DCA Ladder CalculatorThis script is a DCA (Dollar-Cost Averaging) Ladder Calculator with Risk & Leverage Management baked in.
It’s designed for both LONG and SHORT positions, and helps you:
🎯 Strategically scale into positions across multiple entry points
🔐 Control risk exposure via defined capital allocation
⚖️ Utilize leverage responsibly — for efficiency, not destruction
🧮 Visualize risk, stop loss level, and entry distribution
🔁 Adapt to trend reversals or key zones, especially when combined with reversal indicators or higher timeframe signals
🧠 How It Works
This tool takes a capital allocation approach to building a ladder of positions:
1. You define:
- Portfolio value
- Risk per trade (as %)
- Leverage
- Number of DCA levels
- Entry multiplier (e.g. 1x, 2x, 4x...)
2. The script then:
- Calculates total margin to risk = Portfolio × Risk %
- Calculates total leveraged position size = Margin × Leverage
- Distributes entries according to exponential weights (1x, 2x, 4x...), totaling 7 for 3 levels
- Calculates per-entry:
- Entry price (based on price zone spacing)
- Multiplier
- Exact margin per entry
- Leverage per entry (margin × leverage)
- Computes:
- Average entry price (margin-weighted)
- Approximate stop loss level based on recent ATR and price structure
- % drawdown to SL
- Total margin and position size
3. Displays all this in a clean on-chart table.
📈 How to Use It
1. Apply the indicator to a chart (default: 1D — ideal for clean zones).
2. Configure your:
- Portfolio Value (total trading capital)
- Risk per Trade (%) (your acceptable loss)
- Leverage (exchange or strategy-based)
- DCA Levels (e.g. 3 = anchor + 2 entries)
- Multiplier (typically 2.0 for doubling)
3. Choose LONG or SHORT mode depending on direction.
4. The table will show:
- Entry price ladder
- Margin used per entry
- Total position size
- Approx. stop loss (where your full risk is defined)
Use in conjunction with price action, S/R zones, trendline breaks, volume divergence, or reversal indicators.
✅ Best Practices for Using This Tool
- Leverage is a tool, not a weapon. Use it to scale smartly — not recklessly.
- Use fewer, higher-conviction entries. Don’t blindly ladder; combine with price structure and signals.
- Stick to your risk percent. Never risk more than you can afford to lose. Let this calculator enforce discipline.
- Combine with other confirmation tools, like RSI divergence, momentum shifts, OB zones, etc.
- Avoid martingale-style over-exposure. This is not a gambling tool — it’s for capital efficiency.
🛡️ What This Tool Does NOT Do
- This is not a trade signal indicator.
- It does not place trades or auto-manage positions.
- It does not replace personal responsibility or strategy — it's a tool to help apply structure.
⚠️ Disclaimer
This script is for educational and informational purposes only.
It does not constitute financial advice, nor is it a recommendation to buy or sell any financial instrument.
Always consult a licensed financial advisor before making investment decisions.
Use of leverage involves high risk and can lead to substantial losses.
The author and publisher assume no liability for any trading losses resulting from use of this script.
Portfolio
Stock Management (Zeiierman)█ Overview
Stock Management (Zeiierman) gives investors a complete, real-time view of their portfolio directly inside TradingView. It tracks performance, allocation, volatility, and dividends in one unified interface, making it easy to understand both how your portfolio is performing and how it behaves in terms of risk and exposure.
Rather than analyzing each chart in isolation, Stock Management (Zeiierman) turns TradingView into a lightweight portfolio cockpit. You can define up to 20 stock positions (ticker, shares, average cost), and the tool will:
Normalize all positions into a single user-selected currency
Calculate live position value, PnL, PnL%, and daily movement
Compute total portfolio value, performance, and volatility
Optionally generate a risk-parity style Recommended Allocation
Display upcoming dividend amounts, ex-dates, and pay-dates for your holdings
All of this appears as clean on-chart tables, including a main portfolio table, an optional dividend table, and an optional summary panel, allowing you to manage your portfolio while still watching price action. It is a visual portfolio layer built entirely around your own inputs, integrated seamlessly into the TradingView environment.
⚪ Why This One Is Unique
Most investors rely on basic broker dashboards that show position values but provide little insight into risk, exposure, or how each holding interacts with the rest of the portfolio. Stock Management (Zeiierman) goes far beyond that by building an intelligent, unified portfolio layer directly inside TradingView.
It automatically normalizes global holdings into a single reporting currency using live FX data, stabilizes allocation with a volatility-aware weighting engine, and structures your information through an adaptive column framework that highlights performance and risk in real time. A weighted summary blends portfolio movement, volatility, and long-horizon behavior into a clean snapshot, while dividend schedules and projected payouts are fully integrated into the same interface.
█ Main Features
⚪ 1. Portfolio Tracker
The core of Stock Management (Zeiierman) is a dynamic, real-time portfolio table that brings all key position data into one intelligent view. Each holding is displayed with:
Ticker
Sector
Price
Average Paid Price
Shares
Position Value
Position Weight
Profit & Loss
Profit & Loss %
Today % Change
Recommended Allocation
The table updates continuously with market prices, giving investors an immediate understanding of performance, exposure, and risk across all positions.
⚪ 2. Dividend Information
Dividend data for your holdings is automatically fetched, organized, and presented alongside your positions. This includes dividend amount, ex-date, and pay-date, along with projected payouts based on your share count. All dividend-related information is integrated directly into the portfolio view, so you can plan cash flow without switching tools.
⚪ 3. Portfolio Summary
A dedicated summary panel consolidates the entire portfolio into a single snapshot: total value, total PnL, YTD %, today’s change, and overall volatility. The volatility reading is particularly valuable, providing a quick gauge of your portfolio’s risk level and how sensitive it may be to market movement.
⚪ 4. Portfolio Weight Recommendation
An intelligent weighting engine reviews your current allocations and highlights where your portfolio is overexposed or underweighted. It offers recommended allocation levels designed to reduce concentration risk and improve balance, giving you a clearer path toward a more stable long-term positioning.
█ How to Use
⚪ Performance Tracking
Quickly assess your entire portfolio’s profit, loss, daily movement, and volatility from one centralized dashboard. The summary panel gives you an instant read on how your holdings are performing and how sensitive they are to market swings.
⚪ Dividend Management
Monitor upcoming dividend amounts, ex-dates, and pay-dates directly inside your portfolio table. This ensures you never miss a payout opportunity and can plan your expected cash flow with complete clarity.
⚪ Risk Management & Optimization
Use portfolio-wide volatility and the intelligent Recommended Allocation engine to identify imbalances in your holdings. These insights help you adjust position sizes, reduce concentration risk, and maintain a more stable long-term portfolio profile.
⚪ Currency Comparison
Switch between different base currencies to evaluate performance in local or international terms. All positions are automatically normalized using live FX data, making global portfolio management effortless.
█ How It Works
Stock Management (Zeiierman) continuously gathers price, currency, dividend, and volatility data for every ticker you track. All values are automatically converted into your selected reporting currency, so global holdings remain comparable in one unified view.
It builds a live portfolio snapshot of each bar, updating position values, PnL, daily returns, YTD performance, and overall volatility. This gives you an always-current understanding of how your portfolio is performing and how each holding contributes to risk and exposure.
An intelligent, volatility-aware allocation model generates recommended portfolio weights and position sizes, helping you identify where you may be overexposed or underweighted. Dividend information is integrated directly into the table, projecting future payouts and highlighting upcoming ex-dates and pay-dates.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Multi-Asset % Performance Table | v2.1 | TCP Multi-Asset % Performance Table | v2.1 | TCP
ESSENTIAL SUMMARY:
Multi-Asset % Performance Table eliminates the need to manually draw and manage individual "Price Range" tools for every asset. It automatically tracks up to 15 tickers independently in a single dashboard, calculating a TOTAL SCORE (Portfolio Average) for you. Unlike manual drawings, it supports a Global Range while allowing Custom Dates for specific assets, ensuring each ticker is calculated based on its own precise entry/exit. The Smart Visuals dynamically draw the correct date lines only for the ticker you are currently viewing, keeping your chart automatic, accurate, and clutter-free.
FUL DESCRIPTION:
📊 What is this tool?
The Multi-Asset % Performance Table is a powerful portfolio dashboard designed to track the percentage performance of up to 15 different assets simultaneously.
Instead of checking tickers one by one or manually drawing price ranges, this indicator aggregates everything into a single, clean table. It allows you to compare the ROI (Return on Investment) of a basket of coins or stocks over a specific time period and calculates an aggregate TOTAL SCORE (Average %) for your selection.
🚀 Key Features
15 Asset Slots: Monitor up to 15 different tickers (Crypto, Stocks, Forex, etc.) in one view.
Global vs. Custom Dates: Set a "Global" start/end date for the whole portfolio, but override specific assets with Custom Dates if they entered the portfolio at a different time.
Smart Visuals: Automatically draws vertical dashed lines on your chart representing the start and end dates of the ticker you are currently viewing.
Total Score Calculation: Calculates the average percentage change of your portfolio. You can dynamically include or exclude specific assets from this average using the settings.
Status Column: A quick visual reference (✔ or ✘) in the table showing which assets are currently included in the Total Score calculation.
⚙️ How it Works
Data Fetching: The script pulls "Close" prices from the Daily timeframe to ensure accuracy across long periods.
Smart Matching: The visual lines automatically detect which asset you are viewing. For example, if you are looking at BTCUSDT and have custom dates set for it, the vertical lines will jump to those specific dates. If you view a ticker not in your list, it defaults to the Global dates.
Visual Protection: The script uses advanced logic to ensure only one set of range lines appears on the chart at a time, keeping your workspace clean.
🛠️ Instructions & Settings
1. Setting up your Assets
Open the Settings (Cogwheel icon).
Under ASSET 1 through ASSET 15, enter the tickers you want to track (e.g., BINANCE:BTCUSDT).
Include in Avg?: Uncheck this if you want to see the asset in the table but exclude it from the "TOTAL SCORE" average.
2. Defining Time Ranges
Global Settings: Set the Global Start and Global End dates at the top. This applies to all assets by default.
Custom Dates: If a specific asset (e.g., Asset 4) was bought on a different day, check the "Custom Dates?" box for that asset and enter its specific Start/End time.
3. Reading the Table
The table appears on the chart (default: Bottom Right) with three columns:
Asset: The name of the ticker.
% Change: The percentage move from Start Date to End Date. (Green = Positive, Red = Negative).
Inc: Shows a ✔ if the asset is included in the Total Score average, or a ✘ if excluded.
4. The Visual Lines
Two vertical dashed lines will appear on your chart.
Note: These lines are visual references only. You cannot drag them to change the dates. To change the dates, you must use the Settings menu.
💡 Tips
Hover for Details: Hover your mouse over the % Change value in the table to see a tooltip showing the exact Start Price and End Price used for the calculation.
Resolution: The script defaults to 1 Day resolution for optimal accuracy on historical data.
v2.1 | TCP - Custom Built for Precision Performance Tracking
Volatility-Targeted Momentum Portfolio [BackQuant]Volatility-Targeted Momentum Portfolio
A complete momentum portfolio engine that ranks assets, targets a user-defined volatility, builds long, short, or delta-neutral books, and reports performance with metrics, attribution, Monte Carlo scenarios, allocation pie, and efficiency scatter plots. This description explains the theory and the mechanics so you can configure, validate, and deploy it with intent.
