Big Candle Highlighter (Nifty 1m)This indicator will help option buyers to avoid taking trade in impulsive candles.
For Example :
Normal 1m candle: ~10–15 pts
Big candle (possible liquidity/impulse): >18 pts
Very large / avoid chasing: >25 pts
If you see a candle that breaks structure with a 25-30 point range and closes strong, it’s often:
A liquidity sweep
A news spike
Or the start of an impulsive leg — in which case entering at close can be risky without a retest
스크립트에서 "nifty"에 대해 찾기
Reversal Strength Meter – Adib NooraniThe Reversal Strength Meter is an oscillator designed to identify potential reversal zones based on supply and demand dynamics. It uses smoothed stochastic logic to reduce noise and highlight areas where momentum may be weakening, signaling possible market turning points.
🔹 Smooth, noise-reduced stochastic oscillator
🔹 Custom zones to highlight potential supply and demand imbalances
🔹 Non-repainting, compatible across all timeframes and assets
🔹 Visual-only tool — intended to support discretionary trading decisions
This oscillator assists scalpers and intraday traders in tracking subtle shifts in momentum, helping them identify when a market may be preparing to reverse — always keeping in mind that trading is based on probabilities, not certainties.
📘 How to Use the Indicator Efficiently
For Reversal Trading:
Buy Setup
– When the blue line dips below the 20 level, wait for it to re-enter above 20.
– Look for reversal candlestick patterns (e.g., bullish engulfing, hammer, or morning star).
– Enter above the pattern’s high, with a stop loss below its low.
Sell Setup
– When the blue line rises above the 80 level, wait for it to re-enter below 80.
– Look for bearish candlestick patterns (e.g., bearish engulfing, inverted hammer, or evening star).
– Enter below the pattern’s low, with a stop loss above its high.
🛡 Risk Management Guidelines
Risk only 0.5% of your capital per trade
Book 50% profits at a 1:1 risk-reward ratio
Trail the remaining 50% using price action or other supporting indicators
Reversal Scalping Ribbon - Adib NooraniThe Reversal Scalping Ribbon is a trend-following overlay tool designed to visually identify potential reversal zones based on price extremes and dynamic volatility bands. It calculates adaptive upper and lower bands using price action and custom ATR logic, helping traders quickly assess market direction and possible turning points
🔹 Volatility-adjusted bands based on price highs/lows
🔹 Color-coded ribbons to indicate trend bias and potential reversal shifts
🔹 No repainting, works on all timeframes and assets
🔹 Visual-only display, no trade signals — supports discretion-based entries
This ribbon is designed for scalpers and intraday traders to spot reversal setups with clarity. It enhances your trading by showing real-time market bias without unnecessary distractions. By focusing on probabilities, it helps to improve decision-making in fast-paced environments
How to use the indicator efficiently
For Reversal Trading:
Buy: When price closes below the green ribbon with a red candle, then re-enters with a green candle. Enter above the high of the green candle with a stop loss below the lowest low of the recent green/red candles
Sell: When price closes above the red ribbon with a green candle, then re-enters with a red candle. Enter below the low of the red candle with a stop loss above the highest high of the recent red/green candles
Risk Management:
Limit risk to 0.5% of your capital per trade
Take 50% profit at a 1:1 risk-reward ratio
For the remaining 50%, trail using the lower edge of the green band for buys and the upper edge of the red band for sells
Wick Sweep EntriesWick Sweep Entry designed by Finweal Finance (Indicator Originator : Prajyot Mahajan) :
This Indicator is specially designed for Nifty, Sensex and Banknifty Options Buying. This works well on Expiry Days.
Setup Timeframe : 5m and 1m.
Entry Criteria :
For Long/CE :
Wait for Sweep of 5m Candle Low with next 5m Candle but you do not wait for the next 5 minute candle to close, you enter directly whenever any 1 minute candle of next 5minute candle to close above the low of previous 5m Candle.
For Short/PE :
Wait for Sweep of 5m Candle High with next 5m Candle but you do not wait for the next 5 minute candle to close, you enter directly whenever any 1 minute candle of next 5minute candle to close below the High of previous 5m Candle.
Key notes :
1. As this is the Scalping High Frequency Strategy, it is to be used for scalping purpose only. You might have losses too so to avoid the noise in the market, i suggest you to use this strategy in the first 45 minutes to 1 hour of Indian Markets as this is a volatility Strategy.
2. Although Nifty and Banknifty are independent indices, they still show some reactions with each other, so if you spot a long entry on BNF and Short Entry on nifty then you will avoid taking the trade, you will take the trade only if there is a tandem activity or At least the other index is not showing opposite signal.
