t+1)/t)\text{Daily Slope} = \frac{\log(P_2 / P_1)}{\log((t+1)/t)}\text{Daily Slope} = \frac{\log(P_2 / P_1)}{\log((t+1)/t)}
This normalization "stabilizes" the returns by dividing out the theoretical decay factor log((t+1)/t)\log((t+1)/t)\log((t+1)/t)
, which diminishes as ( t ) increases (reflecting slower growth in mature systems).
Result: The Daily Slope represents a "local n" that should remain stable, oscillating around the global slope of ~5.9 without long-term drift. Empirical data shows this stability holds over Bitcoin's 16-year history, with oscillations but no systematic change—indicating Bitcoin has statistically "done the same thing" since inception.
Interpretation:
Positive deviations (Daily Slope > 5.9) signal bullish momentum or potential local maxima.
Negative deviations (Daily Slope < 5.9) indicate bearish pressure or local minima.
The metric adjusts for absolute volatility, which appears to decrease over time due to diminishing returns. However, when normalized via Daily Slopes, relative volatility has been constant for the last 8 years, underscoring Bitcoin's resilience to macroeconomic factors.
Distribution Fitting and Parameter Estimation:
To quantify the behavior of Daily Slopes, the indicator fits them to a t-location scale distribution (Student's t-distribution with location and scale parameters) over a user-configurable moving window (e.g., 365 days for annual analysis).
This distribution is chosen as the best empirical fit for the heavy-tailed, outlier-prone nature of Bitcoin's normalized returns, outperforming alternatives like Gaussian or Laplacian.t-Location Scale Distribution:
The distribution is parameterized by:μ (mu): Location parameter, representing the mean or "average slope." This is the most critical metric, stable around 5.9 across Bitcoin's history. It tracks the central tendency of Daily Slopes and signals overall market regime (e.g., rising mu indicates strengthening momentum).
σ (sigma): Scale parameter, akin to standard deviation, measuring the spread or volatility of slopes. It has shown slight increases in certain contexts (e.g., hash rate applications) but remains stable for price data.
ν (nu): Degrees of freedom, controlling the "tailedness" (lower ν means heavier tails, capturing extreme events like bubbles or crashes).
Fitting is performed on a rolling basis, updating μ, σ, and ν dynamically.
Plotting:
Local μ: Plotted as a central line, showing the moving average slope.
Deviation Bands: μ + σ (upper band) and μ - σ (lower band), highlighting 1-standard-deviation ranges.
These bands help identify overbought/oversold conditions by measuring deviations from the global mean of 5.9.
For example:
Crossing above μ + σ may signal a local maximum (potential sell opportunity).
Dipping below μ - σ could indicate a local minimum (buy signal).
Additional visualizations include raw Daily Slopes (oscillating series) and smoothed averages for clarity.
Stability and Insights:μ has remained remarkably stable over 16 years, oscillating without drift, validating the power law's predictive power.
Parameters may show minor trends in rolling windows (e.g., slight σ increases), but no monotonic drift is observed in price data. This stability extends to related metrics like addresses and hash rate, where Daily Slopes can be derived similarly (e.g., via log(A2/A1) / log((t+1)/t) for addresses, yielding equivalent slopes around 5.9).
Monte Carlo Simulations for Future Projections
The indicator enables short-term forecasting (up to 100 days) by reversing the normalization process and simulating paths using the fitted distribution.
Projection Mechanism:
Recover expected daily returns: Multiply the sampled Daily Slope (drawn from the t-location scale distribution with current μ, σ, ν) by log((t+1)/t)\log((t+1)/t)\log((t+1)/t)
.
Generate randomized samples to create up to 500 Monte Carlo paths, incorporating the distribution's properties to model uncertainty (e.g., heavy tails for rare events).
Simulations can use the full historical dataset for broader spreads or recent windows (e.g., last 8 years) for tighter, regime-specific forecasts.
Output: Fan chart of projected prices, showing median path (based on μ), confidence intervals (e.g., ±σ bands), and extreme scenarios.