Table of contents
What the script does at a glance
Momentum, what it is, how to know if it is present
Volatility targeting, why and how it is done here
Portfolio construction modes: Long Only, Short Only, Delta Neutral
Regime filter and when the strategy goes to cash
Transaction cost modelling in this script
Backtest metrics and definitions
Performance attribution chart
Monte Carlo simulation
Scatter plot analysis modes
Asset allocation pie chart
Inputs, presets, and deployment checklist
Suggested workflow
1) What the script does at a glance
Pulls a list of up to 15 tickers, computes a simple momentum score on each over a configurable lookback, then volatility-scales their bar-to-bar return stream to a target annualized volatility.
Ranks assets by raw momentum, selects the top 3 and bottom 3, builds positions according to the chosen mode, and gates exposure with a fast regime filter.
Accumulates a portfolio equity curve with risk and performance metrics, optional benchmark buy-and-hold for comparison, and a full alert suite.
Adds visual diagnostics: performance attribution bars, Monte Carlo forward paths, an allocation pie, and scatter plots for risk-return and factor views.
2) Momentum: definition, detection, and validation
Momentum is the tendency of assets that have performed well to continue to perform well, and of underperformers to continue underperforming, over a specific horizon. You operationalize it by selecting a horizon, defining a signal, ranking assets, and trading the leaders versus laggards subject to risk constraints.
Signal choices . Common signals include cumulative return over a lookback window, regression slope on log-price, or normalized rate-of-change. This script uses cumulative return over lookback bars for ranking (variable cr = price/price - 1). It keeps the ranking simple and lets volatility targeting handle risk normalization.
How to know momentum is present .
Leaders and laggards persist across adjacent windows rather than flipping every bar.
Spread between average momentum of leaders and laggards is materially positive in sample.
Cross-sectional dispersion is non-trivial. If everything is flat or highly correlated with no separation, momentum selection will be weak.
Your validation should include a diagnostic that measures whether returns are explained by a momentum regression on the timeseries.
Recommended diagnostic tool . Before running any momentum portfolio, verify that a timeseries exhibits stable directional drift. Use this indicator as a pre-check: It fits a regression to price, exposes slope and goodness-of-fit style context, and helps confirm if there is usable momentum before you force a ranking into a flat regime.
3) Volatility targeting: purpose and implementation here
Purpose . Volatility targeting seeks a more stable risk footprint. High-vol assets get sized down, low-vol assets get sized up, so each contributes more evenly to total risk.
Computation in this script (per asset, rolling):
Return series ret = log(price/price ).
Annualized volatility estimate vol = stdev(ret, lookback) * sqrt(tradingdays).
Leverage multiplier volMult = clamp(targetVol / vol, 0.1, 5.0).
This caps sizing so extremely low-vol assets don’t explode weight and extremely high-vol assets don’t go to zero.
Scaled return stream sr = ret * volMult. This is the per-bar, risk-adjusted building block used in the portfolio combinations.
Interpretation . You are not levering your account on the exchange, you are rescaling the contribution each asset’s daily move has on the modeled equity. In live trading you would reflect this with position sizing or notional exposure.
4) Portfolio construction modes
Cross-sectional ranking . Assets are sorted by cr over the chosen lookback. Top and bottom indices are extracted without ties.
Long Only . Averages the volatility-scaled returns of the top 3 assets: avgRet = mean(sr_top1, sr_top2, sr_top3). Position table shows per-asset leverages and weights proportional to their current volMult.
Short Only . Averages the negative of the volatility-scaled returns of the bottom 3: avgRet = mean(-sr_bot1, -sr_bot2, -sr_bot3). Position table shows short legs.
Delta Neutral . Long the top 3 and short the bottom 3 in equal book sizes. Each side is sized to 50 percent notional internally, with weights within each side proportional to volMult. The return stream mixes the two sides: avgRet = mean(sr_top1,sr_top2,sr_top3, -sr_bot1,-sr_bot2,-sr_bot3).
Notes .
The selection metric is raw momentum, the execution stream is volatility-scaled returns. This separation is deliberate. It avoids letting volatility dominate ranking while still enforcing risk parity at the return contribution stage.
If everything rallies together and dispersion collapses, Long Only may behave like a single beta. Delta Neutral is designed to extract cross-sectional momentum with low net beta.
5) Regime filter
A fast EMA(12) vs EMA(21) filter gates exposure.
Long Only active when EMA12 > EMA21. Otherwise the book is set to cash.
Short Only active when EMA12 < EMA21. Otherwise cash.
Delta Neutral is always active.
This prevents taking long momentum entries during obvious local downtrends and vice versa for shorts. When the filter is false, equity is held flat for that bar.
6) Transaction cost modelling
There are two cost touchpoints in the script.
Per-bar drag . When the regime filter is active, the per-bar return is reduced by fee_rate * avgRet inside netRet = avgRet - (fee_rate * avgRet). This models proportional friction relative to traded impact on that bar.
Turnover-linked fee . The script tracks changes in membership of the top and bottom baskets (top1..top3, bot1..bot3). The intent is to charge fees when composition changes. The template counts changes and scales a fee by change count divided by 6 for the six slots.
Use case: increase fee_rate to reflect taker fees and slippage if you rebalance every bar or trade illiquid assets. Reduce it if you rebalance less often or use maker orders.
Practical advice .
If you rebalance daily, start with 5–20 bps round-trip per switch on liquid futures and adjust per venue.
For crypto perp microcaps, stress higher cost assumptions and add slippage buffers.
If you only rotate on lookback boundaries or at signals, use alert-driven rebalances and lower per-bar drag.
7) Backtest metrics and definitions
The script computes a standard set of portfolio statistics once the start date is reached.
Net Profit percent over the full test.
Max Drawdown percent, tracked from running peaks.
Annualized Mean and Stdev using the chosen trading day count.
Variance is the square of annualized stdev.
Sharpe uses daily mean adjusted by risk-free rate and annualized.
Sortino uses downside stdev only.
Omega ratio of sum of gains to sum of losses.
Gain-to-Pain total gains divided by total losses absolute.
CAGR compounded annual growth from start date to now.
Alpha, Beta versus a user-selected benchmark. Beta from covariance of daily returns, Alpha from CAPM.
Skewness of daily returns.
VaR 95 linear-interpolated 5th percentile of daily returns.
CVaR average of the worst 5 percent of daily returns.
Benchmark Buy-and-Hold equity path for comparison.
8) Performance attribution
Cumulative contribution per asset, adjusted for whether it was held long or short and for its volatility multiplier, aggregated across the backtest. You can filter to winners only or show both sides. The panel is sorted by contribution and includes percent labels.
9) Monte Carlo simulation
The panel draws forward equity paths from either a Normal model parameterized by recent mean and stdev, or non-parametric bootstrap of recent daily returns. You control the sample length, number of simulations, forecast horizon, visibility of individual paths, confidence bands, and a reproducible seed.
Normal uses Box-Muller with your seed. Good for quick, smooth envelopes.
Bootstrap resamples realized returns, preserving fat tails and volatility clustering better than a Gaussian assumption.
Bands show 10th, 25th, 75th, 90th percentiles and the path mean.
10) Scatter plot analysis
Four point-cloud modes, each plotting all assets and a star for the current portfolio position, with quadrant guides and labels.
Risk-Return Efficiency . X is risk proxy from leverage, Y is expected return from annualized momentum. The star shows the current book’s composite.
Momentum vs Volatility . Visualizes whether leaders are also high vol, a cue for turnover and cost expectations.
Beta vs Alpha . X is a beta proxy, Y is risk-adjusted excess return proxy. Useful to see if leaders are just beta.
Leverage vs Momentum . X is volMult, Y is momentum. Shows how volatility targeting is redistributing risk.
11) Asset allocation pie chart
Builds a wheel of current allocations.
Long Only, weights are proportional to each long asset’s current volMult and sum to 100 percent.
Short Only, weights show the short book as positive slices that sum to 100 percent.
Delta Neutral, 50 percent long and 50 percent short books, each side leverage-proportional.
Labels can show asset, percent, and current leverage.
12) Inputs and quick presets
Core
Portfolio Strategy . Long Only, Short Only, Delta Neutral.
Initial Capital . For equity scaling in the panel.
Trading Days/Year . 252 for stocks, 365 for crypto.
Target Volatility . Annualized, drives volMult.
Transaction Fees . Per-bar drag and composition change penalty, see the modelling notes above.
Momentum Lookback . Ranking horizon. Shorter is more reactive, longer is steadier.
Start Date . Ensure every symbol has data back to this date to avoid bias.
Benchmark . Used for alpha, beta, and B&H line.
Diagnostics
Metrics, Equity, B&H, Curve labels, Daily return line, Rolling drawdown fill.
Attribution panel. Toggle winners only to focus on what matters.
Monte Carlo mode with Normal or Bootstrap and confidence bands.
Scatter plot type and styling, labels, and portfolio star.
Pie chart and labels for current allocation.
Presets
Crypto Daily, Long Only . Lookback 25, Target Vol 50 percent, Fees 10 bps, Regime filter on, Metrics and Drawdown on. Monte Carlo Bootstrap with Recent 200 bars for bands.
Crypto Daily, Delta Neutral . Lookback 25, Target Vol 50 percent, Fees 15–25 bps, Regime filter always active for this mode. Use Scatter Risk-Return to monitor efficiency and keep the star near upper left quadrants without drifting rightward.
Equities Daily, Long Only . Lookback 60–120, Target Vol 15–20 percent, Fees 5–10 bps, Regime filter on. Use Benchmark SPX and watch Alpha and Beta to keep the book from becoming index beta.
13) Suggested workflow
Universe sanity check . Pick liquid tickers with stable data. Thin assets distort vol estimates and fees.
Check momentum existence . Run on your timeframe. If slope and fit are weak, widen lookback or avoid that asset or timeframe.
Set risk budget . Choose a target volatility that matches your drawdown tolerance. Higher target increases turnover and cost sensitivity.
Pick mode . Long Only for bull regimes, Short Only for sustained downtrends, Delta Neutral for cross-sectional harvesting when index direction is unclear.
Tune lookback . If leaders rotate too often, lengthen it. If entries lag, shorten it.
Validate cost assumptions . Increase fee_rate and stress Monte Carlo. If the edge vanishes with modest friction, refine selection or lengthen rebalance cadence.
Run attribution . Confirm the strategy’s winners align with intuition and not one unstable outlier.
Use alerts . Enable position change, drawdown, volatility breach, regime, momentum shift, and crash alerts to supervise live runs.
Important implementation details mapped to code
Momentum measure . cr = price / price - 1 per symbol for ranking. Simplicity helps avoid overfitting.
Volatility targeting . vol = stdev(log returns, lookback) * sqrt(tradingdays), volMult = clamp(targetVol / vol, 0.1, 5), sr = ret * volMult.
Selection . Extract indices for top1..top3 and bot1..bot3. The arrays rets, scRets, lev_vals, and ticks_arr track momentum, scaled returns, leverage multipliers, and display tickers respectively.
Regime filter . EMA12 vs EMA21 switch determines if the strategy takes risk for Long or Short modes. Delta Neutral ignores the gate.
Equity update . Equity multiplies by 1 + netRet only when the regime was active in the prior bar. Buy-and-hold benchmark is computed separately for comparison.
