Stock ETF Tracker 2.0The Stock Sector ETF tracker with Indicators is a versatile tool designed to track the performance of sector-specific ETFs relative to the current asset. It automatically identifies the sector of the underlying symbol and displays the corresponding ETF’s price action alongside key technical indicators. This helps traders analyze sector trends and correlations in real time.
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Key Features
Automatic Sector Detection:
Fetches the sector of the current asset (e.g., "Technology" for AAPL).
Maps the sector to a user-defined ETF (default: SPDR sector ETFs) .
Technical Indicators:
Simple Moving Average (SMA): Tracks the ETF’s trend.
Bollinger Bands: Highlights volatility and potential reversals.
Donchian High (52-Week High): Identifies long-term resistance levels.
SPY Regime Filter: Red background color if SP500 is below 200 day SMA.
Customizable Inputs:
Adjust indicator parameters (length, visibility).
Override default ETFs for specific sectors.
Informative Table:
Displays the current sector and ETF symbol in the bottom-right corner.
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Input Settings
SMA Settings
SMA Length: Period for calculating the Simple Moving Average (default: 200).
Show SMA: Toggle visibility of the SMA line.
Bollinger Bands Settings
BB Length: Period for Bollinger Bands calculation (default: 20).
BB Multiplier: Standard deviation multiplier (default: 2.0).
Show Bollinger Bands: Toggle visibility of the bands.
Donchian High (52-Week High)
Daily High Length: Days used to calculate the high (default: 252, approx. 1 year).
Show High: Toggle visibility of the 52-week high line.
Sector Selections
Customize ETFs for each sector (e.g., replace XLU with another utilities ETF).
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Example Use Cases
Trend Analysis: Compare a stock’s price action to its sector ETF’s SMA for trend confirmation.
Volatility Signals: Use Bollinger Bands to spot ETF price squeezes or breakouts.
Sector Strength: Monitor if the ETF is approaching its 52-week high to gauge sector momentum.
Enjoy tracking sector trends with ease! 🚀
ค้นหาในสคริปต์สำหรับ " TABLE"
Stock Sector ETF with IndicatorsThe Stock Sector ETF with Indicators is a versatile tool designed to track the performance of sector-specific ETFs relative to the current asset. It automatically identifies the sector of the underlying symbol and displays the corresponding ETF’s price action alongside key technical indicators. This helps traders analyze sector trends and correlations in real time.
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Key Features
Automatic Sector Detection:
Fetches the sector of the current asset (e.g., "Technology" for AAPL).
Maps the sector to a user-defined ETF (default: SPDR sector ETFs) .
Technical Indicators:
Simple Moving Average (SMA): Tracks the ETF’s trend.
Bollinger Bands: Highlights volatility and potential reversals.
Donchian High (52-Week High): Identifies long-term resistance levels.
Customizable Inputs:
Adjust indicator parameters (length, visibility).
Override default ETFs for specific sectors.
Informative Table:
Displays the current sector and ETF symbol in the bottom-right corner.
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Input Settings
SMA Settings
SMA Length: Period for calculating the Simple Moving Average (default: 200).
Show SMA: Toggle visibility of the SMA line.
Bollinger Bands Settings
BB Length: Period for Bollinger Bands calculation (default: 20).
BB Multiplier: Standard deviation multiplier (default: 2.0).
Show Bollinger Bands: Toggle visibility of the bands.
Donchian High (52-Week High)
Daily High Length: Days used to calculate the high (default: 252, approx. 1 year).
Show High: Toggle visibility of the 52-week high line.
Sector Selections
Customize ETFs for each sector (e.g., replace XLU with another utilities ETF).
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Example Use Cases
Trend Analysis: Compare a stock’s price action to its sector ETF’s SMA for trend confirmation.
Volatility Signals: Use Bollinger Bands to spot ETF price squeezes or breakouts.
Sector Strength: Monitor if the ETF is approaching its 52-week high to gauge sector momentum.
Enjoy tracking sector trends with ease! 🚀
Position Size Calculator (MOEX Futures)Описание на русском языке
Этот скрипт для TradingView создан специально для трейдеров, работающих с фьючерсами на Московской бирже. Его основная цель – помочь трейдерам быстро и точно рассчитывать параметры позиции, такие как количество контрактов, риск на сделку, общий размер маржи, а также цены стоп-лосса и тейк-профита.
Функционал:
Расчет цены контракта: учитывает цену актива (в пунктах) и стоимость одного пункта.
Риск на сделку: определяется как процент от общего капитала.
Размер позиции: рассчитывается на основе риска на сделку и стоп-лосса.
Количество контрактов: округляется до целого числа вниз.
Общий размер маржи: определяется исходя из количества контрактов и маржи на один контракт.
Цены стоп-лосса и тейк-профита: вычисляются как для лонг-, так и для шорт-позиций.
Интерактивная таблица: статично отображается в правом верхнем углу графика и обновляется автоматически при изменении входных данных.
Скрипт заточен исключительно под специфику фьючерсов Московской биржи и позволяет трейдерам оптимизировать расчёты, минимизировать ошибки и экономить время.
Description in English
This TradingView script is specifically designed for traders working with futures on the Moscow Exchange. Its primary purpose is to help traders quickly and accurately calculate position parameters, such as the number of contracts, risk per trade, total margin size, and stop-loss and take-profit prices.
Features:
Contract price calculation: Takes into account the asset price (in points) and the price per point.
Risk per trade: Defined as a percentage of the total capital.
Position size: Calculated based on the risk per trade and stop-loss percentage.
Number of contracts: Rounded down to the nearest whole number.
Total margin size: Determined based on the number of contracts and margin per contract.
Stop-loss and take-profit prices: Calculated for both long and short positions.
Interactive table: Statically displayed in the top-right corner of the chart and dynamically updated when input parameters change.
This script is tailored exclusively to the specifics of futures trading on the Moscow Exchange, enabling traders to optimize calculations, minimize errors, and save time.