Applications and Limitations:
Useful for risk assessment, e.g., probability of reaching $200K in 2025 is low (1-2% per recent simulations).
Assumes parameters evolve minimally; if drift is detected, simulations can adjust dynamically.
Not for long-term predictions (beyond 100 days), as the power law excels in multi-year trends rather than short-term noise.
Empirical validation: Simulations align with historical backtests, where deviations (bubbles/crashes) revert to the power-law trend.
Usage Notes Inputs:
Customize moving window size, number of Monte Carlo paths (default: 500), projection horizon (up to 100 days), and global slope (default: 5.9).
Visuals: Overlay on BTCUSD log-log chart for context; bands and simulations appear in separate panels.
Caveats: This is not financial advice. The power law describes emergent behavior from network effects, not guarantees. Cycles and bubbles are secondary deviations, not core to the model.
Extensions: The concept applies beyond price (e.g., to addresses or hash rate), revealing interconnected power laws in Bitcoin's ecosystem.
This indicator transforms Santostasi's theoretical insights into a practical tool, empowering users to navigate Bitcoin's dynamics with statistical rigor.
Seasonality con números RAMÓN SEGOVIAMonthly Bands – Colored Monthly Stripes for Statistical Analysis
Short Description
This indicator paints vertical background stripes by calendar month on your chart, making it easy to run statistical/seasonality analysis, compare monthly performance, and visually identify recurring patterns across assets and timeframes.
How It Works
Detects each new month and applies a background band spanning from the first to the last candle of that month.
Alternates colors automatically so consecutive months are easy to distinguish, or use a single uniform color for a clean look.
Optional: add dotted lines at the start/end of each month for precise separation.
Inputs / Settings
Color mode: alternating (odd/even months) or single.
Colors & opacity of the bands.
Border style: none / solid / dotted.
Highlight specific months: e.g., “Jan, Apr, Oct” with a different color.
Labels option: show month & year abbreviations at the top/bottom of the chart.
Drawing zone: full background vs. price-only area (to avoid covering lower indicators).
Typical Use Cases
Seasonality studies: identify historically bullish/bearish months.
Visual backtesting: segment the chart by months to evaluate strategy performance.
Context tracking: quickly locate reports, monthly closes, or economic cycles.
Compatibility
Works on all timeframes, including intraday (each band covers the full calendar month).
Lightweight and visual-only; doesn’t interfere with price or indicators.
Pro Tips
Combine with monthly returns (%) or candle counters to quantify each stripe.
Use labels when preparing clean presentations or trade journal screenshots.
Notes
This is a visual tool only, not a buy/sell signal generator.
Default settings are optimized for clarity and minimal clutter.
H/L Swings/pivots detectorThis indicator detects and labels swing highs and swing lows using pivot logic.
It highlights market structure shifts by identifying:
- Higher Highs (HH) and Lower Highs (LH)
- Lower Lows (LL) and Higher Lows (HL)
Traders often use these levels to analyze trends, reversals, and key support/resistance zones.
The script also plots pivot markers above highs and below lows for visual clarity.
This tool is designed for educational and analytical purposes, and it does not provide financial advice or guaranteed results.
📂 Categories (choose when publishing)
Type of script → Indicator
Category → Trend Analysis (fits best for HH/LL pivots)
Optionally → Support/Resistance (if you emphasize pivots as zones)
swing high
swing low
pivot points
market structure
trend analysis
higher high
lower low
support resistance
Multi-TF 👀### Multi-Timeframe Analysis (MTF-Analysis)
**Overview**
The Multi-Timeframe Analysis indicator is a powerful visualization tool designed for traders who incorporate multi-timeframe (MTF) strategies into their decision-making process. It overlays compact, customizable candle representations from up to four higher timeframes directly on your chart, positioned to the right of the last bar for quick reference. This allows you to monitor price action, momentum via EMAs, and key levels like Fair Value Gaps (FVGs) across multiple resolutions without switching charts. Built with efficiency in mind, it supports automatic timeframe detection, real-time updates, and a clean, non-intrusive design that enhances your trading workflow.
