The Ultimate Lot Size Calculator Backstory
I created this Pine Script tool to calculate lot sizes with precision. While there are many lot size calculators available on TradingView, I found that most had significant flaws. I started teaching myself Pine Script over three and a half years ago with the sole purpose of building this tool. My first version was messy and lacked accuracy, so I never published it. I wanted it to be better than any other available tool, but my limited knowledge back then held me back.
Recently, I received a request to create a similar tool, as the current options still fail to deliver the precision and reliability traders need. This inspired me to revisit my original idea. With improved skills and a better understanding of Pine Script, I redesigned the tool from scratch, making it as precise, reliable, and efficient as possible.
This tool features built-in error detection to minimize mistakes and ensure accuracy in lot size calculations. I've spent more time on this project than on any other, focusing on delivering a solution that stands out on TradingView. While I plan to add more features based on user feedback, the current version is already a powerful, dependable, and easy-to-use tool for traders who value precision and efficiency in their lot size calculations.
How to use the tool ?
At first it might seem complicated, but it is quite easy to use the tool. There are two modes: auto and manual. By default, the tool is set on manual mode. When you apply the tool on the chart, it will ask you to choose the entry price, then the stop-loss price, and at last the take-profit price. Select all of them one by one. These values can be changed later.
Settings
There are various setting given for making the tool as flexible as possible. Here is the explanation for some of most important settings. Play with them and make yourself comfortable.
General settings
Auto mode : Use this mode if you want the the risk reward to be fixed and stop loss to be based on ATR. However the stop loss can be changed to be based on user input.
Manual mode : Use this mode if you want full control over entry, stop loss and take profit.
Contract Size : The tool works perfectly for all forex pairs including gold and silver but as the contract size is different for different assets it is difficult to add every single asset into the script manually so i have provided this option. In case you want to calculate lot size for a asset other then forex, gold or silver make sure to change this. Contract size = Quantity of the asset in 1 standerd lot.
Account settings
Automatic mode settings and ATR stop settings
Manual mode settings
Table and risk-reward box settings are pretty much self-explanatory i guess.
Error handling
A lot size calculator is a complex program. There are numerous points where it may fail and produce incorrect results. To make it robust and accurate, these issues must be addressed and managed properly, which practically all existing lot size calculator scripts fail to do.
Golden tip
When the symbol is changed it will display a symbol change warning as the entry, stop loss and take profit price won't change.
There are 2 ways to get fix this. Either manually enter all three values which i hate the most or remove the script from the chart and re-apply the script on chart again.
So to re-apply the indicator in most easy way follow the following instructions:
Note : If you encounter any other error then read the instruction to fix it and if it is an unknow error pleas report it to me in comments or DM.
Recherche dans les scripts pour "THE SCRIPT"
RoGr75 - EMA 50/8 Cross With Buy/Sell Signals RoGr75 - EMA 50/8 Cross With Buy/Sell Signals
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**Overview:**
This script is designed to generate **Buy** and **Sell** signals based on the crossover and crossunder of two Exponential Moving Averages (EMAs): **EMA 8** (green line) and **EMA 50** (blue line). The signals are plotted at a user-defined distance from the candles, ensuring clear visibility and adaptability to market volatility.
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**Key Features:**
1. **EMA Cross Signals**:
- A **Buy Signal** is generated when the **EMA 8** crosses above the **EMA 50**.
- A **Sell Signal** is generated when the **EMA 8** crosses below the **EMA 50**.
2. **Variable Signal Distance**:
- The distance of the Buy and Sell signals from the candles is controlled by a **user-defined input** (`signal_distance`).
- The distance is calculated using the **Average True Range (ATR)** to adapt to market volatility.
3. **Customizable Parameters**:
- `signal_distance`: Adjust the distance of the signals from the candles (default: 2.0).
- ATR period: Fixed at 14 but can be modified in the script.
4. **Visual Enhancements**:
- Buy signals are displayed as green labels below the candles.
- Sell signals are displayed as red labels above the candles.
- Optional background highlighting for Buy and Sell signals.
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**How It Works:**
- The script calculates the **EMA 8** and **EMA 50** and plots them on the chart.
- When a crossover or crossunder occurs, a label is placed at a distance determined by the formula:
- **Buy Signal Position**: `low - (signal_distance * ATR(14))`
- **Sell Signal Position**: `high + (signal_distance * ATR(14))`
- The signals are clearly visible and adapt to the volatility of the asset.
---
**Input Parameters:**
- `signal_distance` (type: input float): Controls the distance of the Buy and Sell signals from the candles. Default value is `2.0`.
---
**Usage:**
1. Add the script to your chart in TradingView.
2. Adjust the `signal_distance` input to set the desired distance of the signals from the candles.
3. Monitor the Buy and Sell signals generated by the script for potential trading opportunities.
---
**Example:**
- If `signal_distance` is set to `2.0`, the Buy signal will appear **2x ATR** below the candle's low, and the Sell signal will appear **2x ATR** above the candle's high.
---
**Customization:**
- Modify the ATR period or replace it with a fixed value for static distance.
- Adjust the colors, styles, and sizes of the labels and EMAs to suit your preferences.
---
**Ideal For:**
- Traders looking for a simple and effective EMA crossover strategy.
- Users who want customizable signal placement for better visibility.
- Those who prefer volatility-adjusted signal distances.
---
**Note:**
This script is for educational and informational purposes only. Always backtest and validate strategies before using them in live trading.
Donchian Reversal Scanner by Hitesh2603How It Works:
Bearish Side Logic:
If the price is falling with bearish candles and touching the lower Donchian Channel, the bearishCondition flag is set to true.
When a bullish candle appears afterward, the flag is reset, and the bullishReversalSquare condition becomes true.
Bullish Side Logic:
If the price is rising with bullish candles and touching the upper Donchian Channel, the bullishCondition flag is set to true.
When a bearish candle appears afterward, the flag is reset, and the bearishReversalSquare condition becomes true.
Plotting Squares:
A green square is plotted below the candle when bullishReversalSquare is true.
A red square is plotted above the candle when bearishReversalSquare is true.
Scanner Output:
The scanCondition variable is true when either bullishReversalSquare or bearishReversalSquare is true.
How to Use the Script:
On the Chart:
Add the script to your chart.
You will see squares plotted on the chart when the conditions are met:
Green squares below the candle for bullish reversals.
Red squares above the candle for bearish reversals.
In the Scanner:
Open the Scanner tab in TradingView.
Click on "Create New Scanner".
In the "Condition" field, select the script you just created.
Choose the market or watchlist you want to scan (e.g., "NYSE", "NASDAQ", or a custom watchlist).
Run the scan. The Scanner will return a list of instruments where the scanCondition is true.
Why This Works:
The scanCondition variable is now properly declared and used.
The plotchar function explicitly outputs the scanCondition variable as a plot, which the Scanner can recognize.
BTC-SPX Momentum Gauge + EMA SignalHere's an explanation of the market dynamics and signal benefits of this script:
Momentum and Sentiment Indicator:
The script uses the momentum of the S&P 500 to change the chart's background color, providing a quick visual cue of market sentiment. Green indicates potential bullish momentum in the broader market, while red suggests bearish momentum. This can help traders gauge overall market direction at a glance.
Bitcoin Trend Analysis:
By plotting the scaled TEMA of Bitcoin (BTC), traders can see how Bitcoin's trend correlates or diverges from the current asset being analyzed. Since Bitcoin is often viewed as a hedge against traditional financial systems or inflation, its trend can signal broader economic shifts or investor sentiment towards alternative investments.
Dual Trend Confirmation:
The script offers two trend lines: one for Bitcoin and one for the current ticker. When these lines move in tandem, it might indicate a strong market trend across both traditional and crypto markets. Divergence between these lines can highlight potential market anomalies or opportunities for arbitrage or hedging.
Smoothness vs. Reactivity:
The use of TEMA for Bitcoin provides a smoother signal than a simple moving average, reducing lag while still reacting to price changes. This can be particularly useful for identifying longer-term trends in Bitcoin's volatile market. The 20-period EMA for the current ticker, on the other hand, gives a quicker response to price changes in the asset you're directly trading.
Cross-Asset Correlation:
By overlaying Bitcoin's trend on another asset's chart, traders can analyze how these markets might influence each other. For instance, if Bitcoin is in an uptrend while a traditional asset is declining, it might suggest capital rotation into cryptocurrencies.
Trading Signals:
Crossovers or divergences between the TEMA of Bitcoin and the EMA of the current ticker could be used as signals for entry or exit points. For example, if the BTC TEMA crosses above the current ticker's EMA, it might suggest a shift towards crypto assets.
Risk Management:
The visual cues from the background color and moving averages can aid in risk management. For example, trading in the direction of the momentum indicated by the background color might be seen as going with the market flow, potentially reducing risk.
Macro-Economic Insights:
The relationship between Bitcoin and traditional markets can offer insights into macroeconomic conditions, particularly related to inflation, monetary policy, and investor sentiment towards fiat currencies.