Tables . Position tables show current top or bottom assets with leverage and weights. Metric table prints all risk and performance figures.
Visualization panels . Attribution, Monte Carlo, scatter, and pie use the last bars to draw overlays that update as the backtest proceeds.
Final notes
Momentum is a portfolio effect. The edge comes from cross-sectional dispersion, adequate risk normalization, and disciplined turnover control, not from a single best asset call.
Volatility targeting stabilizes path but does not fix selection. Use the momentum regression link above to confirm structure exists before you size into it.
Always test higher lag costs and slippage, then recheck metrics, attribution, and Monte Carlo envelopes. If the edge persists under stress, you have something robust.
Crypto Index Price# Crypto Index Price - Indicator Description
## 📊 What is this indicator?
**Crypto Index Price** is an indicator for creating your own cryptocurrency index based on an equal-weighted portfolio. It allows you to track the overall dynamics of the cryptocurrency market through a composite index of selected assets.
## 🎯 Key Features
- **Up to 20 assets in the index** — create an index from any trading pairs
- **Equal-weighted methodology** — each asset has the same weight in the index
- **Moving average** — optional trend filter for the index
- **Flexible visualization settings** — customizable colors and line thickness
## 📈 How to Use
The indicator is displayed in a separate pane below the chart and shows:
1. **Blue line** — crypto index value
2. **Orange line** (optional) — moving average of the index
### Trading Applications:
- **Identify overall market trend** — if the index is rising, most coins are in an uptrend
- **Divergences** — divergence between your asset and the index may signal local opportunities
- **Signal confirmation** — use the index to confirm trading decisions on individual coins
- **Market condition filter** — trade longs when index is above MA, shorts when below
## ⚙️ Settings
### Assets (Symbols)
- **Asset 1-10** — main cryptocurrencies (default: BTC, ETH, BNB, SOL, XRP, ADA, AVAX, LINK, DOGE, TRX)
- **Asset 11-20** — additional slots for index expansion
### Visual Parameters
- **Index line color** — main line color (default: blue)
- **Line width** — from 1 to 5 pixels
- **Show moving average** — enable/disable MA
- **MA period** — moving average calculation period (default: 20)
- **MA color** — moving average line color (default: orange)
## 💡 Recommendations
- For a top coins index, use 5-10 largest cryptocurrencies by market cap
- For an altcoin index, add medium and small coins from your sector
- Use MA to filter false signals and identify the global trend
- Compare individual asset behavior with the index to find anomalies
## ⚠️ Important
The indicator uses equal-weighted methodology — each coin contributes equally regardless of price or market cap. This differs from cap-weighted indices and may provide a different market perspective.
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*This indicator is intended for analysis and is not trading advice. Always conduct your own analysis before making trading decisions.*
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Portfolio Strategy TesterThe Portfolio Strategy Tester is an institutional-grade backtesting framework that evaluates the performance of trend-following strategies on multi-asset portfolios. It enables users to construct custom portfolios of up to 30 assets and apply moving average crossover strategies across individual holdings. The model features a clear, color-coded table that provides a side-by-side comparison between the buy-and-hold portfolio and the portfolio using the risk management strategy, offering a comprehensive assessment of both approaches relative to the benchmark.
Portfolios are constructed by entering each ticker symbol in the menu, assigning its respective weight, and reviewing the total sum of individual weights displayed at the top left of the table. For strategy selection, users can choose between Exponential Moving Average (EMA), Simple Moving Average (SMA), Wilder’s Moving Average (RMA), Weighted Moving Average (WMA), Moving Average Convergence Divergence (MACD), and Volume-Weighted Moving Average (VWMA). Moving average lengths are defined in the menu and apply only to strategy-enabled assets.
To accurately replicate real-world portfolio conditions, users can choose between daily, weekly, monthly, or quarterly rebalancing frequencies and decide whether cash is held or redistributed. Daily rebalancing maintains constant portfolio weights, while longer intervals allow natural drift. When cash positions are not allowed, capital from bearish assets is automatically redistributed proportionally among bullish assets, ensuring the portfolio remains fully invested at all times. The table displays a comprehensive set of widely used institutional-grade performance metrics:
CAGR = Compounded annual growth rate of returns.
Volatility = Annualized standard deviation of returns.
Sharpe = CAGR per unit of annualized standard deviation.
Sortino = CAGR per unit of annualized downside deviation.
Calmar = CAGR relative to maximum drawdown.
Max DD = Largest peak-to-trough decline in value.
Beta (β) = Sensitivity of returns relative to benchmark returns.
Alpha (α) = Excess annualized risk-adjusted returns relative to benchmark.
Upside = Ratio of average return to benchmark return on up days.
Downside = Ratio of average return to benchmark return on down days.
Tracking = Annualized standard deviation of returns versus benchmark.
Turnover = Average sum of absolute changes in weights per year.
Cumulative returns are displayed on each label as the total percentage gain from the selected start date, with green indicating positive returns and red indicating negative returns. In the table, baseline metrics serve as the benchmark reference and are always gray. For portfolio metrics, green indicates outperformance relative to the baseline, while red indicates underperformance relative to the baseline. For strategy metrics, green indicates outperformance relative to both the baseline and the portfolio, red indicates underperformance relative to both, and gray indicates underperformance relative to either the baseline or portfolio. Metrics such as Volatility, Tracking Error, and Turnover ratio are always displayed in gray as they serve as descriptive measures.
In summary, the Portfolio Strategy Tester is a comprehensive backtesting tool designed to help investors evaluate different trend-following strategies on custom portfolios. It enables real-world simulation of both active and passive investment approaches and provides a full set of standard institutional-grade performance metrics to support data-driven comparisons. While results are based on historical performance, the model serves as a powerful portfolio management and research framework for developing, validating, and refining systematic investment strategies.
Ultimate Risk Management Toolkit [ T W K ] :Smart Levels is Smart Trades!
All Trading View users and Stock market Enthusiast, get charged with the all new ( never seen before ) " Ultimate Risk Management Toolkit ⚙📏⚙ " .
Inputs and Features:
1: Drag the Bar-Time vertical line to the desired Entry candle ( manually ) for R:R management and controlling emotional trading.
2: Target, Entry, and SL line style, Width input.
3: Manual specific level Entry and Stop-Loss, input option.
4: Three types of Auto / Manual ' R:R ' risk reward ratio, targets with proper Entry, Stop-Loss points, and Stop-Loss level.
5: Three types of Entry options to fix Emotional trading habit.
6: Trailing Stop-Loss input option ( can be utilize as profit locking/booking ).
It will give more Power to manage your trades with proper R:R ( Auto / manual ) ratio, defined Entry and controlled Stop-Loss Levels.
Compatible with All Devices (Laptop / Mobile / Tablet / PC).
✅ HOW TO GET ACCESS :
Add to favorite and enjoy the true Trading View's sprit of community growth, without any limitations.
If you like any of my Invite-Only indicators, kindly DM and let me know!
⚠ RISK DISCLAIMER :
All content provided by "@TradeWithKeshhav" is for informational & educational purposes only.
It does not constitute any financial advice or a solicitation to buy or sell any securities of any type. All investments / trading involve risks. Past performance does not guarantee future results / returns.
Regards :
Team @TradeWithKeshhav
Happy trading and investing!
Portfolio Simulator & BacktesterMulti-asset portfolio simulator with different metrics and ratios, DCA modeling, and rebalancing strategies.
Core Features
Portfolio Construction
Up to 5 assets with customizable weights (must total 100%)
Support for any tradable symbol: stocks, ETFs, crypto, indices, commodities
Real-time validation of allocations
Dollar Cost Averaging
Monthly or Quarterly contributions
Applies to both portfolio and benchmark for fair comparison
Model real-world investing behavior
Rebalancing
Four strategies: None, Monthly, Quarterly, Yearly
Automatic rebalancing to target weights
Transaction cost modeling (customizable fee %)
Key Metrics Table
CAGR: Annualized compound return (S&P 500 avg: ~10%)
Alpha: Excess return vs. benchmark (positive = outperformance)
Sharpe Ratio: Return per unit of risk (>1.0 is good, >2.0 excellent)
Sortino Ratio: Like Sharpe but only penalizes downside (better metric)
Calmar Ratio: CAGR / Max Drawdown (>1.0 good, >2.0 excellent)
Max Drawdown: Largest peak-to-trough decline
Win Rate: % of positive days (doesn't indicate profitability)
Visualization
Dual-chart comparison - Portfolio vs. Benchmark
Dollar or percentage view toggle
Customizable colors and line width
Two tables: Statistics + Asset Allocation
Adjustable table position and text size
🚀 Quick Start Guide
Enter 1-5 ticker symbols (e.g., SPY, QQQ, TLT, GLD, BTCUSD)
Make sure percentage weights total 100%
Choose date range (ensure chart shows full period - zoom out!)
Configure DCA and rebalancing (optional)
Select benchmark (default: SPX)
Analyze results in statistics table
💡 Pro Tips
Chart data matters: Load SPY or your longest-history asset as main chart
If you select an asset that was not available for the selected period, the chart will not show up! E.g. BTCUSD data: Only available from ~2017 onwards.
Transaction fees: 0.1% default (adjust to match your broker)
⚠️ Important Notes
Requires visible chart data (zoom out to show full date range)
Limited by each asset's historical data availability
Transaction fees and costs are modeled, but taxes/slippage are not
Past performance ≠ future results
Use for research and education only, not financial advice
Let me know if you have any suggestions to improve this simulator.
Normalized Portfolio TrackerThis script lets you create, visualize, and track a custom portfolio of up to 15 assets directly on TradingView.
It calculates a synthetic "portfolio index" by combining multiple tickers with user-defined weights, automatically normalizing them so the total allocation always equals 100%.
All assets are scaled to a common starting point, allowing you to compare your portfolio’s performance versus any benchmark like SPY, QQQ, or BTC.
🚀 Goal
This script helps traders and investors:
• Understand the combined performance of their portfolio.
• Normalize diverse assets into a single synthetic chart .
• Make portfolio-level insights without relying on external spreadsheets.
🎯 Use Cases
• Backtest your portfolio allocations directly on the chart.
• Compare your portfolio vs. benchmarks like SPY, QQQ, BTC.
• Track thematic baskets (commodities, EV supply chain, regional ETFs).
• Visualize how each component contributes to overall performance.
📊 Features
• Weighted Portfolio Performance : Combines selected assets into a synthetic value series.
• Base Price Alignment : Each asset is normalized to its starting price at the chosen date.
• Dynamic Portfolio Table : Displays symbols, normalized weights (%), equivalent shares (based on each asset’s start price, sums to 100 shares), and a total row that always sums to 100%.
• Multi-Asset Support : Works with stocks, ETFs, indices, crypto, or any TradingView-compatible symbol.
⚙️ Configuration
Flexible Portfolio Setup
• Add up to 15 assets with custom weight inputs.
• You can enter any arbitrary numbers (e.g. 30, 15, 55).
• The script automatically normalizes all weights so the total allocation always equals 100%.
Start Date Selection
• Choose any custom start date to normalize all assets.
• The portfolio value is then scaled relative to the main chart symbol, so you can directly compare portfolio performance against benchmarks like SPY or QQQ.