Ideal for day traders, swing traders, and scalpers, this indicator helps identify alignments between timeframes, spot potential reversals or continuations, and validate entries/exits based on higher-timeframe context. It leverages Pine Script v6 for smooth performance, with optimizations to handle up to 5000 bars back and extensive drawing limits.
**Key Features**
- **Multi-Timeframe Candle Display**: Renders recent candles (configurable from 5 to 100 per timeframe) from selected higher timeframes (e.g., 5m, 15m, 1H, 4H) as compact bars with customizable width, spacing, and padding. Bullish and bearish candles are color-coded for instant recognition.
- **Automatic Timeframe Adaptation**: When enabled, the indicator intelligently selects complementary timeframes based on your chart's resolution (e.g., on a 1m chart, it might show 5m, 15m, and 1H). Manual overrides are available for full control.
- **EMA Overlays**: Plots EMA9, EMA21, and EMA50 on each MTF section using a user-defined source (e.g., OHLC/4, close). EMAs can be dashed for clarity and enabled/disabled per timeframe, helping to gauge momentum and trend strength.
- **Fair Value Gaps (FVGs)**: Detects bullish (+FVG) and bearish (-FVG) gaps with a configurable lookback length (5-50 bars). Gaps are visualized as dotted boxes extending from the candle, highlighting potential support/resistance zones or imbalances.
- **Time Labels and Debugging**: Displays timestamp labels under every fourth candle for chronological context. A debug mode expands spacing and adds detailed labels (e.g., OHLC, volume, EMA values) for testing and verification.
- **Customization Options**: Extensive inputs for colors (bodies, wicks, EMAs, FVGs), label sizes/styles, and layout ensure seamless integration with your chart theme. Supports futures symbols with a time offset adjustment.
- **Performance Optimizations**: Uses arrays for efficient data management, clears drawings on realtime updates or timeframe changes, and limits buffer sizes to prevent overload.
**How to Use**
1. Add the indicator to your chart via TradingView's "Indicators" menu.
2. Configure timeframes: Enable/disable up to four TFs and set the number of candles to display. Use "Auto Timeframe" for smart defaults.
3. Adjust EMAs: Select the source type and toggle per TF to focus on relevant momentum signals (e.g., EMA9 crossovers for short-term trades).
4. Enable FVGs: Activate per TF and tweak the length to suit your market (shorter for volatile assets, longer for trends).
5. Fine-tune appearance: Modify padding, candle width, and colors to avoid clutter. Use debug mode during setup.
6. Interpret: Align your chart's price action with MTF candles—look for confluence in trends, FVGs filling as support/resistance, or EMA alignments for high-probability setups.
**Input Settings**
- **General**: Hour offset for time adjustments (useful for futures).
- **Timeframes**: Enable TFs 1-4, select resolutions (e.g., "5m"), and set candle counts. Auto mode simplifies this.
- **FVG/iFVG**: Toggle per TF, customize colors and detection length.
- **EMA**: Enable per TF, choose source, colors, and dashed style.
- **Candle Appearance**: Bull/bear colors for bodies/wicks, width/spacing/padding, label size/color.
- **Debug**: Expands view for detailed inspection.
**Notes**
- This indicator is non-repainting and updates in realtime, but performance may vary on lower timeframes with many candles—reduce counts if needed.
- FVGs are calculated locally on recent bars for efficiency; historical gaps beyond the buffer aren't shown.
- Compatible with all symbols, but best on volatile markets like forex, crypto, or indices.
- Feedback welcome—updates may include more MA types or advanced FVG filters.
Enhance your edge with multi-timeframe insights—try MTF-Analysis today!
Pro BTB Pour Samadi Indicator [TradingFinder] Back To Breakeven🔵 Introduction
The Pro BTB (Professional Back To Breakeven) strategy is one of the most advanced price action setups, designed and taught by Mohammad Ali Poursamadi, an international Iranian trader and a well-known instructor of financial market analysis.