Candle 1 2 3 on XAUUSD (by Veronica)Description
Discover the Candle 1 2 3 Strategy, a simple yet effective trading method tailored exclusively for XAUUSD on the 15-minute timeframe. Designed by Veronica, this strategy focuses on identifying key reversal and continuation patterns during the London and New York sessions, making it ideal for traders who prioritise high-probability entries during these active market hours.
Key Features:
1. Session-Specific Trading:
The strategy operates strictly during London (03:00–06:00 UTC) and New York (08:30–12:30 UTC) sessions, where XAUUSD tends to show higher volatility and clearer price movements.
Pattern Criteria:
- Works best if the first candle is NOT a pin bar or a doji.
- Third candle should either:
a. Be a marubozu (large body with minimal wicks).
a. Have a significant body with wicks, ensuring the close of the third candle is above Candle 2 (for Buy) or below Candle 2 (for Sell).
Callout Labels and Alerts:
Automatic Buy and Sell labels are displayed on the chart during qualifying sessions, ensuring clarity for decision-making.
Integrated alerts notify you of trading opportunities in real-time.
Risk Management:
Built-in Risk Calculator to estimate lot sizes based on your account size, risk percentage, and stop-loss levels.
Customizable Table:
Displays your calculated lot size for various stop-loss pip values, making risk management seamless and efficient.
How to Use:
1. Apply the indicator to XAUUSD (M15).
2. Focus on setups appearing within the London and New York sessions only.
3. Ensure the first candle is neither a pin bar nor a doji.
4. Validate the third candle's body placement:
For a Buy, the third candle’s close must be above the second candle.
For a Sell, the third candle’s close must be below the second candle.
5. Use the generated alerts to streamline your entry process.
Notes:
This strategy is meant to complement your existing knowledge of market structure and price action.
Always backtest thoroughly and adjust parameters to fit your personal trading style and risk tolerance.
Credit:
This strategy is the intellectual property of Veronica, developed specifically for XAUUSD (M15) traders seeking precision entries during high-volume sessions.
CauchyTrend [InvestorUnknown]The CauchyTrend is an experimental tool that leverages a Cauchy-weighted moving average combined with a modified Supertrend calculation. This unique approach provides traders with insight into trend direction, while also offering an optional ATR-based range analysis to understand how often the market closes within, above, or below a defined volatility band.
Core Concepts
Cauchy Distribution and Gamma Parameter
The Cauchy distribution is a probability distribution known for its heavy tails and lack of a defined mean or variance. It is characterized by two parameters: a location parameter (x0, often 0 in our usage) and a scale parameter (γ, "gamma").
Gamma (γ): Determines the "width" or scale of the distribution. Smaller gamma values produce a distribution more concentrated near the center, giving more weight to recent data points, while larger gamma values spread the weight more evenly across the sample.
In this indicator, gamma influences how much emphasis is placed on values closer to the current price versus those further away in time. This makes the resulting weighted average either more reactive or smoother, depending on gamma’s value.
// Cauchy PDF formula used for weighting:
// f(x; γ) = (1/(π*γ)) *
f_cauchyPDF(offset, gamma) =>
numerator = gamma * gamma
denominator = (offset * offset) + (gamma * gamma)
pdf = (1 / (math.pi * gamma)) * (numerator / denominator)
pdf
A chart showing different Cauchy PDFs with various gamma values, illustrating how gamma affects the weight distribution.
Cauchy-Weighted Moving Average (CWMA)
Using the Cauchy PDF, we calculate normalized weights to create a custom Weighted Moving Average. Each bar in the lookback period receives a weight according to the Cauchy PDF. The result is a Cauchy Weighted Average (cwm_avg) that differs from typical moving averages, potentially offering unique sensitivity to price movements.
// Summation of weighted prices using Cauchy distribution weights
cwm_avg = 0.0
for i = 0 to length - 1
w_norm = array.get(weights, i) / sum_w
cwm_avg += array.get(values, i) * w_norm
Supertrend with a Cauchy Twist
The indicator integrates a modified Supertrend calculation using the cwm_avg as its reference point. The Supertrend logic typically sets upper and lower bands based on volatility (ATR), and flips direction when price crosses these bands.
In this case, the Cauchy-based average replaces the usual baseline, aiming to capture trend direction via a different weighting mechanism.
When price closes above the upper band, the trend is considered bullish; closing below the lower band signals a bearish trend.
ATR Stats Range (Optional)
Beyond the fundamental trend detection, the indicator optionally computes ATR-based stats to understand price distribution relative to a volatility corridor centered on the cwm_avg line:
Volatility Range:
Defined as cwm_avg ± (ATR * atr_mult), this range creates upper and lower bands. Turning on atr_stats computes how often the daily close falls: Within the range, Above the upper ATR boundary, Below the lower ATR boundary, Within the range but above cwm_avg, Within the range but below cwm_avg
These statistics can help traders gauge how the market behaves relative to this volatility envelope and possibly identify if the market tends to revert to the mean or break out more often.
Backtesting and Performance Metrics
The code is integrated with a backtesting library that allows users to assess strategy performance historically:
Equity Curve Calculation: Compares CauchyTrend-based signals against the underlying asset.
Performance Metrics Table: Once enabled, displays key metrics such as mean returns, Sharpe Ratio, Sortino Ratio, and more, comparing the strategy to a simple Buy & Hold approach.
Alerts and Notifications
The indicator provides Alerts for key events:
Long Alert: Triggered when the trend flips bullish.
Short Alert: Triggered when the trend flips bearish.
Customization and Calibration
Important: The default parameters are not optimized for any specific instrument or time frame. Traders should:
Adjust the length and gamma parameters to influence how sharply or broadly the cwm_avg reacts to price changes.
Tune the atr_len and atr_mult for the Supertrend logic to better match the asset’s volatility characteristics.