Chart Styles
• Candlestick chart
• Heikin Ashi chart
• Line chart
Custom Display
• Adjustable colors and line widths
• Optionally display asset list, normalized weights, and equivalent shares
⚙️ How It Works
• Fetch OHLC data for each asset.
• Normalizes weights internally so totals = 100%.
• Stores each asset’s base price at the selected start date.
• Calculates equivalent “shares” for each allocation.
• Builds a synthetic portfolio value series by summing weighted contributions.
• Renders as Candlestick, Heikin Ashi, or Line chart.
• Adds a portfolio info table for clarity.
⚠️ Notes
• This script is for visualization only . It does not place trades or auto-rebalance.
• Weight inputs are automatically normalized, so you don’t need to enter exact percentages.
Correlation Heatmap Matrix [TradingFinder] 20 Assets Variable🔵 Introduction
Correlation is one of the most important statistical and analytical metrics in financial markets, data mining, and data science. It measures the strength and direction of the relationship between two variables.
The correlation coefficient always ranges between +1 and -1 : a perfect positive correlation (+1) means that two assets or currency pairs move together in the same direction and at a constant ratio, a correlation of zero (0) indicates no clear linear relationship, and a perfect negative correlation (-1) means they move in exactly opposite directions.
While the Pearson Correlation Coefficient is the most common method for calculation, other statistical methods like Spearman and Kendall are also used depending on the context.
In financial market analysis, correlation is a key tool for Forex, the Stock Market, and the Cryptocurrency Market because it allows traders to assess the price relationship between currency pairs, stocks, or coins. For example, in Forex, EUR/USD and GBP/USD often have a high positive correlation; in stocks, companies from the same sector such as Apple and Microsoft tend to move similarly; and in crypto, most altcoins show a strong positive correlation with Bitcoin.
Using a Correlation Heatmap in these markets visually displays the strength and direction of these relationships, helping traders make more accurate decisions for risk management and strategy optimization.
🟣 Correlation in Financial Markets
In finance, correlation refers to measuring how closely two assets move together over time. These assets can be stocks, currency pairs, commodities, indices, or cryptocurrencies. The main goal of correlation analysis in trading is to understand these movement patterns and use them for risk management, trend forecasting, and developing trading strategies.
🟣 Correlation Heatmap
A correlation heatmap is a visual tool that presents the correlation between multiple assets in a color-coded table. Each cell shows the correlation coefficient between two assets, with colors indicating its strength and direction. Warm colors (such as red or orange) represent strong negative correlation, cool colors (such as blue or cyan) represent strong positive correlation, and mid-range tones (such as yellow or green) indicate correlations that are close to neutral.
🟣 Practical Applications in Markets
Forex : Identify currency pairs that move together or in opposite directions, avoid overexposure to similar trades, and spot unusual divergences.
Crypto : Examine the dependency of altcoins on Bitcoin and find independent movers for portfolio diversification.
Stocks : Detect relationships between stocks in the same industry or find outliers that move differently from their sector.
🟣 Key Uses of Correlation in Trading
Risk management and diversification: Select assets with low or negative correlation to reduce portfolio volatility.
Avoiding overexposure: Prevent opening multiple positions on highly correlated assets.
Pairs trading: Exploit temporary deviations between historically correlated assets for arbitrage opportunities.
Intermarket analysis: Study the relationships between different markets like stocks, currencies, commodities, and bonds.
Divergence detection: Spot when two typically correlated assets move apart as a possible trend change signal.
Market forecasting: Use correlated asset movements to anticipate others’ behavior.
Event reaction analysis: Evaluate how groups of assets respond to economic or political events.
❗ Important Note
It’s important to note that correlation does not imply causation — it only reflects co-movement between assets. Correlation is also dynamic and can change over time, which is why analyzing it across multiple timeframes provides a more accurate picture. Combining correlation heatmaps with other analytical tools can significantly improve the precision of trading decisions.
🔵 How to Use
The Correlation Heatmap Matrix indicator is designed to analyze and manage the relationships between multiple assets at once. After adding the tool to your chart, start by selecting the assets you want to compare (up to 20).
Then, choose the Correlation Period that fits your trading strategy. Shorter periods (e.g., 20 bars) are more sensitive to recent price movements, making them suitable for short-term trading, while longer periods (e.g., 100 or 200 bars) provide a broader view of correlation trends over time.
The indicator outputs a color-coded matrix where each cell represents the correlation between two assets. Warm colors like red and orange signal strong negative correlation, while cool colors like blue and cyan indicate strong positive correlation. Mid-range tones such as yellow or green suggest correlations that are close to neutral. This visual representation makes it easy to spot market patterns at a glance.
One of the most valuable uses of this tool is in portfolio risk management. Portfolios with highly correlated assets are more vulnerable to market swings. By using the heatmap, traders can find assets with low or negative correlation to reduce overall risk.
Another key benefit is preventing overexposure. For example, if EUR/USD and GBP/USD have a high positive correlation, opening trades on both is almost like doubling the position size on one asset, increasing risk unnecessarily. The heatmap makes such relationships clear, helping you avoid them.
The indicator is also useful for pairs trading, where a trader identifies assets that are usually correlated but have temporarily diverged — a potential arbitrage or mean-reversion opportunity.
Additionally, the tool supports intermarket analysis, allowing traders to see how movements in one market (e.g., crude oil) may impact others (e.g., the Canadian dollar). Divergence detection is another advantage: if two typically aligned assets suddenly move in opposite directions, it could signal a major trend shift or a news-driven move.
Overall, the Correlation Heatmap Matrix is not just an analytical indicator but also a fast, visual alert system for monitoring multiple markets at once. This is particularly valuable for traders in fast-moving environments like Forex and crypto.
🔵 Settings
🟣 Logic
Correlation Period : Number of bars used to calculate correlation between assets.
🟣 Display
Table on Chart : Enable/disable displaying the heatmap directly on the chart.
Table Size : Choose the table size (from very small to very large).
Table Position : Set the table location on the chart (top, middle, or bottom in various alignments).
🟣 Symbol Custom
Select Market : Choose the market type (Forex, Stocks, Crypto, or Custom).
Symbol 1 to Symbol 20: In custom mode, you can define up to 20 assets for correlation calculation.
🔵 Conclusion
The Correlation Heatmap Matrix is a powerful tool for analyzing correlations across multiple assets in Forex, crypto, and stock markets. By displaying a color-coded table, it visually conveys both the strength and direction of correlations — warm colors for strong negative correlation, cool colors for strong positive correlation, and mid-range tones such as yellow or green for near-zero or neutral correlation.
This helps traders select assets with low or negative correlation for diversification, avoid overexposure to similar trades, identify arbitrage and pairs trading opportunities, and detect unusual divergences between typically aligned assets. With support for custom mode and up to 20 symbols, it offers high flexibility for different trading strategies, making it a valuable complement to technical analysis and risk management.
𝙷✪𝚕𝚍𝚎𝚖 🦇 Multi-Exchange Position Tracker v5.51
𝙷✪𝚕𝚍𝚎𝚖 🦇 Multi-Exchange Position Tracker v5.51
Overview
The 𝙷✪𝚕𝚍𝚎𝚖 🦇 Multi-Exchange Position Tracker v5.51 is a powerful and highly customizable Pine Script v6 indicator designed for traders managing portfolios across multiple exchanges and assets. This advanced dashboard provides real-time tracking of up to 20 positions, offering comprehensive insights into your trading performance with support for Dollar-Cost Averaging (DCA), leverage, and risk management.
Key Features
Multi-Exchange Support : Track positions across major exchanges like Binance, Bybit, Bitvavo, Coinbase, Kraken, and OKX.
Multi-Asset Management : Monitor up to 20 assets with customizable symbols, directions (Long/Short), and leverage settings.
DCA Calculations : Input comma-separated entry prices and sizes for accurate Dollar-Cost Averaging calculations.
Real-Time Data : Fetches current prices for each asset to calculate position value, profit/loss (P/L), and allocation percentages.
Customizable Dashboard : Display key metrics such as Asset, Direction, Leverage, Average Entry, Current Price, Size, Value, P/L, P/L (%), Allocation (%), Risk (%), TP1 (%), and TP2 (%) in a flexible table.
TP/SL/Entry Visualization : Plot Take Profit (TP1, TP2), Stop Loss (SL), and Entry levels directly on the chart with customizable line styles, widths, and colors.
Alerts : Receive notifications when TP1, TP2, or SL levels are hit for any enabled asset.
Theming Options : Choose between Dark and Light themes with adjustable transparency, zebra row styling, and cell padding for enhanced readability.
Currency Conversion : Supports USD and EUR as base currencies, with automatic conversion for assets quoted in different currencies.
Debugging Tools : Enable debug labels to troubleshoot NaN issues or DCA mismatches.
How to Use
1. Configure Assets : In the "Asset Positions" section, enable up to 20 assets and specify their exchange, symbol, direction, leverage, entry prices, sizes, stop loss, and take-profit levels.
2. Customize Dashboard : Adjust visibility of columns, table position, size, and styling under "Dashboard Settings" and "Column Visibility" sections.
3. Set Base Currency : Choose USD or EUR for unified P/L and value calculations.
4. Visualize Levels : Enable TP/SL/Entry plotting to see key price levels on the chart, with customizable styles and label positions.
5. Enable Alerts : Turn on alerts to get notified when price crosses TP or SL levels.
6. Debugging : Use debug labels to identify and resolve any input errors or invalid symbols.
Settings Breakdown
Dashboard Settings : Toggle dashboard visibility, hide zero-size positions, show total account row, and set table position/size.
Column Visibility : Select which columns to display (e.g., Asset, P/L, Risk %).
Styling & Colors : Customize themes (Dark/Light), transparency, zebra row colors, and border styles.
TP/SL/Entry Styling : Adjust line styles, widths, colors, and label positions for Stop Loss, Take Profit, and Entry levels.
Asset Positions : Input details for each asset, including exchange, symbol, direction, leverage, and DCA entries.
Notes
Ensure correct symbol formats (e.g., BTCUSDT for Binance, ADAEUR for Bitvavo) to avoid price fetch errors.
DCA entries and sizes must match in count and be valid numbers to prevent calculation errors.
The indicator supports up to 500 lines and labels for optimal performance.
For best results, use on a chart matching one of your tracked asset symbols to visualize TP/SL/Entry lines.
Why Use This Indicator?
This indicator is ideal for traders juggling multiple positions across exchanges. It consolidates critical data into a single, visually appealing dashboard, saving time and improving decision-making. With robust customization, real-time calculations, and alert functionality, it’s a must-have tool for both novice and experienced traders.
Developed by 𝙷✪𝚕𝚍𝚎𝚖 🦇, 2025 ©
𝙷✪𝚕𝚍𝚎𝚖 🦇 Multi-Exchange Position Tracker v5.51
𝙷✪𝚕𝚍𝚎𝚖 🦇 Multi-Exchange Position Tracker v5.51
Overview
The 𝙷✪𝚕𝚍𝚎𝚖 🦇 Multi-Exchange Position Tracker v5.51 is a powerful and highly customizable Pine Script v6 indicator designed for traders managing portfolios across multiple exchanges and assets. This advanced dashboard provides real-time tracking of up to 20 positions, offering comprehensive insights into your trading performance with support for Dollar-Cost Averaging (DCA), leverage, and risk management.
Key Features
Multi-Exchange Support : Track positions across major exchanges like Binance, Bybit, Bitvavo, Coinbase, Kraken, and OKX.