The main logic of this strategy is based on the natural behavior of the market :
Breakout of a key level: Price moves beyond an important support or resistance.
Retest / Back To Breakeven: Price returns to the broken level.
Continuation of the main trend: Entry at this point allows alignment with the dominant market direction.
To better understand Pro BTB, it is necessary to first know the concept of a Spike. A spike refers to a sudden and powerful movement of price in one direction, usually caused by heavy order flow. Such a move creates an Imbalance between buyers and sellers. Because the market does not have enough time to distribute orders fairly, it leaves an Inefficiency on the chart.
The direct result of this process is the formation of a Fair Value Gap (FVG) a gap between candles that shows trades were not distributed evenly. In simple terms: the spike is the cause, and Imbalance, Inefficiency, and FVG are its consequences.
In practice, Pro BTB works effectively in both bullish and bearish structures. In a Bullish Setup, a bullish spike first breaks a resistance level. Then, when price returns to that same level, a safe and low-risk buying opportunity is created. Conversely, in a Bearish Setup, a bearish spike breaks a support level, and when price comes back to the broken level, it provides the best conditions for a short entry. These two examples illustrate how Pro BTB logic provides precise, low-risk entries in both directions of the market.
🔵 How to Use
The Pro BTB (Back To Breakeven) strategy allows traders to enter precisely after price returns to the breakout level; this way the entry aligns with the natural market flow while risk is minimized. In practice, this method is simple yet powerful: first, identify a valid breakout on a key level, then wait for price to return to that level, and finally, take the entry in the direction of the main trend.
🟣 Bullish Setup
When a bullish spike occurs and a key resistance is broken, price usually returns to the same level. This level, now acting as support, provides the best opportunity for a long entry. In this scenario, the stop-loss is placed behind the breakout candle or slightly below the broken level, and the take-profit target should be defined with at least a 1:2 risk-to-reward ratio. With strong momentum, higher targets can also be considered.
🟣 Bearish Setup
In a bearish scenario, a bearish spike breaks a key support. After the breakout, price usually returns to the same level, which now acts as resistance. This creates the best conditions for a short entry. The stop-loss is placed behind the breakout candle or slightly above the broken level, while the take-profit target is set with a risk-to-reward ratio greater than 1:2.
🟣 General Rules of Pro BTB
To apply Pro BTB correctly, several key rules must be followed :
The breakout must be valid and occur on a key level.
Always wait for the retest; do not enter immediately after the breakout.
Entry should only happen when price touches the broken level and shows candlestick confirmation.
The stop-loss (SL) must be placed behind the breakout candle or the broken level.
The take-profit (TP) must always be at least twice the trade risk.
For higher reliability, the breakout should align with the trend on higher timeframes.
🟣 Six Entry Methods in Pro BTB
For greater flexibility, Pro BTB offers six standard entry methods :
Market Entry : Enter immediately at the breakout level.
Limit Order : Place a limit order on the breakout level.
Stop Order : Enter only after confirmation of continuation.
Confirmation Candle : Enter after a confirmation candle closes on the level.
Pattern Entry : Enter based on candlestick patterns such as Pin Bar or Engulfing.
Zone Entry : Enter from a zone instead of an exact point to account for market noise.
🔵 Setting
🟣 Spike Filter | Movement
Minimum Spike Bars : Defines the minimum number of consecutive candles required for a valid spike.
Movement Power : Enables or disables the momentum-based spike filter.
Movement Power Level : Sets the strength threshold; higher values filter out weaker moves and only detect strong spikes.
🟣 Spike Filter | Gap
Gap Filter : Enables or disables the gap filter.
Gap Type : Selects which type of gap should be detected (All Gaps, Significant, Structural, Major).
🟣 Spike Filter | Doji
Doji Tolerance : Defines whether doji candles are allowed within a spike.
Max Doji Body Ratio : Maximum ratio of body-to-total candle size for classifying a candle as a doji.
Max Doji in Spike Ratio : Maximum percentage of doji candles allowed within a spike.
