Supply In Profit Z-Score | Vistula LabsOverview
The Supply In Profit Z-Score indicator is a Pine Script™ tool developed by Vistula Labs for technical analysis of cryptocurrencies, specifically Bitcoin (BTC) and Ethereum (ETH). It utilizes on-chain data from IntoTheBlock to calculate the difference between the percentage of addresses in profit and those in loss, transforming this metric into a Z-Score. This indicator helps traders identify market sentiment, trend-following opportunities, and overbought or oversold conditions.
What is Supply In Profit?
Supply In Profit is defined as the net difference between the percentage of addresses in profit and those in loss:
Profit Percentage: The proportion of addresses where the current value of holdings exceeds the acquisition price.
Loss Percentage: The proportion of addresses where the current value is below the acquisition price.
A positive value indicates more addresses are in profit, suggesting bullish sentiment, while a negative value indicates widespread losses, hinting at bearish sentiment.
How It Works
The indicator computes a Z-Score to normalize the Supply In Profit data relative to its historical behavior:
Z-Score = (Current Supply In Profit - Moving Average of Supply In Profit) / Standard Deviation of Supply In Profit
Current Supply In Profit: The latest profit-minus-loss percentage.
Moving Average: A customizable average (e.g., EMA, SMA) over a default 180-bar period.
Standard Deviation: Calculated over a default 200-bar lookback period.
Key Features
Data Source:
Selectable between BTC and ETH, pulling daily profit/loss percentage data from IntoTheBlock.
Customization:
Moving Average Type: Options include SMA, EMA, DEMA, RMA, WMA, or VWMA (default: EMA).
Moving Average Length: Default is 180 bars.
Z-Score Lookback: Default is 200 bars.
Thresholds: Adjustable for long/short signals and overbought/oversold levels.
Signals:
Long Signal: Z-Score crosses above the Long Threshold (default: 1.0).
Short Signal: Z-Score crosses below the Short Threshold (default: -0.64).
Overbought/Oversold Conditions:
Overbought: Z-Score > 3.0.
Oversold: Z-Score < -2.0.
Visualizations:
Z-Score Plot: Teal for long signals, magenta for short signals.
Threshold Lines: Dashed lines for long/short, solid lines for overbought/oversold.
Candlestick Coloring: Matches signal colors (teal/magenta).
Arrows: Green up-triangles for long entries, red down-triangles for short entries.
Background Colors: Magenta for overbought, teal for oversold.
Alerts:
Conditions for Long Opportunity, Short Opportunity, Overbought, and Oversold.
Usage Guide
Trend Following
Long Entry: When Z-Score crosses above 1.0, indicating potential upward momentum.
Short Entry: When Z-Score crosses below -0.64, suggesting potential downward momentum.
Overbought/Oversold Analysis
Overbought (Z-Score > 3.0): Consider profit-taking or preparing for a reversal.
Oversold (Z-Score < -2.0): Look for buying opportunities or exiting shorts.
Timeframe
Uses daily IntoTheBlock data, ideal for medium to long-term analysis.
Interpretation
High Z-Score: Indicates Supply In Profit is significantly above its historical mean, potentially signaling overvaluation.
Low Z-Score: Suggests Supply In Profit is below its mean, indicating possible undervaluation.
Signals and thresholds help traders act on shifts in market sentiment or extreme conditions.
Conclusion
The Supply In Profit Z-Score indicator provides a robust, data-driven approach to analyzing cryptocurrency market trends and sentiment. By combining on-chain metrics with statistical normalization, it empowers traders to make informed decisions based on historical context and current market dynamics.
Portföy Yönetimi
Average Daily LiquidityIt is important to have sufficient daily trading value (liquidity) to ensure you can easily enter and, importantly, exit the trade. This indicator allows you to see if the traded value of a stock is adequate. The default average is 10 periods and it is common to average the daily traded value as both price and volume can have spikes causing trading errors. Some investors use a 5 period for a week, 10 period for 2 weeks, 20 or 21 period for 4 weeks/month and 65 periods for a quarter. You need to ascertain your buying amount such as $10000 and then have the average daily trading value be your comfortable moving average more such as average liquidity is more than 10 x MA(close x volume) or $100000 in this example. The value is extremely important for small and micro cap stocks you may wish to purchase.
Spectra RS Inferno | QauntEdgeBIntroducing Spectra RS Inferno
-> Relative Strength Ranking Engine by QuantEdgeB
1. Purpose
Spectra RS Inferno is a multi-asset comparative ranking algorithm designed to surface the strongest-performing altcoins from a basket of up to 25 user-defined assets. Rather than scanning assets in isolation, it calculates relative strength pairwise across all assets producing a 625-signal matrix used to identify true outperformers.
This is a selection engine, not a trade signal generator. It helps you filter noise and allocate focus to statistically dominant assets.
2. Core Philosophy
-> Markets are competitive arenas - not everyone can be a winner at once. Spectra RS Inferno is built on the principle that
-> "Relative strength is the clearest signal of current dominance."
-> Unlike standalone momentum, this system assesses how each asset performs relative to others, making it invaluable for rotating markets, altcoin seasonality, and macro filtering.
3. Feature Architecture
1. Asset Universe
• You can define up to 25 assets (cryptos, forex, indices, etc.).
• Assets are ranked against each other using relative RSI scoring.
2. Relative Strength Score
• Assets are then ranked descendingly based on the sum of their relative strength against the other assets
4. Top Asset Selection
• The top 3 strongest assets (by score) are identified and stored.
• Their:
o Live Price
o Rate of Change (ROC)
o UNI2 Filter Signal
o Asset name
are extracted for use in allocation simulation and dashboard tables.
4. Signal Filtering
• Signals are further validated by a macro regime filter using a universal strategy, which acts as a universal market condition filter.
• The activation threshold is customizable.
• If none of the top assets pass the universal filter, the system allocates to cash (no position).
5. Equity Simulation Logic
✅ Simulation Mode (Optional)
• A non-executing equity curve is calculated to show what would happen if:
o You only held the top asset(s) passing the filter
o With no leverage and full capital rotation
⚙️ Simulation Settings
• Equity curve starts at 1 unit
• Updated at every bar post start date
• Drawdown, Sharpe, Sortino, and Omega ratios are calculated
• Allocation change count tracks how often the asset holding switches
⚠️ Disclaimer:
1. While the backtest feature demonstrates performance potential, this is not the recommended live trading mode. The best use-case for Spectra RS Inferno is asset selection, not execution. Combine it with your personal trading edge or system for superior risk/reward and entry timing.
2. Past performance is not indicative of future performance. Always conduct your own research before investing!
6. Visualization
1. Main Dashboard Table (Right)
-> Signal: ⬆️ if currently allocated; 🔄 otherwise
-> Returns: Total net return across all allocations
-> Max Drawdown: Worst equity drop during any allocation period
2. Backtest Panel (Left-Bottom)
-> Equity Max DD: Worst peak-to-trough drawdown
-> Sharpe Ratio: Return / Volatility (risk-adjusted)
-> Sortino Ratio: Return / Downside Deviation
-> Omega Ratio: Positive Return Area / Negative Return Area
-> Net Profit: Net % return from start
-> Position Changes: Allocation changes across time
3. Top 3 Display (Top Right)
-> Always shows the current top 3 ranked assets.
-> Updated live at every bar.
Color Coding
• Customizable themes ("Strategy", "Solar", "Warm", etc.)
• Active allocation is optionally color-coded per asset
7. Advanced Notes
Pairwise Architecture
The core RS function compares A/B performance via RSI, but the real magic happens in how this comparison is done for all possible asset pairs — creating a relational strength model.
Regime Filtering
Universal Strategy signal is used as a meta-filter, ensuring trades are only allowed in favorable environments. This reduces exposure to false positives in volatile markets.
Alerts
Built-in alert triggers notify when allocation changes - so you never miss a momentum shift.
✅ Ideal Use Case
• Traders or investors managing altcoin portfolios
• Rotational strategies
• Smart allocation across high momentum assets
• Avoiding laggards and weak performers
• Strategic analysis - not auto execution
🔚 Conclusion
Spectra RS Inferno is your momentum microscope, scanning relative strength with mathematical precision. Whether you're rotating into altcoins, leading sectors, or currencies, this tool answers the question:
1. "What’s winning the performance war right now?"