Multi-Asset Management : Monitor up to 20 assets with customizable symbols, directions (Long/Short), and leverage settings.
DCA Calculations : Input comma-separated entry prices and sizes for accurate Dollar-Cost Averaging calculations.
Real-Time Data : Fetches current prices for each asset to calculate position value, profit/loss (P/L), and allocation percentages.
Customizable Dashboard : Display key metrics such as Asset, Direction, Leverage, Average Entry, Current Price, Size, Value, P/L, P/L (%), Allocation (%), Risk (%), TP1 (%), and TP2 (%) in a flexible table.
TP/SL/Entry Visualization : Plot Take Profit (TP1, TP2), Stop Loss (SL), and Entry levels directly on the chart with customizable line styles, widths, and colors.
Alerts : Receive notifications when TP1, TP2, or SL levels are hit for any enabled asset.
Theming Options : Choose between Dark and Light themes with adjustable transparency, zebra row styling, and cell padding for enhanced readability.
Currency Conversion : Supports USD and EUR as base currencies, with automatic conversion for assets quoted in different currencies.
Debugging Tools : Enable debug labels to troubleshoot NaN issues or DCA mismatches.
How to Use
1. Configure Assets : In the "Asset Positions" section, enable up to 20 assets and specify their exchange, symbol, direction, leverage, entry prices, sizes, stop loss, and take-profit levels.
2. Customize Dashboard : Adjust visibility of columns, table position, size, and styling under "Dashboard Settings" and "Column Visibility" sections.
3. Set Base Currency : Choose USD or EUR for unified P/L and value calculations.
4. Visualize Levels : Enable TP/SL/Entry plotting to see key price levels on the chart, with customizable styles and label positions.
5. Enable Alerts : Turn on alerts to get notified when price crosses TP or SL levels.
6. Debugging : Use debug labels to identify and resolve any input errors or invalid symbols.
Settings Breakdown
Dashboard Settings : Toggle dashboard visibility, hide zero-size positions, show total account row, and set table position/size.
Column Visibility : Select which columns to display (e.g., Asset, P/L, Risk %).
Styling & Colors : Customize themes (Dark/Light), transparency, zebra row colors, and border styles.
TP/SL/Entry Styling : Adjust line styles, widths, colors, and label positions for Stop Loss, Take Profit, and Entry levels.
Asset Positions : Input details for each asset, including exchange, symbol, direction, leverage, and DCA entries.
Notes
Ensure correct symbol formats (e.g., BTCUSDT for Binance, ADAEUR for Bitvavo) to avoid price fetch errors.
DCA entries and sizes must match in count and be valid numbers to prevent calculation errors.
The indicator supports up to 500 lines and labels for optimal performance.
For best results, use on a chart matching one of your tracked asset symbols to visualize TP/SL/Entry lines.
Why Use This Indicator?
This indicator is ideal for traders juggling multiple positions across exchanges. It consolidates critical data into a single, visually appealing dashboard, saving time and improving decision-making. With robust customization, real-time calculations, and alert functionality, it’s a must-have tool for both novice and experienced traders.
Developed by 𝙷✪𝚕𝚍𝚎𝚖 🦇, 2025 ©
Portfolio Tracker ARJO (V-01)Portfolio Tracker ARJO (V-01)
This indicator is a user-friendly portfolio tracking tool designed for TradingView charts. It overlays a customizable table on your chart to monitor up to 15 stocks or symbols in your portfolio. It calculates real-time metrics like current market price (CMP), gains/losses, and stoploss breaches, helping you stay on top of your investments without switching between multiple charts. The table uses color-coding for quick visual insights: green for profits, red for losses, and highlights breached stoplosses in red for alerts. It also shows portfolio-wide totals for overall performance.
Key Features
Supports up to 15 Symbols: Enter stock tickers (e.g., NSE:RELIANCE or BSE:TCS) with details like buy price, date, units, and stoploss.
Symbol: The stock ticker and description.
Buy Date: When you purchased it.
Units: Number of shares/units held.
Buy Price: Your entry price.
Stop Loss: Your set stoploss level (highlighted in red if breached by CMP).
CMP: Current market price (fetched from the chart's timeframe).
% Gain/Loss: Percentage change from buy price (color-coded: green for positive, red for negative).
Gain/Loss: Total monetary gain/loss based on units.
Optional Timeframe Columns: Toggle to show % change over 1 Week (1W), 1 Month (1M), 3 Months (3M), and 6 Months (6M) for historical performance.
Portfolio Summary: At the top of the table, see total % gain/loss and absolute gain/loss for your entire portfolio.
Visual Customizations: Adjust table position (e.g., Top Right), size, colors for positive/negative values, and intensity cutoff for gradients.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
How to Use It: Step-by-Step Guide
Add the Indicator to Your Chart: Search for "Portfolio Tracker ARJO (V-01)" in TradingView's indicator library and add it to any chart (preferably Daily timeframe for accuracy).
Input Your Portfolio Symbols:
Open the indicator settings (gear icon).
In the "Symbol 1" to "Symbol 15" groups, fill in:
Symbol: Enter the ticker (e.g., NSE:INFY).
Year/Month/Day: Select your buy date (e.g., 2024-07-01).
Buy Price: Your purchase price per unit.
Stoploss: Your exit price if things go south.
Units: How many shares you own.
Only fill what you need—leave extras blank. The table auto-adjusts to show only entered symbols.
Customize the Table (Optional):
In "Table settings":
Choose position (e.g., Top Right) and size (% of chart).
Toggle "Show Timeframe Columns" to add 1W/1M/3M/6M performance.
In "Color settings":
Pick colors for positive (green) and negative (red) cells.
Set "Color intensity cutoff (%)" to control how strong the colors get (e.g., 10% means changes above 10% max out the color).
Interpret the Table on Your Chart:
The table appears overlaid—scan rows for each symbol's stats.
Look at colors: Greener = better gains; redder = bigger losses.
Check CMP cell: Red means stoploss breached—consider selling!
Portfolio Gain/Loss at the top gives a quick overall health check.
For Best Results:
Use on a Daily chart to avoid CMP errors (the script will warn if on Weekly/Monthly).
Refresh the chart or wait for a new bar if data doesn't update immediately.
For Indian stocks, prefix with NSE: or BSE: (e.g., BSE:RELIANCE).
This is for tracking only—not trading signals. Combine with your strategy.
If no symbols show, ensure inputs are valid (e.g., buy price > 0, valid date).
Finally, this tool makes it quite easy for beginners to track their portfolios, while also giving advanced traders powerful and customizable insights. I'd love to hear your feedback—happy trading!
Custom Portfolio [BackQuant]Custom Portfolio {BackQuant]
Overview
This script turns TradingView into a lightweight portfolio optimizer with institutional-grade analytics and real-time position management capabilities.
Rank up to 15 tickers every bar using a pair-wise relative-strength "league table" that compares each asset against all others through your choice of 12 technical indicators.
Auto-allocate 100% of capital to the single strongest asset and optionally apply dynamic leverage when the aggregate market is trending, with full position tracking and rebalancing logic.
Track performance against a custom buy-and-hold benchmark while watching a fully fledged stats dashboard update in real time, including 15 professional risk metrics.
How it works
Relative-strength engine – Each asset is compared against every other asset with a user-selectable indicator (default: 9/21 EMA cross). The system generates a complete comparison matrix where Asset A vs Asset B, Asset A vs Asset C, and so on, creating strength scores. The summed scores crown a weekly/daily/hourly "winner" that receives the full allocation.
Regime filter – A second indicator applied to TOTAL crypto-market cap (or any symbol you choose) classifies the environment as trending or mean-reverting . Leverage activates only in trending regimes, protecting capital during choppy or declining markets. Choose from indicators like Universal Trend Model, Relative Strength Overlay, Momentum Velocity, or Custom RSI for regime detection.
Capital & position logic – Equity grows linearly when flat and multiplicatively while invested. The system tracks entry prices, calculates returns including leverage adjustments, and handles position transitions seamlessly. Optional intra-trade leverage rebalancing keeps exposure in sync with market conditions, recalculating position sizes as regime conditions change.
Risk & performance analytics – Every confirmed bar records return, drawdown, VaR/CVaR, Sharpe, Sortino, alpha/beta vs your benchmark, gain-to-pain, Calmar, win-rate, Omega ratio, portfolio variance, skewness, and annualized statistics. All metrics render in a professional table for instant inspection with proper annualization based on your selected trading days (252 for traditional markets, 365 for crypto).
Key inputs
Backtest window – Hard-code a start date or let the script run from series' inception with full date range validation.
Asset list (15 slots) – Works with spot, futures, indices, even synthetic spreads (e.g., BYBIT:BTCUSDT.P). The script automatically cleans ticker symbols for display.
Indicator universe – Switch the comparative metric to DEMA, BBPCT, LSMAz adaptive scores, Volatility WMA, DEMA ATR, Median Supertrend, and more proprietary indicators.
With more always being added!
Leverage settings – Max leverage from 1x to any multiple, auto-rebalancing toggle, trend/reversion thresholds with precision controls.
Visual toggles – Show/hide equity curve, rolling drawdown heat-map, daily PnL spikes, position label, advanced metrics table, buy-and-hold comparison equity.
Risk-free rate input – Customize the risk-free rate for accurate Sharpe ratio calculations, supporting both percentage and decimal inputs.
On-chart visuals
Color-coded equity curve with "shadow" offset for depth perception that changes from green (profitable) to red (losing) based on recent performance momentum.
Rolling drawdown strip that fades from light to deep red as losses widen, with customizable maximum drawdown scaling for visual clarity.
Optional daily-return histogram line and zero reference for understanding day-to-day volatility patterns.
Bottom-center table prints the current winning ticker in real time with clean formatting.
Top-right metrics grid updates every bar with 15 key performance indicators formatted to three decimal places for precision.
Benchmark overlay showing buy-and-hold performance of your selected index (default: SPX) for relative performance comparison.
Typical workflow
Add the indicator on a blank chart (overlay off).
Populate ticker slots with the assets you actually trade from your broker's symbol list.
Pick your momentum or mean-reversion metric and a regime filter that matches your market hypothesis.
Set max leverage (1 = spot only) and decide if you want dynamic rebalancing.
Press the little " L " on the price axis to view the equity curve in log scale for better long-term visualization.
Enable the metrics table to monitor Sharpe, Sortino, and drawdown in real time.
Iterate through different asset combinations and indicator settings; compare performance vs buy-and-hold; refine until you find robust parameters.
Who is it for?
Systematic crypto traders looking for a one-click, cross-sectional rotation model with professional risk management.
Portfolio quants who need rapid prototyping without leaving TradingView or exporting to Python/R.
Swing traders wanting an at-a-glance health check of their multi-coin basket with instant position signals.
Fund managers requiring detailed performance attribution and risk metrics for client reporting.
Researchers backtesting momentum and mean-reversion strategies across multiple assets simultaneously.
Important notes & tips
Set Trading Days in a Year to 252 for traditional markets; 365 for 24/7 crypto to ensure accurate annualization.
CAGR and Sharpe assume the backtest start date you choose—short windows can inflate stats, so test across multiple market cycles.
Leverage is theoretical; always confirm your broker's margin rules and account for funding costs not modeled here.
The script is computationally heavy at 15 assets due to the N×N comparison matrix—reduce the list or lengthen the timeframe if you hit execution limits.