Headwind and tailwind:
Currently BTC correlated trade instruments experience headwind or tailwind from the broader market. This indicator lets the user see it to help their trade decision process.
Additional Statement:
As the market realizes the dangers of the fiat that its construct is built upon and evolves and migrates into stable money, incorruptible by inflation, this indicator will reveal the external influence of that corruptible and the internal influence of the incorruptible; having diminishing returns as the rise of stable money overtakes the treasuries of the fiat construct.
MEMEQUANTMEMEQUANT
This script is a comprehensive and specialized tool designed for tracking trends and money flow within meme coins and DEX tokens. By combining various features such as trend lines, Fibonacci levels, and category-based indices, it helps traders make informed decisions in highly volatile markets.
Key Features:
1. Category-Based Indices:
• Tracks the performance of token categories like:
• AI Agent Tokens
• AI Tokens
• Animal Tokens
• Murad Picks
• Each category consists of leader tokens, which are selected based on their higher market cap and trading volume. These tokens act as benchmarks for their respective categories.
• Visualizes category indices in a line chart to identify trends and compare money flow between categories.
2. Fibonacci Correction Zones:
• Highlights key retracement levels (e.g., 60%, 70%, 80%).
• These levels are crucial for identifying potential reversal zones, commonly observed in meme coin trading patterns.
• Fully customizable to match individual trading strategies.
3. Trend Lines:
• Automatically detects major support and resistance levels.
• Separates long-term and short-term trend lines, allowing traders to focus on significant price movements.
4. Enhanced Info Table:
• Provides real-time insights, including:
• % Distance from All-Time High (ATH)
• Current Trading Volume
• 50-bar Average Volume
• Volume Change Percentage
• Displays information in an easy-to-read table on the chart.
5. Customizable Settings:
• Users can adjust transparency, colors, and ranges for Fibonacci zones, trend lines, and the table.
• Enables or disables individual features (e.g., Fibonacci, trend lines, table) based on preferences.
How It Works:
1. Tracking Money Flow Across Categories:
• The script calculates the market cap to volume ratio for each category of tokens to help identify the dominant trend.
• A higher ratio indicates greater liquidity and stability, while a lower ratio suggests higher volatility or price manipulation.
2. Identifying Retracement Patterns:
• Leverages common retracement behaviors (e.g., 70% correction levels) observed in meme coins to detect potential reversal zones.
• Combines this with trend line analysis for additional confirmation.
3. Leader Tokens as Indicators:
• Each category is represented by its leader tokens, which have historically higher liquidity and market cap. This allows the script to accurately reflect the overall trend in each category.
When to Use:
• Trend Analysis: To identify which category (e.g., AI Tokens or Animal Tokens) is leading the market.
• Reversal Zones: To spot potential support or resistance levels using Fibonacci zones.
• Money Flow: To understand how capital is moving across different token categories in real time.
Who Is This For?
This script is tailored for:
• Traders specializing in meme coins and DEX tokens.
• Those looking for an edge in trend-based trading by analyzing market cap, volume, and retracement levels.
• Anyone aiming to track money flow dynamics between different token categories.
Future Updates:
This is the initial version of the script. Future updates may include:
• Support for additional token categories and DEX data.
• More advanced pattern recognition and alerts for volume and price anomalies.
• Enhanced visualization for historical data trends.
With this tool, traders can combine money flow analysis with the 60-70% retracement strategy, turning it into a powerful assistant for navigating the fast-paced world of meme coins and DEX tokens.
This script is designed to provide meaningful insights and practical utility for traders, adhering to TradingView’s standards for originality, clarity, and user value.
[blackcat] L3 Counter Peacock Spread█ OVERVIEW
The script titled " L3 Counter Peacock Spread" is an indicator designed for use in TradingView. It calculates and plots various moving averages, K lines derived from these moving averages, additional simple moving averages (SMAs), weighted moving averages (WMAs), and other technical indicators like slope calculations. The primary function of the script is to provide a comprehensive set of visual tools that traders can use to identify trends, potential support/resistance levels, and crossover signals.
█ LOGICAL FRAMEWORK
Input Parameters:
There are no explicit input parameters defined; all variables are hardcoded or calculated within the script.
Calculations:
• Moving Averages: Calculates Simple Moving Averages (SMA) using ta.sma.
• Slope Calculation: Computes the slope of a given series over a specified period using linear regression (ta.linreg).
• K Lines: Defines multiple exponentially adjusted SMAs based on a 30-period MA and a 1-period MA.
• Weighted Moving Average (WMA): Custom function to compute WMAs by iterating through price data points.
• Other Indicators: Includes Exponential Moving Average (EMA) for momentum calculation.
Plotting:
Various elements such as MAs, K lines, conditional bands, additional SMAs, and WMAs are plotted on the chart overlaying the main price action.
No loops control the behavior beyond those used in custom functions for calculating WMAs. Conditional statements determine the coloring of certain plot lines based on specific criteria.
█ CUSTOM FUNCTIONS
calculate_slope(src, length) :
• Purpose: To calculate the slope of a time-series data point over a specified number of periods.
• Functionality: Uses linear regression to find the current and previous slopes and computes their difference scaled by the timeframe multiplier.
• Parameters:
– src: Source of the input data (e.g., closing prices).
– length: Periodicity of the linreg calculation.
• Return Value: Computed slope value.
calculate_ma(source, length) :
• Purpose: To calculate the Simple Moving Average (SMA) of a given source over a specified period.
• Functionality: Utilizes TradingView’s built-in ta.sma function.
• Parameters:
– source: Input data series (e.g., closing prices).
– length: Number of bars considered for the SMA calculation.
• Return Value: Calculated SMA value.
calculate_k_lines(ma30, ma1) :
• Purpose: Generates multiple exponentially adjusted versions of a 30-period MA relative to a 1-period MA.
• Functionality: Multiplies the 30-period MA by coefficients ranging from 1.1 to 3 and subtracts multiples of the 1-period MA accordingly.
• Parameters:
– ma30: 30-period Simple Moving Average.
– ma1: 1-period Simple Moving Average.
• Return Value: Returns an array containing ten different \u2003\u2022 "K line" values.
calculate_wma(source, length) :
• Purpose: Computes the Weighted Moving Average (WMA) of a provided series over a defined period.
• Functionality: Iterates backward through the last 'n' bars, weights each bar according to its position, sums them up, and divides by the total weight.
• Parameters:
– source: Price series to average.
– length: Length of the lookback window.
• Return Value: Calculated WMA value.
█ KEY POINTS AND TECHNIQUES
• Advanced Pine Script Features: Utilization of custom functions for encapsulating complex logic, leveraging TradingView’s library functions (ta.sma, ta.linreg, ta.ema) for efficient computations.
• Optimization Techniques: Efficient computation of K lines via pre-calculated components (multiples of MA30 and MA1). Use of arrays to store intermediate results which simplifies plotting.
• Best Practices: Clear separation between calculation and visualization sections enhances readability and maintainability. Usage of color.new() allows dynamic adjustments without hardcoding colors directly into plot commands.
• Unique Approaches: Introduction of K lines provides an alternative representation of trend strength compared to traditional MAs. Implementation of conditional band coloring adds real-time context to existing visual cues.
█ EXTENDED KNOWLEDGE AND APPLICATIONS
Potential Modifications/Extensions:
• Adding more user-defined inputs for lengths of MAs, K lines, etc., would make the script more flexible.
• Incorporating alert conditions based on crossovers between key lines could enhance automated trading strategies.
Application Scenarios:
• Useful for both intraday and swing trading due to the combination of short-term and long-term MAs along with trend analysis via slopes and K lines.
• Can be integrated into larger systems combining this indicator with others like oscillators or volume-based metrics.
Related Concepts:
• Understanding how linear regression works internally aids in grasping the slope calculation.
• Familiarity with WMA versus SMA helps appreciate why different types of averaging might be necessary depending on market dynamics.
• Knowledge of candlestick patterns can complement insights gained from this indicator.
Volume-MACD-RSI Integrated StrategyDescription:
This script integrates three well-known technical analysis tools—Volume, MACD, and RSI—into a single signal meant to help traders identify potential turning points under strong market conditions.
Concept Overview:
Volume Filter: We compare the current bar’s volume to a 20-period volume average and require it to exceed a specified multiplier. This ensures that signals occur only during periods of heightened market participation. The logic is that moves on low volume are less reliable, so we wait for increased activity to confirm potential trend changes.
MACD Momentum Shift:
We incorporate MACD crossovers to determine when momentum is changing direction. MACD is a popular momentum indicator that identifies shifts in trend by comparing short-term and long-term EMAs. A bullish crossover (MACD line crossing above the signal line) may suggest upward momentum is building, while a bearish crossunder can indicate momentum turning downward.
