Ticker Pulse Meter BasicPairs nicely with the Contrarian 100 MA located here:
and the Enhanced Stock Ticker with 50MA vs 200MA located here:
Description
The Ticker Pulse Meter Basic is a dynamic Pine Script v6 indicator designed to provide traders with a visual representation of a stock’s price position relative to its short-term and long-term ranges, enabling clear entry and exit signals for long-only trading strategies. By calculating three normalized metrics—Percent Above Long & Above Short, Percent Above Long & Below Short, and Percent Below Long & Below Short—this indicator offers a unique "pulse" of market sentiment, plotted as stacked area charts in a separate pane. With customizable lookback periods, thresholds, and signal plotting options, it empowers traders to identify optimal entry points and profit-taking levels. The indicator leverages Pine Script’s force_overlay feature to plot signals on either the main price chart or the indicator pane, making it versatile for various trading styles.
Key Features
Pulse Meter Metrics:
Computes three percentages based on short-term (default: 50 bars) and long-term (default: 200 bars) lookback periods:
Percent Above Long & Above Short: Measures price strength when above both short and long ranges (green area).
Percent Above Long & Below Short: Indicates mixed momentum (orange area).
Percent Below Long & Below Short: Signals weakness when below both ranges (red area).
Flexible Signal Plotting:
Toggle between plotting entry (blue dots) and exit (white dots) signals on the main price chart (location.abovebar/belowbar) or in the indicator pane (location.top/bottom) using the Plot Signals on Main Chart option.
Entry/Exit Logic:
Long Entry: Triggered when Percent Above Long & Above Short crosses above the high threshold (default: 20%) and Percent Below Long & Below Short is below the low threshold (default: 40%).
Long Exit: Triggered when Percent Above Long & Above Short crosses above the profit-taking level (default: 95%).
Visual Enhancements:
Plots stacked area charts with semi-transparent colors (green, orange, red) for intuitive trend analysis.
Displays threshold lines for entry (high/low) and profit-taking levels.
Includes a ticker and timeframe table in the top-right corner for quick reference.
Alert Conditions: Supports alerts for long entry and exit signals, integrable with TradingView’s alert system for automated trading.
Technical Innovation: Combines normalized price metrics with Pine Script v6’s force_overlay for seamless signal integration on the price chart or indicator pane.
Technical Details
Calculation Logic:
Uses confirmed bars (barstate.isconfirmed) to calculate metrics, ensuring reliability.
Short-term percentage: (close - lowest(low, lookback_short)) / (highest(high, lookback_short) - lowest(low, lookback_short)).
Long-term percentage: (close - lowest(low, lookback_long)) / (highest(high, lookback_long) - lowest(low, lookback_long)).
Derived metrics:
pct_above_long_above_short = (pct_above_long * pct_above_short) * 100.
pct_above_long_below_short = (pct_above_long * (1 - pct_above_short)) * 100.
pct_below_long_below_short = ((1 - pct_above_long) * (1 - pct_above_short)) * 100.
Signal Plotting:
Entry signals (long_entry) use ta.crossover to detect when pct_above_long_above_short crosses above entryThresholdhigh and pct_below_long_below_short is below entryThresholdlow.
Exit signals (long_exit) use ta.crossover for pct_above_long_above_short crossing above profitTake.
Signals are plotted as tiny circles with force_overlay=true for main chart or standard plotting for the indicator pane.
Performance Considerations: Optimized for efficiency by calculating metrics only on confirmed bars and using lightweight plotting functions.
How to Use
Add to Chart:
Copy the script into TradingView’s Pine Editor and apply it to your chart.
Configure Settings:
Short Lookback Period: Adjust the short-term lookback (default: 50 bars) for sensitivity.
Long Lookback Period: Set the long-term lookback (default: 200 bars) for broader context.
Entry Thresholds: Modify high (default: 20%) and low (default: 40%) thresholds for entry conditions.
Profit Take Level: Set the exit threshold (default: 95%) for profit-taking.
Plot Signals on Main Chart: Check to display signals on the price chart; uncheck for the indicator pane.
Interpret Signals:
Long Entry: Blue dots indicate a strong bullish setup when price is high relative to both lookback ranges and weakness is low.
Long Exit: White dots signal profit-taking when strength reaches overbought levels.
Use the stacked area charts to assess trend strength and momentum.
Set Alerts:
Create alerts for Long Entry and Long Exit conditions using TradingView’s alert system.
Customize Visuals:
Adjust colors and thresholds via TradingView’s settings for better visibility.
The ticker table displays the symbol and timeframe in the top-right corner.
Example Use Cases
Swing Trading: Use entry signals to capture short-term bullish moves within a broader uptrend, exiting at profit-taking levels.
Trend Confirmation: Monitor the green area (Percent Above Long & Above Short) for sustained bullish momentum.
Market Sentiment Analysis: Use the stacked areas to gauge bullish vs. bearish sentiment across timeframes.
Notes
Testing: Backtest the indicator on your chosen market and timeframe to validate its effectiveness.
Compatibility: Built for Pine Script v6 and tested on TradingView as of June 20, 2025.
Limitations: Signals are long-only; adapt the script for short strategies if needed.
Enhancements: Consider adding a histogram for the difference between metrics or additional thresholds for nuanced trading.
Acknowledgments
Inspired by public Pine Script examples and designed to simplify complex market dynamics into a clear, actionable tool. For licensing or support, contact Chuck Schultz (@chuckaschultz) on TradingView. Share feedback in the comments, and happy trading!
DCA
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.
SmartScale Envelope DCA This is a Dollar-Cost Averaging (DCA) long strategy that buys when price dips below a moving average envelope and adds to the position in a stepwise, risk-controlled way. It uses up to 8 buy-ins, applies a cooldown between entries, and exits based on either a take profit from average entry price or a stop loss. Backtest range limits trades to the last 365 days for backtest control.
All input settings can and should be adjusted to the chart, as volatility in price action varies. Simply go into the inputs settings, and start from the top and move down to get better backtest results. Moving from the top down has been proven to give the best results. Then, move to properties and set your order size, pyramiding, and so on. It may be necessary to then fine tune your adjustments a second time to dial it in.
Works well on 1 hour time frames and in volatility.
Happy Trading!
DCA StrategyThis strategy makes it easy for you to backtest and automate the DCA strategy based on 2 triggers:
Day of the week
Every X candles
This way you can set up your DCA strategy the way you like and automate on any exchange or even a DEX, which offers an API.
The strategy is auto selling on the last candle, otherwise you won't see any performance numbers because all positions will still be open (non conclusive).
Settings
Start Date & End Date
Use those dates to help you with your backtest period. It also helps when automating, to start at a specific time to mimic what you have already done on your own portfolio and thus be in sync in TV as well.
Capital to invest per trade
Set how capital to use per DCA buy signal. Hover over the tooltip to understand, which currency is used.
Close All on last candle
When backtesting, you must close open positions, otherwise the Strategy Tester won't show you any numbers. This is why the strategy automatically closes all positions on the last candle for your convenience (ON per default).
BUT, when automating, you cannot have this checked because it would sell all of your asset on every candle open. So turn this OFF when automating.
Use Day of Week Mode
This checkbox switches between the "Day of Week" mode or the "Every X Candles" mode.
Day of Week
Opens a long position at the start of the weekday you have set it to.
Hover over the tooltip to understand, which number to use for the day of the week you need.