Experiment with atr_stats on/off to see if that additional volatility distribution information provides helpful insights.
Traders may find certain sets of parameters that align better with their preferred trading style, risk tolerance, or asset volatility profile.
Disclaimer: This indicator is for educational and informational purposes only. Past performance in backtesting does not guarantee future results. Always perform due diligence, and consider consulting a qualified financial advisor before trading.
Trend Speed Analyzer (Zeiierman)█ Overview
The Trend Speed Analyzer by Zeiierman is designed to measure the strength and speed of market trends, providing traders with actionable insights into momentum dynamics. By combining a dynamic moving average with wave and speed analysis, it visually highlights shifts in trend direction, market strength, and potential reversals. This tool is ideal for identifying breakout opportunities, gauging trend consistency, and understanding the dominance of bullish or bearish forces over various timeframes.
█ How It Works
The indicator employs a Dynamic Moving Average (DMA) enhanced with an Accelerator Factor, allowing it to adapt dynamically to market conditions. The DMA is responsive to price changes, making it suitable for both long-term trends and short-term momentum analysis.
Key components include:
Trend Speed Analysis: Measures the speed of market movements, highlighting momentum shifts with visual cues.
Wave Analysis: Tracks bullish and bearish wave sizes to determine market strength and bias.
Normalized Speed Values: Ensures consistency across different market conditions by adjusting for volatility.
⚪ Average Wave and Max Wave
These metrics analyze the size of bullish and bearish waves over a specified Lookback Period:
Average Wave: This represents the mean size of bullish and bearish movements, helping traders gauge overall market strength.
Max Wave: Highlights the largest movements within the period, identifying peak momentum during trend surges.
⚪ Current Wave Ratio
This feature compares the current wave's size against historical data:
Average Wave Ratio: Indicates if the current momentum exceeds historical averages. A value above 1 suggests the trend is gaining strength.
Max Wave Ratio: Shows whether the current wave surpasses previous peak movements, signaling potential breakouts or trend accelerations.
⚪ Dominance
Dominance metrics reveal whether bulls or bears have controlled the market during the Lookback Period:
Average Dominance: Compares the net difference between average bullish and bearish wave sizes.
Max Dominance: Highlights which side had the stronger individual waves, indicating key power shifts in market dynamics.
Positive values suggest bullish dominance, while negative values point to bearish control. This helps traders confirm trend direction or anticipate reversals.
█ How to Use
Identify Trends: Leverage the color-coded candlesticks and dynamic trend line to assess the overall market direction with clarity.
Monitor Momentum: Use the Trend Speed histogram to track changes in momentum, identifying periods of acceleration or deceleration.
Analyze Waves: Compare the sizes of bullish and bearish waves to identify the prevailing market bias and detect potential shifts in sentiment. Additionally, fluctuations in Current Wave ratio values should be monitored as early indicators of possible trend reversals.
Evaluate Dominance: Utilize dominance metrics to confirm the strength and direction of the current trend.
█ Settings
Maximum Length: Sets the smoothing of the trend line.
Accelerator Multiplier: Adjusts sensitivity to price changes.
Lookback Period: Defines the range for wave calculations.
Enable Table: Displays statistical metrics for in-depth analysis.
Enable Candles: Activates color-coded candlesticks.
Collection Period: Normalizes trend speed values for better accuracy.
Start Date: Limits calculations to a specific timeframe.
Timer Option: Choose between using all available data or starting from a custom date.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
LiquidFusion SignalPro [CHE] LiquidFusion SignalPro – Indicator Overview
The LiquidFusion SignalPro is a powerful and sophisticated TradingView indicator designed to identify high-quality trade entries and exits. By combining seven unique sub-indicators, it provides comprehensive market analysis, ensuring traders can make informed decisions. This tool is suitable for all market conditions and supports customization to fit individual trading strategies.
Key Components (Sub-Indicators):
1. RPM (Relative Price Momentum):
- Measures cumulative price momentum over a specified period.
- Provides insights into price strength and directional bias.
- Input Customization:
- Source: Data for momentum calculation.
- Period: Length for momentum measurement.
- Resolution: Timeframe for data fetching.
2. BBO (Bull-Bear Oscillator):
- Calculates the strength of bullish or bearish momentum based on price movement and RSI conditions.
- Uses a super-smoothing technique for reliable signals.
- Customizable parameters include the oscillator's period and repainting options.
3. MACD (Moving Average Convergence Divergence):
- A classic momentum indicator for trend direction and strength.
- Provides buy/sell signals based on the crossover of the MACD line and signal line.
- Input Customization:
- Fast/Slow EMA Periods.
- Signal Line Period.
- Resolution and Source Data.
4. RSI (Relative Strength Index):
- Tracks overbought and oversold conditions.
- A key tool to validate trend continuation or reversals.
- Customizable period, resolution, and source.
5. CCI (Commodity Channel Index):
- Measures the deviation of price from its average.
- Useful for identifying cyclical trends.
- Input Customization includes period, resolution, and source.
6. Stochastic Oscillator:
- Indicates momentum by comparing closing prices to a range of highs and lows.
- Includes smoothing factors for %K and %D lines.
- Customizable parameters:
- %K Length and Smoothing.
- Resolution and Repainting Options.
7. Supertrend:
- A trailing stop-and-reverse system for trend-following strategies.
- Excellent for identifying strong trends and potential reversals.
- Inputs include the multiplier factor and period for ATR-like calculations.
Inputs Overview:
The indicator supports extensive customization for each sub-indicator, grouped under intuitive categories:
- Color Settings: Define bullish and bearish plot colors.
- RPM, BBO, MACD, RSI, CCI, Stochastic, and Supertrend Settings: Tailor each sub-indicator's behavior with adjustable parameters.
- UI Options: Toggle features such as bar coloring, indicator names, and plotted candles.
Trade Signals:
- Long Signal:
- All indicators align in a bullish state:
- RPM > 0, MACD > 0, RSI > 50, Stochastic > 50, CCI > 0, BBO > 0, Supertrend below price.
