Tracking — Göstergeler ve Stratejiler

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. --- 💡 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. --- 🎯 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 --- 🚀 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 --- 📊 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 --- 🔬 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 --- 📊 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. --- 📈 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 --- ⚠️ 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 --- 📚 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. --- © 2025 TradeVizion. All rights reserved.

EntryPrice Gain&Loss Indicator This indicator takes (1) an entry price or average position price and (2) position size (denominator) to calculate current gain or loss and returns those as well as the position change in percent. It will also draw into the Chart and show relevant data in a table. It is mainly supposed to help tracking an (average) spot position easily. It is recommended to switch it to invisible when switching to other charts. You can also use several instances of the indicator to track your positions in different assets. Features: - table position and text size can be adjusted - colors can be changed (recommending 25% opacity for plot backgrounds) - several instances possible (recommended to tuen indicator invisible when switching to other charts or analyzing Version 1.0

lib_tracking Library "lib_tracking" tracking highest and lowest with anchor point to track over dynamic periods, e.g. to track a Session HH/LL live and get the bar/time of the LTF wick that matches the HTF HH/LL // DESIGN DECISION // why anchored replacements for ta.highest / ta.highestbars / ta.lowest / ta.lowestbars: // 1. they require a fixed length/lookback which makes it easier to calculate, but // 2. this prevents us from tracking the HH/LL of a changing timeframe, e.g. live tracking the HH/LL of a running session or unfinished higher timeframe // 3. tracking with anchor/start/reset flag allows to persist values until the next start/reset, so no other external storage is required track_highest(value, reset, track_this_bar) Parameters: value (float) reset (bool) : boolean flag to restart tracking from this point (a.k.a anchor) track_this_bar (bool) : allows enabling and disabling of tracking, e.g. before a session starts or after it ends, values can be kept until next reset. track_lowest(value, reset, track_this_bar) Parameters: value (float) reset (bool) : boolean flag to restart tracking from this point (a.k.a anchor) track_this_bar (bool) : allows enabling and disabling of tracking, e.g. before a session starts or after it ends, values can be kept until next reset. track_hl_htf(htf, value_high, value_low) Parameters: htf (string) : the higher timeframe in pinescript string notation value_high (float) value_low (float) Returns:

TradeTracker Library "TradeTracker" Simple Library for tracking trades method track(this) tracks trade when called on every bar Namespace types: Trade Parameters: this (Trade) : Trade object Returns: current Trade object Trade Has the constituents to track trades generated by any method. Fields: id (series int) direction (series int) : Trade direction. Positive values for long and negative values for short trades initialEntry (series float) : Initial entry price. This value will not change even if the entry is changed in the lifecycle of the trade entry (series float) : Updated entry price. Allows variations to initial calculated entry. Useful in cases of trailing entry. initialStop (series float) : Initial stop. Similar to initial entry, this is the first calculated stop for the lifecycle of trade. stop (series float) : Trailing Stop. If there is no trailing, the value will be same as that of initial trade targets (float ) : array of target values. startBar (series int) : bar index of starting bar. Set by default when object is created. No need to alter this after that. endBar (series int) : bar index of last bar in trade. Set by tracker on each execution startTime (series int) : time of the start bar. Set by default when object is created. No need to alter this after that. endTime (series int) : time of the ending bar. Updated by tracking method. status (series int) : Integer parameter to track the status of the trade retest (series bool) : Boolean parameter to notify if there was retest of the entry price