Every X Candles
Opens a long position after every x candles. Always at the start of every such candle.
On the daily chart, this number represents "1 day", on the 1h chart, it's "1 hour" and so on.
Properties
Initial Capital
DCA has a special quirk and that is that it invests more and more and more funds the longer it runs. But TradingView takes the Initial Capital number to calculate Net Profit, thus the Initial Capital number has to grow with every additional dollar (money) that is being invested over time, otherwise the Net Profit number will be wrong.
Sadly PineScript does not allow to set the Initial Capital number dynamically. So you have to set it manually.
To that end, this strategy shows a Label on the last candle, which shows the Invested Capital. You must take that number and put it into the Initial Capital input and click Ok .
If you don't do this, your Net Profit Number will be totally wrong!
The label must show green .
If it shows red it means you need to change the Initial Capital number before looking at the performance numbers.
After every timeframe or settings change, you must adapt the Initial Capital, otherwise you will get wrong numbers.
DCA Simulation for CryptoCommunity v1.1Overview
This script provides a detailed simulation of a Dollar-Cost Averaging (DCA) strategy tailored for crypto traders. It allows users to visualize how their DCA strategy would perform historically under specific parameters. The script is designed to help traders understand the mechanics of DCA and how it influences average price movement, budget utilization, and trade outcomes.
Key Features:
Combines Interval and Safety Order DCA:
Interval DCA: Regular purchases based on predefined time intervals.
Safety Order DCA: Additional buys triggered by percentage price drops.
Interactive Visualization:
Displays buy levels, average price, and profit-taking points on the chart.
Allows traders to assess how their strategy adapts to price movements.
Comprehensive Dashboard:
Tracks money spent, contracts acquired, and budget utilization.
Shows maximum amounts used if profit-taking is active.
Dynamic Safety Orders:
Resets safety orders when a new higher high is established.
Customizable Parameters:
Adjustable buy frequency, safety order settings, and profit-taking levels.
Suitable for traders with varying budgets and risk tolerances.
Default Strategy Settings:
Account Size: Default account size is set to $10,000 to represent a realistic budget for the average trader.
Commission & Slippage: Includes realistic trading fees and slippage assumptions to ensure accurate backtesting results.
Risk Management: Defaults to risking no more than 5% of the account balance per trade.
Sample Size: Optimized to generate a minimum of 100 trades for meaningful statistical analysis. Users can adjust parameters to fit longer timeframes or different datasets.
Usage Instructions:
Configure Your Strategy: Set the base order, safety order size, and buy frequency based on your preferred DCA approach.
Analyze Historical Performance: Use the chart and dashboard to understand how the strategy performs under different market conditions.
Optimize Parameters: Adjust settings to align with your risk tolerance and trading objectives.
Important Notes:
This script is for educational and simulation purposes. It is not intended to provide financial advice or guarantee profitability.
If the strategy's default settings do not meet your needs, feel free to adjust them while keeping risk management in mind.
TradingView limits the number of open trades to 999, so reduce the buy frequency if necessary to fit longer timeframes.
Relative Risk MetricOVERVIEW
The Relative Risk Metric is designed to provide a relative measure of an asset's price, within a specified range, over a log scale.
PURPOSE
Relative Position Assessment: Visualizes where the current price stands within a user-defined range, adjusted for log scale.
Logarithmic Transformation: Utilizes the natural log to account for a log scale of prices, offering a more accurate representation of relative positions.
Calculation: The indicator calculates a normalized value via the function Relative Price = / log(UpperBound) − log(LowerBound) . The result is a value between 0 and 1, where 0 corresponds to the lower bound and 1 corresponds to the upper bound on a log scale.
VISUALIZATION
The indicator plots three series:
Risk Metric - a plot of the risk metric value that’s computed from an asset's relative price so that it lies within a logarithmic range between 0.0 & 1.0.
Smoothed Risk Metric - a plot of the risk metric that’s been smoothed.
Entry/Exit - a scatter plot for identified entry and exit. Values are expressed as percent and are coded as red being exit and green being entity. E.g., a red dot at 0.02 implies exit 2% of the held asset. A green dot at 0.01 implies use 1% of a designated capital reserve.
USAGE
Risk Metric
The risk metric transformation function has several parameters. These control aspects such as decay, sensitivity, bounds and time offset.
Decay - Acts as an exponent multiplier and controls how quickly dynamic bounds change as a function of the bar_index.
Time Offset - provides a centering effect of the exponential transformation relative to the current bar_index.
Sensitivity - controls how sensitive to time the dynamic bound adjustments should be.
Baseline control - Serves as an additive offset for dynamic bounds computation which ensures that bounds never become too small or negative.
UpperBound - provides headroom to accomodate growth an assets price from the baseline. For example, an upperbound of 3.5 accommodates a 3.5x growth from the baseline value (e.g., $100 -> $350).
LowerBound - provides log scale compression such that the overall metric provides meaningful insights for prices well below the average whilst avoiding extreme scaling. A lowerbound of 0.25 corresponds to a price that is approx one quarter of a normalised baseline in a log context.
Weighted Entry/Exit
This feature provides a weighted system for identifying DCA entry and exit. This weighting mechanism adjusts the metric's interpretation to highlight conditions based on dynamic thresholds and user-defined parameters to identify high-probability zones for entry/exit actions and provide risk-adjusted insights.
Weighting Parameters
The weighting function supports fine-tuning of the computed weighted entry/exit values
Base: determines the foundational multiplier for weighting the entry/exit value. A higher base amplifies the weighting effect, making the weighted values more pronounced. It acts as a scaling factor to control the overall magnitude of the weighting.
Exponent: adjusts the curve of the weighting function. Higher exponent values increase sensitivity, emphasizing differences between risk metric values near the entry or exit thresholds. This creates a steeper gradient for the computed entry/exit value making it more responsive to subtle shifts in risk levels.
Cut Off: specifies the maximum percentage (expressed as a fraction of 1.0) that the weighted entry/exit value can reach. This cap ensures the metric remains within a meaningful range and avoids skewing
Exit condition: Defines a threshold for exit. When the risk metric is below the exit threshold (but above the entry threshold) then entry/exit is neutral.
Entry condition: Defines a threshold for entry. When the risk metric is above the entry threshold (but below the exit threshold) then entry/exit is neutral.
Weighting Behaviour
For entry conditions - value is more heavily weighted as the metric approaches the entry threshold, emphasizing lower risk levels.
For exit conditions - value is more heavily weighted as the metric nears the exit threshold, emphasizing increased risk levels.
USE-CASES
Identifying potential overbought or oversold conditions within the specified logarithmic range.
Assisting in assessing how the current price compares to historical price levels on a logarithmic scale.
Guiding decision-making processes by providing insights into the relative positioning of prices within a log context
CONSIDERATIONS
Validation: It's recommended that backtesting over historical data be done before acting on any identified entry/exit values.
User Discretion: This indicator focus on price risk. Consider other risk factors and general market conditions as well.
00 Averaging Down Backtest Strategy by RPAlawyer v21FOR EDUCATIONAL PURPOSES ONLY! THE CODE IS NOT YET FULLY DEVELOPED, BUT IT CAN PROVIDE INTERESTING DATA AND INSIGHTS IN ITS CURRENT STATE.
This strategy is an 'averaging down' backtester strategy. The goal of averaging/doubling down is to buy more of an asset at a lower price to reduce your average entry price.