- Plot: Green triangle below the candle.
- Alert: Notifies the trader of a potential long entry.
- Short Signal:
- All indicators align in a bearish state:
- RPM < 0, MACD < 0, RSI < 50, Stochastic < 50, CCI < 0, BBO < 0, Supertrend above price.
- Plot: Red triangle above the candle.
- Alert: Notifies the trader of a potential short entry.
Features:
- Enhanced Visuals: Plots sub-indicator statuses using labels and color-coded shapes for clarity.
- Alerts: Integrated alert conditions for both long and short trades.
- Bar Coloring: Provides overall trend bias with green (bullish), red (bearish), or gray (neutral) bars.
- Customizable Table: Displays the indicator's status in the chart’s top-right corner.
Trading Benefits:
The LiquidFusion SignalPro excels in generating high-quality entries and exits by:
- Reducing noise through multiple indicator alignment.
- Supporting multiple timeframes and resolutions for flexibility.
- Offering customizable inputs for personalized trading strategies.
Use this tool to enhance your market analysis and improve your trading performance.
Disclaimer:
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
This indicator is inspired by the Super 6x Indicators: RSI, MACD, Stochastic, Loxxer, CCI, and Velocity . A special thanks to Loxx for their relentless effort, creativity, and contributions to the TradingView community, which served as a foundation for this work.
Happy trading and best regards
Chervolino
Sequence Waves [OmegaTools]the sequence waves indicator, developed by omegatools, is a multi-functional tool designed to detect trends, sequences, and potential reversal signals based on price movements and volume. this indicator has two main modes, "trend" and "sequence," which determine how the indicator calculates directional changes. additional enhancements in this version include reversal signals, allowing users to identify potential long and short opportunities with specific entry cues.
input parameters
mode (mode): chooses the calculation basis for directional movement.
- "trend": uses a midline calculated from the highest high and lowest low over the "trend mode length" period to assess if the price is in an upward or downward trend.
- "sequence": compares the current price to the closing price of the previous "sequence mode length" period to detect shifts in direction.
counter mode (modec): sets whether the counter increments by a fixed amount (1 or -1) or the volume of the bar, impacting the indicator’s sensitivity.
- "fixed": increments or decrements the counter by 1.
- "volume": increments or decrements based on the period’s volume, making the indicator more responsive to high-volume periods.
percentile length (lntp): defines the lookback period for calculating overbought and oversold thresholds using a percentile method. shorter lengths make ob/os levels more reactive.
sensitivity (sens): controls the percentile-based ob/os thresholds, ranging from 10 to 100. higher values narrow ob/os zones, while lower values widen them, impacting signal frequency.
trend mode length (lnt1): sets the period length for midline calculation in trend mode, defaulting to 21. longer periods smooth the midline for detecting major trends.
sequence mode length (lnt2): sets the lookback period in sequence mode, with a default of 4. shorter lengths capture more frequent directional changes, while longer lengths smooth signals.
visual colors:
- up color (upc): sets the color for upward movements.
- down color (dnc): sets the color for downward movements.
calculation logic
midline calculation: in trend mode, a midline is derived from the average of the highest high and lowest low over the "trend mode length" period, acting as a reference to detect upward or downward movements.
counter calculation:
- in trend mode, if the close price is above the midline, the counter increases (or volume if volume mode is selected). it decreases when the price is below.
- in sequence mode, the counter increases if the close is above the closing price from "sequence mode length" periods ago and decreases if below.
the counter resets to zero on direction changes, creating clear directional transitions.
overbought/oversold percentiles: separate arrays track the counter’s values each time the direction changes, creating historical up and down values. ob and os thresholds are dynamically determined based on these arrays, with sizes limited by the percentile length and sensitivity inputs.
reversal signals: two new variables, "long" and "short," detect potential reversal points when the counter crosses specific thresholds:
- long: a long signal is generated when the counter switches to positive and exceeds the down percentile.
- short: a short signal is triggered when the counter switches to negative and exceeds the up percentile.
visual and display elements
counter plot: plots the counter value on the chart with color-coded columns, making it easy to spot directional momentum.
up and down percentiles: displays overbought (up percentile) and oversold (down percentile) thresholds to identify potential reversal zones.
regime background: the background color changes based on market regime:
- bullish (up percentile > down percentile): greenish background.
- bearish (down percentile > up percentile): reddish background.
- neutral (both percentiles equal): grayish background.
reversal signals: plotted as small triangles on the chart for visual confirmation of potential long (triangle up) and short (triangle down) reversal signals.
obs background: changes color when the counter exceeds ob or os thresholds, creating a visual cue for extreme market conditions:
- overbought: background changes to a faint down color.
- oversold: background changes to a faint up color.
status table: displayed on the right side of the chart, providing real-time status information:
- status: shows "overbought," "oversold," "long," "short," or "none" based on the current counter position.
- regime: indicates whether the market is in a "bullish," "bearish," or "neutral" state based on the percentile comparison.
- percentile up/down: displays the current up and down percentiles for quick reference.
how to use the indicator
trend following: in trend mode, use the midline-based counter to gauge if the market is in an uptrend (positive counter) or downtrend (negative counter).
reversal detection: the ob/os thresholds assist in identifying potential reversal points. when the counter exceeds the up percentile, it may indicate an overbought state, suggesting a bearish reversal. similarly, dropping below the down percentile may indicate an oversold state, suggesting a bullish reversal.
entry signals: use the long and short reversal signals for potential entry points, particularly in trending or range-bound markets. these signals are indicated by up and down triangles.
sequence trading: in sequence mode, the indicator tracks shorter-term directional shifts, making it suitable for detecting smaller momentum patterns based on recent price comparisons.
volume sensitivity: selecting volume mode enhances sensitivity to high-volume moves, allowing it to detect stronger market activity in both trend and sequence modes.
the sequence waves indicator is suited to both short-term and long-term traders. it allows for detailed trend analysis, reversal detection, and dynamic ob/os signals. the inclusion of visual reversal cues makes it a flexible tool adaptable to a variety of trading strategies.