🟣 Position Management
Stop-Loss Threshold : Enables or disables the stop-loss threshold feature.
Stop-Loss Threshold Value : Defines the value of the stop-loss threshold for risk management.
Risk-Reward Ratio : Sets the desired risk-to-reward ratio (e.g., 1:1 or 1:2).
Include SL Threshold in R:R : Determines whether the stop-loss threshold is included in risk-to-reward calculations.
🟣 Display Settings
Display Mode : Chooses between Setup (showing setups) or Signal (showing trade signals).
Show Entry Levels: Displays entry levels on the chart (buy/sell zones) when enabled
Only Display the Last Position : Displays only the most recent position on the chart when enabled.
Setup Width Drawing : Adjusts the visual width of the setup drawings on the chart for better visibility.
🟣 Alert
Alert : Enables alert notifications. When turned on, you can set TradingView alerts to receive notifications once the setup or signal conditions are met
🔵 Conclusion
The Pro BTB (Back To Breakeven) strategy is a smart and structured entry method based on natural market behavior after a breakout and retest of the broken level. It helps traders avoid emotional, high-risk entries by waiting for market confirmation and entering precisely at a point that aligns with the main trend and sits closest to the key level.
The simplicity of its rules, flexibility in entry methods, and a risk-to-reward ratio above 2 have made Pro BTB one of the most popular tools among price action traders. Nevertheless, as with any strategy, it is recommended to practice it in demo accounts or through personal backtesting before applying it to real trading, in order to find the entry conditions that best suit your trading style.
PongExperience PONG! The classic arcade game, now on your charts!
With this indicator, you can finally achieve your lifelong dream of beating the Markets. . . at PONG!
Pong is jam-packed with features! Such as:
2 Paddles
A moving dot
Floating numbers
The idea of a net
This indicator is solely a visualization, it serves simply as an exercise to depict what is capable through PineScript. It can be used to re-skin other indicators or data, but on its own, is not intended as a market indicator.
With that out of the way...
> PONG
The Pong indicator is a recreation of the classic arcade game Pong developed to pit the markets against the cold hard logic of a CPU player.
Given the lack of interaction that is capable, the game is not played in the typical sense, by a player and computer or 2 players.
This version of Pong uses the chart price movements to control the "Market" Paddle, and it is contrasted by a (not AI) "CPU" Paddle, which is controlled by its own set of logic.
> Market Paddle
The Market Paddle is controlled by a data source which can be input by the user.
By default (Auto Mode), the Market Paddle is controlled through a fixed length Donchian channel range, pinning the range high to 100 and range low to 0. As seen below.
This can be altered to use data from different symbols or indicators, and can optionally be smoothed using multiple types of Moving Averages.
In the chart below, you can see how the RSI indicator is imported and smoothed to control the Market Paddle.
Note: The Market Paddle follows the moving average. If not desired, simply set the "Smoothing" input to "NONE".
> CPU Paddle
In simple terms, the CPU Paddle is a handicapped Aimbot.
Its logic is, more or less, "move directly towards the ball's vertical location".
If it were allowed to have full range of the screen, it would be impossible for it to lose a point. Due to this, we must slow it down to "play fair"... as fair as that may be.
The CPU Paddle is allowed to move at a rate specified by a certain Percent of its vertical width. By default, this is set to 2%.
Each update, the CPU Paddle can advance up or down 2% of its vertical width. The directional movement is determined based on the angle of the ball, and it's current position relative to the CPU Paddle's position. Given that it is not a direct follow, it may at times seem more... "human".
When a point is scored, the CPU paddle maintains its position, similar to the original Pong game, the paddles were controlled solely by the raw output of the controllers and did not reset.
> Ball
At the start of each point, the ball begins at the center of the screen and moves in a randomly determined angle at its base speed.
The direction is determined by the player who scored the last point. The loser of the last point "serves" the ball.
Given the circumstances, serving is a gigantic advantage. So the loser serving is just another place where the Market is given an advantage.