This backtester code proves why you shouldn't do averaging down, but the code can be developed (and will be developed) further, and there might be settings even in its current form that prove that averaging down can be done effectively.
Different averaging down strategies exist:
- Linear/Fixed Amount: buy $1000 every time price drops 5%
- Grid Trading: Placing orders at price levels, often with increasing size, like $1000 at -5%, $2000 at -10%
- Martingale: doubling the position size with each new entry
- Reverse Martingale: decreasing position size as price falls: $4000, then $2000, then $1000
- Percentage-Based: position size based on % of remaining capital, like 10% of available funds at each level
- Dynamic/Adaptive: larger entries during high volatility, smaller during low
- Logarithmic: position sizes increase logarithmically as price drops
Unlike the above average costing strategies, it applies averaging down (I use DCA as a synonym) at a very strong trend reversal. So not at a certain predetermined percentage negative PNL % but at a trend reversal signaled by an indicator - hence it most closely resembles a dynamically moving grid DCA strategy.
Both entering the trade and averaging down assume a strong trend. The signals for trend detection are provided by an indicator that I published under the name '00 Parabolic SAR Trend Following Signals by RPAlawyer', but any indicator that generates numeric signals of 1 and -1 for buy and sell signals can be used.
The indicator must be connected to the strategy: in the strategy settings under 'External Source' you need to select '00 Parabolic SAR Trend Following Signals by RPAlawyer: Connector'. From this point, the strategy detects when the indicator generates buy and sell signals.
The strategy considers a strong trend when a buy signal appears above a very conservative ATR band, or a sell signal below the ATR band. The conservative ATR is chosen to filter ranging markets. This very conservative ATR setting has a default multiplier of 8 and length of 40. The multiplier can be increased up to 10, but there will be very few buy and sell signals at that level and DCA requirements will be very high. Trade entry and DCA occur at these strong trends. In the settings, the 'ATR Filter' setting determines the entry condition (e.g., ATR Filter multiplier of 9), and the 'DCA ATR' determines when DCA will happen (e.g., DCA ATR multiplier of 6).
The DCA levels and DCA amounts are determined as follows:
The first DCA occurs below the DCA Base Deviation% level (see settings, default 3%) which acts as a threshold. The thick green line indicates the long position avg price, and the thin red line below the green line indicates the 3% DCA threshold for long positions. The thick red line indicates the short position avg price, and the thin red line above the thick red line indicates the short position 3% DCA threshold. DCA size multiplier defines the DCA amount invested.
If the loss exceeds 3% AND a buy signal arrives below the lower ATR band for longs, or a sell signal arrives above the upper ATR band for shorts, then the first DCA will be executed. So the first DCA won't happen at 3%, rather 3% is a threshold where the additional condition is that the price must close above or below the ATR band (let's say the first DCA occured at 8%) – this is why the code resembles a dynamic grid strategy, where the grid moves such that alongside the first 3% threshold, a strong trend must also appear for DCA. At this point, the thick green/red line moves because the avg price is modified as a result of the DCA, and the thin red line indicating the next DCA level also moves. The next DCA level is determined by the first DCA level, meaning modified avg price plus an additional +8% + (3% * the Step Scale Multiplier in the settings). This next DCA level will be indicated by the modified thin red line, and the price must break through this level and again break through the ATR band for the second DCA to occur.
Since all this wasn't complicated enough, and I was always obsessed by the idea that when we're sitting in an underwater position for days, doing DCA and waiting for the price to correct, we can actually enter a short position on the other side, on which we can realize profit (if the broker allows taking hedge positions, Binance allows this in Europe).
This opposite position in this strategy can open from the point AFTER THE FIRST DCA OF THE BASE POSITION OCCURS. This base position first DCA actually indicates that the price has already moved against us significantly so time to earn some money on the other side. Breaking through the ATR band is also a condition for entry here, so the hedge position entry is not automatic, and the condition for further DCA is breaking through the DCA Base Deviation (default 3%) and breaking through the ATR band. So for the 'hedge' or rather opposite position, the entry and further DCA conditions are the same as for the base position. The hedge position avg price is indicated by a thick black line and the Next Hedge DCA Level is indicated by a thin black line.
The TPs are indicated by green labels for base positions and red labels for hedge positions.
No SL built into the strategy at this point but you are free to do your coding.
Summary data can be found in the upper right corner.
The fantastic trend reversal indicator Machine learning: Lorentzian Classification by jdehorty can be used as an external indicator, choose 'backtest stream' for the external source. The ATR Band multiplicators need to be reduced to 5-6 when using Lorentz.
The code can be further developed in several aspects, and as I write this, I already have a few ideas 😊
DCA Valuation & Unrealized GainsThis Pine Script for TradingView calculates and visualizes the relationship between a Dollar Cost Average (DCA) price and the All-Time High (ATH) price for over 50 different cryptocurrencies. Here's what it does:
1. Inputs for DCA Prices:
- Users can manually input DCA prices for specific cryptocurrencies (e.g., BTC, ETH, BNB).
2. Dynamic ATH Calculation:
- Dynamically calculates the ATH price for the current asset using the highest price in the chart's loaded data and persists this value across bars.
3. Percentage Change from DCA to ATH:
- Computes the percentage gain from the DCA price to the ATH price.
4. Visualizations:
- Draws a line at the DCA price and the ATH price, both extended to the right.
- Adds an arrow pointing from the DCA price to the ATH, offset by 10 bars into the future.
- Displays labels for:
- The percentage gain from DCA to ATH.
- "No DCA Configured" if no valid DCA price is set for the asset.
5. Color Coding:
- Labels and arrows are color-coded to indicate positive or negative percentage changes:
- Green for gains.
- Red for losses.
6. Adaptability:
- The script dynamically adjusts to the current asset based on its ticker and uses the corresponding DCA price.
This functionality provides traders with clear insights into their investment's performance relative to its ATH, aiding in decision-making.
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To add a new asset to the script:
1. Define the DCA Input: Add a new input for the asset's DCA price using the `input.float` function. For example:
dcaPriceNEW = input.float(title="NEW DCA Price", defval=0.1, tooltip="Set the DCA price for NEW")
2. Add the Asset Logic: Include a conditional check for the new asset in the ticker matching logic:
if str.contains(currentAsset, "NEW") and dcaPriceNEW != 0
dcaPrice := dcaPriceNEW
Where NEW is the ticker symbol of the asset you're adding.
NOTE: SOLO had to be put before SOL because otherwise the indicator was pulling the DCA price from SOL even on the SOLO chart. If you have a similar issue, try that fix.
Adding an asset requires only these two changes. Once done, the script dynamically incorporates the new asset into its calculations and visualizations.
Dollar Cost Averaging (YavuzAkbay)The Dollar Cost Averaging (DCA) indicator is designed to support long-term investors following a Dollar Cost Averaging strategy. The core aim of this tool is to provide insights into overbought and oversold levels, assisting investors in managing buy and sell decisions with a clear visual cue system. Specifically developed for use in trending or fluctuating markets, this indicator leverages support and resistance levels to give structure to investors' buying strategies. Here’s a detailed breakdown of the indicator’s key features and intended usage:
Key Features and Color Coding
Overbought/Oversold Detection:
The indicator shades candles from light green to dark green when an asset becomes increasingly overbought. Dark green signals indicate a peak, where the asset is overbought, suggesting a potential opportunity to take partial profits.