Best results often come from mixing assets with different volatility profiles rather than highly correlated instruments.
The regime filter symbol can be changed from CRYPTOCAP:TOTAL to any broad market index that represents your asset universe.
Assets Correlation by GDM📊 Correlation Matrix Table between Two Assets
This indicator calculates and displays the rolling correlation between the asset on your chart and a second asset of your choice. The correlation is computed based on log returns over a user-defined lookback period. A live summary table appears in the bottom left corner, providing a real-time snapshot of the current correlation and its context.
How it works:
Comparison Asset:
Select any symbol to compare with the chart asset (e.g., compare BTCUSD to ETHUSD).
Lookback Period:
Choose the rolling window (in bars) used to calculate the Pearson correlation coefficient.
Dynamic Table:
A table in the lower left corner summarizes:
Main asset symbol
Comparison symbol
Analysis period (bars)
Current correlation value (rounded to 2 decimals)
Correlation strength & direction (Strong, Moderate, Weak | Positive/Negative)
Visual Plot:
The indicator plots the correlation value over time so you can observe changes and trends.
Table Positioning:
Table location can be adjusted from settings (bottom left/right, top left/right).
How to use:
Risk Management & Diversification:
Quickly assess if two assets move together (positive correlation), in opposite directions (negative correlation), or independently.
Pairs Trading:
Identify opportunities when correlation diverges from historical norms.
Portfolio Construction:
Avoid overexposure to highly correlated assets, or use negative correlation for hedging.
Limitations & Tips:
Correlation values are based on historical returns and may change during periods of market stress or volatility.
Use multiple lookback periods (short, medium, long) for a more robust view.
Correlation does not imply causation—always complement with additional analysis.
Script Features:
User-selectable comparison asset and lookback window.
Real-time correlation calculation.
Clean summary table with correlation stats.
Optional alert logic and correlation plot for more advanced usage.
If you find this indicator useful, please leave a like and let me know your suggestions for improvements!
Risk and Position Sizing📏 Why Position Size Should Be Based on Risk?
Let’s say you are ready to lose 1,000 in a trade. Based on your stop loss level, you can calculate how many shares (or quantity) to buy, so that if the stop hits, you only lose that ₹1,000.
This is called risk-based position sizing. It makes your trade size dynamic — small when SL is wide, bigger when SL is tight. No more random position sizes — just systematic.
Portfolio size is multiplied by the selected risk % to get money risk per trade.
This amount is then used to calculate how many shares can be bought for the given stop-loss.
So chose your portfolio size in settings. Default Portfolio size is 1,00,000 .
You can select your risk % per portfolio in the settings — for example:
0.25% for conservative style
0.5% to 1% for balanced traders
1.25% or 1.5% for aggressive ones (not recommended for beginners)
This script will automatically calculate how much quantity you should buy, for each stop-loss scenario.
📈 Progressive & Inverse-Progressive Risk Styles
Some traders follow progressive position sizing — they start with small risk when the trend is just starting, and increase the risk % as the trend confirms.
Others follow inverse-progressive sizing — they take high risk at early stages of a bull market, and reduce risk as the trend matures (when upside becomes limited).
📌 This script allows you to manually control the risk % in settings, so you can adjust it based on your trading phase and style.
📋 Three SL Scenarios – Choose What Matches Your Style
The table shows three different stop-loss conditions, and for each one it calculates:
Today’s Low – tightest stop loss
Yesterday’s Low – slightly safer, ideal for short-term swing trades
EMA Stop (configurable) – gives more breathing room.
You can visually compare all 3 in the table and choose whichever fits your strategy and comfort.
Also, you can customize:
Theme: dark or light
Font size
Table position (upper/lower corners)
🧠 Designed for traders who take risk management seriously.
Let this script handle the math. You focus on execution.
Happy Trading!
– LensOfChartist
Zuper Custom Index (Up to 40 Stocks)Description:
This indicator empowers you to create your own custom index from up to 40 stocks, with full control over the weight of each component. Whether you want to track a sector, a basket of favourites, or build your own benchmark, this tool gives you the flexibility and visualisation you need—all directly on your TradingView chart.
Key Features:
Supports Up to 40 Stocks:
Combine up to 40 different symbols into a single, custom index.
Flexible Weighting:
Assign a custom percentage weight to each stock. The script automatically normalizes your weights to ensure the index always sums to 100%.
Candlestick or Line Chart Display:
Choose between a candlestick chart (showing open, high, low, close of the index) or a simple line chart (close only) for your custom index.
Dynamic Rebalancing:
Change weights or symbols at any time; the index recalculates instantly.
Easy Symbol Input:
Add or remove stocks with simple input fields—no code editing required.
Perfect for Sector Analysis & Custom Baskets:
Track sectors, strategies, or any group of assets you care about.
How to Use:
Add the Indicator to Your Chart.
Enter Up to 40 Stock Symbols in the input fields.
Assign Weights (as percentages) to each symbol.
If all weights are left at zero, the index will use equal weighting.
If you enter custom weights, they will be automatically normalized.
Choose Your Display Type:
Select between a candlestick or line chart for your index.
Analyze Your Custom Index!
Use Cases:
Build your own sector or thematic index.
Track a custom ETF or fund composition.
Compare your portfolio’s performance as a single chart.
Visualize the impact of different weightings on a basket of stocks.
Notes:
The indicator uses TradingView’s latest Pine Script version for maximum performance and flexibility.
You can use any valid TradingView symbol (stocks, ETFs, indices, etc.).
For best results, ensure all symbols are available on your selected timeframe and exchange.
Create, visualize, and analyze your own custom indices—right on your TradingView chart!
40 Ticker Cross-Sectional Z-Scores [BackQuant]40 Ticker Cross-Sectional Z-Scores
BackQuant’s 40 Ticker Cross-Sectional Z-Scores is a powerful portfolio management strategy that analyzes the relative performance of up to 40 different assets, comparing them on a cross-sectional basis to identify the top and bottom performers. This indicator computes Z-scores for each asset based on their log returns and evaluates them relative to the mean and standard deviation over a rolling window. The Z-scores represent how far an asset's return deviates from the average, and these values are used to rank the assets, allowing for dynamic asset allocation based on performance.
By focusing on the strongest-performing assets and avoiding the weakest, this strategy aims to enhance returns while managing risk. Additionally, by adjusting for standard deviations, the system offers a risk-adjusted method of ranking assets, making it suitable for traders who want to dynamically allocate capital based on performance metrics rather than just price movements.
Key Features
1. Cross-Sectional Z-Score Calculation:
The system calculates Z-scores for 40 different assets, evaluating their log returns against the mean and standard deviation over a rolling window. This enables users to assess the relative performance of each asset dynamically, highlighting which assets are performing better or worse compared to their historical norms. The Z-score is a useful statistical tool for identifying outliers in asset performance.
2. Asset Ranking and Allocation:
The system ranks assets based on their Z-scores and allocates capital to the top performers. It identifies the top and bottom assets, and traders can allocate capital to the top-performing assets, ensuring that their portfolio is aligned with the best performers. Conversely, the bottom assets are removed from the portfolio, reducing exposure to underperforming assets.
3. Rolling Window for Mean and Standard Deviation Calculations:
The Z-scores are calculated based on rolling means and standard deviations, making the system adaptive to changing market conditions. This rolling calculation window allows the strategy to adjust to recent performance trends and minimize the impact of outdated data.
4. Mean and Standard Deviation Visualization:
The script provides real-time visualizations of the mean (x̄) and standard deviation (σ) of asset returns, helping traders quickly identify trends and volatility in their portfolio. These visual indicators are useful for understanding the current market environment and making more informed allocation decisions.
5. Top & Bottom Performer Tables:
The system generates tables that display the top and bottom performers, ranked by their Z-scores. Traders can quickly see which assets are outperforming and underperforming. These tables provide clear and actionable insights, helping traders make informed decisions about which assets to include in their portfolio.
6. Customizable Parameters:
The strategy allows traders to customize several key parameters, including:
Rolling Calculation Window: Set the window size for the rolling mean and standard deviation calculations.
Top & Bottom Tickers: Choose how many of the top and bottom assets to display and allocate capital to.
Table Orientation: Select between vertical or horizontal table formats to suit the user’s preference.
7. Forward Test & Out-of-Sample Testing:
The system includes out-of-sample forward tests, ensuring that the strategy is evaluated based on real-time performance, not just historical data. This forward testing approach helps validate the robustness of the strategy in dynamic market conditions.
8. Visual Feedback and Alerts:
The system provides visual feedback on the current asset rankings and allocations, with dynamic labels and plots on the chart. Additionally, users receive alerts when allocations change, keeping them informed of important adjustments.
9. Risk Management via Z-Scores and Std Dev:
The system’s approach to asset selection is based on Z-scores, which normalize performance relative to the historical mean. By incorporating standard deviation, it accounts for the volatility and risk associated with each asset. This allows for more precise risk management and portfolio construction.
10. Note on Mean Reversion Strategy:
If you take the inverse of the signals provided by this indicator, the strategy can be used for mean-reversion rather than trend-following. This would involve buying the underperforming assets and selling the outperforming ones. However, it's important to note that this approach does not work well with highly correlated assets, as the relationship between the assets could result in the same directional movement, undermining the effectiveness of the mean-reversion strategy.
References
www.uts.edu.au
onlinelibrary.wiley.com
www.cmegroup.com
Final Thoughts
The 40 Ticker Cross-Sectional Z-Scores strategy offers a data-driven approach to portfolio management, dynamically allocating capital based on the relative performance of assets. By using Z-scores and standard deviations, this strategy ensures that capital is directed to the strongest performers while avoiding weaker assets, ultimately improving the risk-adjusted returns of the portfolio. Whether you’re focused on trend-following or looking to explore mean-reversion strategies, this flexible system can be tailored to suit your investment goals.
Cross-Sectional Altcoin Portfolio [BackQuant]Cross-Sectional Altcoin Portfolio
Introducing BackQuant's Cross-Sectional Altcoin Portfolio, a sophisticated trading system designed to dynamically rotate among a selection of major altcoins. This portfolio strategy compares multiple assets based on real-time performance metrics, such as momentum and trend strength, to select the strongest-performing coins. It uses a combination of adaptive scoring and regime filters to ensure the portfolio is aligned with favorable market conditions, minimizing exposure during unfavorable trends.
This system offers a comprehensive solution for crypto traders who want to optimize portfolio allocation based on cross-asset performance, while also accounting for market regimes. It allows traders to compare multiple altcoins dynamically and allocate capital to the top performers, ensuring the portfolio is always positioned in the most promising assets.
Key Features
1. Dynamic Asset Rotation:
The portfolio constantly evaluates the relative strength of 10 major altcoins: SOLUSD, RUNEUSD, ORDIUSD, DOGEUSDT, ETHUSD, ENAUSDT, RAYUSDT, PENDLEUSD, UNIUSD, and KASUSDT.
Using a ratio matrix, the system selects the strongest asset based on momentum and trend performance, dynamically adjusting the allocation as market conditions change.
2. Long-Only Portfolio with Cash Reserve:
The portfolio only takes long positions or remains in cash. The system does not enter short positions, reducing the risk of exposure during market downturns.
A powerful regime filter ensures the system is inactive during periods of market weakness, defined by the Universal Trend Performance Indicator (TPI) and other market data.