The ball's base speed is 1, it will move 1 (horizontal) bar on each update of the script. This speed can "technically" increase to infinity over time, if given the perfect rally. This is due to the hit logic as described below.
Note: The minimum ball speed is also 1.
> Bonk Math
When the ball hits a paddle, essentially 3 outcomes can occur, each resulting in the ball's direction being changed from positive to negative.
Action A: Its angle is doubled, and its speed is doubled.
Action B: Its angle is reversed, and its speed is decreased if it is going faster than base speed.
Action C: Its angle is preserved, and its speed is preserved. "Basic Bounce"
Each paddle is segmented into 3 zones, with the higher and lower tips (20%) of the paddles producing special actions.
The central 60% of each paddle produces a basic bounce. The special actions are determined by the trajectory of the ball and location on the paddle.
> Custom Mode
As stated above, the script loads in "Auto Mode" by default. While this works fine to simply watch the gameplay, the Custom Mode unlocks the ability to visualize countless possibilities of indicators and analyses playing Pong!
In the chart below, we have set up the game to use the NYSE TICK Index as our Market Player. The NYSE TICK Index shows the number of NYSE stocks trading on an uptick minus those on a downtick. Its values fluctuate throughout the day, typically ranging between +1000 and -1000.
Therefore, we have set up Pong to use Ticker USI:TICK and set the Upper Boundary to 1000 and Lower Boundary to -1000. With this method, the paddle is directly controlled by the overall (NYSE) market behaviors.
As seen in a chart earlier, you can also take advantage of the Custom Mode to overlay Pong onto traditional oscillators for use anywhere!
> Styles
This version of Pong comes stocked with 5 colorways to suit your chart vibes!
> Pro Tips & Additional Information
- This game has sound! For the full experience, set alerts for this indicator and a notification sound will play on each hit!*
*Due to server processing, the notification sounds are not precisely played at each hit. :(
- In auto mode, decreasing the length used will give an advantage to the market, as its actions become more sporadic over this window.
- The CPU logic system actually allows the market to have a "technical" edge, since the Market Paddle is not bound to any speed, and is solely controlled by the raw market movements/data input.
- This type of visualization only works on live charts, charts without updates will not see any movement.
- Indicator sources can only be imported from other indicators on the same chart.
- The base screen resolution is 159 bars wide, with the height determined by the boundaries.
- When using a symbol and an outside source, be mindful that the script is attempting to pull the source from the input symbol. Data can appear wonky when not considering the interactions of these inputs.
There are many small interesting details that can't be seen through the description. For example, the mid-line is made from a box. This is because a line object would not appear on top of the box used for the screen. For those keen eye'd coders, feel free to poke around in the source code to make the game truly custom.
Just remember:
The market may never be fair, but now at least it can play Pong!
Enjoy!
WaveMacBollI wanted to see the two indicators in the candle chart, not in a separate window. And within the Bollinger band, it seemed to put it fine.
Important Note on Line Styles
Due to TradingView's multi-timeframe environment restrictions (timeframe = '', timeframe_gaps = true), I couldn't implement dotted or dashed line styles programmatically. The indicator uses solid lines by default.
If you prefer dotted/dashed lines for better visual distinction:
Add the indicator to your chart
Click on the indicator settings (gear icon)
Go to "Style" tab
Manually change line styles for each plot
Unfortunately, PineScript doesn't support line.new() or similar drawing functions in multi-timeframe mode, limiting our styling options to basic plot styles.
If you know a good solution for implementing dotted/dashed lines in multi-timeframe indicators without using drawing objects, please share it in the comments! I'd love to improve this aspect of the indicator
Traders Tool by DeepanIndiaThis powerful Pine Script is designed to support both beginner and advanced traders by providing a comprehensive trading setup alongside core fundamental tools to enhance decision-making
Sortable Relative Performance | viResearchSortable Relative Performance | viResearch
Conceptual Foundation and Purpose
The Sortable Relative Performance indicator from viResearch is designed as a multi-asset ranking and comparison system that allows traders to evaluate the relative strength of up to 14 different assets over a user-defined lookback period. Unlike single-symbol indicators, this tool provides a comparative view of performance, making it ideal for traders seeking to understand how assets perform relative to each other within a watchlist, sector, or market segment. The indicator calculates the percentage return of each asset from a chosen starting point and presents the results both graphically and in a sorted, tabular format, helping traders identify outperformers and underperformers at a glance.