Conversely, candles turn from light red to dark red when the market is oversold. Dark red signifies a heavily oversold condition, marking an ideal buying window for initiating or adding to a position. This color scheme provides a quick visual reference for investors to manage entries and exits effectively.
Support and Resistance Levels:
To address the risk of assets falling further after an overbought signal, the DCA indicator dynamically calculates support and resistance levels. These levels guide investors on key price areas to watch for potential price reversals, allowing them to make more informed buying or selling decisions.
Support levels help investors assess whether they should divide their capital across multiple buy orders, starting at the current oversold zone and extending to anticipated support zones for maximum flexibility.
Usage Methodology
This indicator is intended for Dollar Cost Averaging, a method where investors gradually add to their position rather than entering all at once. Here’s how it complements the DCA approach:
Buy at Oversold Levels: When the indicator shows a dark red candle, it signals that the asset is oversold, marking an optimal entry point. The presence of support levels can help investors determine if they should fully invest their intended amount or stagger buys at potential lower levels.
Sell at Overbought Levels: When the indicator transitions to dark green, it suggests that the asset is overbought. This is an ideal time to consider selling a portion of holdings to realize gains. The resistance levels, marked by the indicator, offer guidance on where the price may encounter selling pressure, aiding investors in planning partial exits.
Customizable Settings
The DCA indicator offers several user-adjustable parameters:
Pivot Frequency and Source: Define the pivot point frequency and the source (candle wick or body) for more tailored support/resistance detection.
Maximum Pivot Points: Set the maximum number of pivot points to be used in support/resistance calculations, providing flexibility in adapting to different market structures.
Channel Width and Line Width: Adjust the width of the channel for support/resistance levels and the thickness of the lines for easier visual tracking.
Color Intensities for Overbought/Oversold Levels: Customize the shading intensity for each overbought and oversold level to align with your trading preferences.
Wolf DCA CalculatorThe Wolf DCA Calculator is a powerful and flexible indicator tailored for traders employing the Dollar Cost Averaging (DCA) strategy. This tool is invaluable for planning and visualizing multiple entry points for both long and short positions. It also provides a comprehensive analysis of potential profit and loss based on user-defined parameters, including leverage.
Features
Entry Price: Define the initial entry price for your trade.
Total Lot Size: Specify the total number of lots you intend to trade.
Percentage Difference: Set the fixed percentage difference between each DCA point.
Long Position: Toggle to switch between long and short positions.
Stop Loss Price: Set the price level at which you plan to exit the trade to minimize losses.
Take Profit Price: Set the price level at which you plan to exit the trade to secure profits.
Leverage: Apply leverage to your trade, which multiplies the potential profit and loss.
Number of DCA Points: Specify the number of DCA points to strategically plan your entries.
How to Use
1. Add the Indicator to Your Chart:
Search for "Wolf DCA Calculator" in the TradingView public library and add it to your chart.
2. Configure Inputs:
Entry Price: Set your initial trade entry price.
Total Lot Size: Enter the total number of lots you plan to trade.
Percentage Difference: Adjust this to set the interval between each DCA point.
Long Position: Use this toggle to choose between a long or short position.
Stop Loss Price: Input the price level at which you plan to exit the trade to minimize losses.
Take Profit Price: Input the price level at which you plan to exit the trade to secure profits.
Leverage: Set the leverage you are using for the trade.
Number of DCA Points: Specify the number of DCA points to plan your entries.
3. Analyze the Chart:
The indicator plots the DCA points on the chart using a stepline style for clear visualization.
It calculates the average entry point and displays the potential profit and loss based on the specified leverage.
Labels are added for each DCA point, showing the entry price and the lots allocated.
Horizontal lines mark the Stop Loss and Take Profit levels, with corresponding labels showing potential loss and profit.
Benefits
Visual Planning: Easily visualize multiple entry points and understand how they affect your average entry price.
Risk Management: Clearly see your Stop Loss and Take Profit levels and their impact on your trade.
Customizable: Adapt the indicator to your specific strategy with a wide range of customizable parameters.
TTP Intelligent AccumulatorThe intelligent accumulator is a proof of concept strategy. A hybrid between a recurring buy and TA-based entries and exits.
Distribute the amount of equity and add to your position as long as the TA condition is valid.
Use the exit TA condition to define your exit strategy.
Decide between adding only into losing positions to average down or take a riskier approach by allowing to add into a winning position as well.
Take full profit or distribute your exit into multiple take profit exists of the same size.
You can also decide if you allow your exit conditions to close your position in a loss or require a minimum take profit %.
The strategy includes a default built-in TA conditions just for showcasing the idea but the final intent of this script is to delegate the TA entries and exists to external sources.
The internal conditions use RSI length 7 crossing below the BB with std 1 for entries and above for exits.
To control the number of orders use the properties from settings:
- adjust the pyramiding
- adjust the percentage of equity
- make sure that pyramiding * % equity equals 100 to prevent over use of equity (unless using leverage)
The script is designed as an alternative to daily or weekly recurring buys but depending on the accuracy of your TA conditions it might prove profitable also in lower timeframes.
The reason the script is named Intelligent is because recurring buy is most commonly used without any decision making: buy no matter what with certain frequency. This strategy seeks to still perform recurring buys but filtering out some of the potential bad entries that can delay unnecessarily seeing the position in profits. The second reason is also securing an exit strategy from the beginning which no recurring buy option offers out-of-the-box.
Grospector DCA V.4This is system for DCA with strategy and can trade on trend technique "CDC Action Zone".
We upgrade Grospector DCA V.3 by minimizing unnecessary components and it is not error price predictions.
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Idea : Everything has average in its life. For bitcoin use 4 years for halving. I think it will be interesting price.
Default : I set MA is 365*4 days and average it again with 365 days.
Input :
len: This input represents the length of the moving average.
strongLen: This input represents the length of the moving average used to calculate the strong buy and strong sell zone.
shortMulti: This input represents the multiplier * moveing average used to calculate the short zone.
strongSellMulti: This input represents the multiplier used to calculate the strong sell signal.
sellMulti: This input represents the multiplier * moveing average used to calculate the sell zone.
strongBuyMulti: This input represents the multiplier used to calculate the strong sell signal.
longMulti: This input represents the multiplier * moveing average used to calculate the long zone.
*Diff sellMulti and strongBuyMulti which is normal zone.
useDerivative: This input is a boolean flag that determines whether to use the derivative display zone. If set to true, the derivative display zone will be used, otherwise it will be hidden.
zoneSwitch: This input determines where to display the channel signals. A value of 1 will display the signals in all zones, a value of 2 will display the signals in the chart pane, a value of 3 will display the signals in the data window, and a value of 4 will hide the signals.
price: Defines the price source used for the indicator calculations. The user can select from various options, with the default being the closing price.
labelSwitch: Defines whether to display assistive text on the chart. The user can select a boolean value (true/false), with the default being true.
zoneSwitch: Defines which areas of the chart to display assistive zones. The user can select from four options: 1 = all, 2 = chart only, 3 = data only, 4 = none. The default value is 2.
predictFuturePrice: Defines whether to display predicted future prices on the chart. The user can select a boolean value (true/false), with the default being true.
DCA: Defines the dollar amount to use for dollar-cost averaging (DCA) trades. The user can input an integer value, with a default value of 5.