3. Equity Tracking:
The script provides real-time visualizations of portfolio equity compared to buy-and-hold strategies.
Users can compare the performance of the portfolio against holding individual assets (e.g., BTC, ETH) and see the benefits of the dynamic allocation.
4. Performance Metrics:
The system provides key performance metrics such as:
Sharpe Ratio: Measures risk-adjusted returns.
Sortino Ratio: Focuses on downside risk.
Omega Ratio: Evaluates returns relative to risk.
Maximum Drawdown: The maximum observed loss from a peak to a trough.
These metrics allow traders to assess the effectiveness of the strategy versus simply holding the assets.
5. Regime Filter:
The system incorporates a regime filter that evaluates the overall market trend using the TPI and other indicators. If the market is in a downtrend, the system exits positions and moves to cash, avoiding exposure to negative market conditions.
Users can customize the thresholds for the long and short trends to fit their risk tolerance.
6. Customizable Parameters:
Traders can adjust key parameters, such as the backtest start date, starting capital, leverage multiplier, and visualization options, including equity plot colors and line widths.
The system supports different levels of customizations for traders to optimize their strategies.
7. Equity and Buy-and-Hold Comparisons:
This script enables traders to see the side-by-side comparison of the portfolio’s equity curve and the equity curve of a buy-and-hold strategy for each asset.
The comparison allows users to evaluate the performance of the dynamic strategy versus holding the altcoins in isolation.
8. Forward Test (Out-of-Sample Testing):
The system includes a note that the portfolio provides out-of-sample forward tests, ensuring the robustness of the strategy. This is crucial for assessing the portfolio's performance beyond historical backtesting and validating its ability to adapt to future market conditions.
9. Visual Feedback:
The system offers detailed visual feedback on the current asset allocation and performance. Candles are painted according to the trend of the selected assets, and key metrics are displayed in real-time, including the momentum scores for each asset.
10. Alerts and Notifications:
Real-time alerts notify traders when the system changes asset allocations or moves to cash, ensuring they stay informed about portfolio adjustments.
Visual labels on the chart provide instant feedback on which asset is currently leading the portfolio allocation.
How the Rotation Works
The portfolio evaluates 10 different assets and calculates a momentum score for each based on their price action. This score is processed through a ratio matrix, which compares the relative performance of each asset.
Based on the rankings, the portfolio allocates capital to the top performers, ensuring it rotates between the strongest assets while minimizing exposure to underperforming assets.
If no asset shows strong performance, the system defaults to cash to preserve capital.
Final Thoughts
BackQuant’s Cross-Sectional Altcoin Portfolio provides a dynamic and systematic approach to altcoin portfolio management. By employing real-time performance metrics, adaptive scoring, and regime filters, this strategy aims to optimize returns while minimizing exposure to market downturns. The inclusion of out-of-sample forward tests ensures that the system remains robust in live market conditions, making it an ideal tool for crypto traders seeking to enhance their portfolio's performance with a data-driven, momentum-based approach.
Performance Metrics With Bracketed Rebalacing [BackQuant]Performance Metrics With Bracketed Rebalancing
The Performance Metrics With Bracketed Rebalancing script offers a robust method for assessing portfolio performance, integrating advanced portfolio metrics with different rebalancing strategies. With a focus on adaptability, the script allows traders to monitor and adjust portfolio weights, equity, and other key financial metrics dynamically. This script provides a versatile approach for evaluating different trading strategies, considering factors like risk-adjusted returns, volatility, and the impact of portfolio rebalancing.
Please take the time to read the following:
Key Features and Benefits of Portfolio Methods
Bracketed Rebalancing:
Bracketed Rebalancing is an advanced strategy designed to trigger portfolio adjustments when an asset's weight surpasses a predefined threshold. This approach minimizes overexposure to any single asset while maintaining flexibility in response to market changes. The strategy is particularly beneficial for mitigating risks that arise from significant asset weight fluctuations. The following image illustrates how this method reacts when asset weights cross the threshold:
Daily Rebalancing:
Unlike the bracketed method, Daily Rebalancing adjusts portfolio weights every trading day, ensuring consistent asset allocation. This method aims for a more even distribution of portfolio weights, making it a suitable option for traders who prefer less sensitivity to individual asset volatility. Here's an example of Daily Rebalancing in action:
No Rebalancing:
For traders who prefer a passive approach, the "No Rebalancing" option allows the portfolio to remain static, without any adjustments to asset weights. This method may appeal to long-term investors or those who believe in the inherent stability of their selected assets. Here’s how the portfolio looks when no rebalancing is applied:
Portfolio Weights Visualization:
One of the standout features of this script is the visual representation of portfolio weights. With adjustable settings, users can track the current allocation of assets in real-time, making it easier to analyze shifts and trends. The following image shows the real-time weight distribution across three assets:
Rolling Drawdown Plot:
Managing drawdown risk is a critical aspect of portfolio management. The Rolling Drawdown Plot visually tracks the drawdown over time, helping traders monitor the risk exposure and performance relative to the peak equity levels. This feature is essential for assessing the portfolio's resilience during market downturns:
Daily Portfolio Returns:
Tracking daily returns is crucial for evaluating the short-term performance of the portfolio. The script allows users to plot daily portfolio returns to gain insights into daily profit or loss, helping traders stay updated on their portfolio’s progress:
Performance Metrics
Net Profit (%):
This metric represents the total return on investment as a percentage of the initial capital. A positive net profit indicates that the portfolio has gained value over the evaluation period, while a negative value suggests a loss. It's a fundamental indicator of overall portfolio performance.
Maximum Drawdown (Max DD):
Maximum Drawdown measures the largest peak-to-trough decline in portfolio value during a specified period. It quantifies the most significant loss an investor would have experienced if they had invested at the highest point and sold at the lowest point within the timeframe. A smaller Max DD indicates better risk management and less exposure to significant losses.
Annual Mean Returns (% p/y):
This metric calculates the average annual return of the portfolio over the evaluation period. It provides insight into the portfolio's ability to generate returns on an annual basis, aiding in performance comparison with other investment opportunities.
Annual Standard Deviation of Returns (% p/y):
This measure indicates the volatility of the portfolio's returns on an annual basis. A higher standard deviation signifies greater variability in returns, implying higher risk, while a lower value suggests more stable returns.
Variance:
Variance is the square of the standard deviation and provides a measure of the dispersion of returns. It helps in understanding the degree of risk associated with the portfolio's returns.
Sortino Ratio:
The Sortino Ratio is a variation of the Sharpe Ratio that only considers downside risk, focusing on negative volatility. It is calculated as the difference between the portfolio's return and the minimum acceptable return (MAR), divided by the downside deviation. A higher Sortino Ratio indicates better risk-adjusted performance, emphasizing the importance of avoiding negative returns.
Sharpe Ratio:
The Sharpe Ratio measures the portfolio's excess return per unit of total risk, as represented by standard deviation. It is calculated by subtracting the risk-free rate from the portfolio's return and dividing by the standard deviation of the portfolio's excess return. A higher Sharpe Ratio indicates more favorable risk-adjusted returns.
Omega Ratio:
The Omega Ratio evaluates the probability of achieving returns above a certain threshold relative to the probability of experiencing returns below that threshold. It is calculated by dividing the cumulative probability of positive returns by the cumulative probability of negative returns. An Omega Ratio greater than 1 indicates a higher likelihood of achieving favorable returns.
Gain-to-Pain Ratio:
The Gain-to-Pain Ratio measures the return per unit of risk, focusing on the magnitude of gains relative to the severity of losses. It is calculated by dividing the total gains by the total losses experienced during the evaluation period. A higher ratio suggests a more favorable balance between reward and risk.
www.linkedin.com
Compound Annual Growth Rate (CAGR) (% p/y):
CAGR represents the mean annual growth rate of the portfolio over a specified period, assuming the investment has been compounding over that time. It provides a smoothed annual rate of growth, eliminating the effects of volatility and offering a clearer picture of long-term performance.
Portfolio Alpha (% p/y):
Portfolio Alpha measures the portfolio's performance relative to a benchmark index, adjusting for risk. It is calculated using the Capital Asset Pricing Model (CAPM) and represents the excess return of the portfolio over the expected return based on its beta and the benchmark's performance. A positive alpha indicates outperformance, while a negative alpha suggests underperformance.
Portfolio Beta:
Portfolio Beta assesses the portfolio's sensitivity to market movements, indicating its exposure to systematic risk. A beta greater than 1 suggests the portfolio is more volatile than the market, while a beta less than 1 indicates lower volatility. Beta is used to understand the portfolio's potential for gains or losses in relation to market fluctuations.
Skewness of Returns:
Skewness measures the asymmetry of the return distribution. A positive skew indicates a distribution with a long right tail, suggesting more frequent small losses and fewer large gains. A negative skew indicates a long left tail, implying more frequent small gains and fewer large losses. Understanding skewness helps in assessing the likelihood of extreme outcomes.
Value at Risk (VaR) 95th Percentile:
VaR at the 95th percentile estimates the maximum potential loss over a specified period, given a 95% confidence level. It provides a threshold value such that there is a 95% probability that the portfolio will not experience a loss greater than this amount.
Conditional Value at Risk (CVaR):
CVaR, also known as Expected Shortfall, measures the average loss exceeding the VaR threshold. It provides insight into the tail risk of the portfolio, indicating the expected loss in the worst-case scenarios beyond the VaR level.
These metrics collectively offer a comprehensive view of the portfolio's performance, risk exposure, and efficiency. By analyzing these indicators, investors can make informed decisions, balancing potential returns with acceptable levels of risk.
Conclusion
The Performance Metrics With Bracketed Rebalancing script provides a comprehensive framework for evaluating and optimizing portfolio performance. By integrating advanced metrics, adaptive rebalancing strategies, and visual analytics, it empowers traders to make informed decisions in managing their investment portfolios. However, it's crucial to consider the implications of rebalancing strategies, as academic research indicates that predictable rebalancing can lead to market impact costs. Therefore, adopting flexible and less predictable rebalancing approaches may enhance portfolio performance and reduce associated costs.
DCA Investment Tracker Pro [tradeviZion]DCA Investment Tracker Pro: Educational DCA Analysis Tool
An educational indicator that helps analyze Dollar-Cost Averaging strategies by comparing actual performance with historical data calculations.
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💡 Why I Created This Indicator
As someone who practices Dollar-Cost Averaging, I was frustrated with constantly switching between spreadsheets, calculators, and charts just to understand how my investments were really performing. I wanted to see everything in one place - my actual performance, what I should expect based on historical data, and most importantly, visualize where my strategy could take me over the long term .
What really motivated me was watching friends and family underestimate the incredible power of consistent investing. When Napoleon Bonaparte first learned about compound interest, he reportedly exclaimed "I wonder it has not swallowed the world" - and he was right! Yet most people can't visualize how their $500 monthly contributions today could become substantial wealth decades later.
Traditional DCA tracking tools exist, but they share similar limitations:
Require manual data entry and complex spreadsheets
Use fixed assumptions that don't reflect real market behavior
Can't show future projections overlaid on actual price charts
Lose the visual context of what's happening in the market
Make compound growth feel abstract rather than tangible
I wanted to create something different - a tool that automatically analyzes real market history, detects volatility periods, and shows you both current performance AND educational projections based on historical patterns right on your TradingView charts. As Warren Buffett said: "Someone's sitting in the shade today because someone planted a tree a long time ago." This tool helps you visualize your financial tree growing over time.