RSI Market Condition Check:
RSI helps us identify overbought or oversold conditions. By requiring that RSI be oversold on buy signals and overbought on sell signals, we attempt to pinpoint entries where price could be at an extreme. The idea is to position entries or exits at junctures where price may be due for a reversal.
How the Script Works Together:
Volume Confirmation: No signals fire unless there’s strong volume. This reduces false positives.
MACD Momentum Check: Once volume confirms market interest, MACD crossover events serve as a trigger to initiate consideration of a trade signal.
RSI Condition: Finally, RSI determines whether the market is at an extreme. This final layer helps ensure we only act on signals that have both momentum shift and a price at an extreme level, potentially increasing the reliability of signals.
Intended Use:
This script can help highlight potential reversal points or trend shifts during active market periods.
Traders can use these signals as a starting point for deeper analysis. For instance, a “BUY” arrow may prompt a trader to investigate the market context, confirm with other methods, or look for patterns that further support a long entry.
The script is best used on markets with reliable volume data, such as stocks or futures, and can be experimented with across different timeframes. Adjusting the RSI thresholds, MACD parameters, and volume multiplier can help tailor it to specific instruments or trading styles.
Chart Setup:
When adding this script to your chart, it should be the only indicator present, so you can clearly see the red “BUY” arrows and green “SELL” arrows at the candle closes where signals occur.
The chart should be kept clean and uncluttered for clarity. No other indicators are necessary since the logic is already integrated into this single script.
MicuRobert EMA Cross StrategyThis is a repost of a old strategy that cant be updated anymore, it was a request for a user made in Oct, 6, 2015
Here's a possible engaging description for the tradingview script:
**MicuRobert EMA Cross V2: A Powerful Trading Strategy**
Join the ranks of successful traders with this advanced strategy, designed to help you profit from market trends. The MicuRobert EMA Cross V2 combines two essential indicators - Exponential Moving Average (EMA) and Divergence EMA (DEMA) - to generate buy and sell signals.
**Key Features:**
* **Trading Session Filter**: Only trade during your preferred session, ensuring you're in sync with market conditions.
* **Trailing Stop**: Automatically adjust stop-loss levels to lock in profits or limit losses.
* **Customizable Trade Size**: Set the size of each trade based on your risk tolerance and trading goals.
**How it Works:**
The script uses two EMAs (5-period and 34-period) to identify trends. When the shorter EMA crosses above the longer one, a buy signal is generated. Conversely, when the shorter EMA falls below the longer one, a sell signal is triggered. The strategy also incorporates divergence analysis between price action and the EMAs.
**Visual Aids:**
* **EMA Plots**: Visualize the two EMAs on your chart to gauge market momentum.
* **Buy/Sell Signals**: See when buy or sell signals are generated, along with their corresponding entry prices.
* **Trailing Stop Lines**: Monitor stop-loss levels as they adjust based on price action.
**Get Started:**
Download this script and start trading like a pro! With its robust features and customizable settings, the MicuRobert EMA Cross V2 is an excellent addition to any trader's arsenal.
~Llama3
Coinbase Premium HeatmapCoinbase Premium Heatmap visualizes spot bitcoin premium (or discount) on Coinbase, relative to other spot markets, visualized as a heatmap overlay.
OPTIMIZED FOR CLARITY
Coinbase Premium can whipsaw quickly, with dramatic state changes over relatively brief periods, unnecessarily complicating its use (for our purposes).
To mitigate whipsaws, the script (a) averages premium/discount on an hourly basis, and (b) introduces lightweight exponential smoothing, to further simplify/clarify state.
WHY IT MATTERS
Spot Coinbase premium is a strong proxy for bullish institutional sentiment and net inflows/accumulation by western financial institutions, ETF providers, and corporations (like MicroStrategy) adding bitcoin to their treasury.
In aggregate, this holder cohort drives trend & sentiment more than any other, so it's important to know their directional bias.
HOW IT'S CALCULATED
Premium / discount calculates the spread between Coinbase spot BTC price, and spot price on Binance + Bybit. Calculation is averaged hourly, with light exponential smoothing.
HOW WE USE THE SCRIPT
When assessing optimal moments to hedge exposure (or sell spot assets) near a presumed impending cycle top, awareness of institutional sentiment is a crucial variable. This script:
(a) Filters out unnecessarily early cycle exit signals (if Coinbase premium is still present)
(b) Confirms other metrics that indicate an impending cycle top (if the neutral to bearish institutional sentiment we'd expect to see is in effect), and
(c) Visualizes state changes (from bearish to bullish & vice versa), that often make for good swing entries & exits on lower timeframes.
STRATEGY Fibonacci Levels with High/Low Criteria - AYNET
Here is an explanation of the Fibonacci Levels Strategy with High/Low Criteria script:
Overview
This strategy combines Fibonacci retracement levels with high/low criteria to generate buy and sell signals based on price crossing specific thresholds. It utilizes higher timeframe (HTF) candlesticks and user-defined lookback periods for high/low levels.
Key Features
Higher Timeframe Integration:
The script calculates the open, high, low, and close values of the higher timeframe (HTF) candlestick.
Users can choose to calculate levels based on the current or the last HTF candle.
Fibonacci Levels:
Fibonacci retracement levels are dynamically calculated based on the HTF candlestick's range (high - low).
Users can customize the levels (0.000, 0.236, 0.382, 0.500, 0.618, 0.786, 1.000).
High/Low Lookback Criteria:
The script evaluates the highest high and lowest low over user-defined lookback periods.
These levels are plotted on the chart for visual reference.
Trade Signals:
Long Signal: Triggered when the close price crosses above both:
The lowest price criteria (lookback period).
The Fibonacci level 3 (default: 0.5).
Short Signal: Triggered when the close price crosses below both:
The highest price criteria (lookback period).
The Fibonacci level 3 (default: 0.5).
Visualization:
Plots Fibonacci levels and high/low criteria on the chart for easy interpretation.
Inputs
Higher Timeframe:
Users can select the timeframe (default: Daily) for the HTF candlestick.
Option to calculate based on the current or last HTF candle.
Lookback Periods:
lowestLookback: Number of bars for the lowest low calculation (default: 20).
highestLookback: Number of bars for the highest high calculation (default: 10).
Fibonacci Levels:
Fully customizable Fibonacci levels ranging from 0.000 to 1.000.
Visualization
Fibonacci Levels:
Plots six customizable Fibonacci levels with distinct colors and transparency.
High/Low Criteria:
Plots the highest and lowest levels based on the lookback periods as reference lines.
Trading Logic
Long Condition:
Price must close above:
The lowest price criteria (lowcriteria).
The Fibonacci level 3 (50% retracement).
Short Condition:
Price must close below:
The highest price criteria (highcriteria).
The Fibonacci level 3 (50% retracement).
Use Case
Trend Reversal Strategy:
Combines Fibonacci retracement with recent high/low criteria to identify potential reversal or breakout points.
Custom Timeframe Analysis:
Incorporates higher timeframe data for multi-timeframe trading strategies.
Zero-Lag MA Trend FollowingScript Name: Zero-Lag MA Trend Following Auto-Trading
Purpose and Unique Features:
This script is designed to implement a trend-following auto-trading strategy by combining the Zero-Lag Moving Average (ZLMA), Exponential Moving Average (EMA), and ATR Bands. To differentiate it from similar scripts, the following key aspects are emphasized:
Zero-Lag MA (ZLMA):
Responds quickly to price changes, minimizing lag compared to EMA.
Detects crossovers with EMA and generates Diamond Signals to indicate trend reversals.
ATR Bands:
Measures market volatility to set stop-loss levels.
Helps optimize entry points and manage risk effectively.
Diamond Signals:
A vital visual cue indicating the early stages of trend reversals.
Green diamonds signal an uptrend, while red diamonds signal a downtrend.
Each component plays a distinct role, working synergistically to enhance trend detection and risk management. This system doesn’t merely combine indicators but optimizes them for comprehensive trend-following and risk control.
Usage Instructions:
Entry Conditions:
Long Entry:
Enter when a green Diamond Signal appears (ZLMA crosses above EMA).
Short Entry:
Enter when a red Diamond Signal appears (ZLMA crosses below EMA).
Exit Conditions:
Stop Loss:
Set at the lower boundary of the ATR band for BUY or the upper boundary for SELL at entry.
Take Profit:
Automatically executed based on a 1:2 risk-reward ratio.
Account Size: ¥100,0000
Commissions and Slippage: Assumed commission of 90 pips per trade and slippage of 1 pip.
Risk per Trade: 10% of account equity (adjustable based on risk tolerance).
Improvements and Original Features:
While based on open-source code, this script incorporates the following critical enhancements:
Diamond Signals from ZLMA and EMA Integration:
Improves entry accuracy with a proprietary trend detection strategy.
ATR Bands Utilization:
Adds a volatility-based risk management function.
Optimized Visual Entry Signals:
Includes plotted triangles (▲, ▼) to clearly indicate trend-following entry points.