WaitingDCA: Defines the amount of time to wait before executing a DCA trade. The user can input a float value, with a default value of 0.
Invested: Defines the amount of money invested in the asset. The user can input an integer value, with a default value of 0.
strategySwitch: Defines whether to turn on the trading strategy. The user can select a boolean value (true/false), with the default being true.
seperateDayOfMonth: Defines a specific day of the month on which to execute trades. The user can input an integer value from 1-31, with the default being 28.
useReserve: Defines whether to use a reserve amount for trading. The user can select a boolean value (true/false), with the default being true.
useDerivative: Defines whether to use derivative data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
useHalving: Defines whether to use halving data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
extendHalfOfHalving: Defines the amount of time to extend the halving date. The user can input an integer value, with the default being 200.
Every Zone: It calculate percent from top to bottom which every zone will be splited 10 step.
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
Greedy DCA█ OVERVIEW
Detect price crashes in volatile conditions. This is an indicator for a greedy dollar cost average (DCA) strategy. That is, for people who want to repeatedly buy an asset over time when its price is crashing.
█ CONCEPTS
Price crashes are indicated if the price falls below one or more of the 4 lower Bollinger Bands which are calculated with increasing multipliers for the standard deviation.
In these conditions, the price is far below the average. Therefore they are considered good buying opportunities.
No buy signals are emitted if the Bollinger Bands are tight, i.e. if the bandwidth (upper -lower band) is below the value of the moving average multiplied with a threshold factor. This ensures that signals are only emitted if the conditions are highly volatile.
The Bollinger Bands are calculated based on the daily candles, irrespective the chart time frame. This allows to check the strategy on lower time frames
DCA Liquidation Calculation [ChartPrime]The DCA Liquidation Calculator is a powerful table indicator designed for both manual and bot-assisted traders who practice Dollar Cost Averaging (DCA). Its primary objective is to help traders avoid getting liquidated and make informed decisions when managing their positions. This comprehensive table indicator provides essential information to DCA traders, enabling them to plan their trades effectively and mitigate potential risks of liquidation.
Key Features:
Liquidation Price Awareness: The DCA Liquidation Calculator calculates and displays the liquidation price for each trade within your position. This critical information empowers traders to set appropriate stop-loss levels and avoid being liquidated in adverse market conditions, especially in leveraged trading scenarios.
DCA Recommendations: Whether you are executing DCA manually or using a trading bot, the DCA Liquidation Calculator offers valuable guidance. It suggests optimal entry prices and provides insights into the percentage deviation from the current market price, helping traders make well-timed and well-informed DCA decisions.
Position Sizing: Proper position sizing is essential for risk management. The DCA Liquidation Calculator helps traders determine the percentage of capital to allocate to each trade based on the provided insights. By using the recommended position sizing, traders can protect their capital and potentially maximize profits.
Profit and Loss Visualization: Gain real-time visibility into your Profit and Loss (PnL) with the DCA Liquidation Calculator. This feature allows you to monitor your trades' performance, enabling you to adapt your strategies as needed and make data-driven decisions.
Margin Call Indicators: Anticipating potential margin calls is crucial for maintaining a healthy trading account. The DCA Liquidation Calculator's smart analysis helps you identify and manage potential margin call situations, reducing the risk of account liquidation.
Capital Requirements: Before entering a trade, it's vital to know the required capital. The DCA Liquidation Calculator provides you with this information, ensuring you are adequately prepared to execute your trades without overextending your resources.
Maximum Trade Limit: Considering your available capital, the DCA Liquidation Calculator helps you determine the maximum number of trades you can enter. This feature ensures you maintain a disciplined and sustainable trading approach aligned with your financial capabilities.
Color-Coded Risk Indicators:
Green Liquidation Price Cell: Indicates that the position is considered safe from liquidation at the given parameters.
Yellow Liquidation Price Cell: Warns traders of potential liquidation risk. Exercise caution and monitor the trade closely to avoid undesirable outcomes.
Purple Liquidation Price Cell: Shows the liquidation price, but it does not necessarily indicate an imminent liquidation. Use this information to make prudent risk management decisions.
Red Row: Signals that the trade cannot be executed due to insufficient capital. Consider alternative strategies or ensure adequate capitalization before proceeding.
Settings explained:
In conclusion, the DCA Liquidation Calculator equips traders with essential tools to make well-calculated decisions, minimize liquidation risks, and optimize their Dollar Cost Averaging strategy. By offering comprehensive insights into your trading position, this indicator empowers you to navigate the markets with confidence and increase your potential for successful and sustainable trading.
GDCA ScreenerThis is upgrated system for Screener to DCA from "Grospector DCA V.3".
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Price Type: Allows the user to select the price type (open, high, low, close) for calculations.
ALL SET
Length MA for normal zone: The length of the moving average used in the normal zone.
Length for strong zone: The length of the moving average used in the strong zone, which is averaged from the normal zone moving average.
Multiple for Short: The multiplication factor applied to determine the threshold for the short zone.
Multiple for Strong Sell: The multiplication factor applied to determine the threshold for the strong sell zone.
Multiple for Sell Zone: The multiplication factor applied to determine the threshold for the sell zone.
Multiple for Buy Zone: The multiplication factor applied to determine the threshold for the buy zone.
Multiple for Strong Buy: The multiplication factor applied to determine the threshold for the strong buy zone.
Multiple for Long: The multiplication factor applied to determine the threshold for the long zone.
ZONE
Start Short Zone %: The start percentage of the short zone.
End Short Zone %: The end percentage of the short zone.
Start Sell Zone %: The start percentage of the sell zone.
End Sell Zone %: The end percentage of the sell zone.
Start Normal Zone %: The start percentage of the normal zone.
End Normal Zone %: The end percentage of the normal zone.
Start Buy Zone %: The start percentage of the buy zone.
End Buy Zone %: The end percentage of the buy zone.
Start Long Zone %: The start percentage of the long zone.
End Long Zone %: The end percentage of the long zone.
DISPLAY
Show Price: Controls the visibility of the price column in the display table.
Show Mode: Controls the visibility of the mode column in the display table.
Show GDCA: Controls the visibility of the GDCA column in the display table.
Show %: Controls the visibility of the percentage column in the display table.
Show Short: Controls the visibility of the short column in the display table.
Show Strong Sell: Controls the visibility of the strong sell column in the display table.
Show Sell: Controls the visibility of the sell column in the display table.
Show Buy: Controls the visibility of the buy column in the display table.
Show Strong Buy: Controls the visibility of the strong buy column in the display table.
Show Long: Controls the visibility of the long column in the display table.
Show Suggestion Trend: Controls the visibility of the suggestion trend column in the display table.
Show Manual Custom Code: Controls the visibility of the manual custom code column in the display table.
Show Dynamic Trend: Controls the visibility of the dynamic trend column in the display table.
Symbols: Boolean parameters that control the visibility of individual symbols in the display table.
Mode: Integer parameters that determine the mode for each symbol, specifying different settings or trends.
My mindset has been customed = AAPL , MSFT
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
Mizar_LibraryThe "Mizar_Library" is a powerful tool designed for Pine Script™ programmer’s, providing a collection of general functions that facilitate the usage of Mizar’s DCA (Dollar-Cost-Averaging) bot system.
To begin using the Mizar Library, you first need to import it into your indicator script. Insert the following line below your indicator initiation line: import Mizar_Trading/Mizar_Library/1 as mizar (mizar is the chosen alias).