Multi-timeframe 24 moving averages + BB+SAR+Supertrend+VWAP █ OVERVIEW
The script allows to display up to 24 moving averages ("MA"'s) across 5 timeframes plus two bands (Bollinger Bands or Supertrend or Parabolic SAR or VWAP bands) each from its own timeframe.
The main difference of this script from many similar ones is the flexibility of its settings:
- Bulk enable/disable and/or change properties of several MAs at once.
- Save 3 of your frequently used templates as presets using CSV text configurations.
█ HOW TO USE
Some use examples:
In order to "show 31, 50, 200 EMAs and 20, 100, 200 SMAs for each of 1H, 4H, D, W, M timeframes using blue for short MA, yellow for mid MA and red for long MA" use the settings as shown on a screenshot below.
In order to "Show a band of chart timeframe MA's of lengths 5, 8, 13, 21, 34, 55, 100 and 200 plus some 1H, 4H, D and W MAs. Be able to quickly switch off the band of chart tf's MAs. For chart timeframe MA's only show labels for 21, 100 and 200 EMAs". You can set TF1 and TF2 to chart's TF and set you fib MAs there and configure fixed higher timeframe MAs using TF3, TF4 and TF5 (e.g. using 1H, D and W timeframes and using 1H 800 in place of 4H 200 MA). However, quicker way may be using CSV - the syntax is very simple and intuitive, see Preset 2 as it comes in the script. You can easily switch chart tf's band of MAs by toggling on/off your chart timeframe TF's (in our example, TF1 and TF2).
The settings are either obvious or explained in tooltips.
Note 1: When using group settings and CSV presets do not forget that individual setting affected will no have any effect. So, if some setting does not work, check whether it is overridden with some group setting or a CSV preset.
Note 2: Sometimes you can notice parts of MA's hanging in the air, not lasting up to the last bar. This is not a bug as explained on this screenshot:
█ FOR DEVELOPERS
The script is a use case of my CSVParser library, which in turn uses Autotable library, both of which I hope will be quite helpful. Autotable is so powerful and comprehensive that you will hardly ever wish to use normal table functions again for complex tables.
The indicator was inspired by Pablo Limonetti's url=https://www.tradingview.com/script/nFs56VUZ/]Multi Timeframe Moving Averages and Raging @RagingRocketBull's # Multi SMA EMA WMA HMA BB (5x8 MAs Bollinger Bands) MAX MTF - RRB
Flat Market Range Pro [CHE]Flat Market Range Pro Indicator
Introduction
Hey there! 👋
Welcome to our overview of the Flat Market Range Pro indicator. Whether you're new to trading or a seasoned pro, this tool is designed to help you spot those flat market conditions where prices are chilling within a certain range. By highlighting these consolidation zones and potential breakout points, it offers some pretty neat insights to boost your trading strategies. Let’s dive in and explore how this indicator can make your trading journey smoother and more informed!
How It Works
The Flat Market Range Pro indicator is all about understanding the ebb and flow of the market. Here's a simple breakdown:
Range Detection:
Range Period (range_period): This sets the number of bars (think of them as time slices) the indicator looks back to find the highest highs and lowest lows. It’s like setting the scope for your search.
Minimum Candles in Range (min_candles_in_range): Ensures that there are enough candles (price bars) within the range to make the detection meaningful. No point in highlighting a range if it’s too short, right?
Adaptive Moving Average (AMA):
Think of AMA as the indicator’s way of staying flexible. It smooths out the price data to better spot trends within those flat ranges. Don’t worry, it’s working behind the scenes and won’t clutter your chart.
Breakout Detection:
When the price decides to break free from its cozy range, the indicator flags it. It waits for confirmation to make sure it’s not just a fleeting move, adding a layer of reliability to your signals.
Visualization:
Flat Market Zones: These are shaded areas that highlight where the price has been consolidating.
Support and Resistance Lines: Automatically drawn lines that mark key price levels, helping you see where the price might bounce or break through.
Trade Signals: Arrows popping up to show potential buy or sell opportunities when breakouts occur.
Breaking It Down
1. Detecting the Range
The indicator scans through the past range_period bars to find the highest and lowest prices. This creates a dynamic range that adjusts as new data comes in. It’s like having a smart assistant keeping an eye on where the action is happening.
2. The Role of AMA
Even though you won’t see AMA on your chart, it plays a crucial role. It helps the indicator adapt to changing market conditions by smoothing out the data, making sure the breakout signals are spot-on and not just random noise.
3. Spotting Breakouts
A breakout happens when the price moves beyond the established range. The indicator marks these moments with clear arrows, so you know when it might be a good time to jump in or out of a trade. Plus, it waits for confirmation to ensure these signals are solid.
4. Visualizing Flat Markets
Shaded boxes highlight the areas where the price has been consolidating, making it easy to see when the market is flat. Support and resistance lines are drawn automatically, and you can even customize how they look to match your personal style.
Customize It Your Way
One of the best things about the Flat Market Range Pro indicator is how customizable it is. Here’s what you can tweak:
Range Settings:
Adjust the range_period to fit different timeframes.
Set the min_candles_in_range to ensure the ranges you see are meaningful.
Moving Average Settings:
Change the ma_length and ma_lookback to fine-tune how the AMA responds to price movements.
Visual Tweaks:
Pick your favorite colors and transparency levels for the shaded zones.
Choose whether to display support and resistance lines and extend them indefinitely if you like.
Toggle trade arrows and labels on or off based on what you find most helpful.
Organizing these settings into logical groups makes it super easy to customize the indicator just the way you like it.