2. It’s not a trigger - it’s your targeting system.
3. Use it to deploy your capital only where strength is proven.
📌 Trade with Statistical Precision | Powered by QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Altitude Alpha | QuantEdgeB✨ Altitude Alpha | Altcoin Screener by QuantEdgeB ✨
1. Objective
Altitude Alpha is a quantitative altcoin screener designed to systematically identify the strongest outperforming assets from a universe of 20 selected altcoins. With 7 layered filters and a robust scoring engine, this system empowers traders to focus only on high-potential candidates, eliminating guesswork and emotional bias and maximize opportunity cost.
2. 🧠 Purpose & Core Philosophy
The primary goal of Altitude Alpha is not to trigger buy or sell signals, but to highlight where strength is concentrated in the altcoin space. In the most volatile and noisy market environment, relative strength is your compass. By identifying coins that not only outperform their peers but also meet trend, volatility, and statistical benchmarks, Altitude Alpha becomes your strategic alpha-finder.
💡 Winners are displayed visually and intuitively in the “🏆 Winners Dash” table at the bottom left.
3. ⚙️ What Makes It Powerful?
Altitude Alpha uses a multi-dimensional 7-filter scoring model built around these components:
🔹 1. Relative Strength Matrix
Each altcoin is scored relative to all others in the pool using pairwise strength logic. The result: the strongest of the strong rise to the top.
🔹 2. Trend Structure
Three independent trend assessments are used to validate the momentum. A coin must sustain multi-angle trend agreement to pass.
🔹 3. Regime Filter
Filters out noisy environments. Only coins in “Trending” or strong “Neutral” regimes are considered.
🔹 4. Beta Screening
Measures each asset’s sensitivity compared to the broader market (BTC Index by default). Higher beta = higher potential volatility-based opportunity.
🔹 5. Alpha Screening
Only assets showing positive alpha—returns exceeding what their beta would explain—are considered worthy of your attention.
🔹 6. Composite Score Threshold
Trend + Regime + Alpha/Beta strength must all align for a coin to qualify.
🔹 7. Top N Rank Filter
Customize your scope: allocate to top 1, 2, 3...5 ranked altcoins dynamically, based on their total composite score.
4. 🧪 Backtest Mode Explained
Altitude Alpha includes an optional backtest simulation, allocating capital to the currently top-ranked assets. This model applies equal-weight dynamic allocation to assets that pass all filters.
⚠️ Disclaimer:
1. While the backtest feature demonstrates performance potential, this is not the recommended live trading mode. The best use-case for Altitude Alpha is asset selection, not execution. Combine it with your personal trading edge or system for superior risk/reward and entry timing.
2. Past performance is not indicative of future performance. Always conduct your own research before investing!
5. ✅ Recommended Use
• Use Altitude Alpha to scan for the best-performing altcoins.
• Select 1–3 assets from the “🏆 Winners Dash” panel.
• Apply your own entry strategy or confirmation setup (e.g., price action, strategies, valution alignment, market structure, etc.)
• Only allocate capital when your personal system confirms opportunity.
• You may optionally allocate based on the system itself—just be aware this introduces higher exposure and risk.
6. 🧬 Customization Features
• 🖌️ Multiple color palettes (Strategy, Solar, Warm, Cool, etc.)
• 🌓 Text readability toggles (Dark/Light)
• 🔢 Adjustable Alpha/Beta periods and benchmark (BTC by default)
• 🔁 Allocation rank selection (Top 1–5)
7. 📈 Visual Output & Dashboards
• 🔍 Altitude Alpha Dashboard — Complete transparency into ranks, trends, scores, and regimes.
• 🏆 Winners Dash Table — Clean, minimal summary of top-selected altcoins.
• 📊 Backtest Panel — Equity curve and stats (Sharpe, Sortino, Omega, Max Drawdown).
• 🌌 Futuristic Glow Plotting — High-contrast equity visuals with layered gradients.
Conclusion & Key Highlights
Altitude Alpha is not just a screener—it's a precision instrument designed to cut through market noise and systematically reveal where true strength lies in the altcoin universe.
While most traders are busy chasing hype, Altitude Alpha offers clarity through quantitative filtration. It’s not about timing the perfect entry. It’s about focusing attention on the highest-potential coins, so you never waste energy on underperformers again.
📌 Key Takeaways:
🧭 Purpose-Built-> Helps identify the strongest altcoin out of 20 dynamically.
🧮 7-Layer Filter Logic-> Combines trend, regime, alpha, beta, and composite strength into one decision engine.
📊 Winners Dash Panel-> Clean display of current top performers — no noise, just output.
⚙️ Backtest Feature-> Optional equity curve based on rotating into ranked leaders (educational use).
🔎 Customizable Framework-> Tweak ranking depth, visual style, and filter sensitivity.
✅ Best Use Case ->Select strong coins, then apply your own entry strategy - maximize risk/reward.
📌 Trade with Statistical Precision | Powered by QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
ETF Builder & Backtest System [TradeDots]Create, analyze, and monitor your own custom “ETF-like” portfolio directly on TradingView. This script merges up to 10 different assets with user-defined weightings into a single composite chart, allowing you to see how your personalized portfolio would have performed historically. It is an original tool designed to help traders and investors quickly gauge risk and return profiles without leaving the TradingView platform.
📝 HOW IT WORKS
1. Custom Portfolio Construction
Multiple Assets : Combine up to 10 different stocks, ETFs, cryptocurrencies, or other symbols.
User-Defined Weights : Allocate each asset a percentage weight (e.g., 15% in AAPL, 10% in MSFT, etc.).
Single Composite Value : The script calculates a weighted “ETF-style” price, effectively simulating a merged portfolio curve on your chart.
2. Performance Tracking & Return Analysis
Automatic History Capture : The indicator records each asset’s starting price when it first appears in your chosen date range.
Rolling Updates : As time progresses, all asset prices are continually evaluated and the portfolio value is updated in real time.
Buy & Hold Returns : See how each asset—and the overall portfolio—performed from the “start” date to the most recent bar.
Annualized Return : Automatically calculates CAGR (Compound Annual Growth Rate) to help visualize performance over varying timescales.
3. Table & Visual Output
Performance Table : A comprehensive table displays individual asset returns, annualized returns, and portfolio totals.
Normalized Chart Plot : The composite ETF value is scaled to 100 at the start date, making it easy to compare relative growth or decline.
Optional Time Filter : You can define a specific date range (Start/End Dates) to focus on a particular period or to limit historical data.
⚙️ KEY FEATURES
1. Flexible Asset Selection
Choose any symbols from multiple asset classes. The script will only run calculations when data is available—no need to worry about missing quotes.
2. Dynamic Table Reporting
Start Price for each asset
Percentage Weight in the portfolio
Total Return (%) and Annualized Return (%)
3. Simple Backtesting Logic
This script takes a straightforward Buy & Hold perspective. Once the start date is reached, the portfolio remains static until the end date, so you can quickly assess hypothetical growth.
4. Plot Customization
Toggle the main “ETF” plot on/off.
Alter the visual style for tables and text.
Adjust the time filter to limit or extend your performance measurement window.
🚀 HOW TO USE IT
1. Add the Script
Search for “ETF Builder & Backtest System ” in the Indicators & Strategies tab or manually add it to your chart after saving it in your Pine Editor.
2. Configure Inputs
Enable Time Filter : Choose whether to restrict the analysis to a particular date range.
Start & End Date : Define the period you want to measure performance over (e.g., from 2019-12-31 to 2025-01-01).
Assets & Weights : Enter each symbol and specify a percentage weight (up to 10 assets).
Display Options : Pick where you want the Table to appear and choose background/text colors.
3. Interpret the Table & Plots
Asset Rows : Each asset’s ticker, weighting, start price, and performance metrics.
ETF Total Row : Summarizes total weighting, composite starting value, and overall returns.
Normalized Plot : Tracks growth/decline of the combined portfolio, starting at 100 on the chart.
4. Refine Your Strategy
Compare how different weights or a new mix of assets would have performed over the same period.
Assess if certain assets contribute disproportionately to your returns or volatility.
Use the results to guide allocations in your real trading or paper trading accounts.
❗️LIMITATIONS
1. Buy & Hold Only
This script does not handle rebalancing or partial divestments. Once the portfolio starts, weights remain fixed throughout the chosen timeframe.
2. No Reinvestment Tracking
Dividends or other distributions are not factored into performance.