Credits:
This script builds upon indicators developed by ChartPrime, whose innovative approach and insights have enabled a more advanced trend-following strategy. We extend our gratitude for their foundational work.
Additionally, it integrates technical methods based on Zero-Lag Moving Average (ZLMA), EMA, and ATR Bands, leveraging insights from the trading community.
Chart Display Options:
The script offers options to toggle the visual signals (Diamond Signals, trend lines, and entry points) on or off, keeping the chart clean while maximizing analytical efficiency.
Disclaimer:
This script is provided for educational purposes and past performance does not guarantee future results.
Use it responsibly with proper risk management.
Market Stats Panel [Daveatt]█ Introduction
I've created a script that brings TradingView's watchlist stats panel functionality directly to your charts. This isn't just another performance indicator - it's a pixel-perfect (kidding) recreation of TradingView's native stats panel.
Important Notes
You might need to adjust manually the scaling the firs time you're using this script to display nicely all the elements.
█ Core Features
Performance Metrics
The panel displays key performance metrics (1W, 1M, 3M, 6M, YTD, 1Y) in real-time, with color-coded boxes (green for positive, red for negative) for instant performance assessment.
Display Modes
Switch seamlessly between absolute prices and percentage returns, making it easy to compare assets across different price scales.
Absolute mode
Percent mode
Historical Comparison
View year-over-year performance with color-coded lines, allowing for quick historical pattern recognition and analysis.
Data Structure Innovation
Let's talk about one of the most interesting challenges I faced. PineScript has this quirky limitation where request.security() can only return 127 tuples at most. £To work around this, I implemented a dual-request system. The first request handles indices 0-63, while the second one takes care of indices 64-127.
This approach lets us maintain extensive historical data without compromising script stability.
And here's the cool part: if you need to handle even more years of historical data, you can simply extend this pattern by adding more request.security() calls.
Each additional call can fetch another batch of monthly open prices and timestamps, following the same structure I've used.
Think of it as building with LEGO blocks - you can keep adding more pieces to extend your historical reach.
Flexible Date Range
Unlike many scripts that box you into specific timeframes, I've designed this one to be completely flexible with your date selection. You can set any start year, any end year, and the script will dynamically scale everything to match. The visual presentation automatically adjusts to whatever range you choose, ensuring your data is always displayed optimally.
█ Customization Options
Visual Settings
The panel's visual elements are highly customizable. You can adjust the panel width to perfectly fit your workspace, fine-tune the line thickness to match your preferences, and enjoy the pre-defined year color scheme that makes tracking historical performance intuitive and visually appealing.
Box Dimensions
Every aspect of the performance boxes can be tailored to your needs. Adjust their height and width, fine-tune the spacing between them, and position the entire panel exactly where you want it on your chart. The goal is to make this tool feel like it's truly yours.
█ Technical Challenges Solved
Polyline Precision
Creating precise polylines was perhaps the most demanding aspect of this project.
The challenge was ensuring accurate positioning across both time and price axes, while handling percentage mode scaling with precision.
The script constantly updates the current year's data in real-time, seamlessly integrating new information as it comes in.
Axis Management
Getting the axes right was like solving a complex puzzle. The Y-axis needed to scale dynamically whether you're viewing absolute prices or percentages.
The X-axis required careful month labeling that stays clean and readable regardless of your selected timeframe.
Everything needed to align perfectly while maintaining proper spacing in all conditions.
█ Final Notes
This tool transforms complex market data into clear, actionable insights. Whether you're day trading or analyzing long-term trends, it provides the information you need to make informed decisions. And remember, while we can't predict the future, we can certainly be better prepared for it with the right tools at hand.
A word of warning though - seeing those red numbers in a beautifully formatted panel doesn't make them any less painful! 😉
---
Happy Trading! May your charts be green and your stops be far away!
Daveatt
Three Bar Reversal Pattern [LuxAlgo]The Three Bar Reversal Pattern indicator identifies and highlights three bar reversal patterns on the user price chart.
The script also provides an option for incorporating various trend indicators used to filter out detected signals, allowing them to enhance their accuracy and help obtain a more comprehensive analysis.
🔶 USAGE
The script automates the detection of three-bar reversal patterns and provides a clear, visually identifiable signal for potential trend reversals.
When a reversal chart pattern is confirmed and price action aligns with the pattern, the pattern's boundaries are extended, forming levels, with the upper boundary often acting as a resistance and the lower boundary as a support.
The script allows users to filter patterns based on a specific trend direction detected by multiple trend indicators. Users can choose to view patterns that are either aligned with the detected trend or opposite to it.
Included trend indicators are: Moving Average Cloud, Supertrend, and Donchian Channels.
🔶 DETAILS
The three-bar reversal pattern is a technical analysis pattern that signals a potential reversal in the prevailing trend. The pattern consists of three consecutive bar formations:
First Bar and Second Bar: 2 consecutive of the same sentiment, representing the prevailing trend in the market.
Third Bar: Confirms the reversal by closing beyond the high or low of the first bar, signaling a potential change in market sentiment.
Various types of three-bar reversal patterns are documented. The script supports two main types:
Normal Pattern: Detects three-bar reversal patterns without requiring the third bar closing price to surpass the high (bullish pattern) or low (bearish pattern) of the first bar. It identifies basic formations signaling potential trend reversals.
Enhanced Pattern: Specifically identifies three-bar reversal patterns where the third bar closing price surpasses the high (bullish pattern) or low (bearish pattern) of the first bar. This type provides a more selective signal for stronger trend reversals.
🔶 SETTINGS
Pattern Type: Users can choose the type of 3-bar reversal patterns to detect: Normal, Enhanced, or All. "Normal" detects patterns that do not necessarily surpass the high/low of the first bar. "Enhanced" detects patterns where the third bar surpasses the high/low of the first bar. "All" detects both Normal and Enhanced patterns.
Derived Support and Resistance: Toggles the visibility of the support and resistance levels/zones.
🔹 Trend Filtering
Filtering: Allows users to filter patterns based on the trend indicators: Moving Average Cloud, Supertrend, and Donchian Channels. The "Aligned" option only detects patterns that align with the trend and conversely, the "Opposite" option detects patterns that go against the trend.
🔹 Trend Indicator Settings
Moving Average Cloud: Allows traders to choose the type of moving averages (SMA, EMA, HMA, etc.) and set the lengths for fast and slow-moving averages.
Supertrend: Options to set the ATR length and factor for Supertrend.
Donchian Channels: Option to set the length for the channel calculation.
🔶 RELATED SCRIPTS
Reversal-Candlestick-Structure .
Reversal-Signals .
Rolling VWAPGuide for Traders
What is the Rolling VWAP?
The Volume Weighted Average Price (VWAP) is a key indicator used by traders to assess the average price of an asset, weighted by volume over a specified period. Unlike a simple moving average, the VWAP accounts for trading volume, making it a more accurate reflection of price action and market sentiment.
The Rolling VWAP in this script dynamically updates based on a user-defined period, allowing traders to view the average price over a chosen number of bars. This is particularly useful for identifying trends and potential entry or exit points in the market.
Key Benefits of Using Rolling VWAP
Better Market Insight: VWAP provides insight into where most trading is occurring, helping you gauge the strength of a price move.
Support and Resistance Levels: It often acts as dynamic support or resistance, signaling areas where price might reverse.
Trend Confirmation: A rising VWAP suggests a bullish trend, while a falling VWAP indicates a bearish trend.
Informed Entry/Exit Decisions: Use the VWAP to find entry points below it in an uptrend or exit points above it in a downtrend.
How to Use this Script:
Custom Period Input:
You can modify the "VWAP Period" to adjust the number of bars considered in the rolling calculation.
The default period is 14 bars, but you can set it based on your strategy (e.g., shorter for intraday trading, longer for swing trading).
Chart Interpretation
Bullish Signals: When the price is above the VWAP line, it suggests upward momentum, and you may consider buying opportunities.
Bearish Signals: When the price is below the VWAP, it indicates downward momentum, and you may consider selling or shorting opportunities.
Reversion to VWAP: Prices often revert to the VWAP after extended moves away from it, offering potential trade setups.
Combine with Other Indicators:
Momentum Indicators: Use with RSI, MACD, or moving averages for confirmation.
Volume Analysis: VWAP works well when combined with volume indicators to assess if a breakout is supported by high trading volume.
Customization:
Traders can customize the script's period and plot color to fit their charting preferences.
Practical Tips:
Intraday Traders: Use shorter periods (e.g., 5 or 10) to capture VWAP trends in fast-moving markets.
Swing Traders: Use longer periods (e.g., 50 or 100) to assess longer-term price and volume trends.
By integrating this Rolling VWAP into your strategy, you can better understand where the majority of trading volume has occurred, allowing you to make more informed decisions in your trading process.