Real-World Examples
1. Spotting Consolidation: Imagine you’re watching a stock that’s been moving sideways for a while. The indicator highlights this consolidation with shaded boxes and support/resistance lines, giving you a clear picture of where the price is hanging out.
2. Trading Breakouts: When the price finally decides to break free from the range, the indicator pops up buy or sell arrows. This helps you catch the move early, whether you’re looking to enter a new trade or exit an existing one.
3. Making Informed Decisions: With clear visual cues and reliable signals, you can make smarter trading decisions without getting overwhelmed by too much information.
Behind the Scenes: Technical Insights
For those curious about the nuts and bolts, here’s a peek into how the Flat Market Range Pro indicator is built:
Efficient Range Calculation:
Uses loops to scan through the specified range_period, ensuring accurate detection of high and low points.
Adaptive Logic with AMA:
Incorporates the Simple Moving Average (SMA) to create a threshold coefficient, making the indicator responsive to market changes.
Clear Visualization:
Utilizes box.new and label.new for intuitive visual representations of flat markets.
Employs plotshape and plot to display breakout signals clearly on your chart.
Optimized Performance:
Avoids plotting unnecessary elements like AMA, keeping your chart clean and focused on what matters.
Why You’ll Love It
The Flat Market Range Pro indicator brings a lot to the table:
Accurate Range Detection:
Pinpoints consolidation zones by analyzing historical highs and lows.
Flexible and Adaptive:
AMA ensures the indicator stays responsive to different market conditions.
User-Friendly Visuals:
Shaded zones, support/resistance lines, and clear trade signals make your chart easy to understand at a glance.
Highly Customizable:
Tailor the settings to match your trading style and preferences.
Reliable Signals:
Confirmation mechanisms help reduce false signals, giving you more confidence in your trades.
Wrapping It Up
The Flat Market Range Pro indicator is a fantastic tool for anyone looking to navigate flat or consolidating markets with ease. By combining precise range detection, adaptive logic, and clear visual cues, it helps you identify consolidation phases and seize breakout opportunities effectively. Its customizable features ensure that it fits seamlessly into your trading strategy, whether you’re just starting out or have years of experience under your belt.
For more details, a step-by-step guide on using the indicator, and access to the full Pine Script code, check out the accompanying documentation or reach out for support. Happy trading! 🌟
Questions and Further Information
Got questions or need a hand with the Flat Market Range Pro indicator? Feel free to reach out! Whether you’re curious about how it works or need tips on customizing it for your trading style, we’re here to help. Also, give the indicator a try on different charts to see how it performs in various market conditions. Let’s make your trading experience better together!
Best regards
Chervolino
This script was inspired by: Trend Regularity Adaptive Moving Average
and
Range Detection by HasanRifat
Moving Average Cross Probability [AlgoAlpha]Moving Average Cross Probability 📈✨
The Moving Average Cross Probability by AlgoAlpha calculates the probability of a cross-over or cross-under between the fast and slow values of a user defined Moving Average type before it happens, allowing users to benefit by front running the market.
✨ Key Features:
📊 Probability Histogram: Displays the Probability of MA cross in the form of a histogram.
🔄 Data Table: Displays forecast information for quick analysis.
🎨 Customizable MAs: Choose from various moving averages and customize their length.
🚀 How to Use:
🛠 Add Indicator: Add the indicator to favorites, and customize the settings to suite your trading style.
📊 Analyze Market: Watch the indicator to look for trend shifts early or for trend continuations.
🔔 Set Alerts: Get notified of bullish/bearish points.
✨ How It Works:
The Moving Average Cross Probability Indicator by AlgoAlpha determines the probability by looking at a probable range of values that the price can take in the next bar and finds out what percentage of those possibilities result in the user defined moving average crossing each other. This is done by first using the HMA to predict what the next price value will be, a standard deviation based range is then calculated. The range is divided by the user defined resolution and is split into multiple levels, each of these levels represent a possible value for price in the next bar. These possible predicted values are used to calculate the possible MA values for both the fast and slow MAs that may occur in the next bar and are then compared to see how many of those possible MA results end up crossing each other.
Stay ahead of the market with the Moving Average Cross Probability Indicator AlgoAlpha! 📈💡
[SGM GARCH Volatility]I'm excited to share with you a Pine Script™ that I developed to analyze GARCH (Generalized Autoregressive Conditional Heteroskedasticity) volatility. This script allows you to calculate and plot GARCH volatility on TradingView. Let's see together how it works!
Introduction
Volatility is a key concept in finance that measures the variation in prices of a financial asset. The GARCH model is a statistical method that predicts future volatility based on past volatilities and prediction residuals (errors).
Indicator settings
We define several parameters for our indicator:
length = input.int(20, title="Length")
p = input.int(1, title="Lag order (p)")
q = input.int(1, title="Degree of moving average (q)")
cluster_value = input(0.2,title="cluster value")
length: The period used for the calculations, default 20.
p: The order of the delay for the GARCH model.
q: The degree of the moving average for the GARCH model.
cluster_value: A threshold value used to color the graph.