3. Data Availability
If historical data for a particular asset is unavailable on TradingView, related results may display as “N/A.”
4. Market Regimes & Volatility
Past performance does not guarantee similar future behavior. Markets can change rapidly, which may render historical backtests less predictive over time.
⚠️ RISK DISCLAIMER
Trading and investing carry significant risk and can result in financial loss. The “ETF Builder & Backtest System ” is provided for informational and educational purposes only. It does not constitute financial advice.
Always conduct your own research.
Use proper risk management and position sizing.
Past performance does not guarantee future results.
This script is an original creation by TradeDots, published under the Mozilla Public License 2.0.
Use this indicator as part of a broader trading or investment approach—consider fundamental and technical factors, overall market context, and personal risk tolerance. No trading tool can assure profits; exercise caution and responsibility in all financial decisions.
Grid Bot Visualizer V1
📊 Grid Bot Visualizer – V1
A dynamic and visual support tool for grid trading strategies.
🔧 Key Features
• Fixed grid levels based on a central entry price
• Customizable spacing, number of levels, and range
• Color-coded lines (🟢 green above, 🔴 red below)
• Expands automatically when price exceeds boundaries (within the defined box)
• Optional price labels shown outside the grid
• Grid visually framed by a blue box
• Vertical line to mark grid origin
• Built-in alert when price hits a grid level
⚙️ Use Case
Ideal for visualizing grid bot logic in volatile markets.
Monitor how price interacts with predefined zones.
✅ Alert Ready
Use alertcondition to get notified when a grid level is touched.
MVA-PMI ModelThe Macroeconomic Volatility-Adjusted PMI Alpha Strategy: A Proprietary Trading Approach
The relationship between macroeconomic indicators and financial markets has been extensively documented in the academic literature (Fama, 1981; Chen et al., 1986). Among these indicators, the Purchasing Managers' Index (PMI) has emerged as a particularly valuable forward-looking metric for economic activity and, by extension, equity market returns (Lahiri & Monokroussos, 2013). The PMI captures manufacturing sentiment before many traditional economic indicators, providing investors with early signals of potential economic regime shifts.
The MVA-PMI trading strategy presented here leverages these temporal advantages through a sophisticated algorithmic framework that extends beyond traditional applications of economic data. Unlike conventional approaches that rely on static thresholds described in previous literature (Koenig, 2002), our proprietary model employs a multi-dimensional analysis of PMI time series data through various moving averages and momentum indicators.
As noted by Beckmann et al. (2020), composite signals derived from economic indicators significantly enhance predictive power compared to simpler univariate models. The MVA-PMI model adopts this principle by synthesizing multiple PMI-derived features through a machine learning optimization process. This approach aligns with Johnson and Watson's (2018) findings that trailing averages of economic indicators often outperform point-in-time readings for investment decision-making.
A distinctive feature of the model is its adaptive volatility mechanism, which draws on the extensive volatility feedback literature (Campbell & Hentschel, 1992; Bollerslev et al., 2011). This component dynamically adjusts position sizing according to market volatility regimes, reflecting the documented inverse relationship between market turbulence and expected returns. Such volatility-based position sizing has been shown to enhance risk-adjusted performance across various strategy types (Harvey et al., 2018).
The model's signal generation employs an asymmetric approach for long and short positions, consistent with Estrada and Vargas' (2016) research highlighting the positive long-term drift in equity markets and the inherently higher risks associated with short selling. This asymmetry is implemented through a proprietary scoring system that synthesizes multiple factors while maintaining different thresholds for bullish and bearish signals.
Extensive backtesting demonstrates that the MVA-PMI strategy exhibits particular strength during economic transition periods, correctly identifying a significant percentage of economic inflection points that preceded major market movements. This characteristic aligns with Croushore and Stark's (2003) observations regarding the value of leading indicators during periods of economic regime change.
The strategy's performance characteristics support the findings of Neely et al. (2014) and Rapach et al. (2010), who demonstrated that macroeconomic-based investment strategies can generate alpha that is distinct from traditional factor models. The MVA-PMI model extends this research by integrating machine learning for parameter optimization, an approach that has shown promise in extracting signal from noisy economic data (Gu et al., 2020).
These findings contribute to the growing literature on systematic macro trading and offer practical implications for portfolio managers seeking to incorporate economic cycle positioning into their allocation frameworks. As noted by Beber et al. (2021), strategies that successfully capture economic regime shifts can provide valuable diversification benefits within broader investment portfolios.
References
Beckmann, J., Glycopantis, D. & Pilbeam, K., 2020. The dollar-euro exchange rate and economic fundamentals: A time-varying FAVAR model. Journal of International Money and Finance, 107, p.102205.
Beber, A., Brandt, M.W. & Luisi, M., 2021. Economic cycles and expected stock returns. Review of Financial Studies, 34(8), pp.3803-3844.
Bollerslev, T., Tauchen, G. & Zhou, H., 2011. Volatility and correlations: An international GARCH perspective. Journal of Econometrics, 160(1), pp.102-116.
Campbell, J.Y. & Hentschel, L., 1992. No news is good news: An asymmetric model of changing volatility in stock returns. Journal of Financial Economics, 31(3), pp.281-318.
Chen, N.F., Roll, R. & Ross, S.A., 1986. Economic forces and the stock market. Journal of Business, 59(3), pp.383-403.
Croushore, D. & Stark, T., 2003. A real-time data set for macroeconomists: Does the data vintage matter? Review of Economics and Statistics, 85(3), pp.605-617.
Estrada, J. & Vargas, M., 2016. Black swans, beta, risk, and return. Journal of Applied Corporate Finance, 28(3), pp.48-61.
Fama, E.F., 1981. Stock returns, real activity, inflation, and money. The American Economic Review, 71(4), pp.545-565.
Gu, S., Kelly, B. & Xiu, D., 2020. Empirical asset pricing via machine learning. The Review of Financial Studies, 33(5), pp.2223-2273.
Harvey, C.R., Hoyle, E., Korgaonkar, R., Rattray, S., Sargaison, M. & Van Hemert, O., 2018. The impact of volatility targeting. Journal of Portfolio Management, 45(1), pp.14-33.
Johnson, R. & Watson, K., 2018. Economic indicators and equity returns: The importance of time horizons. Journal of Financial Research, 41(4), pp.519-552.
Koenig, E.F., 2002. Using the purchasing managers' index to assess the economy's strength and the likely direction of monetary policy. Economic and Financial Policy Review, 1(6), pp.1-14.
Lahiri, K. & Monokroussos, G., 2013. Nowcasting US GDP: The role of ISM business surveys. International Journal of Forecasting, 29(4), pp.644-658.
Neely, C.J., Rapach, D.E., Tu, J. & Zhou, G., 2014. Forecasting the equity risk premium: The role of technical indicators. Management Science, 60(7), pp.1772-1791.
Rapach, D.E., Strauss, J.K. & Zhou, G., 2010. Out-of-sample equity premium prediction: Combination forecasts and links to the real economy. Review of Financial Studies, 23(2), pp.821-862.
[Kpt-Ahab] Simple AlgoPilot Riskmgt and Backtest Simple AlgoPilot Riskmgt and Backtest
This script provides a compact solution for automated risk management and backtesting within TradingView.
It offers the following core functionalities:
Risk Management:
The system integrates various risk limitation mechanisms:
Percentage-based or trailing stop-loss
Maximum losing streak limitation
Maximum drawdown limitation relative to account equity
Flexible position sizing control (based on equity, fixed size, or contracts)
Dynamic repurchasing of positions ("Repurchase") during losses with adjustable size scaling
Supports multi-stage take-profit targets (TP1/TP2) and automatic stop-loss adjustment to breakeven
External Signal Processing for Backtesting:
In addition to its own moving average crossovers, the script can process external trading signals:
External signals are received via a source input variable (e.g., from other indicators or signal generators)
Positive values (+1) trigger long positions, negative values (–1) trigger short positions
This allows for easy integration of other indicator-based strategies into backtests
Additional Backtesting Features:
Selection between different MA types (SMA, EMA, WMA, VWMA, HMA)
Flexible time filtering (trade only within defined start and end dates)
Simulation of commission costs, slippage, and leverage
Optional alert functions for moving average crossovers
Visualization of liquidation prices and portfolio development in an integrated table
Note: This script is primarily intended for strategic backtesting and risk setting optimization.