Technical Composition and Methodology
At its core, the script calculates the relative performance of each selected asset by comparing its current closing price with the closing price from the lookback period. This performance metric is expressed as a percentage and computed using Pine Script’s request.security() function, allowing for seamless cross-asset analysis within a single pane. Each asset is visually represented as a vertical column, color-coded according to a predefined identity map that reflects common asset branding. The best-performing asset is dynamically labeled on the chart, displaying its name and current return, while a real-time performance table updates and ranks all active assets in descending order based on their return values. The table and columns automatically adjust based on the user’s selection, creating an interactive and responsive comparative dashboard.
Features and Configuration
The indicator includes a customizable date filter, allowing traders to activate the display from a specific start date. This is particularly useful for performance reviews tied to events, such as earnings reports, Fed meetings, or macroeconomic releases. The lookback period is adjustable and determines how far back in time performance is measured, making the tool adaptable to both short-term and long-term strategies. Traders can toggle individual assets on or off, enabling focused analysis on specific coins, stocks, or indices. Up to 14 assets can be analyzed simultaneously, with each one clearly distinguished by unique, branded colors in both the plot and the ranking table. The script intelligently highlights the top performer with a floating label, drawing immediate attention to the strongest asset within the group.
Strategic Use and Application
This indicator is especially valuable for traders employing relative strength or momentum-based strategies. By visualizing asset performance in real time, it becomes easier to rotate capital into strong assets and away from laggards. Whether tracking cryptocurrencies, sectors, or forex pairs, the ability to assess comparative returns without switching charts provides an operational edge. The tool supports portfolio analysis, sector rotation, and cross-market studies, making it suitable for discretionary traders, systematic investors, and even macro analysts looking for a visual breakdown of market behavior.
Conclusion and Practical Value
The Sortable Relative Performance indicator by viResearch delivers a clean and effective way to measure and rank asset performance over time. By combining visual clarity with real-time calculation and dynamic sorting, it offers a powerful lens through which traders can evaluate market leadership and laggard behavior. Its flexibility and modular design ensure it can be integrated into a wide range of strategies and trading styles. Whether you're managing a crypto portfolio or monitoring traditional markets, this tool provides essential insights into where momentum resides and how capital is flowing across assets.
Note: Backtests are based on past results and are not indicative of future performance.
Volume-Weighted RSI & Multi-Normalized MACD### Description for Publishing: Volume-Weighted RSI & Multi-Normalized MACD
**Overview**
The "Volume-Weighted RSI & Multi-Normalized MACD" indicator is a powerful and versatile tool designed for traders seeking enhanced momentum and trend analysis. Combining a volume-weighted Relative Strength Index (VW-RSI) with a customizable Moving Average Convergence Divergence (MACD) featuring multiple normalization methods, this indicator provides deep insights into market dynamics. It supports multi-timeframe (MTF) analysis and includes an optional stepped plotting mode for discrete signal visualization, making it ideal for both trend-following and mean-reversion strategies across various markets (stocks, forex, crypto, etc.).
**Key Features**
1. **Volume-Weighted RSI (VW-RSI)**:
- A modified RSI that incorporates trading volume for greater sensitivity to market activity.
- Normalized to a user-defined range (default: -50 to +50) for consistent analysis.
- Optional smoothing with multiple moving average types (SMA, EMA, WMA, VWMA, SMMA, or SMA with Bollinger Bands) to reduce noise and highlight trends.
- Overbought (+20) and oversold (-20) levels for quick reference.
2. **Multi-Normalized MACD**:
- Offers six normalization methods for MACD, allowing traders to tailor the output to their strategy:
- Normalized Volume Weighted MACD (unbounded).