HarmonicPatternTracking Library "HarmonicPatternTracking" Library contains few data structures and methods for tracking harmonic pattern trades via pinescript. method draw(this) Creates and draws HarmonicDrawing object for given HarmonicPattern Namespace types: HarmonicPattern Parameters: this (HarmonicPattern) : HarmonicPattern object Returns: current HarmonicPattern object method addTrade(this) calculates HarmonicTrade and sets trade object for HarmonicPattern Namespace types: HarmonicPattern Parameters: this (HarmonicPattern) : HarmonicPattern object Returns: bool true if pattern trades are valid, false otherwise method delete(this) Deletes drawing objects of HarmonicDrawing Namespace types: HarmonicDrawing Parameters: this (HarmonicDrawing) : HarmonicDrawing object Returns: current HarmonicDrawing object method delete(this) Deletes drawings of harmonic pattern Namespace types: HarmonicPattern Parameters: this (HarmonicPattern) : HarmonicPattern object Returns: current HarmonicPattern object HarmonicDrawing Drawing objects of Harmonic Pattern Fields: xa (series line) : xa line ab (series line) : ab line bc (series line) : bc line cd (series line) : cd line xb (series line) : xb line bd (series line) : bd line ac (series line) : ac line xd (series line) : xd line x (series label) : label for pivot x a (series label) : label for pivot a b (series label) : label for pivot b c (series label) : label for pivot c d (series label) : label for pivot d xabRatio (series label) : label for XAB Ratio abcRatio (series label) : label for ABC Ratio bcdRatio (series label) : label for BCD Ratio xadRatio (series label) : label for XAD Ratio HarmonicTrade Trade tracking parameters of Harmonic Patterns Fields: initialEntry (series float) : initial entry when pattern first formed. entry (series float) : trailed entry price. initialStop (series float) : initial stop when trade first entered. stop (series float) : current stop updated as per trailing rules. target1 (series float) : First target value target2 (series float) : Second target value target3 (series float) : Third target value target4 (series float) : Fourth target value status (series int) : Trade status referenced as integer retouch (series bool) : Flag to show if the price retouched after entry HarmonicProperties Display and trade calculation properties for Harmonic Patterns Fields: fillMajorTriangles (series bool) : Display property used for using linefill for harmonic major triangles fillMinorTriangles (series bool) : Display property used for using linefill for harmonic minor triangles majorFillTransparency (series int) : transparency setting for major triangles minorFillTransparency (series int) : transparency setting for minor triangles showXABCD (series bool) : Display XABCD pivot labels lblSizePivots (series string) : Pivot label size showRatios (series bool) : Display Ratio labels useLogScaleForScan (series bool) : Use log scale to determine fib ratios for pattern scanning useLogScaleForTargets (series bool) : Use log scale to determine fib ratios for target calculation base (series string) : base on which calculation of stop/targets are made. entryRatio (series float) : fib ratio to calculate entry stopRatio (series float) : fib ratio to calculate initial stop target1Ratio (series float) : fib ratio to calculate first target target2Ratio (series float) : fib ratio to calculate second target target3Ratio (series float) : fib ratio to calculate third target target4Ratio (series float) : fib ratio to calculate fourth target HarmonicPattern Harmonic pattern object to track entire pattern trade life cycle Fields: id (series int) : Pattern Id dir (series int) : pattern direction x (series float) : X Pivot a (series float) : A Pivot b (series float) : B Pivot c (series float) : C Pivot d (series float) : D Pivot xBar (series int) : Bar index of X Pivot aBar (series int) : Bar index of A Pivot bBar (series int) : Bar index of B Pivot cBar (series int) : Bar index of C Pivot dBar (series int) : Bar index of D Pivot przStart (series float) : Start of PRZ range przEnd (series float) : End of PRZ range patterns (bool ) : array representing the patterns patternLabel (series string) : string representation of list of patterns patternColor (series color) : color assigned to pattern properties (HarmonicProperties) : HarmonicProperties object containing display and calculation properties trade (HarmonicTrade) : HarmonicTrade object to track trades drawing (HarmonicDrawing) : HarmonicDrawing object to manage drawings

Average Cost (Costo Promedio)ENGLISH This 'Average Cost' script allows the user to input and visualize profit or loss for different stocks (up to 50) with average cost and quantity data on a single chart. This is useful for tracking the profit or loss of each stock in real-time. To use this script, the user should follow these steps: 1. Add the 'Average Cost' script to your TradingView chart. 2. In the script's configuration window, input the tickers, average costs, and quantity of shares for each ticker you want to monitor. 3. Click 'Accept' to apply the changes. This script is primarily designed for stock markets, but can also be useful in other financial markets where the user is interested in tracking the performance of multiple assets. ESPAÑOL Este script de "Costo Promedio" permite al usuario ingresar y visualizar si hay ganancia o perdida para diferentes acciones (hasta 50) con los datos de costos promedio y cantidad de acciones en un solo gráfico. Esto es útil para realizar un seguimiento de la ganancia o pérdida de cada acción en tiempo real. Para utilizar este script, el usuario debe seguir estos pasos: 1. Agregue el script "Costo Promedio" a su gráfico en TradingView. 2. En la ventana de configuración del script, ingrese los tickers, costos promedio y cantidad de acciones para cada ticker que desee monitorear. 3. Haga clic en "Aceptar" para aplicar los cambios. Este script está diseñado principalmente para los mercados de acciones, pero también puede ser útil en otros mercados financieros donde el usuario esté interesado en rastrear el rendimiento de múltiples activos.