Real-time applications should be tested with caution. All order executions, alerts, and risk calculations are purely simulation-based.
Explanation of Calculations and Logics:
1. Risk Management and Position Sizing:
The position size is calculated based on the user’s choice using three possible methods:
Percentage of Equity:
The position size is a defined fraction of the available capital, dynamically adjusted based on market price (riskPerc / close).
Fixed Size (in currency): The user defines a fixed monetary amount to be used per trade.
Contracts: A fixed number of contracts is traded regardless of the current price.
Leverage: The selected leverage multiplies the position size for margin calculations.
2. Trade Logic and Signal Triggering:
Trades can be triggered through two mechanisms:
Internal Signals:
When a fast moving average crosses above or below a slower moving average (ta.crossover, ta.crossunder). The type of moving averages (SMA, EMA, WMA, VWMA, HMA) can be freely selected.
External Signals:
Signals from other indicators can be received via an input source field.
+1 triggers a long entry, –1 triggers a short entry.
Position Management:
Once entered, the position is actively managed.
Multiple take-profit targets are set.
Upon reaching a profit target, the stop-loss can optionally be moved to breakeven.
3. Stop-Loss and Take-Profit Logic:
Stop-Loss Types:
Fixed Percentage Stop:
A fixed distance below/above the entry price.
Trailing Stop:
Dynamically adjusts as the trade moves into profit.
Fast Trailing Stop:
A more aggressive variant of trailing that reacts quicker to price changes.
Take-Profit Management:
Two take-profit targets (TP1 and TP2) are supported, allowing partial exits at different stages.
Remaining positions can either reach the second target or be closed by the stop-loss.
4. Repurchase Strategy ("Scaling In" on Losses):
If a position reaches a specified loss threshold (e.g., –15%), an automatic additional purchase can occur.
The position size is increased by a configurable percentage.
Repurchases happen only if an initial position is already open.
5. Backtesting Control and Filters:
Time Filters:
A trading period can be defined (start and end date).
All trades outside the selected period are ignored.
Risk Filters: Trading is paused if:
A maximum losing streak is reached.
A maximum allowed drawdown is exceeded.
6. Liquidation Calculation (Simulation Only):
The script simulates liquidation prices based on the account balance and position size.
Liquidation lines are drawn on the chart to better visualize potential risk exposure.
This is purely a visual aid — no real broker-side liquidation is performed.
Max RR CalculatorAutomatically calculates the maximum RR reached during trade. Entry is at the candle close. There is an option available that takes another trade after getting stopped out on the next candle that is in same bias as first trade.
(If the first trade is a long and gets stopped out, then the second trade will wait until the next up candle to enter long again)
Price Map Profile [BigBeluga]An advanced volume-based tool designed to map out how trading activity is distributed across price levels. It combines dynamic volume profiling with structural pivot detection to highlight key levels of interest in the market — including hidden support/resistance zones and dominant liquidity areas.
Unlike traditional volume profiles locked to fixed sessions, this indicator continuously processes historical bars to build a real-time "map" of volume distribution. It intelligently reveals where buyers and sellers were most active, helping traders pinpoint high-impact zones with clarity.
🔵 KEY FEATURES
Creates a volume map profile by scanning price action over a defined lookback window (`length`).
Divides price vertically into volume bins (default: 100) and aggregates either total volume or bar count per bin.
Bins are plotted as horizontal zones extending to the right of the chart — wider offset means more volume at that price.
Each zone is color-coded using gradients to represent volume magnitude:
- Below average volume = cool tones (blue/teal)
- Above average volume = warm tones (red/orange)
The highest volume bin is highlighted with a red label showing the exact volume, helping to identify strong price agreement.
Detects pivot highs and lows using a 15-bar swing method, marking them as potential S/R levels.
If a pivot level is located inside a low-volume zone (volume < average), it is emphasized with a dashed line and label .
Pivot line color matches direction:
- High pivots = yellow
- Low pivots = aqua
The volume of the bin containing the pivot is shown alongside the pivot, providing volume context for the structural level.
Filters out nearby duplicate pivots using ATR-based distance checks to ensure clean and non-redundant signals.
🔵 HOW TO USE
Use the wide red zones as liquidity and consolidation areas where price may stall, reverse, or absorb volume.
Pivot-based dashed lines within low-volume zones highlight hidden support/resistance levels where price may react sharply.
Combine this indicator with trend or order flow tools to validate reversal or breakout setups .
Switch between Volume and Frequency modes to adapt to the type of data your asset provides.
🔵 CONCLUSION
The Price Map Profile transforms raw volume into an actionable visual map. By aligning volume depth with key market structure levels, it helps traders identify where market participants are most active — and where hidden inefficiencies lie. Ideal for traders seeking precision entries, dynamic S/R zones, and deeper volume structure insight.
Altcoin Screener | QuantumResearchAltcoin Screener | QuantumResearch
🔍 Multi-Factor Asset Ranking & Portfolio Allocator for Altcoins
This screener is an advanced tool designed to help crypto investors identify the strongest-performing altcoins among a custom selection of up to 40 assets. It evaluates multiple factors across trend strength, momentum, relative performance, and risk-adjusted returns — then allocates a portfolio accordingly.
🔬 How it Works:
Each altcoin is scored using a blend of custom-built indicators developed by QuantumResearch:
Beta (volatility relative to BTC) – Measures how much an asset moves compared to Bitcoin. Higher beta = higher volatility.
Alpha – Measures the asset’s excess return versus Bitcoin (BTC is the required benchmark for this model).
ARSI – Adaptative RSI signal score to determine directional strength.
AVWO – Adaptative Volume-weighted momentum oscillator detecting momentum
Uni1 – Universal algorithme 1
Uni2 – Universal algorithme 2
7D ROC – 7-day rate of change (short-term momentum).
Relative Strength Matrix – Evaluates price ratio behavior between all selected assets.
Omega Ratio – A refined risk/reward filter favoring stable upside.
All scores are aggregated into a Final Score, which determines each token’s overall rank in the current environment.
⚠️ Important Requirements:
This script must be applied to the BTCor TOTAL chart, as BTC/TOTAL is used as the benchmark to compute accurate Beta and Alpha values.
All selected assets must have at least 300 bars of price history to ensure the filters function properly (especially for Alpha, Beta, and Omega computations).
💼 Portfolio Allocation Modes:
Choose how you'd like to allocate based on your risk preference:
🧠 Conservative → Top 3 assets (50% / 30% / 20%)
⚖️ Mix → Top 2 assets (80% / 20%)
🔥 Aggressive → Top 1 asset (100%)
The result is a simple and powerful table showing your top allocations, backed by sound multi-factor analysis.
📊 Key Features:
Supports up to 40 customizable assets from any exchange
Displays performance stats like Beta, Alpha, and Omega
Color-coded tables highlight winners, metrics, and risk zones
Automatically updates allocation tables based on rankings
View mean & median values for deeper benchmarking
🧠 Use Cases:
Build a custom altcoin portfolio with solid statistical backing
Identify strong trends early with momentum + ratio blend
Visualize volatility and risk-adjusted strength versus BTC
Allocate based on signals, not social hype
🔧 Built by QuantumResearch
📈 Engineered for strategic signal discovery
⚠️ For research and educational purposes only — not financial advice.
Prop Firm Business SimulatorThe prop firm business simulator is exactly what it sounds like. It's a plug and play tool to test out any tradingview strategy and simulate hypothetical performance on CFD Prop Firms.
Now what is a modern day CFD Prop Firm?
These companies sell simulated trading challenges for a challenge fee. If you complete the challenge you get access to simulated capital and you get a portion of the profits you make on those accounts payed out.
I've included some popular firms in the code as presets so it's easy to simulate them. Take into account that this info will likely be out of date soon as these prices and challenge conditions change.
Also, this tool will never be able to 100% simulate prop firm conditions and all their rules. All I aim to do with this tool is provide estimations.
Now why is this tool helpful?
Most traders on here want to turn their passion into their full-time career, prop firms have lately been the buzz in the trading community and market themselves as a faster way to reach that goal.
While this all sounds great on paper, it is sometimes hard to estimate how much money you will have to burn on challenge fees and set realistic monthly payout expectations for yourself and your trading. This is where this tool comes in.
I've specifically developed this for traders that want to treat prop firms as a business. And as a business you want to know your monthly costs and income depending on the trading strategy and prop firm challenge you are using.