- Min-Max Normalization (bounded).
- Volatility Normalization (unbounded, volatility-adjusted).
- Volatility Normalization with Min-Max (bounded).
- Hyperbolic Tangent Normalization (bounded).
- Arctangent Normalization (bounded).
- Min-Max with Smoothing (bounded).
- All bounded methods scale to the user-defined range (default: -50 to +50), ensuring comparability with VW-RSI.
- Dynamic color changes for MACD line (lime/red) and histogram (aqua/blue/red/maroon) based on momentum and signal line crosses.
3. **Stepped Plotting Mode**:
- Optional mode to plot RSI and MACD as discrete, stepped lines, reducing noise by only updating when values change significantly (configurable thresholds).
- Ideal for traders focusing on clear, actionable signal changes.
4. **Multi-Timeframe Support**:
- Configurable timeframe input (default: chart timeframe) for analyzing RSI and MACD on higher or lower timeframes, enhancing cross-timeframe strategies.
5. **Customizable Display**:
- Toggle options to show/hide MACD line, signal line, histogram, and cross dots.
- Bollinger Bands for RSI smoothing (optional) with adjustable standard deviation multiplier.
- Clear visual cues with horizontal lines for overbought/oversold levels, midline, and MACD bounds.
**Usage Instructions**
1. **Add to Chart**: Apply the indicator to any symbol (e.g., BTCUSD, SPY) on any timeframe (1H, 1D, etc.).
2. **Configure Settings**:
- **General**: Adjust `Lower Bound` (-50 default) and `Upper Bound` (+50 default) for the output range. Set `Timeframe` for MTF analysis. Enable `Stepped?` for discrete plotting.
- **RSI**: Choose `Price Source` (default: ohlc4), `RSI Length` (default: 9), and smoothing options (e.g., EMA, Bollinger Bands). Adjust `RSI Diff Threshold` for stepped mode.
- **MACD**: Select `Price Source`, `Fast Length` (9), `Slow Length` (21), `Signal Length` (9), and a normalization method (default: Volatility Min-Max). Adjust `MACD Diff Threshold` for stepped mode.
- **Display Options**: Toggle MACD components and histogram colors for clarity.
3. **Interpretation**:
- **VW-RSI**: Watch for crosses above +20 (overbought) or below -20 (oversold) for potential reversals. Use smoothed RSI or Bollinger Bands for trend confirmation.
- **MACD**: Look for MACD/Signal line crosses (dots indicate crossings) and histogram changes for momentum shifts. Bounded normalizations align with RSI for unified analysis.
- **Stepped Mode**: Focus on significant changes in RSI/MACD for clearer signals.
4. **Companion Overlay**: For visualization on the main price chart, use the companion script "VW-RSI & MACD Price Overlay" (available separately, requires this script to be published). It plots RSI and MACD as price-scaled echo lines, with toggles to show/hide and customizable scaling (high/low or ATR).
**Who Is This For?**
- **Trend Traders**: Use MACD normalizations and MTF to identify momentum shifts across timeframes.
- **Mean-Reversion Traders**: Leverage VW-RSI’s overbought/oversold signals for entry/exit points.
- **Technical Analysts**: Customize normalization and smoothing to match specific market conditions.
- **All Markets**: Works on stocks, forex, cryptocurrencies, and more, with any timeframe.
**Notes**
- Unbounded MACD normalizations (`enable_nvw`, `enable_vol`) may produce values outside -50/+50, suitable for volatility-focused strategies.
- For price chart overlay, publish this script and use its ID in the companion script’s `request.security` call.
- Adjust scaling inputs in the companion script for optimal visualization on volatile or stable assets.
**Author’s Note**
Developed by NEPOLIX, this indicator combines volume-weighted precision with flexible normalization for robust technical analysis. Feedback and suggestions are welcome to enhance future versions!
Custom Candle Coloring (3% Drop / Breakout / Follow-through)Naveen's custom bars. It helps with custom color of the bars to see significant candle movements and their interpretations