In the import statement, Mizar_Trading.Mizar_Library_v1 refers to the specific version of the Mizar Library you wish to use. Feel free to modify mizar to your preferred alias name.
Once the library is imported, you can leverage its functions by prefixing them with mizar. . This will prompt auto-completion suggestions displaying all the available user-defined functions provided by the Mizar Library.
Now, let's delve into some of the key functions available in the Mizar Library:
DCA_bot_msg(_cmd)
The DCA_bot_msg function accepts an user-defined type (UDT) _cmd as a parameter and returns a string with the complete JSON command for a Mizar DCA bot.
Parameters:
_cmd (bot_params) : ::: User-defined type (UDT) that holds all the necessary information for the bot command.
Returns: A string with the complete JSON command for a Mizar DCA bot.
rounding_to_ticks(value, ticks, rounding_type)
The rounding_to_ticks function rounds a calculated price to the nearest actual price based on the specified tick size.
Parameters:
value (float) : ::: The calculated price as float type, to be rounded to the nearest real price.
ticks (float) : ::: The smallest possible price obtained through a request in your script.
rounding_type (int) : ::: The rounding type for the price: 0 = closest real price, 1 = closest real price above, 2 = closest real price below.
Returns: A float value representing the rounded price to the next tick.
bot_params
Bot_params is an user-defined type (UDT) that represents the parameters required for a Mizar DCA bot.
Fields:
bot_id (series string) : The ID number of your Mizar DCA bot.
api_key (series string) : Your private API key from your Mizar account (keep it confidential!).
action (series string) : The command to perform: "open" (standard) or "close" optional .
tp_perc (series string) : The take profit percentage in decimal form (1% = "0.01") optional .
base_asset (series string) : The cryptocurrency you want to buy (e.g., "BTC").
quote_asset (series string) : The coin or fiat currency used for payment (e.g., "USDT" is standard if not specified) optional .
direction (series string) : The direction of the position: "long" or "short" (only applicable for two-way hedge bots) optional .
To obtain the JSON command string for the alert_function call, you can use the DCA_bot_msg function provided by the library. Simply pass the cmd_msg UDT as an argument and assign the returned string value to a variable.
Here's an example to illustrate the process:
// Import of the Mizar Library to use the included functions
import/Mizar_Trading/Mizar_Library/1 as mizar
// Example to set a variable called “cmd_msg” and all of its parameters
cmd_msg = mizar.bot_params. new()
cmd_msg.action := "open"
cmd_msg.api_key := "top secret"
cmd_msg.bot_id := "9999"
cmd_msg.base_asset := "BTC"
cmd_msg.quote_asset := "USDT"
cmd_msg.direction := "long"
cmd_msg.tp_perc := "0.015"
// Calling the Mizar conversion function named “DCA_bot_msg()” with the cmd_msg as argument to receive the JSON command and save it in a string variable called “alert_msg”
alert_msg = mizar.DCA_bot_msg(cmd_msg)
Feel free to utilize (series) string variables instead of constant strings. By incorporating the Mizar Library into your Pine Script, you gain access to a powerful set of functions and can leverage them according to your specific requirements.
For additional help or support, you can join the Mizar Discord channel. There, you'll find a dedicated Pine Script channel where you can ask any questions related to Pine Script.
Simple Dollar Cost AverageThis simple DCS indicator shows:
Invested Amount
Portfolio Value
Profit
Assets
Cost per Share
Fees
You can define:
Starting Investment
Investment per Cycle
Fee Ratio
Cycle Frequency
Start and End Date
Simple_RSI+PA+DCA StrategyThis strategy is a result of a study to understand better the workings of functions, for loops and the use of lines to visualize price levels. The strategy is a complete rewrite of the older RSI+PA+DCA Strategy with the goal to make it dynamic and to simplify the strategy settings to the bare minimum.
In case you are not familiar with the older RSI+PA+DCA Strategy, here is a short explanation of the idea behind the strategy:
The idea behind the strategy based on an RSI strategy of buying low. A position is entered when the RSI and moving average conditions are met. The position is closed when it reaches a specified take profit percentage. As soon as the first the position is opened multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price hits the layer another position with the same position size is is opened. This causes the average cost price (the white line) to decrease. If the price drops more, another position is opened with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches the specified take profit. The positions can be re-opened when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified Stop level (the red line) on top of it, it closes all the positions at once and cancels all orders. From that moment on it waits for another price dip before it opens a new position.
This is the old RSI+PA+DCA Strategy:
The reason to completely rewrite the code for this strategy is to create a more automated, adaptable and dynamic system. The old version is static and because of the linear use of code the amount of DCA levels were fixed to max 6 layers. If you want to add more DCA layers you manually need to change the script and add extra code. The big difference in the new version is that you can specify the amount of DCA layers in the strategy settings. The use of 'for loops' in the code gives the possibility to make this very dynamic and adaptable.
The RSI code is adapted, just like the old version, from the RSI Strategy - Buy The Dips by Coinrule and is used for study purpose. Any other low/dip finding indicator can be used as well
The distance between the DCA layers are calculated exponentially in a function. In the settings you can define the exponential scale to create the distance between the layers. The bigger the scale the bigger the distance. This calculation is not working perfectly yet and needs way more experimentation. Feel free to leave a comment if you have a better idea about this.
The idea behind generating DCA layers with a 'for loop' is inspired by the Backtesting 3commas DCA Bot v2 by rouxam .
The ideas for creating a dynamic position count and for opening and closing different positions separately based on a specified take profit are taken from the Simple_Pyramiding strategy I wrote previously.
This code is a result of a study and not intended for use as a full functioning strategy. To make the code understandable for users that are not so much introduced into pine script (like myself), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
DCA Simulator A simple yet powerful Dollar Cost Averaging (DCA) simulator.
You just add the script to your chart, and you'll be able to see:
- Every single entry with its size
- The evolution of you average price in time (blue line)
- The profit and loss areas (where market price < average price the DCA is at loss, and the background is colored in red. At the contrary, where mkt price is > average price, it's profit area and the background is green).
- Max drawdown: the point in price and time where the DCA loss is maximum in the considered time interval. The drawdown amount is specified.
- Profit (or loss) and total cost at the end of the time interval or at the present day: the script shows how much the DCA is netting at a profit or loss, as well as the total cost of the DCA itself.
The parameters are:
- Date start and date end: time interval of the DCA simulation
- DCA period (you can choose between daily, weekly and monthly)
- Week day or month day if you choose those periods
- Single operation size (in base currency)
- Option to choose a DCA LONG or DCA SHORT (for uber bears)
- Option to include an exit strategy that partially closes your position (the % size closed can be chosen as well with the parameter "exit_close_perc") every time the DCA realizes a specific gain (choosable with the parameter "exit_gain_threshold"). If you choose "none" as an exit strategy, the script will assume to never close positions until the end of the period or the present day for simulation purpose.
NB: just ignore the TV strategy tester results, all the data are visible on the chart.