How to use this tool
It's quite simple you remove the top part of the script and replace it with your own strategy. Make sure it's written in same version of pinescript before you do that.
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
//--$$$$$--Strategy-- --$$$$$$--// ******************************************************************************************************************************
//--$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$--//--------------------------------------------------------------------------------------------------------------------------$$$$$$
length = input.int(20, minval=1, group="Keltner Channel Breakout")
mult = input(2.0, "Multiplier", group="Keltner Channel Breakout")
src = input(close, title="Source", group="Keltner Channel Breakout")
exp = input(true, "Use Exponential MA", display = display.data_window, group="Keltner Channel Breakout")
BandsStyle = input.string("Average True Range", options = , title="Bands Style", display = display.data_window, group="Keltner Channel Breakout")
atrlength = input(10, "ATR Length", display = display.data_window, group="Keltner Channel Breakout")
esma(source, length)=>
s = ta.sma(source, length)
e = ta.ema(source, length)
exp ? e : s
ma = esma(src, length)
rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
//--Graphical Display--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
u = plot(upper, color=#2962FF, title="Upper", force_overlay=true)
plot(ma, color=#2962FF, title="Basis", force_overlay=true)
l = plot(lower, color=#2962FF, title="Lower", force_overlay=true)
fill(u, l, color=color.rgb(33, 150, 243, 95), title="Background")
//--Risk Management--// *-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-*-$$$$$$
riskPerTradePerc = input.float(1, title="Risk per trade (%)", group="Keltner Channel Breakout")
le = high>upper ? false : true
se = lowlower
strategy.entry('PivRevLE', strategy.long, comment = 'PivRevLE', stop = upper, qty=riskToLots)
if se and upper>lower
strategy.entry('PivRevSE', strategy.short, comment = 'PivRevSE', stop = lower, qty=riskToLots)
The tool will then use the strategy equity of your own strategy and use this to simulat prop firms. Since these CFD prop firms work with different phases and payouts the indicator will simulate the gains until target or max drawdown / daily drawdown limit gets reached. If it reaches target it will go to the next phase and keep on doing that until it fails a challenge.
If in one of the phases there is a reward for completing, like a payout, refund, extra it will add this to the gains.
If you fail the challenge by reaching max drawdown or daily drawdown limit it will substract the challenge fee from the gains.
These gains are then visualised in the calendar so you can get an idea of yearly / monthly gains of the backtest. Remember, it is just a backtest so no guarantees of future income.
The bottom pane (non-overlay) is visualising the performance of the backtest during the phases. This way u can check if it is realistic. For instance if it only takes 1 bar on chart to reach target you are probably risking more than the firm wants you to risk. Also, it becomes much less clear if daily drawdown got hit in those high risk strategies, the results will be less accurate.
The daily drawdown limit get's reset every time there is a new dayofweek on chart.
If you set your prop firm preset setting to "'custom" the settings below that are applied as your prop firm settings. Otherwise it will use one of the template by default it's FTMO 100K.
The strategy I'm using as an example in this script is a simple Keltner Channel breakout strategy. I'm using a 0.05% commission per trade as that is what I found most common on crypto exchanges and it's close to the commissions+spread you get on a cfd prop firm. I'm targeting a 1% risk per trade in the backtest to try and stay within prop firm boundaries of max 1% risk per trade.
Lastly, the original yearly and monthly performance table was developed by Quantnomad and I've build ontop of that code. Here's a link to the original publication:
That's everything for now, hope this indicator helps people visualise the potential of prop firms better or to understand that they are not a good fit for their current financial situation.
Advanced Momentum Scanner [QuantAlgo]The Advanced Momentum Scanner is a sophisticated technical indicator designed to identify market momentum and trend direction using multiple exponential moving averages (EMAs), momentum metrics, and adaptive visualization techniques. It is particularly valuable for those looking to identify trading and investing opportunities based on trend changes and momentum shifts across any market and timeframe.
🟢 Technical Foundation
The Advanced Momentum Scanner utilizes a multi-layered approach with four different EMA periods to identify market momentum and trend direction:
Ultra-Fast EMA for quick trend changes detection (default: 5)
Fast EMA for short-term trend analysis (default: 10)
Mid EMA for intermediate confirmation (default: 30)
Slow EMA for long-term trend identification (default: 100)
For momentum detection, the indicator implements a Rate of Change (RoC) calculation to measure price momentum over a specified period. It further enhances analysis by incorporating RSI readings for overbought/oversold conditions, volatility measurements through ATR, and optional volume confirmation. When these elements align, the indicator generates trading signals based on the selected sensitivity mode (Conservative, Balanced, or Aggressive).
🟢 Key Features & Signals
1. Multi-Period Trend Identification
The indicator combines multiple EMAs of different lengths to provide comprehensive trend analysis within the same timeframe, displaying the information through color-coded visual elements on the chart.
When an uptrend is detected, chart elements are colored with the bullish theme color (default: green/teal).
Similarly, when a downtrend is detected, chart elements are colored with the bearish theme color (default: red).
During neutral or indecisive periods, chart elements are colored with a neutral gray color, providing clear visual distinction between trending and non-trending market conditions.
This visualization provides immediate insights into underlying trend direction without requiring separate indicators, helping traders and investors quickly identify the market's current state.
2. Trend Strength Information Panel
The trend panel operates in three different sensitivity modes (Conservative, Aggressive, and Balanced), each affecting how the indicator processes and displays market information.
The Conservative mode prioritizes trend sustainability over frequency, showing only strong trend movements with high probability.
The Aggressive mode detects early trend changes, providing more frequent signals but potentially more false positives.
The Balanced mode offers a middle ground with moderate signal frequency and reliability.
Regardless of the selected mode, the panel displays:
Current trend direction (UPTREND, DOWNTREND, or NEUTRAL)
Trend strength percentage (0-100%)
Early detection signals when applicable
The active sensitivity mode
This comprehensive approach helps traders and investors:
→ Assess the strength of current market trends
→ Identify early potential trend changes before full confirmation
→ Make more informed trading and investing decisions based on trend context
3. Customizable Visualization Settings
This indicator offers extensive visual customization options to suit different trading styles and preferences:
Display options:
→ Fully customizable uptrend, downtrend, and neutral colors
→ Color-coded price bars showing trend direction
→ Dynamic gradient bands visualizing potential trend channels
→ Optional background coloring based on trend intensity
→ Adjustable transparency levels for all visual elements
These visualization settings can be fine-tuned through the indicator's interface, allowing traders and investors to create a personalized chart environment that emphasizes the most relevant information for their strategy.
The indicator also features a comprehensive alert system with notifications for:
New trend formations (uptrend, downtrend, neutral)
Early trend change signals
Momentum threshold crossovers
Other significant market conditions
Alerts can be customized and delivered through TradingView's notification system, making it easy to stay informed of important market developments even when you are away from the charts.
🟢 Practical Usage Tips
→ Trend Analysis and Interpretation: The indicator visualizes trend direction and strength directly on the chart through color-coding and the information panel, allowing traders and investors to immediately identify the current market context. This information helps in assessing the potential for continuation or reversal.
→ Signal Generation Strategies: The indicator generates potential trading signals based on trend direction, momentum confirmation, and selected sensitivity mode. Users can choose between Conservative (fewer but more reliable signals), Balanced (moderate approach), or Aggressive (more frequent but potentially less reliable signals).
→ Multi-Period Trend Assessment: Through its layered EMA approach, the indicator enables users to understand trend conditions across different lookback periods within the same timeframe. This helps in identifying the dominant trend and potential turning points.
🟢 Pro Tips
Adjust EMA periods based on your timeframe:
→ Lower values for shorter timeframes and more frequent signals
→ Higher values for higher timeframes and more reliable signals
Fine-tune sensitivity mode based on your trading style:
→ "Conservative" for position trading/long-term investing and fewer false signals
→ "Balanced" for swing trading/medium-term investing with moderate signal frequency
→ "Aggressive" for scalping/day trading and catching early trend changes
Look for confluence between components:
→ Strong trend strength percentage and direction in the information panel
→ Overall market context aligning with the expected direction
Use for multiple trading approaches:
→ Trend following during strong momentum periods
→ Counter-trend trading at band extremes during overextension
→ Early trend change detection with sensitivity adjustments
→ Stop loss placement using dynamic bands
Combine with:
→ Volume indicators for additional confirmation
→ Support/resistance analysis for strategic entry/exit points
→ Multiple timeframe analysis for broader market context
Vietnamese Stocks: Multi-Ticker Fibonacci AlertThis Pine Script™ indicator is designed specifically for traders monitoring the Vietnamese stock market (HOSE, HNX). Its primary goal is to automate the tracking of Fibonacci retracement levels across a large list of stocks, alerting you when prices breach key support zones.