This isn't just another calculator - it's a visualization tool that makes the magic of compound growth impossible to ignore.
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🎯 What This Indicator Does
This educational indicator provides DCA analysis tools. Users can input investment scenarios to study:
Theoretical Performance: Educational calculations based on historical return data
Comparative Analysis: Study differences between actual and theoretical scenarios
Historical Projections: Theoretical projections for educational analysis (not predictions)
Performance Metrics: CAGR, ROI, and other analytical metrics for study
Historical Analysis: Calculates historical return data for reference purposes
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🚀 Key Features
Volatility-Adjusted Historical Return Calculation
Analyzes 3-20 years of actual price data for any symbol
Automatically detects high-volatility stocks (meme stocks, growth stocks)
Uses median returns for volatile stocks, standard CAGR for stable stocks
Provides conservative estimates when extreme outlier years are detected
Smart fallback to manual percentages when data insufficient
Customizable Performance Dashboard
Educational DCA performance analysis with compound growth calculations
Customizable table sizing (Tiny to Huge text options)
9 positioning options (Top/Middle/Bottom + Left/Center/Right)
Theme-adaptive colors (automatically adjusts to dark/light mode)
Multiple display layout options
Future Projection System
Visual future growth projections
Timeframe-aware calculations (Daily/Weekly/Monthly charts)
1-30 year projection options
Shows projected portfolio value and total investment amounts
Investment Insights
Performance vs benchmark comparison
ROI from initial investment tracking
Monthly average return analysis
Investment milestone alerts (25%, 50%, 100% gains)
Contribution tracking and next milestone indicators
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📊 Step-by-Step Setup Guide
1. Investment Settings 💰
Initial Investment: Enter your starting lump sum (e.g., $60,000)
Monthly Contribution: Set your regular DCA amount (e.g., $500/month)
Return Calculation: Choose "Auto (Stock History)" for real data or "Manual" for fixed %
Historical Period: Select 3-20 years for auto calculations (default: 10 years)
Start Year: When you began investing (e.g., 2020)
Current Portfolio Value: Your actual portfolio worth today (e.g., $150,000)
2. Display Settings 📊
Table Sizes: Choose from Tiny, Small, Normal, Large, or Huge
Table Positions: 9 options - Top/Middle/Bottom + Left/Center/Right
Visibility Toggles: Show/hide Main Table and Stats Table independently
3. Future Projection 🔮
Enable Projections: Toggle on to see future growth visualization
Projection Years: Set 1-30 years ahead for analysis
Live Example - NASDAQ:META Analysis:
Settings shown: $60K initial + $500/month + Auto calculation + 10-year history + 2020 start + $150K current value
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🔬 Pine Script Code Examples
Core DCA Calculations:
// Calculate total invested over time
months_elapsed = (year - start_year) * 12 + month - 1
total_invested = initial_investment + (monthly_contribution * months_elapsed)
// Compound growth formula for initial investment
theoretical_initial_growth = initial_investment * math.pow(1 + annual_return, years_elapsed)
// Future Value of Annuity for monthly contributions
monthly_rate = annual_return / 12
fv_contributions = monthly_contribution * ((math.pow(1 + monthly_rate, months_elapsed) - 1) / monthly_rate)
// Total expected value
theoretical_total = theoretical_initial_growth + fv_contributions
Volatility Detection Logic:
// Detect extreme years for volatility adjustment
extreme_years = 0
for i = 1 to historical_years
yearly_return = ((price_current / price_i_years_ago) - 1) * 100
if yearly_return > 100 or yearly_return < -50
extreme_years += 1
// Use median approach for high volatility stocks
high_volatility = (extreme_years / historical_years) > 0.2
calculated_return = high_volatility ? median_of_returns : standard_cagr
Performance Metrics:
// Calculate key performance indicators
absolute_gain = actual_value - total_invested
total_return_pct = (absolute_gain / total_invested) * 100
roi_initial = ((actual_value - initial_investment) / initial_investment) * 100
cagr = (math.pow(actual_value / initial_investment, 1 / years_elapsed) - 1) * 100
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📊 Real-World Examples
See the indicator in action across different investment types:
Stable Index Investments:
AMEX:SPY (SPDR S&P 500) - Shows steady compound growth with standard CAGR calculations
Classic DCA success story: $60K initial + $500/month starting 2020. The indicator shows SPY's historical 10%+ returns, demonstrating how consistent broad market investing builds wealth over time. Notice the smooth theoretical growth line vs actual performance tracking.
MIL:VUAA (Vanguard S&P 500 UCITS) - Shows both data limitation and solution approaches
Data limitation example: VUAA shows "Manual (Auto Failed)" and "No Data" when default 10-year historical setting exceeds available data. The indicator gracefully falls back to manual percentage input while maintaining all DCA calculations and projections.
MIL:VUAA (Vanguard S&P 500 UCITS) - European ETF with successful 5-year auto calculation
Solution demonstration: By adjusting historical period to 5 years (matching available data), VUAA auto calculation works perfectly. Shows how users can optimize settings for newer assets. European market exposure with EUR denomination, demonstrating DCA effectiveness across different markets and currencies.
NYSE:BRK.B (Berkshire Hathaway) - Quality value investment with Warren Buffett's proven track record
Value investing approach: Berkshire Hathaway's legendary performance through DCA lens. The indicator demonstrates how quality companies compound wealth over decades. Lower volatility than tech stocks = standard CAGR calculations used.
High-Volatility Growth Stocks:
NASDAQ:NVDA (NVIDIA Corporation) - Demonstrates volatility-adjusted calculations for extreme price swings
High-volatility example: NVIDIA's explosive AI boom creates extreme years that trigger volatility detection. The indicator automatically switches to "Median (High Vol): 50%" calculations for conservative projections, protecting against unrealistic future estimates based on outlier performance periods.
NASDAQ:TSLA (Tesla) - Shows how 10-year analysis can stabilize volatile tech stocks
Stable long-term growth: Despite Tesla's reputation for volatility, the 10-year historical analysis (34.8% CAGR) shows consistent enough performance that volatility detection doesn't trigger. Demonstrates how longer timeframes can smooth out extreme periods for more reliable projections.
NASDAQ:META (Meta Platforms) - Shows stable tech stock analysis using standard CAGR calculations
Tech stock with stable growth: Despite being a tech stock and experiencing the 2022 crash, META's 10-year history shows consistent enough performance (23.98% CAGR) that volatility detection doesn't trigger. The indicator uses standard CAGR calculations, demonstrating how not all tech stocks require conservative median adjustments.
Notice how the indicator automatically detects high-volatility periods and switches to median-based calculations for more conservative projections, while stable investments use standard CAGR methods.
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📈 Performance Metrics Explained
Current Portfolio Value: Your actual investment worth today
Expected Value: What you should have based on historical returns (Auto) or your target return (Manual)
Total Invested: Your actual money invested (initial + all monthly contributions)
Total Gains/Loss: Absolute dollar difference between current value and total invested
Total Return %: Percentage gain/loss on your total invested amount
ROI from Initial Investment: How your starting lump sum has performed
CAGR: Compound Annual Growth Rate of your initial investment (Note: This shows initial investment performance, not full DCA strategy)
vs Benchmark: How you're performing compared to the expected returns
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⚠️ Important Notes & Limitations
Data Requirements: Auto mode requires sufficient historical data (minimum 3 years recommended)
CAGR Limitation: CAGR calculation is based on initial investment growth only, not the complete DCA strategy
Projection Accuracy: Future projections are theoretical and based on historical returns - actual results may vary
Timeframe Support: Works ONLY on Daily (1D), Weekly (1W), and Monthly (1M) charts - no other timeframes supported
Update Frequency: Update "Current Portfolio Value" regularly for accurate tracking
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📚 Educational Use & Disclaimer
This analysis tool can be applied to various stock and ETF charts for educational study of DCA mathematical concepts and historical performance patterns.
Study Examples: Can be used with symbols like AMEX:SPY , NASDAQ:QQQ , AMEX:VTI , NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:GOOGL , NASDAQ:AMZN , NASDAQ:TSLA , NASDAQ:NVDA for learning purposes.
EDUCATIONAL DISCLAIMER: This indicator is a study tool for analyzing Dollar-Cost Averaging strategies. It does not provide investment advice, trading signals, or guarantees. All calculations are theoretical examples for educational purposes only. Past performance does not predict future results. Users should conduct their own research and consult qualified financial professionals before making any investment decisions.
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© 2025 TradeVizion. All rights reserved.
Correlation MA – 15 Assets + Average (Optional)This indicator calculates the moving average of the correlation coefficient between your charted asset and up to 15 user-selected symbols. It helps identify uncorrelated or inversely correlated assets for diversification, pair trading, or hedging.
Features:
✅ Compare your current chart against up to 15 assets
✅ Toggle assets on/off individually
✅ Custom correlation and MA lengths
✅ Real-time average correlation line across enabled assets
✅ Horizontal lines at +1, 0, and -1 for easy visual reference
Ideal for:
Portfolio diversification analysis
Finding low-correlation stocks
Mean-reversion & pair trading setups
Crypto, equities, ETFs
To use: set the benchmark chart (e.g. TSLA), choose up to 15 assets, and adjust settings as needed. Look for assets with correlation near 0 or negative values for uncorrelated performance.
Risk Calculator PRO — manual lot size + auto lot-suggestionWhy risk management?
90 % of traders blow up because they size positions emotionally. This tool forces Risk-First Thinking: choose the amount you’re willing to lose, and the script reverse-engineers everything else.
Key features
1. Manual or Market Entry – click “Use current price” or type a custom entry.
2. Setup-based ₹-Risk – four presets (A/B/C/D). Edit to your workflow.
3. Lot-Size Input + Auto Lot Suggestion – you tell the contract size ⇒ script tells you how many lots.
4. Auto-SL (optional) – tick to push stop-loss to exactly 1-lot risk.
5. Instant Targets – 1 : 2, 1 : 3, 1 : 4, 1 : 5 plotted and alert-ready.
6. P&L Preview – table shows potential profit at each R-multiple plus real ₹ at SL.
7. Margin Column – enter per-lot margin once; script totals it for any size.
8. Clean Table UI – dark/light friendly; updates every 5 bars.
9. Alert Pack – SL, each target, plus copy-paste journal line on the chart.
How to use
1. Add to chart > “Format”.
2. Type the lot size for the symbol (e.g., 1250 for Natural Gas, 1 for cash equity).
3. Pick Side (Buy / Sell) & Setup grade.
4. ✅ If you want the script to place SL for you, tick Auto-SL (risk = 1 lot).
5. Otherwise type your own Stop-loss.
6. Read the table:
• Suggested lots = how many to trade so risk ≤ setup ₹.
• Risk (currency) = real money lost if SL hits.
7. Set TradingView alerts on the built-in conditions (T1_2, SL_hit, etc.) if you’d like push / email.
8. Copy the orange CSV label to Excel / Sheets for journalling.
Best practices
• Never raise risk to “fit” a trade. Lower size instead.
• Review win-rate vs. R multiple monthly; adjust setups A–D accordingly.
• Test Auto-SL in replay before going live.
Disclaimer
This script is educational. Past performance ≠ future results. The author isn’t responsible for trading losses.