CSVParser█ OVERVIEW
The library contains functions for parsing and importing complex CSV configurations (with a special simple syntax) into a special hierarchical object (of type objProps ) as follows:
Functions:
parseConfig() - reads CSV text into an objProps object.
toT() - displays the contents of an objProps object in a table form, which allows to check the CSV text for syntax errors.
getPropAr() - returns objProps.arS array for child object with `prop` key in mpObj map (or na if not found)
This library is handy in allowing users to store presets for the scripts and switch between them (see, e.g., my HTF moving averages script where users can switch between several preset configuations of 24 MA's across 5 timeframes).
█ HOW THE SCRIPT WORKS.
The script works as follows:
all values read from config text are stored as strings
Nested brackets in config text create a named nested objects of objProps0, ... , objProps9 types.
objProps objects of each level have the following fields:
- array arS for storing values without names (e.g. "12, 23" will be imported into a string array arS as )
- map mpS for storing items with names (e.g. "tf = 60, length = 21" will be imported as <"tf", "60"> and <"length", "21"> pairs into mpS )
- map mpObj for storing nested objects (e.g. "TF1(tf=60, length(21,50,100))" creates a <"TF1, objProps0 object> pair in mpObj map property of the top level object (objProps) , "tf=60" is stored as <"tf", "60"> key-value pair in mpS map property of a next level object (objProps0) and "length (...)" creates a <"length", objProps1> pair in objProps0.mpObj map while length values are stored in objProps1.arS array as strings. Every opening bracket creates a next level objProps object.
If objects or properties with duplicate names are encountered only the latest is imported
(e.g. for "TF1(length(12,22)), TF1(tf=240)" only "TF1(tf=240)" will be imported
Line breaks are not regarded as part of syntax (i.e. values are imported with line breaks, you can supply
symbols "(" , ")" , "," and "=" are special characters and cannot be used within property values (with the exception of a quoted text as a value of a property as explained below)
named properties can have quoted text as their value. In that case special characters within quotation marks are regarded as normal characters. Text between "=" and opening quotation mark as well as text following the closing quotation mark and until next property value is ignored. E.g. "quote = ignored "The quote" also ignored" will be imported as <"quote", "The quote">. Quotation marks within quotes must be excaped with "\" .
if a key names happens to be a multi-line then only first line containing non-space characters (trimmed from spaces) is taken as a key.
")," or ") ," and similar do not create an empty ("") array item while ",," does. (",)" creates an "" array item)
█ CSV CONFIGURATION SYNTAX
Unnamed values: just list them comma separated and they will be imported into arS of the object of the current level.
Named values: use "=" sign as follows: "property1=value1, property2 = value2"
Value of several objects: Use brackets after the name of the object ant list all object properties within the brackets (including its child objects if necessary). E.g. "TF1(tf =60, length(21,200), TF2(tf=240, length(50,200)"
Named and unnamed values as well as objects can go in any order. E.g. "12, tf=60, 21" will be imported as follows: "12", "21" will go to arS array and <"tf", "60"> will go to mpS maP of objProps (the top level object).
You can play around and test your config text using demo in this library, just edit your text in script settings and see how it is parsed into objProps objects.
█ USAGE RECOMMENDATIONS AND SAMPLE USE
I suggest the following approach:
- create functions for your UDT which can set properties by name.
- create enumerator functions which iterates through all the property names (supplied as a const string array) and imports their values into the object
█ SAMPLE USE
A sample use of this library can be seen in my Multi-timeframe 24 moving averages + BB+SAR+Supertrend+VWAP script where settings for the MAs across many timeframes are imported from CSV configurations (presets).
█ FULL LIST OF FUNCTIONS AND PROPERTIES
nzs(_s, nz)
Like nz() but for strings. Returns `nz` arg (default = "") if _s is na.
Parameters:
_s (string)
nz (string)
method init(this)
Initializes objProps obj (creates child maps and arrays)
Namespace types: objProps
Parameters:
this (objProps)
method toT(this, nz)
Outputs objProps to string matrices for further display using autotable().
Namespace types: objProps, objProps1, ..., objProps9
Parameters:
this (objProps/objProps1/..../objProps9)
nz (string)
Returns: A tuple - value, merge and color matrix (autotable() parameters)
method parseConfig(this, s)
Reads config text into objProps (unnamed values into arS, named into mpS, sub-levels into mpObj)
Namespace types: objProps
Parameters:
this (objProps)
s (string)
method getPropArS(this, prop)
Returns a string array of values for a given property name `prop`. Looks for a key `prop` in objProps.mpObj
if finds pair returns obj.arS, otherwise returns na. Returns a reference to the original, not a copy.
Namespace types: objProps, objProps1, ..., objProps8
Parameters:
this (objProps/objProps1/..../objProps8)
prop (string)
method getPropVal(this, prop, id)
Checks if there is an array of values for property `prop` and returns its `id`'s element or na if not found
Namespace types: objProps, objProps1, ..., objProps8
Parameters:
this (objProps/objProps1/..../objProps8) : objProps object containing array of property values in a child objProp object corresponding to propertty name.
prop (string) : (string) Name of the property
id (int) : (int) Id of the element to be returned from the array pf property values
objProps9 type
Object for storing values read from CSV relating to a particular object or property name.
Fields:
mpS (map) : (map() Stores property values as pairs
arS (array) : (string ) Array of values
objProps, objProps0, ... objProps8 types
Object for storing values read from CSV relating to a particular object or property name.
Fields:
mpS (map) : (map() Stores property values as pairs
arS (array) : (string ) Array of values
mpObj (map) : (map() Stores objProps objects containing properties's data as pairs
N Bar Reversal Detector [LuxAlgo]The N Bar Reversal Detector is designed to detect and highlight N-bar reversal patterns in user charts, where N represents the length of the candle sequence used to detect the patterns. The script incorporates various trend indicators to filter out detected signals and offers a range of customizable settings to fit different trading strategies.
🔶 USAGE
The N-bar reversal pattern extends the popular 3-bar reversal pattern. While the 3-bar reversal pattern involves identifying a sequence of three bars signaling a potential trend reversal, the N-bar reversal pattern builds on this concept by incorporating additional bars based on user settings. This provides a more comprehensive indication of potential trend reversals. The script automates the identification of these patterns and generates clear, visually distinct signals to highlight potential trend changes.
When a reversal chart pattern is confirmed and aligns with the price action, the pattern's boundaries are extended to create levels. The upper boundary serves as resistance, while the lower boundary acts as support.
The script allows users to filter patterns based on the trend direction identified by various trend indicators. Users can choose to view patterns that align with the detected trend or those that are contrary to it.
🔶 DETAILS
🔹 The N-bar Reversal Pattern
The N-bar reversal pattern is a technical analysis tool designed to signal potential trend reversals in the market. It consists of N consecutive bars, with the first N-1 bars used to identify the prevailing trend and the Nth bar confirming the reversal. Here’s a detailed look at the pattern:
Bullish Reversal : In a bullish reversal setup, the first bar is the highest among the first N-1 bars, indicating a prevailing downtrend. Most of the remaining bars in this sequence should be bearish (closing lower than where they opened), reinforcing the existing downward momentum. The Nth (most recent) bar confirms a bullish reversal if its high price is higher than the high of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be higher than the high of the first bar.
Bearish Reversal : In a bearish reversal setup, the first bar is the lowest among the first N-1 bars, indicating a prevailing uptrend. Most of the remaining bars in this sequence should be bullish (closing higher than where they opened), reinforcing the existing upward momentum. The Nth bar confirms a bearish reversal if its low price is lower than the low of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be lower than the low of the first bar.
🔹 Min Percentage of Required Candles
This parameter specifies the minimum percentage of candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) among the first N-1 candles in a pattern. For higher values of N, it becomes more challenging for all of the first N-1 candles to be consistently bullish or bearish. By setting a percentage value, P, users can adjust the requirement so that only a minimum of P percent of the first N-1 candles need to meet the bullish or bearish condition. This allows for greater flexibility in pattern recognition, accommodating variations in market conditions.
🔶 SETTINGS
Pattern Type: Users can choose the type of the N-bar reversal patterns to detect: Normal, Enhanced, or All. "Normal" detects patterns that do not necessarily surpass the high/low of the first bar. "Enhanced" detects patterns where the last bar surpasses the high/low of the first bar. "All" detects both Normal and Enhanced patterns.
Reversal Pattern Sequence Length: Specifies the number of candles (N) in the sequence used to identify a reversal pattern.
Min Percentage of Required Candles: Sets the minimum percentage of the first N-1 candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) to qualify as a valid reversal pattern.
Derived Support and Resistance: Toggles the visibility of the support and resistance levels/zones.
🔹 Trend Filtering
Filtering: Allows users to filter patterns based on the trend indicators: Moving Average Cloud, Supertrend, and Donchian Channels. The "Aligned" option only detects patterns that align with the trend and conversely, the "Opposite" option detects patterns that go against the trend.
🔹 Trend Indicator Settings
Moving Average Cloud: Allows traders to choose the type of moving averages (SMA, EMA, HMA, etc.) and set the lengths for fast and slow moving averages.