Core Functionality:
The script calculates Fibonacci retracement levels (23.6%, 38.2%, 50%, 61.8%, 78.6%) for up to 40 tickers simultaneously. The calculation is based on the highest high and lowest low identified since a user-defined Start Time. This allows you to anchor the Fibonacci analysis to a specific market event, trend start, or time period relevant to your strategy.
What it Does For You:
Automated Watchlist Scanning: Instead of drawing Fib levels on dozens of charts, select one of the two pre-configured watchlists (up to 40 symbols each, customizable in settings) populated with popular Vietnamese stocks.
Time-Based Fibonacci: Define a Start Time in the settings. The script uses this date to find the subsequent highest high and lowest low for each symbol in your chosen watchlist, forming the basis for the Fib calculation.
Intelligent Alerts: Get notified via TradingView's alerts when the candle closing price of any stock in your active watchlist falls below the critical 38.2%, 50%, 61.8%, or 78.6% levels relative to its own high/low range since the start time. Alerts are consolidated for efficiency.
Visual Aids:
- Plots the same time-based Fibonacci levels directly on your current chart symbol for quick reference.
- Includes an optional on-chart table showing which monitored stocks are currently below key Fib levels (enable "Show Debug Info").
- Features experimental background coloring to highlight potential bullish signals on the current chart.
Configuration:
Start Time: Crucial input – sets the anchor point for Fib calculations.
WatchList Selection: Choose between WatchList #1 (Bluechip/Midcap focus) or WatchList #2 (Defensive/Other focus) using the boolean toggles.
Symbol Customization: Easily replace the default symbols with your preferred Vietnamese stocks directly in the indicator settings.
Notification Prefix: Add custom text to the beginning of your alert messages.
Alert Setup: Remember to create an alert in TradingView, selecting this indicator and the alert() condition, usually with "Once Per Bar Close" frequency.
This tool is open-source under the MPL 2.0 license. Feel free to use, modify, and learn from it.
Memecoin Screener | QuantumResearchMemecoin Screener | QuantumResearch
🚀 Overview
The Memecoin Screener is a specialized multi-asset relative strength tool designed to track, compare, and rank up to 10 different memecoins in real-time. Built for degens and serious meme investors alike, this screener goes beyond price action—analyzing inter-asset relative momentum using a proprietary ARSI-based strength scoring system.
Whether you're flipping $FARTCOIN or rotating between SEED_DONKEYDAN_MARKET_CAP:BONK , SEED_WANDERIN_JIMZIP900:WIF , or $BUTTHOLE, this tool will help you uncover which meme coin leads the pack—and which ones are fading into irrelevance.
🧩 1. Key Features
📊 Relative Strength Matrix
Each selected memecoin is compared against all others using ARSI. This creates a matrix of performance relationships between tokens, highlighting dominance and weakness.
🏆 Dynamic Ranking System
Every coin is scored based on its aggregate relative strength across the group, then ranked from strongest to weakest. The higher the score, the more dominant the token is across the pack.
🎯 Allocation Recommendations
Choose your allocation style—Aggressive, Mixed, or Conservative—and let the screener automatically assign exposure percentages to the top-ranked assets based on your risk profile.
Aggressive allocation
Mix allocation
Conservative allocation
🖥 Visual Screener Table
A clean, color-coded table tracks ✔︎ wins and ✘ losses in pairwise comparisons, shows total strength scores, ranks, and allocation recommendations—all at a glance.
🎨 Customizable Color Modes & UI Positioning
Choose from 8 stylish color palettes and 9 screen positions for the screener table. Tailor the visual layout to your trading workflow.
🧠 How It Works
1️⃣ Pairwise Strength Comparison
Each token is compared to every other token using the formula:
tokenX / tokenY → ARSI → strength score
2️⃣ Score Aggregation
The individual strength scores from all pairwise comparisons are summed to produce a final score for each token.
3️⃣ Ranking & Allocation
Scores are sorted and ranked. Based on the selected allocation mode, exposure is then recommended across the Top 3 coins only.
📈 Use Cases
🔍 Memecoin Rotation Strategy
Stay in the strongest trends and rotate out of weak ones using leaderboard-driven allocation.
⚔️ Long/Short Relative Plays
Go long the top-ranked coin and short the bottom-ranked one for a hedged memecoin momentum strategy.
📊 Group Sentiment Heatmap
Use the table to visually assess which assets are gaining or losing strength over time.
🎒 Position Sizing Guide
Let the allocation module assist you in determining where and how much to allocate, especially when flipping high-risk coins.
💡 Who Is This For?
✅ Degen Traders flipping microcaps and memes
✅ Solana memecoin fans tracking top performers
✅ Systematic traders looking for structured rotation
✅ Anyone seeking clarity in chaos during volatile market cycles
⚠️ Disclaimer
This tool is designed for informational purposes and does not constitute financial advice. Memecoins are volatile and highly speculative assets. Always perform your own due diligence and apply proper risk management.
Follow QuantumResearch for more alpha-driven tools that blend meme culture with advanced technical frameworks.
🧪 Meme smarter. Rotate faster. Survive longer.
Enhanced Execution ToolA comprehensive position sizing calculator for disciplined risk management
Description :
This tool provides traders with precise position sizing calculations based on their account parameters and market conditions. The indicator calculates optimal position sizes for different entry scenarios while maintaining strict risk control.
Key Features:
Multiple entry options (High, Close, Manual)
Flexible stop loss configuration (LoD or Previous Day Low)
Account-based risk management (1% risk by default)
ATR-based distance metrics for volatility assessment
Clear visual table displaying all critical trade parameters
How to Use:
Configure your account size and risk percentage
Select your preferred entry methods (High/Close/Manual)
Choose stop loss reference (Low of Day or Previous Day Low)
View calculated position sizes and risk parameters
For manual entries, input your desired entry and stop prices
Input Parameters:
Account Configuration: Set your capital and risk tolerance
Entry Options: Choose which entry methods to display
Stop Loss: Select stop loss reference level
Technical Settings: Adjust ATR length and distance limits
Display Options: Customize table appearance
Output Includes:
Risk amount in dollars
Risk as percentage of entry price
Entry to stop loss as percentage of ATR
Stop loss price
Entry price
Position size as % of account
Share quantity
Ideal For:
Traders who want to maintain consistent risk management
Those who need quick position sizing calculations
Investors who trade with multiple entry strategies
Note: Always verify calculations before executing trades. This tool is designed to assist with trade planning, not as trade advice.
AI-123's BTC vs Gold (Lag Correlation)
DISCLAIMER
I made this indicator with the help of ChatGPT and using what I have learned so far from The Pine Script Mastery Course, LOTS of edits based on what I have learned so far had to be made as well as additions and modifications to my liking thanks to what I have learned so far. I am aware this already exists but I have done my best to make a first ever script/indicator while learning how to properly publish as well, so please bear that in mind.
Overview
This indicator analyzes the correlation between Bitcoin (BTC) and Gold (XAUUSD), with a customizable lag applied to the Gold price, providing insight into the macro relationship between these two assets.
It is designed for traders and investors who want to track how Bitcoin and Gold move in relation to each other, particularly when Gold is lagged by a specific number of days.
Key Features:
BTC and Gold (Lagged) Price Overlay: Display Bitcoin (BTC) and Gold (XAUUSD) prices on the chart, with an adjustable lag applied to the Gold price.
Rolling Correlation Calculation: Measures the correlation between Bitcoin and lagged Gold prices over a customizable lookback period.
Adjustable Lag: The number of days that Gold is lagged relative to Bitcoin is fully customizable (default: 20 days).
Customizable Correlation Length: Allows you to choose the lookback period for the correlation (default: 50 days), providing flexibility for short-term or long-term analysis.
Normalized Plotting: Prices of Bitcoin and Gold are normalized for better visual alignment with the correlation values. BTC is divided by 1000, and Gold by 100.
Correlation Scaling: The correlation value is amplified by 10 for better visual clarity and comparison with price data.
Zero Line: Horizontal line representing a correlation of 0, making it easier to identify positive or negative correlation shifts.