Linear EDCA v1.2Strategy Description:
Linear EDCA (Linear Enhanced Dollar Cost Averaging) is an enhanced version of the DCA fixed investment strategy. It has the following features:
1. Take the 1100-day SMA as a reference indicator, enter the buy range below the moving average, and enter the sell range above the moving average
2. The order to buy and sell is carried out at different "speed", which are set with two linear functions, and you can change the slope of the linear function to achieve different trading position control purposes
3. This fixed investment is a low-frequency strategy and only works on a daily level cycle
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Strategy backtest performance:
BTCUSD (September 2014~September 2022): Net profit margin 26378%, maximum floating loss 47.12% (2015-01-14)
ETHUSD (August 2018~September 2022): Net profit margin 1669%, maximum floating loss 49.63% (2018-12-14)
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How the strategy works:
Buying Conditions:
The closing price of the day is below the 1100 SMA, and the ratio of buying positions is determined by the deviation of the closing price from the moving average and the buySlope parameter
Selling Conditions:
The closing price of the day is above the 1100 SMA, and the ratio of the selling position is determined by the deviation of the closing price and the moving average and the sellSlope parameter
special case:
When the sellOffset parameter>0, it will maintain a small buy within a certain range above the 1100 SMA to avoid prematurely starting to sell
The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
----------------
Version Information:
Current version v1.2 (the first officially released version)
v1.2 version setting parameter description:
defInvestRatio: The default fixed investment ratio, the strategy will calculate the position ratio of a single fixed investment based on this ratio and a linear function. The default 0.025 represents 2.5% of the position
buySlope: the slope of the linear function of the order to buy, used to control the position ratio of a single buy
sellSlope: the slope of the linear function of the order to sell, used to control the position ratio of a single sell
sellOffset: The offset of the order to sell. If it is greater than 0, it will keep a small buy within a certain range to avoid starting to sell too early
maxSellRate: Controls the maximum sell multiple. The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
maxBuyRate: Controls the maximum buy multiple. The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
maPeriod: the length of the moving average, 1100-day MA is used by default
smoothing: moving average smoothing algorithm, SMA is used by default
useDateFilter: Whether to specify a date range when backtesting
settleOnEnd: If useDateFilter==true, whether to close the position after the end date
startDate: If useDateFilter==true, specify the backtest start date
endDate: If useDateFilter==true, specify the end date of the backtest
investDayofweek: Invest on the day of the week, the default is to close on Monday
intervalDays: The minimum number of days between each invest. Since it is calculated on a weekly basis, this number must be 7 or a multiple of 7
The v1.2 version data window indicator description (only important indicators are listed):
MA: 1100-day SMA
RoR%: floating profit and loss of the current position
maxLoss%: The maximum floating loss of the position. Note that this floating loss represents the floating loss of the position, and does not represent the floating loss of the overall account. For example, the current position is 1%, the floating loss is 50%, the overall account floating loss is 0.5%, but the position floating loss is 50%
maxGain%: The maximum floating profit of the position. Note that this floating profit represents the floating profit of the position, and does not represent the floating profit of the overall account.
positionPercent%: position percentage
positionAvgPrice: position average holding cost
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策略说明：
Linear EDCA（Linear Enhanced Dollar Cost Averaging）是一个DCA定投策略的增强版本，它具有如下特性：
1. 以1100日SMA均线作为参考指标，在均线以下进入定买区间，在均线以上进入定卖区间
2. 定买和定卖以不同的“速率”进行，它们用两条线性函数设定，并且你可以通过改变线性函数的斜率，以达到不同的买卖仓位控制的目的
3. 本定投作为低频策略，只在日级别周期工作
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策略回测表现：
BTCUSD（2014年09月~2022年09月）：净利润率26378%，最大浮亏47.12%（2015-01-14）
ETHUSD（2018年08~2022年09月）：净利润率1669%，最大浮亏49.63%（2018-12-14）
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策略工作原理：
买入条件：
当日收盘价在 1100 SMA 之下，由收盘价和均线的偏离度，以及buySlope参数决定买入仓位比例
卖出条件：
当日收盘价在 1100 SMA之上，由收盘价和均线的偏离度，以及sellSlope参数决定卖出仓位比例
特例：
当sellOffset参数>0，则在 1100 SMA以上一定范围内还会保持小幅买入，避免过早开始卖出
单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
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版本信息：
当前版本v1.2（第一个正式发布的版本）
v1.2版本设置参数说明：
defInvestRatio: 默认定投比例，策略会根据此比例和线性函数计算得出单次定投的仓位比例。默认0.025代表2.5%仓位
buySlope: 定买的线性函数斜率，用来控制单次买入的仓位倍率
sellSlope: 定卖的线性函数斜率，用来控制单次卖出的仓位倍率
sellOffset: 定卖的偏移度，如果大于0，则在一定范围内还会保持小幅买入，避免过早开始卖出
maxSellRate: 控制最大卖出倍率。单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
maxBuyRate: 控制最大买入倍率。单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
maPeriod: 均线长度，默认使用1100日MA
smoothing: 均线平滑算法，默认使用SMA
useDateFilter: 回测时是否要指定日期范围
settleOnEnd: 如果useDateFilter==true，在结束日之后是否平仓所持有的仓位平仓
startDate: 如果useDateFilter==true，指定回测开始日期
endDate: 如果useDateFilter==true，指定回测结束日期
investDayofweek: 每次在周几定投，默认在每周一收盘
intervalDays: 每次定投之间的最小间隔天数，由于是按周计算，所以此数字必须是7或7的倍数
v1.2版本数据窗口指标说明（只列出重要指标）：
MA：1100日SMA
RoR%: 当前仓位的浮动盈亏
maxLoss%: 仓位曾经的最大浮动亏损，注意此浮亏代表持仓仓位的浮亏情况，并不代表整体账户浮亏情况。例如当前仓位是1%，浮亏50%，整体账户浮亏是0.5%，但仓位浮亏是50%
maxGain%: 仓位曾经的最大浮动盈利，注意此浮盈代表持仓仓位的浮盈情况，并不代表整体账户浮盈情况。
positionPercent%: 仓位持仓占比
positionAvgPrice: 仓位平均持仓成本
3Commas Bot DCA Backtester & Signals FREEThis is a DCA Strategy backtester + signals, built to emulate the 3Commas DCA bots. It uses your choice of 4 different buy signals, 2 of which can be adjusted in the settings. Everything is customizable so you can backtest specific settings with different buy signals and find the best performing strategy for your risk tolerance and capital. It can be used to backtest strategies on stocks as well, but just make sure your base order is larger than the share price for the entire backtesting range or it will not calculate properly.
You can use this template to code your own buy signals and then backtest them as a DCA strategy if you know some basic pine script.
The indicator shows all of your backtesting orders on the chart. The red line is your take profit level, the blue line is your average price level, the white line is your first order and the green lines are your average down orders. If you enable a stop loss in the settings your stop loss will be shown as an orange line once all of your average down orders have been hit, it will not be set until price has dipped below your covered trading range.
These levels update when things change during backtesting so you can visualize your strategy and how it would perform as well as see if your percentage deviation is large enough to cover dips. When backtesting trades are taken, the chart will show where they were taken(in backtesting) along with info on those trades such as the number each order is, the size of that order and the percentage deviation that order is from the initial buy.
SENDING SIGNALS TO 3COMMAS
Tradingview cannot sync this backtester to 3Commas and with the way alerts are setup for strategies on Tradingview, the best option for you to give signals to your bot would be to use this backtester to figure out what trigger you want to use and then setup that indicator separately to send alerts to your bot. All of the indicators used for signals in this backtester are available for free and can be configured to match this backtester and send alerts to 3Commas for you. Just make sure you set your alerts to once per bar close and don’t use less than a 15 second timeframe because then you could trigger the Tradingview threshold for alerts and get your alerts shut off.