Supertrend: Options to set the ATR length and factor for Supertrend.
Donchian Channels: Option to set the length for the channel calculation.
🔶 RELATED SCRIPTS
Reversal-Candlestick-Structure.
Reversal-Signals.
Tick CVD [Kioseff Trading]Hello!
This script "Tick CVD" employs live tick data to calculate CVD and volume delta! No tick chart required.
Features
Live price ticks are recorded
CVD calculated using live ticks
Delta calculated using live ticks
Tick-based HMA, WMA, EMA, or SMA for CVD and price
Key tick levels (S/R CVD & price) are recorded and displayed
Price/CVD displayable as candles or lines
Polylines are used - data visuals are not limited to 500 points.
Efficiency mode - remove all the bells and whistles to capitalize on efficiently calculated/displayed tick CVD and price
How it works
While historical tick-data isn't available to non-professional subscribers, live tick data is programmatically accessible. Consequently, this indicator records live tick data to calculate CVD, delta, and other metrics for the user!
Generally, Pine Scripts use the following rules to calculate volume/price-related metrics:
Bullish Volume: When the close price is greater than the open price.
Bearish Volume: When the close price is less than the open price.
This script, however, improves on that logic by utilizing live ticks. Instead of relying on time-series charts, it records up ticks as buying volume and down ticks as selling volume. This allows the script to create a more accurate CVD, delta, or price tick chart by tracking real-time buying and selling activity.
Price can tick fast; therefore, tick aggregation can occur. While tick aggregation isn't necessarily "incorrect", if you prefer speed and efficiency it's advised to enable "efficiency mode" in a fast market.
The image above highlights the tick CVD and price tick graph!
Green price tick graph = price is greater than its origin point (first script load)
Red price tick graph = price is less than its origin point
Blue tick CVD graph = CVD, over the calculation period, is greater than 0.
Red tick CVD graph = CVD is less than 0 over the calculation period.
The image above explains the right-oriented scales. The upper scale is for the price graph and the lower scale for the CVD graph.
The image above explains the circles superimposed on the scale lines for the price graph and the CVD graph.
The image above explains the "wavy" lines shown by the indicator. The wavy lines correspond to tick delta - whether the recorded tick was an uptick or down tick and whether buy volume or sell volume transpired.
The image above explains the blue/red boxes displayed by the indicator. The boxes offer an alternative visualization of tick delta, including the magnitude of buying/selling volume for the recorded tick.
Blue boxes = buying volume
Red boxes = selling volume
Bright blue = high buying volume (relative)
Bright red = high selling volume (relative)
Dim blue = low buying volume (relative)
Dim red = low selling volume (relative)
The numbers displayed in the box show the numbered tick and the volume delta recorded for the tick.
The image above further explains visuals for the CVD graph.
Dotted red lines indicate key CVD peaks, while dotted blue lines indicate key CVD bottoms.
The white dotted line reflects the CVD average of your choice: HMA, WMA, EMA, SMA.
The image above offers a similar explanation of visuals for the price graph.
The image above offers an alternative view for the indicator!
The image above shows the indicator when efficiency mode is enabled. When trading a fast market, enabling efficiency mode is advised - the script will perform quicker.
Of course, thank you to @RicardoSantos for his awesome library I use in almost every script :D
Thank you for checking this out!
Dual Chain StrategyDual Chain Strategy - Technical Overview
How It Works:
The Dual Chain Strategy is a unique approach to trading that utilizes Exponential Moving Averages (EMAs) across different timeframes, creating two distinct "chains" of trading signals. These chains can work independently or together, capturing both long-term trends and short-term price movements.
Chain 1 (Longer-Term Focus):
Entry Signal: The entry signal for Chain 1 is generated when the closing price crosses above the EMA calculated on a weekly timeframe. This suggests the start of a bullish trend and prompts a long position.
bullishChain1 = enableChain1 and ta.crossover(src1, entryEMA1)
Exit Signal: The exit signal is triggered when the closing price crosses below the EMA on a daily timeframe, indicating a potential bearish reversal.
exitLongChain1 = enableChain1 and ta.crossunder(src1, exitEMA1)
Parameters: Chain 1's EMA length is set to 10 periods by default, with the flexibility for user adjustment to match various trading scenarios.
Chain 2 (Shorter-Term Focus):
Entry Signal: Chain 2 generates an entry signal when the closing price crosses above the EMA on a 12-hour timeframe. This setup is designed to capture quicker, shorter-term movements.
bullishChain2 = enableChain2 and ta.crossover(src2, entryEMA2)
Exit Signal: The exit signal occurs when the closing price falls below the EMA on a 9-hour timeframe, indicating the end of the shorter-term trend.
exitLongChain2 = enableChain2 and ta.crossunder(src2, exitEMA2)
Parameters: Chain 2's EMA length is set to 9 periods by default, and can be customized to better align with specific market conditions or trading strategies.
Key Features:
Dual EMA Chains: The strategy's originality shines through its dual-chain configuration, allowing traders to monitor and react to both long-term and short-term market trends. This approach is particularly powerful as it combines the strengths of trend-following with the agility of momentum trading.
Timeframe Flexibility: Users can modify the timeframes for both chains, ensuring the strategy can be tailored to different market conditions and individual trading styles. This flexibility makes it versatile for various assets and trading environments.
Independent Trade Logic: Each chain operates independently, with its own set of entry and exit rules. This allows for simultaneous or separate execution of trades based on the signals from either or both chains, providing a robust trading system that can handle different market phases.
Backtesting Period: The strategy includes a configurable backtesting period, enabling thorough performance assessment over a historical range. This feature is crucial for understanding how the strategy would have performed under different market conditions.
time_cond = time >= startDate and time <= finishDate
What It Does:
The Dual Chain Strategy offers traders a distinctive trading tool that merges two separate EMA-based systems into one cohesive framework. By integrating both long-term and short-term perspectives, the strategy enhances the ability to adapt to changing market conditions. The originality of this script lies in its innovative dual-chain design, providing traders with a unique edge by allowing them to capitalize on both significant trends and smaller, faster price movements.
Whether you aim to capture extended market trends or take advantage of more immediate price action, the Dual Chain Strategy provides a comprehensive solution with a high degree of customization and strategic depth. Its flexibility and originality make it a valuable tool for traders seeking to refine their approach to market analysis and execution.
How to Use the Dual Chain Strategy
Step 1: Access the Strategy
Add the Script: Start by adding the Dual Chain Strategy to your TradingView chart. You can do this by searching for the script by name or using the link provided.
Select the Asset: Apply the strategy to your preferred trading pair or asset, such as #BTCUSD, to see how it performs.
Step 2: Configure the Settings
Enable/Disable Chains:
The strategy is designed with two independent chains. You can choose to enable or disable each chain depending on your trading style and the market conditions.
enableChain1 = input.bool(true, title='Enable Chain 1')
enableChain2 = input.bool(true, title='Enable Chain 2')
By default, both chains are enabled. If you prefer to focus only on longer-term trends, you might disable Chain 2, or vice versa if you prefer shorter-term trades.
Set EMA Lengths:
Adjust the EMA lengths for each chain to match your trading preferences.
Chain 1: The default EMA length is 10 periods. This chain uses a weekly timeframe for entry signals and a daily timeframe for exits.
len1 = input.int(10, minval=1, title='Length Chain 1 EMA', group="Chain 1")
Chain 2: The default EMA length is 9 periods. This chain uses a 12-hour timeframe for entries and a 9-hour timeframe for exits.
len2 = input.int(9, minval=1, title='Length Chain 2 EMA', group="Chain 2")
Customize Timeframes:
You can customize the timeframes used for entry and exit signals for both chains.
Chain 1:
Entry Timeframe: Weekly
Exit Timeframe: Daily
tf1_entry = input.timeframe("W", title='Chain 1 Entry Timeframe', group="Chain 1")
tf1_exit = input.timeframe("D", title='Chain 1 Exit Timeframe', group="Chain 1")
Chain 2:
Entry Timeframe: 12 Hours
Exit Timeframe: 9 Hours
tf2_entry = input.timeframe("720", title='Chain 2 Entry Timeframe (12H)', group="Chain 2")
tf2_exit = input.timeframe("540", title='Chain 2 Exit Timeframe (9H)', group="Chain 2")
Set the Backtesting Period:
Define the period over which you want to backtest the strategy. This allows you to see how the strategy would have performed historically.
startDate = input.time(timestamp('2015-07-27'), title="StartDate")
finishDate = input.time(timestamp('2026-01-01'), title="FinishDate")
Step 3: Analyze the Signals
Understand the Entry and Exit Signals:
Buy Signals: When the price crosses above the entry EMA, the strategy generates a buy signal.
bullishChain1 = enableChain1 and ta.crossover(src1, entryEMA1)
Sell Signals: When the price crosses below the exit EMA, the strategy generates a sell signal.
bearishChain2 = enableChain2 and ta.crossunder(src2, entryEMA2)
Review the Visual Indicators:
The strategy plots buy and sell signals on the chart with labels for easy identification:
BUY C1/C2 for buy signals from Chain 1 and Chain 2.