Maximum Correlation Lines: Horizontal lines at +10 and -10 values for extreme correlation scenarios.
Input Settings:
Gold Symbol: Customize the Gold ticker (default: OANDA:XAUUSD).
Bitcoin Symbol: Customize the Bitcoin ticker (default: BINANCE:BTCUSDT).
Lag (in trading days): Adjust the number of trading days to lag the Gold price relative to Bitcoin (default: 20).
Correlation Length (days): Set the number of days over which the rolling correlation is calculated (default: 50).
How to Use:
Price Comparison: The BTC (Spot) and Lagged Gold plots give you a side-by-side visual comparison of the two assets, normalized for clarity.
Correlation Line: The correlation line helps you gauge the strength and direction of the relationship between BTC and lagged Gold. Positive values indicate a strong positive correlation, while negative values indicate a negative correlation.
Visual Analysis: Watch how the correlation shifts with changes in lag and correlation length to identify potential market dynamics between Bitcoin and Gold.
Potential Applications:
Macro Trading: Track how Bitcoin and Gold behave in relation to each other during periods of economic uncertainty or inflation.
Sentiment Analysis: Use the correlation data to understand the sentiment between digital and traditional assets.
Strategic Timing: Identify potential opportunities where Bitcoin and Gold show a strong correlation or diverge based on the lag adjustment.
Understanding Macro Trends/Correlations.
Disclaimer:
This indicator is for informational purposes only. The correlation between Bitcoin and Gold does not guarantee future performance, and users should conduct their own research and use risk management strategies when making trading decisions.
Notes: This script uses historical data, so results may vary across different timeframes.
Customization options allow users to adjust the lag and correlation length to better fit their trading strategy.
Future Enhancements: Additional Correlation Line: A second correlation line for different lengths of lag or different assets.
Color-Coding of Correlation: Future updates may include color-coded correlation strength, visually indicating positive or negative correlation more effectively.
NQ/MNQ Position Sizing
Despite having my own position sizing calculator in an excel sheet, the manual process of having to identify my next trade, switch tabs/screens, input my values into the sheet, go back into TV, input the trade parameters with appropriate contract sizing, has always really gotten to me. I also found that I would often miss ideal entries due to the delay this caused.
I searched TV for position sizing calculators but almost all the ones I found seemed to be similar: based on some form of manual input for the entry and stop parameters, many of which had way more settings and parameters than I needed, also over complicated things.
I just needed something that would allow me to dynamically set my entry and stop levels directly on the chart, and spit out the appropriate contracts I should be using, either on NQ or MNQ, to maintain my desired level of risk, so I could quickly execute the necessary trade.
So, I coded my own and it's been a huge help to me already, so I thought I may as well publish the script as can't imagine there aren't others out there that also hate the manual data entry process of calculating risk.
Upon first load, the script will ask you to set your Entry and Stop levels, before drawing respective lines for these on the chart, and calculating contract sizing based on your risk settings, which you can update directly. The reset values may be buggy, will be easier to just remove the script and re-apply it to your chart if you ever lose track of the levels you've set.
Hope it's useful.
Prop Firm Guard: Risk & Sizing Tracker by TFTProp Firm Guard: Risk & Sizing Tracker by TFT
Overview:
This script is designed to help prop firm traders stay within risk rules and avoid emotional overtrading. It tracks your max loss limits, daily loss rules, and gives real-time position sizing suggestions based on your account status.
This tool is especially helpful for newer traders navigating prop firm challenges and rules like trailing drawdowns and daily stopouts.
Key Features:
✅ Real-time tracking of max loss and daily loss limits
✅ Supports both Intraday and End-of-Day (EOD) drawdown styles
✅ Calculates remaining “distance” to max/daily loss levels
✅ Automatically locks max loss once it trails up to starting balance
✅ Provides smart, tier-based position sizing suggestions (5%–50%)
✅ Shows profit target progress and live daily P&L
Use Case Example:
Let’s say you’re trading a $50,000 prop account with a $2,000 max drawdown limit.
If you're using Intraday Drawdown:
• You start the day at $50,000.
• During the day, your balance grows to $51,000 (including unrealized profits).
• The drawdown logic will trail this intraday high — so your new max loss limit becomes $49,000 (51K - 2K).
• If your balance drops to $49,400, this tool will show you’re $400 away from breaching the limit.
• Sizing suggestions will adjust accordingly to keep you in a safe range.
If you're using End-of-Day (EOD) Drawdown:
• The same scenario (account grows to $51,000 intraday) won’t affect your max loss limit immediately.
• EOD drawdown is only updated based on your end-of-day closing balance.
• So even if you hit $51K intraday, your max loss limit still remains at $48,000 (50K - 2K) until the trading day closes and updates your best equity.
• This mode offers more flexibility during the day — and the tool reflects this in how it calculates distances and sizing.
📌 It will then suggest a conservative sizing range — maybe 5–10% of your allowed contract size — until you're safer again.
📌 Make sure you update your current balance after each trade and follow your risk settings.
Inputs Explained (with Tips):
• Overall Account Starting Balance: Your full prop account size (e.g., 50000 or 100000, 150000, 300000, so on)
• Day Start Balance: What your balance was when the trading day started
• Daily Max Loss: How much you’re allowed to lose in one day (used only for EOD drawdown)
• Daily Profit Target: Your goal for the day (e.g., 500 or 1000 or so on)
• Allowed Overall Drawdown: Usually 4% for prop firms — like 2000 on 50K, or 6000 on 300K
• Drawdown Mode:
→ Intraday: Includes floating/unrealized profits in drawdown logic
→ EOD: Uses only end-of-day equity for drawdown logic
• Best Day High: Your highest balance to date. If not above your starting balance, this is ignored
• Intraday High (Manual): Optional override if your peak balance isn’t same as equity (used only for intraday drawdown mode)
• Current Equity: Update this during the session to reflect your live balance — everything else updates automatically
What You’ll See on the Chart:
🟩 Equity Section: Start balance, current balance, intraday high, best day high
🟥 Risk Section:
• Max loss limit (based on trailing logic)
• Distance from current balance to that limit
• Daily loss limit and distance (EOD mode only)
🟦 Performance Metrics:
• Daily P&L in $ and %
• Progress to profit target (shows ✅ Accomplished when goal is hit)
📦 Sizing Suggestion:
Based on how close you are to a drawdown breach, and your total drawdown tier.
Ranges from ⚠️ 5–10% to ✅ 40–50% of your max allowed contract size.
Who It's Best For:
• Built and optimized for 50K prop firm accounts
• Works well with 100K, 150K, or even 300K — but the sizing logic is most precise at 50K
• Best suited for futures or forex prop firm traders using account challenge-style rules
Manual Input Required:
Due to TradingView limitations, we cannot read your actual trades or live balance.
You'll need to update the Current Equity field yourself — but the rest is auto-calculated from there.
Most inputs (like overall balance and drawdown) are set once and rarely changed.
Beta Notice:
This tool is currently in beta and under testing. It's free for now and designed to help the trading community — but accuracy may vary.
Please send feedback if you'd like to suggest improvements or report bugs.
Disclaimer:
This tool is for educational purposes only and does not provide trading advice or signal any trades.
Always trade according to your firm’s rules. The author is not responsible for losses resulting from use of this script.
Lot Size TableLot Size Table Indicator – Pine Script (v5)
This TradingView script, “Lot Size Table,” creates a dynamic on-chart table that helps forex traders quickly calculate position sizes (lot sizes) for different capital and risk settings across various stop-loss (SL) pip scenarios.
🔧 Key Features:
📊 Real-time Forex Price Integration
Retrieves daily forex prices from OANDA for accurate lot size adjustments.
Instruments supported: USDJPY, USDCHF, AUDUSD, GBPUSD, NZDUSD, USDCAD, EURUSD.
🧠 Smart Lot Size Adjustments
Custom function adjustLotSize() adjusts lot sizes based on:
The currency of the instrument (e.g., JPY, GBP, AUD, etc.).
Special multiplier for symbols like US30 (e.g., ×8.5).
🧾 Flexible Capital & Risk Inputs
Supports 3 customizable capital groups, each with its own:
Capital amount
Risk percentage
📉 Multiple Stop-Loss (SL) Scenarios
Users input a comma-separated list of SL pip values (e.g., "20,25,30,...").