You can also use this backtester with your own buy triggers if you know a little pine script. Just make copy of the script and code in your own buy signals and see how it backtests.
INFO PANEL FOR ANALYZING YOUR STRATEGY
The right hand side of the screen will show an info panel that shows a lot of different information so you can quickly see your bot settings and how it performed right on the screen.
In the top right corner you will see in purple your bot settings. These include your stoploss % if turned on, take profit %, average down order %, average down order % multiplier, volume multiplier, max number of orders allowed and size of your base order.
The top section of the first column “Current Trade” shows these stats: the open trade’s average price, the open trade’s take profit price, the open trade’s PNL, how far price is from your open tarde’s take profit level in percentage, your open position size and number of open orders.
The bottom section of the first column “Overall Performance” shows these stats: total number of trades taken during backtesting range, the largest amount of trades that were open at one time during backtesting, the max drawdown, the average number of bars per trade, gross profit, net profit, percent profit from your initial capital, current portfolio value and your initial capital.
CUSTOMIZABLE OPTIONS TO FIND THE PERFECT STRATEGY
Stoploss On/Off
This will turn your stoploss on or off. By default it is set to off and will not affect anything unless turned on.
Stoploss Percentage
This is the percentage below your final average down order price that will be set as a stoploss to keep your account from going too far in the red on big dips.
Take Profit Percentage - This is the percentage of profit you want the trade to hit before taking profit on your entire DCA trade. This level updates everytime you average down.
Average Down Percentage - This is the percentage that price has to drop from your initial order to initiate your first safety order. If the Average Down Percent Multiplier is set to 1 then this percentage will be the same for every average down order.
Average Down Percentage Multiplier - This multiplies your Average Down Percentage so each safety order needs a larger percentage deviation than the previous one. This keeps your buys closer together at the beginning and further apart when you hit more orders so you can extend your trading range but still be aggressive when price is going sideways.
Volume Multiplier Per New Order - This multiplies the size of each trade based on your base order. If you set it to a 2x multiplier then each average down order will be 2 times the size of the last one. So for example, a $100 base order with a 2x multiplier would have these values for the first 3 average down orders: 200, 400, 800.
Size Of Base Order - This is the size of your first position entry and will be used as a starting point for the volume multiplier. If your base order is $100 then it will buy $100 worth of whatever crypto you are backtesting this on. If you are looking at stock charts, you need to make sure your base order is higher than the share price across the entire backtesting range or it will not perform correctly.
Max Number Of Orders - This is the maximum number of orders the bot can take, including your base order. Adjust this to suit the amount of capital you are willing to allocate to your bot based on how much money it will require to run according to your bot settings.
TIPS ON HOW TO USE FOR BEST RESULTS
If you don’t have a lot of capital to work with, then use longer timeframes with a reasonable take profit percentage so that you don’t need a lot of average down orders. You can also try keeping the volume multiplier close to 1.
You can use the 3Commas dca bot settings page to see how much capital you will need for your strategy if you match it to the settings you have on this indicator. You can also check to see how much of a percentage deviation your bot is covering to make sure you have a reasonable range to trade in and orders to cover big dips. You can also check your coverage by seeing how far down the chart the green lines cover, which are your average down orders.
Make sure the initial capital in the properties tab of the settings has enough to cover all of your orders otherwise you will get unrealistic backtesting results. Also, make sure you leave the order size in the properties tab on contracts so it calculates your trades correctly. The only settings you need to touch in the properties tab is the initial capital. Unless you are trading somewhere that has lower commission fees, then you can change that to match, but leave all the other settings as is for it to function properly.
Increasing the volume multiplier will make your average price and take profit target follow the price action a lot closer as price falls, but it can also lead to having very large orders very quickly once you get into the 1.5-3x multiple range. Try using a high volume multiplier with less safety orders and you will get better results, however you need to have money on the sidelines to add on major dips to keep your bot turning a profit. Be very careful with this as greed and impatience will hurt your overall performance. This bot is meant to make money with lots of small wins so don’t get greedy and make sure you have enough money to cover large dips. If you are being aggressive with your bot, then I recommend only using 25% or less of your portfolio to trade aggressively and then use the smart trade feature on 3commas to add chunks of funds to your trades when price dips below your last safety order. Or if you want it to run without any supervision, then use lower volume multipliers and have lots of safety orders that can cover entire bear markets and still keep buying lower.
It’s a good idea to have some capital on the sidelines that you can add in when price dips quickly. This will help lower your average price and allow your bot to get out in profit quicker. 3Commas bot has a smart trade feature that will allow you to track your average price when adding extra funds and it will automatically update your other orders which is very convenient. Look at the longer timeframes when price dips and only add chunks at major areas where price is very likely to bounce. Or you can be aggressive when trading and add to your position when price dips and is at a likely bounce zone to maximize profits.
Only trade coins that have a good amount of liquidity as the larger your orders get, the harder it will be to sell if there isn’t much liquidity. Also, beware of how large your first order is as it will usually be a market order and can move the market if there is not much liquidity.
Since this bot takes a lot of trades and performs best when taking small profits consistently, you will need to factor in exchange fees. The bot is set to .5% commission(you can change this) on the buy and sell orders as most exchanges charge that amount. Some exchanges offer no fee trading on certain coins so be sure to look around for those so you can keep the commissions and maximize profits.
I strongly encourage you to try out a lot of different setting combinations across multiple different coins and do it across a few months to see how it would have performed under various market conditions. This will help you get a better idea of how much of a percentage deviation you’ll need to be able to cover to keep your bot running and making constant profits. You can also use the deep backtesting feature of the strategy panel to see how it would have done, but just beware that the info panel of the indicator will not reflect deep backtesting results, only the normal backtesting range.
MARKETS
This backtester can be used on any market including crypto, stocks, forex & futures. You just need to make sure your base order is larger than the share price when using this on things besides crypto.
TIMEFRAMES
This backtester can be used on all timeframes.
DCA After Downtrend v2 (by BHD_Trade_Bot)The purpose of the strategy is to identify the end of a short-term downtrend . So that you can easily to DCA certain amount of money for each month.
ENTRY
The buy orders are placed on a monthly basis for assets at the end of a short-term downtrend:
- Each month condition: In 1-hour time frame, each month has 24 * 30 candles
- The end of short-term downtrend condition: use MACD for less delay
CLOSE
The sell orders are placed when:
- Is last bar
The strategy use $1000 and trading fee is 1.1% for each order.
Pro tip: The 1-hour time frame has the best results on average:
- Total spent: $1000 x 33 = $33,000
- Total profit: $65,578
DCA After Downtrend (by BHD_Trade_Bot)The purpose of the strategy is to identify the end of a short-term downtrend . So that you can easily to DCA certain amount of money for each month.
ENTRY
The buy orders are placed on a monthly basis for assets at the end of a short-term downtrend:
- Each month condition: In 1-hour time frame, each month has 240 candles
- The end of short-term downtrend condition: use MACD for less delay
CLOSE
The sell orders are placed when:
- Is last bar
The strategy use $1000 and trading fee is 0.1% for each order.
Pro tip: The 1-hour time frame for TSLA has the best results on average:
- Total spent: $1000 x 85 = $85,000
- Total profit: $790,556