Calculation of logarithmic returns
We calculate logarithmic returns to capture price changes:
logReturns = math.log(close) - math.log(close )
Initializing arrays
We initialize arrays to store residuals and volatilities:
var float residuals = array.new_float(length, 0)
var float volatilities = array.new_float(length, 0)
We add the new logarithmic returns to the tables and keep their size constant:
array.unshift(residuals, logReturns)
if (array.size(residuals) > length)
array.pop(residuals)
We then calculate the mean and variance of the residuals:
meanResidual = array.avg(residuals)
varianceResidual = array.stdev(residuals, meanResidual)
volatility = math.sqrt(varianceResidual)
We update the volatility table with the new value:
array.unshift(volatilities, volatility)
if (array.size(volatilities) > length)
array.pop(volatilities)
GARCH volatility is calculated from accumulated data:
var float garchVolatility = na
if (array.size(volatilities) >= length and array.size(residuals) >= length)
alpha = 0.1 // Alpha coefficient
beta = 0.85 // Beta coefficient
omega = 0.01 // Omega constant
sumVolatility = 0.0
for i = 0 to p-1
sumVolatility := sumVolatility + beta * math.pow(array.get(volatilities, i), 2)
sumResiduals = 0.0
for j = 0 to q-1
sumResiduals := sumResiduals + alpha * math.pow(array.get(residuals, j), 2)
garchVolatility := math.sqrt(omega + sumVolatility + sumResiduals)
Plot GARCH volatility
We finally plot the GARCH volatility on the chart and add horizontal lines for easier visual analysis:
plt = plot(garchVolatility, title="GARCH Volatility", color=color.rgb(33, 149, 243, 100))
h1 = hline(0.1)
h2 = plot(cluster_value)
h3 = hline(0.3)
colorGarch = garchVolatility > cluster_value ? color.red: color.green
fill(plt, h2, color = colorGarch)
colorGarch: Determines the fill color based on the comparison between garchVolatility and cluster_value.
Using the script in your trading
Incorporating this Pine Script™ into your trading strategy can provide you with a better understanding of market volatility and help you make more informed decisions. Here are some ways to use this script:
Identification of periods of high volatility:
When the GARCH volatility is greater than the cluster value (cluster_value), it indicates a period of high volatility. Traders can use this information to avoid taking large positions or to adjust their risk management strategies.
Anticipation of price movements:
An increase in volatility can often precede significant price movements. By monitoring GARCH volatility spikes, traders can prepare for potential market reversals or accelerations.
Optimization of entry and exit points:
By using GARCH volatility, traders can better identify favorable times to enter or exit a position. For example, entering a position when volatility begins to decrease after a peak can be an effective strategy.
Adjustment of stops and objectives:
Since volatility is an indicator of the magnitude of price fluctuations, traders can adjust their stop-loss and take-profit orders accordingly. Periods of high volatility may require wider stops to avoid being exited from a position prematurely.
That's it for the detailed explanation of this Pine Script™ script. Don’t hesitate to use it, adapt it to your needs and share your feedback! Happy analysis and trading everyone!
DOUBLE RSI+MA ALERTS SETUPThis is an indicator that provides two verses of relative force indices (RSI) - an RSI Rapid and an RSI Normal, but as moving media (MA) applied with an RSI Rapid for suavização.
Rapid RSI and Normal RSI:
Or RSI is a momentum indicator that mediates the speed and alteração of preço movements of an ativo. No script, we calculate the RSI variations:
O RSI Rápido, com um período configurável que por padrão é but curto (5 períodos), para reactor but quickly to these mudanças no preço.
Or RSI Normal, with a configured period, but with a maximum value (14 periods), proportionate to an analysis but correct.
Media Móvel do RSI Rápido:
We have a simple mobile media (SMA) application with RSI Rapido, using the same number of times as RSI to monitor variations and facilitate viewing of the direction of the trend.
Levels of Overbought and Oversold:
These are the levels of overbought (sobrevendido) and oversold (sobrecomprado). Therefore, the overbought level is set at 80 and the overbought level is 20, depending on the classic RSI settings.
Alert Conditions:
Criamos alert conditions to inform you when the RSI of each type is ultrapassed or they are not defined as overbought and oversold. Assim, we can be notified of potential entry points or conditions based on these extreme market conditions. These messages are personalized to ensure that you quickly identify when the RSI has disappeared or alerted you if it is an overbought or oversold condition.
Visualization Graphic:
The indicator plots as RSI Rapid and RSI Normal lines not graphically for visual analysis, but with horizontal lines indicating the level of overbought and oversold. A cor dessas linehas éjustável para clareza.
Informative Table:
The tab is added to the lower side of the graphic fornecendo values at the real time of the RSI Fast as the RSI Normal, making it easier to visualize quickly and to compare unless it is necessary to print directly for the graphic.
This script has a powerful ferrament for operators that provides integrated analysis of RSI into its strategies, offering flexibility to monitor the dynamics of the preço and different tempo scales. Personal alerts are particularly important to be aware of marketing conditions without the need for constant monitoring. Algum additional functionality that you find useful or extra personalization that you want?
ARIMA Moving Average and Forecaster [SS]Finally releasing this. This took months, over 3 months to be precise, to figure out, code and troubleshoot! I honestly was going to give up on this project, but I finally got it to actually work fairly reliably. So hopefully you like it!
This is a very basic ARIMA modeler. It can do the following:
1. Provide you with an ARIMA based Moving Average;
2. Provide you with a standard error band;
3. Auto-select a lag length for assessment based on stationarity;
3. Provide you with the option of extending the error range by a user selected amount of standard deviations; and
4. Forecasting and plotting the forecast on the chart.
I will go over each function individually, but before I do, I think its important to talk a bit about what an ARIMA Model is and does:
ARIMA stands for AutoRegressive Integrated Moving Average and is an approach to modeling and time series forecasting. In simple terms, it combines autoregressive (AR) and moving average (MA) components to capture the underlying patterns in a time series data. The "AutoRegressive" part accounts for the relationship between an observation and its previous values, while the "Moving Average" part considers the relationship between an observation and a residual error from past observations. The "Integrated" component involves differencing the time series to make it stationary, which aids in stabilizing the model. ARIMA models help predict future values based on patterns observed in historical data, making them useful for forecasting in various fields such as economics, finance, and weather prediction.
The benefits to ARIMA is it will forecast based on the current trend, but it also provides for both the up and down scenario of the trend (i.e., if we are in a downtrend, what it would look like and what values we could expect if the trend reverses and vice versa). All of this is within the scope of this indicator, believe it or not!
If you would like more information on ARIMA, you can check out my educational post about it here:
Alrighty, now for the indicator functions.