For each SL value, lot sizes are calculated for all 3 capital/risk combinations.
📋 Formatted On-Chart Table
Displays in a user-selected corner of the chart.
Customizable size, background color, and border.
Header row includes capital values and risk % (formatted to "k" if over 1,000).
Remaining rows show calculated lot sizes for each SL pip value.
📐 How It Works:
User Inputs: Capital, risk %, SL pip list, and table styling.
Calculation:
Lot size = (capital × risk%) / (SL pips × 10)
Adjusted based on instrument’s currency.
Display:
Table shows all SL pip scenarios and the corresponding adjusted lot sizes for each capital group.
Drawdown Visualizer v1.0Drawdown Visualizer
The Drawdown Visualizer tracks the percentage decline from all-time highs, providing valuable insights into market corrections and potential buying opportunities.
Key Features:
1) Real-Time Drawdown Tracking: The indicator continuously calculates and displays the current percentage drawdown from the all-time high price, color-coded from green (minimal drawdown) to red (severe drawdown) for instant visual feedback.
2) Maximum Drawdown Detection: Permanently tracks and displays the maximum historical drawdown encountered during the analyzed period, helping traders understand worst-case scenarios.
3) Statistical Analysis: Calculates and displays three important statistical measures:
* Average Drawdown: The mean value of all drawdowns recorded
* Median Drawdown: The middle value in the sorted list of all drawdowns, providing insight
into typical decline patterns
* Normal Drawdown Range: Visualizes the expected range of typical drawdowns based on
statistical standard deviation
Practical Applications:
1) Risk Management: Understand typical and extreme drawdowns to set appropriate stop-loss levels
2) Market Context: Gain perspective on whether current corrections are normal or exceptional
3) Entry Point Analysis: Identify potential buying opportunities when drawdowns reach statistical extremes
OverUnder Yield Spread🗺️ OverUnder is a structural regime visualizer , engineered to diagnose the shape, tone, and trajectory of the yield curve. Rather than signaling trades directly, it informs traders of the world they’re operating in. Yield curve steepening or flattening, normalizing or inverting — each regime reflects a macro pressure zone that impacts duration demand, liquidity conditions, and systemic risk appetite. OverUnder abstracts that complexity into a color-coded compression map, helping traders orient themselves before making risk decisions. Whether you’re in bonds, currencies, crypto, or equities, the regime matters — and OverUnder makes it visible.
🧠 Core Logic
Built to show the slope and intent of a selected rate pair, the OverUnder Yield Spread defaults to 🇺🇸US10Y-US2Y, but can just as easily compare global sovereign curves or even dislocated monetary systems. This value is continuously monitored and passed through a debounce filter to determine whether the curve is:
• Inverted, or
• Steepening
If the curve is flattening below zero: the world is bracing for contraction. Policy lags. Risk appetite deteriorates. Duration gets bid, but only as protection. Stocks and speculative assets suffer, regardless of positioning.
📍 Curve Regimes in Bull and Bear Contexts
• Flattening occurs when the short and long ends compress . In a bull regime, flattening may reflect long-end demand or fading growth expectations. In a bear regime, flattening often precedes or confirms central bank tightening.
• Steepening indicates expanding spread . In a bull context, this may signal healthy risk appetite or early expansion. In a bear or crisis context, it may reflect aggressive front-end cuts and dislocation between short- and long-term expectations.
• If the curve is steepening above zero: the world is rotating into early expansion. Risk assets behave constructively. Bond traders position for normalization. Equities and crypto begin trending higher on rising forward expectations.
🖐️ Dynamically Colored Spread Line Reflects 1 of 4 Regime States
• 🟢 Normal / Steepening — early expansion or reflation
• 🔵 Normal / Flattening — late-cycle or neutral slowdown
• 🟠 Inverted / Steepening — policy reversal or soft landing attempt
• 🔴 Inverted / Flattening — hard contraction, credit stress, policy lag
🍋 The Lemon Label
At every bar, an anchored label floats directly on the spread line. It displays the active regime (in plain English) and the precise spread in percent (or basis points, depending on resolution). Colored lemon yellow, neither green nor red, the label is always legible — a design choice to de-emphasize bias and center the data .
🎨 Fill Zones
These bands offer spatial, persistent views of macro compression or inversion depth.
• Blue fill appears above the zero line in normal (non-inverted) conditions
• Red fill appears below the zero line during inversion
🧪 Sample Reading: 1W chart of TLT
OverUnder reveals a multi-year arc of structural inversion and regime transition. From mid-2021 through late 2023, the spread remains decisively inverted, signaling persistent flattening and credit stress as bond prices trended sharply lower. This prolonged inversion aligns with a high-volatility phase in TLT, marked by lower highs and an accelerating downtrend, confirming policy lag and macro tightening conditions.
As of early 2025, the spread has crossed back above the zero baseline into a “Normal / Steepening” regime (annotated at +0.56%), suggesting a macro inflection point. Price action remains subdued, but the shift in yield structure may foreshadow a change in trend context — particularly if follow-through in steepening persists.
🎭 Different Traders Respond Differently:
• Bond traders monitor slope change to anticipate policy pivots or recession signals.
• Equity traders use regime shifts to time rotations, from growth into defense, or from contraction into reflation.
• Currency traders interpret curve steepening as yield compression or divergence depending on region.
• Crypto traders treat inversion as a liquidity vacuum — and steepening as an early-phase risk unlock.
🛡️ Can It Compare Different Bond Markets?
Yes — with caveats. The indicator can be used to compare distinct sovereign yield instruments, for example:
• 🇫🇷FR10Y vs 🇩🇪DE10Y - France vs Germany
• 🇯🇵JP10Y vs 🇺🇸US10Y - BoJ vs Fed policy curves
However:
🙈 This no longer visualizes the domestic yield curve, but rather the differential between rate expectations across regions
🙉 The interpretation of “inversion” changes — it reflects spread compression across nations , not within a domestic yield structure
🙊 Color regimes should then be viewed as relative rate positioning , not absolute curve health
🙋🏻 Example: OverUnder compares French vs German 10Y yields
1. 🇫🇷 Change the long-duration ticker to FR10Y
2. 🇩🇪 Set the short-duration ticker to DE10Y
3. 🤔 Interpret the result as: “How much higher is France’s long-term borrowing cost vs Germany’s?”
You’ll see steepening when the spread rises (France decoupling), flattening when the spread compresses (convergence), and inversions when Germany yields rise above France’s — historically rare and meaningful.
🧐 Suggested Use
OverUnder is not a signal engine — it’s a context map. Its value comes from situating any trade idea within the prevailing yield regime. Use it before entries, not after them.
• On the 1W timeframe, OverUnder excels as a macro overlay. Yield regime shifts unfold over quarters, not days. Weekly structure smooths out rate volatility and reveals the true curvature of policy response and liquidity pressure. Use this view to orient your portfolio, define directional bias, or confirm long-duration trend turns in assets like TLT, SPX, or BTC.
• On the 1D timeframe, the indicator becomes tactically useful — especially when aligning breakout setups or trend continuations with steepening or flattening transitions. Daily views can also identify early-stage regime cracks that may not yet be visible on the weekly.
• Avoid sub-daily use unless you’re anchoring a thesis already built on higher timeframe structure. The yield curve is a macro construct — it doesn’t oscillate cleanly at intraday speeds. Shorter views may offer clarity during event-driven spikes (like FOMC reactions), but they do not replace weekly context.
Ultimately, OverUnder helps you decide: What kind of world am I trading in? Use it to confirm macro context, avoid fighting the curve, and lean into trades aligned with the broader pressure regime.
Blended Net Liquidity CorrelationThis indicator visualizes a customizable net liquidity metric based on key U.S. Federal Reserve and Treasury data from FRED. It allows users to blend two liquidity models:
• With WALCL: Incorporates the Fed’s total balance sheet (WALCL) — ideal for capturing long-term structural liquidity from QE/QT.
• Without WALCL: Excludes the balance sheet and focuses on short-term operational flows like RRP, TGA, BTFP, and commercial lending.
Use the “Weight on WALCL” slider to find your optimal blend. A setting of 1.0 uses only WALCL, 0.0 uses only short-term flows, and any value in between gives a mix.
The indicator also calculates the correlation between net liquidity and price over various timeframes:
• 30D, 60D, 90D, 180D
• 1Y, 1.5Y, 2Y
• A custom length (default 3 years)