SELL C1/C2 for sell signals from Chain 1 and Chain 2.
This visual aid helps you quickly understand when and why trades are being executed.
Step 4: Optimize the Strategy
Backtest Results:
Review the strategy’s performance over the backtesting period. Look at key metrics like net profit, drawdown, and trade statistics to evaluate its effectiveness.
Adjust the EMA lengths, timeframes, and other settings to see how changes affect the strategy’s performance.
Customize for Live Trading:
Once satisfied with the backtest results, you can apply the strategy settings to live trading. Remember to continuously monitor and adjust as needed based on market conditions.
Step 5: Implement Risk Management
Use Realistic Position Sizing:
Keep your risk exposure per trade within a comfortable range, typically between 1-2% of your trading capital.
Set Alerts:
Set up alerts for buy and sell signals, so you don’t miss trading opportunities.
Paper Trade First:
Consider running the strategy in a paper trading account to understand its behavior in real market conditions before committing real capital.
This dual-layered approach offers a distinct advantage: it enables the strategy to adapt to varying market conditions by capturing both broad trends and immediate price action without one chain's activity impacting the other's decision-making process. The independence of these chains in executing transactions adds a level of sophistication and flexibility that is rarely seen in more conventional trading systems, making the Dual Chain Strategy not just unique, but a powerful tool for traders seeking to navigate complex market environments.
Three Drive Pattern Detector [LuxAlgo]The Three Drives Pattern Detector indicator focuses on detecting and displaying completed Three Drives patterns on the user chart. This harmonic pattern is characterized by successive higher highs / lower lows following specific ratios.
The script uses a multi-length swing detection approach, as well as adjusting ratios to ensure flexibility and a maximum number of visible Three Drives patterns.
🔶 USAGE
The bullish/bearish Three Drives pattern is commonly interpreted as a reversal pattern and is characterized by three extensions (drives) and two intermediary retracements creating consecutive higher lows (for a bullish case) or lower highs (for a bearish case).
The multi-length swing detection approach taken by the indicator allows for detecting shorter-term alongside medium/longer-term patterns simultaneously, allowing to increase in the amount of detected patterns.
Users can set a Minimum Swing length (for example 2) and a Maximum Swing length (for example 100) which defines the range of the swing point detection length, higher values for these settings will detect longer-term Three-Drives patterns, while a larger range will allow for the detection of a larger number of patterns.
Sometimes multiple dashed lines as the last segment can be observed. This means multiple Three Drives patterns sharing multiple swing points have formed, with only the last segment being different.
🔹 Retracement/Extension Ratios
The Three Drives pattern often associates the retracement/extension to Fibonacci ratios of respectively 0.618/1.272.
Some sources specify a maximum retracement/extension level of 0.786/1.618, which means the retracement should be within the 0.618-0.786 range and the extension between 1.272-1.618.
Since finding a pattern where the retracement/extension is precisely at the 0.618/1.272 levels, or even between 0.618-0.786/1.272-1.618 is rare, the script allows users to adjust those ratios, which ensures more flexibility. Depending on the widening/tightening of the ratios, allowing users to find more patterns (but potentially less valid) or more valid (but fewer patterns).
In the example above, " Show Ratios " is set to " Ratios With Margin ", showing the ideal retracement/extension level together with the margin, while in the example below, " Show Ratios " is set to " Ratios ", which shows only a line where the price should ideally reverse.
While setting the ratios wider will result in more frequent but less valid patterns, it can also create good trading opportunities.
🔹 Best Practices
The indicator doesn't include Stop Loss (SL) or Take Profit (TP) levels, however, the 1.618 Fibonacci Extension level of the last leg can commonly be used as stop loss.
Typical Take Profit areas include:
Starting point of the pattern
Each retracement level (2x)
The 0.618 retracement level of the complete pattern
In the above bullish examples, the price was lower than the lowest point of the pattern. The price reversed and attained all TP levels without hitting the SL level.
In the above bearish example, the price went above the highest point of the pattern but did not hit the SL level, after which two TP levels were hit. Then, the price quickly went up, just missing the SL level before it came back down again, hitting the last 2 TP levels.
This example shows that other Fibonacci levels an also be effective when combined with the Three Drives pattern, even in the longer term.
🔶 DETAILS
🔹 Multi Length
The core of this publication is the multi-length swing detection. To ensure the maximum amount of Three Drives patterns are found, up to 99 different swing length periods can be used to detect swing points which are then tested for valid patterns.
Using a wider variety of swing points also ensures that patterns visible only with specific Swing settings can be found on the same chart without the user needing to constantly adjust the Swing settings to find other patterns.
The user only needs to set the desired minimum and maximum Swing Length.
In this case, swing detection using swing Lengths from 3 to 100 (97 different) are computed and evaluated for patterns. Three different patterns were found on the same chart, with swing lengths 3, 4, and 6.
Note: The Maximum Swing length should be equal to or higher than the Minimum Swing Length . If the maximum value is lower than the minimum, the script will automatically take the minimum value as the maximum to prevent errors.
🔹 Width Margin %
Users can filter out patterns based on the duration of each extension/retracement segment. When the users want segments of the detected patterns to be of a similar duration, the width percentage should be set lower. When the focus is on detecting more patterns the width percentage can be set higher.
🔹 Retracement/Extension Settings
Show Ratios , set to Ratios , show the ideal Fibonacci retracement/extension level, while Ratios With Margin (example below) show the additional margins for retracement/extension.
The upper and lower limits can be visualized while hovering over the calculated ratio label.
The dashed line shows an older pattern, where the last leg has been updated.
🔹 Last Known Pattern
The included dashboard highlights the date of the most recently detected pattern; the text will show " None " if no pattern is found.
🔹 Calculated Bars
The "Calculated Bars" setting makes use of the recently introduced calc_bars_count parameter, making it possible to effectively reduce the number of historical bars during the computation of the script, which significantly improves the loading speed of the script.
Users wishing to see the most recent patterns can set this setting to 1000 for example, where only the most recent 1000 bars are used to find patterns. If every bar must be used for pattern detection, set " Calculated bars " at 0.
🔶 SETTINGS
Minimum Swing Length: Minimum length used for the swing detection.
Maximum Swing Length: Maximum length used for the swing detection.
Retracement: Range of required ratios used for testing retracements.
Extension: Range of required ratios used for testing extensions.
Width Margin: Influences the symmetry of the pattern; with a higher number allowing for less symmetry.
🔹 Style
Text Size: Text size of the ratio labels.
Show Ratios: Show the ideal ratio, upper/lower limit of ratios, or none.
🔹 Dashboard
Show Dashboard: Toggle dashboard which shows the date of the last found pattern.
Location: Location of the dashboard on the chart.
Size: Text size.
🔹 Calculation
Calculated Bars: Allows the usage of fewer bars for performance/speed improvement.
Prometheus Black-Scholes Option PricesThe Black-Scholes Model is an option pricing model developed my Fischer Black and Myron Scholes in 1973 at MIT. This is regarded as the most accurate pricing model and is still used today all over the world. This script is a simulated Black-Scholes model pricing model, I will get into why I say simulated.
What is an option?
An option is the right, but not the obligation, to buy or sell 100 shares of a certain stock, for calls or puts respective, at a certain price, on a certain date (assuming European style options, American options can be exercised early). The reason these agreements, these contracts exist is to provide traders with leverage. Buying 1 contract to represent 100 shares of the underlying, more often than not, at a cheaper price. That is why the price of the option, the premium , is a small number. If an option costs $1.00 we pay $100.00 for it because 100 shares * 1 dollar per share = 100 dollars for all the shares. When a trader purchases a call on stock XYZ with a strike of $105 while XYZ stock is trading at $100, if XYZ stock moves up to $110 dollars before expiration the option has $5 of intrinsic value. You have the right to buy something at $105 when it is trading at $110. That agreement is way more valuable now, as a result the options premium would increase. That is a quick overview about how options are traded, let's get into calculating them.
Inputs for the Black-Scholes model
To calculate the price of an option we need to know 5 things:
Current Price of the asset
Strike Price of the option
Time Till Expiration
Risk-Free Interest rate
Volatility
The price of a European call option 𝐶 is given by:
𝐶 = 𝑆0 * Φ(𝑑1) − 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(𝑑2)
where:
𝑆0 is the current price of the underlying asset.
𝐾 is the strike price of the option.
𝑟 is the risk-free interest rate.
𝑇 is the time to expiration.
Φ is the cumulative distribution function of the standard normal distribution.
𝑑1 and 𝑑2 are calculated as:
𝑑1 = (ln(𝑆0 / 𝐾) + (𝑟 + (𝜎^2 / 2)) * 𝑇) / (𝜎 * sqrt(𝑇))
𝑑2= 𝑑1 - (𝜎 * sqrt(𝑇))
𝜎 is the volatility of the underlying asset.