ARIMA Moving Average and Standard Error Band
The ARIMA moving average is very simple, it takes the SMA of the current trend, lags it and plots out the lagged SMA. You can toggle the auto-select lag on, or you can pick your own lag manually. The above image is an auto-selected lag, but if we manually lag it by 5, this is what it looks like:
Its simply a lagged average of the 5 SMA (that is essentially how ARIMA works, by creating a moving average and lagging the moving average).
There are some implications to selecting a lag factor when it comes to forecasting, but I will cover this in the forecasting section. But I do want to make mention, you can use the ARIMA moving average in lieu of other moving averages. The advantage to doing this is it will be able to plot out the error bands. For example, if we wanted to get an ARIMA MA of the 200 SMA, we can toggle on the error bands and this is what we get:
Or the 50 MA:
NOTE: You ABSOLUTELY SHOULD NEVER use more than a lag of 4 or 5 for Forecasting (will be discussed later).
Auto-Select Lag
The indicator pulls the ARIMA modeler framework from my Forecasting library and pulls the stationarity assessment from my SPTS library. When you are doing an ARIMA model for forecasting, we need to ensure the data is stationary. Thus, if you want to forecast out the current trend, its highly recommended you select the "Auto Determine Lag Length" to find the most appropriate lag and forecast accordingly.
You can, however, chose your own lag order (model order), but this should never be above 4 or 5.
You should never select a lag of more than 5 because you are introducing too much "trendiness" into the equation, and you will get astronomical readings. ARIMA models never generally exceed a lag of 3 or 4 at most, as they are supposed be stationary and de-trended.
Extending by Standard Deviation
There is an option to select a standard deviation extension band. This is helpful for active day trading. Here is NIO extended by 2 standard deviations:
General suggestion is to only extend by 2 standard deviations and this is sufficient for most stocks.
Forecasting
The hallmark of an ARIMA model is the ability to use it for forecasting. Thus, the forecasting feature is a large portion of this indicator. You can see it displayed in the main chart above, but let's show some other examples:
NIO on the 1 hour:
TSLA on the 4 hour:
You can also display a forecasting table:
The result row shows the most likely, conservative, price at each time increment.
The Upper Confidence and Lower Confidence show what the trend would look like if it continued up or down at the current rate and the 95% confidence intervals show the values that the true source is likely to fall between at various increments in time with a 95% confidence (i.e. 95% probability that it should fall between these levels at period xyz assuming normal distribution).
The important levels, in my opinion, are the upper and lower confidence levels. These show you the current rate of decline or increase that the stock is expecting and what the trend would look like with a continuation or a reversal. This is ARIMA's biggest strength, as it has the ability to plot both outcomes assuming the current trend rate and time remains constant.
And that is the indicator! ARIMA is a bit of a complex process, but its a very powerful tool when used properly!
Troubleshooting:
One thing of note. Sometimes when autoselecting a length for forecasting, if there has been a heavy trend in one direction, you will not get the upper or lower confidence levels because of the lack of any up or down movement. In this case, manually select a lag of 3 to 5 to correct for this.
Let me know if you have any questions below and safe trades everyone!
Mandelbrot SetThe Mandelbrot set represents a set of complex numbers with distinctive and very well known intricate geometric properties. Here I have attempted to implement it in Pinescript leveraging tables.
The defining formula for the set is:
Zn+1 = Zn2 + C
If, after a certain number of iterations, the magnitude of the complex number remains bounded (does not diverge to infinity), the point is considered part of the Mandelbrot set.
The Mandelbrot set exhibits intricate and infinitely detailed fractal patterns, characterized by self-similarity at different scales. Due to limitations in Pinescript and the number of possible table cells (Pinescript is not designed for this at all and this is merely a showcase of how flexible & great Pinescript can be it is) the resolution over this set is low.
Users can zoom in and out of the set via the provided inputs.
The values in each cell represent the number of iterations required for the corresponding point in the Mandelbrot set to escape a certain threshold.
Linear Regression Forecast Tool [Daveatt]Hello traders,
Navigating through the financial markets requires a blend of analysis, insight, and a touch of foresight.
My Linear Regression Forecast Tool is here to add that touch of foresight to your analysis toolkit on TradingView!
Linear Regression is the heart of this tool, a statistical method that explores the relationship between a dependent variable and one (or more) independent variable(s).
In simpler terms, it finds a straight line that best fits a set of data points.
This "line of best fit" then becomes a visual representation of the relationship in the data, providing a basis for making predictions.
Here's what the Linear Regression Forecast Tool brings to your trading table:
Multiple Indicator Choices: Select from various market indicators like Simple Moving Averages, Bollinger Bands, or the Volume Weighted Average Price as the basis for your linear regression analysis.
Customizable Forecast Periods: Define how many periods ahead you want to forecast, adjusting to your analysis needs, whether that's looking 5, 7, or 10 periods into the future.
On-Chart Forecast Points: The tool plots the forecasted points on your chart, providing a straightforward visual representation of potential future values based on past data.
In this script:
1. We first calculate the indicator using the specified period.
2. We then use the ta.linreg function to calculate a linear regression curve fitted to the indicator over the last Period bars.
3. We calculate the slope of the linear regression curve using the last two points on the curve.
We use this slope to extrapolate the linear regression curve to forecast the next X points of the indicator.
4/ Finally, we use the plot function to plot the original indicator and the forecasted points on the chart, using the offset parameter to shift the forecasted points to the right (into the future).
This method assumes that the trend represented by the linear regression curve will continue, which may not always be the case, especially in volatile or changing market conditions.
Examples:
Works with a moving average
Works with a Bollinger band
The code can be adapted to work with any other indicator (imagine RSI, MACD, other Moving Average Type, PSAR, Supertrend, etc...)
Conclusion
The Linear Regression Forecast Tool doesn't promise to tell the future but provides a structured way to visualize possible future price trends based on historical data. I
Remember, no tool can predict market conditions with certainty.
It's always advisable to corroborate findings with other analysis methods and stay updated with market news and events.
Happy trading!