The price of a European put option 𝑃 is given by:
𝑃 = 𝐾 * 𝑒^(−𝑟 * 𝑇) * Φ(−𝑑2) − 𝑆0 * Φ(−𝑑1)
where 𝑑1 and 𝑑2 are as defined above.
Key Assumptions of the Black-Scholes Model
The price of the underlying asset follows a lognormal distribution.
There are no transaction costs or taxes.
The risk-free interest rate and volatility of the underlying asset are constant.
The underlying asset does not pay dividends during the life of the option.
The markets are efficient, meaning that all known information is already reflected in the prices.
Options can only be exercised at expiration (European-style options).
Understanding the Script
Here I have arrows pointing to specific spots on the table. They point to Historical Volatility and Inputted DTE . Inputted DTE is a value the user may input to calculate premium for options that expire in that many days. Historical Volatility , is the value calculated by this code.
length = 252 // One year of trading days
hv = ta.stdev(math.log(close / close ), length) * math.sqrt(365)
And then made daily like the Black-Scholes model needs from this step in the code.
hv_daily = request.security(syminfo.tickerid, "1D", hv)
The user has the option to input their own volatility to the Script. I will get into why that may be advantageous in a moment. If the user chooses to do so the Script will change which value it is using as so.
hv_in_use = which_sig == false ? hv_daily : sig
There is a lot going on in this image but bare with me, it will all make sense by the end. The column to the far left of both the green and maroon colored columns represent the strike price of the contract, if the numbers are white that means the contract is out of the money, gray means in the money. If you remember from the calculation this represents the price to buy or sell shares at, for calls or puts respective. The column second from the left shows a value for Simulated Market Price . This is a necessary part of this script so we can show changes in implied volatility. See, when we go to our brokerages and look at options prices, sure the price was calculated by a pricing model, but that is rarely the true price of the model. Market participant sentiment affects this value as their estimates for future volatility, Implied Volatility changes.
For example, if a call option is supposed to be worth $1.00 from the pricing model, however everyone is bullish on the stock and wants to buy calls, the premium may go to $1.20 from $1.00 because participants juice up the Implied Volatility . Higher Implied Volatility generally means higher premium, given enough time to expiration. Buying an option at $0.80 when it should be worth $1.00 due to changes in sentiment is a big part of the Quant Trading industry.
Of course I don't have access to an actual exchange so get prices, so I modeled participant decisions by adding or subtracting a small random value on the "perfect premium" from the Black-Scholes model, and solving for implied volatility using the Newton-Raphson method.
It is like when we have speed = distance / time if we know speed and time , we can solve for distance .
This is what models the changing Implied Volatility in the table. The other column in the table, 3rd from the left, is the Black-Scholes model price without the changes of a random number. Finally, the 4th column from the left is that Implied Volatility value we calculated with the modified option price.
More on Implied Volatility
Implied Volatility represents the future expected volatility of an asset. As it is the value in the future it is not know like Historical Volatility, only projected. We provide the user with the option to enter their own Implied Volatility to start with for better modeling of options close to expiration. If you want to model options 1 day from expiration you will probably have to enter a higher Implied Volatility so that way the prices will be higher. Since the underlying is so close to expiration they are traded so much and traders manipulate their Implied Volatility , increasing their value. Be safe while trading these!
Thank you all for clicking on my indicator and reading this description! Happy coding, Happy trading, Be safe!
Good reference: www.investopedia.com
Supports & Resistances [UAlgo]The "Supports & Resistances " indicator is designed to identify and visualize key support and resistance levels on the price chart. It utilizes the Average True Range (ATR) and Pivot Points to define the boundaries of S & R zones and considers historical price action to assess the strength of these zones.
🔶 How to Obtain Zones
The script continuously analyzes the price action and identifies potential support and resistance zones based on the following criteria:
Zone Creation: For swing highs, a zone is created with the high price at the zone length as the top and the top minus the Average True Range (ATR) as the bottom. Conversely, for swing lows, the zone is created with the low price at the zone length as the bottom and the low plus the ATR as the top.
Zone Strength Calculation: The script iterates through historical bars within the zone and counts how many times the price (low for support, high for resistance) touched but failed to break entirely through the zone. This count is assigned as the zone's "strength".
Zone Display and Removal: It identifying zones by assigning a "strength" value based on how many times the price has approached but failed to break the zone. This helps prioritize stronger potential support/resistance levels. Only zones exceeding the defined "strength threshold" are visually displayed on the chart. Weaker zones or those broken by price are automatically removed.
🔶 Parameters
Zone Length: Traders can adjust S & R detection sensitivity, length to be used to find pivot points.
Strength Threshold: Set the minimum number of times the price needs to touch but fail to break a zone for it to be considered "strong" and displayed.
Visual Settings: Tailor the appearance of the support/resistance zones by defining separate colors and text size for borders, backgrounds, and zone text.
🔶 Disclaimer
The "Supports & Resistances " indicator is provided for educational and informational purposes only.
It should not be considered as financial advice or a recommendation to buy or sell any financial instrument.
The use of this indicator involves inherent risks, and users should employ their own judgment and conduct their own research before making any trading decisions. Past performance is not indicative of future results.
🔷 Related Scripts
Support and Resistance with Signals
ATR Based Support and Resistance Zones
Fibonacci Period Range [UkutaLabs]█ OVERVIEW
The Fibonacci Period Range Indicator is a powerful trading tool that draws levels of support and resistance that are based on key Fibonacci levels. The script will identify the high and low of a range that is specified by the user, then draw several levels of support and resistance based on Fibonacci levels.
The script will also draw extension levels outside of the specified range that are also based on Fibonacci levels. These extension levels can be turned off in the indicator settings.
Each level is also labelled to help traders understand what each line represents. These labels can be turned off in the indicator settings.
The purpose of this script is to simplify the trading experience of users by giving them the ability to customize the time period that is identified, then draw levels of support and resistance that are based on the price action during this time.
█ USAGE
In the indicator settings, the user has access to a setting called Session Range. This gives users control over the range that will be used.
The script will then identify the high and low of the range that was specified and draw several levels of support and resistance based on Fibonacci levels between this range. The user can also choose to have extension levels that display more levels outside of the range.
These lines will extend until the end of the current trading day at 5:00 pm EST.
█ SETTINGS
Configuration
• Display Mode: Determines the number of days that will be displayed by the script.
• Show Labels: Determines whether or not identifying labels will be displayed on each line.
• Font Size: Determines the text size of labels.
• Label Position: Determines the justification of labels.
• Extension Levels: Determines whether or not extension levels will be drawn outside of the high and low of the specified range.
Session
• Session Range: Determines the time period that will be used for calculations.
• Timezone Offset (+/-): Determines how many hours the session should be offset by.
Speedometer RevisitedSpeedometer Revisited is a new way to draw custom metric speedometers and is intended to be a utility for other coders to use.
@rumpypumpydumpy originally introduced the Speedometer Toolkit in version 4 of Pine Script. Since then, Pine Script has been updated to version 5, introducing some amazing new features such as polylines and chart.points. This indicator is an example of what can be done with these newer features.
The indicator starts off with a handful of functions that will be used to create the drawings. Notes are left throughout the code explaining what each line of the functions does. My goal was to make these functions user-friendly and somewhat easy to understand. I then demonstrate two examples: one speedometer with five segments and another with three.
The first example demonstrates how to visually represent the analysts' ratings for a stock using the built-in syminfo.recommendations. The speedometer is divided into five segments, each representing a different level of analyst recommendation: strong sell, sell, hold, buy, and strong buy.
Each segment is drawn using a polyline from the createSeg function, with colors assigned as follows:
Red for 'Strong Sell'
Maroon for 'Sell'
Yellow for 'Hold'
Green for 'Buy'
Lime for 'Strong Buy'
The script identifies the maximum value among the analyst ratings, calculates the midpoint of the corresponding segment, and draws a needle pointing to this midpoint.
The second example employs the speedometer design to display market sentiment through the put-call ratio. The put-call ratio is a gauge of investor sentiment, where values above 1 indicate a bearish sentiment (more puts being bought relative to calls), and values below 1 suggest a bullish outlook (more calls being bought relative to puts).
The speedometer is divided into three segments, reflecting different ranges of the put-call ratio:
Red for a ratio greater than 1 (bearish sentiment)
Yellow for a ratio between 0.8 and 1 (neutral to bearish sentiment)
Lime for a ratio less than 0.8 (bullish sentiment)
Depending on the value of the put-call ratio, the script calculates which segment the current value falls into and determines the appropriate segment number. The script calculates the midpoint of the selected segment and draws a needle pointing to this value.
Both examples show how the speedometer can be used as a visual indicator of certain market conditions, helping traders quickly recognize trends and adjust their strategies accordingly.
A big thanks to @rumpypumpydumpy for his original Speedometer Toolbox. I hope this take on it can be useful for other coders.