3. If target is not hit and you spot another entry, you will avoid taking the new entry.
The Indicator will automatically spot/plot the entry signal, all you need to do is enter as soon as 1minute candle closes either below prior 5 minute candle High for Short/PE or closes above 5minute low for Long/CE.
For Targets :
You Can Target recent minor pull back, FVG, or Order blocks.
Remember : This is a scalping strategy so don't hold trade for more than 4/5 1minute Candles
Rolling ATR Momentum
Rolling ATR Momentum Indicator – User Manual
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🔍 Overview
The Rolling ATR Momentum Indicator is a simple yet powerful tool designed to detect shifts in market volatility. It compares the current Average True Range (ATR) with the ATR from a previous point in time to measure how market volatility is changing.
This indicator is especially useful for:
- Spotting the beginning or fading of a momentum phase
- Filtering out low-volatility market conditions
- Enhancing timing for entries and exits in trending or breakout trades
---
📊 Key Components
✅ ATR Delta (Rolling)
- Definition: `ATR Delta = Current ATR - Past ATR`
- Inputs:
- ATR Period (default: 14): The base ATR calculation window
- Lookback Period (default: 5): How many bars ago to compare ATR
- Interpretation:
- Positive ATR Delta (Green Line): Market volatility is increasing
- Negative ATR Delta (Red Line): Market volatility is decreasing
📈 Zero Line
- A horizontal baseline at zero helps you easily see when ATR momentum shifts from negative to positive (or vice versa).
🟩/🟥 Background Color
- Green Background: ATR Delta is positive (rising volatility)
- Red Background: ATR Delta is negative (falling volatility)
🔵 Optional: ATR Reference Lines
- You can optionally display raw Current ATR and Past ATR by changing their visibility settings.
---
✅ How to Use It
Entry Timing (Futures/Options)
- Use ATR Delta as a filter:
- Only take trades when ATR Delta is positive → confirms momentum is building
- Avoid trades when ATR Delta is negative → market might be slow, sideways, or losing steam
Breakout Anticipation
- A rising ATR Delta after a tight range or consolidation can suggest that a breakout is underway
Stop-loss Strategy
- Use high ATR periods for wider stops (to avoid noise)
- Use low ATR periods for tighter stops or skip trading
---
🧠 Pro Tips
- This indicator doesn’t predict direction—combine with trend or price structure tools (like EMA, PPMA, candlesticks)
- Works best in trending or breakout environments
- Add it to multi-timeframe layouts to see volatility buildup on higher timeframes
---
⚙️ Settings
| Parameter | Description |
|----------|-------------|
| ATR Period | Length of the ATR calculation (default 14) |
| Lookback Period | How many bars back to compare ATR values |
---
🧭 Best For:
- Index futures (Nifty, BankNifty)
- Option buyers needing volatility confirmation
- Intraday & swing traders looking to trade momentum setups
---
Use the Rolling ATR Momentum indicator as your volatility radar—simple, clean, and highly effective for staying on the right side of market energy.
End of Manual
Rolling ATR Momentum - EnhancedATR Rolling Momentum Indicator – User Manual
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🔍 Overview
The ATR Rolling Momentum Indicator is a dynamic volatility tool built on the Average True Range (ATR). It not only tracks increasing or decreasing momentum but also provides early warnings and confirmation signals for potential breakout moves. It’s especially powerful for futures and options traders looking to align with expanding price action.
---
📊 Core Components
✅ ATR Delta (Rolling ATR)
- Definition: Difference between current ATR and past ATR (user-defined lookback).
- Use: Tells whether volatility is expanding (positive delta) or contracting (negative delta).
- Visual: Green line for rising momentum, red for declining.
🟣 ATR Delta Slope
- Definition: Measures acceleration in momentum.
- Use: Helps identify early signs of breakout buildup.
- Visual: Purple line. Watch for slope turning up from below.
🟡 Volatility Squeeze (Yellow Dot)
- Definition: Current ATR is significantly lower than its 20-period average.
- Use: Indicates the market is coiling—possible breakout ahead.
🔼 Momentum Start (Green Triangle)
- Definition: ATR Delta slope turns from negative to positive.
- Use: Early warning to prepare for volatility expansion.
🔷 Breakout Confirmation (Blue Label Up)
- Definition: ATR Delta exceeds its high of the last 10 candles.
- Use: Confirms volatility breakout—trade opportunity if direction aligns.
🟩/🟥 Background Color
- Green Background: Momentum rising (positive ATR delta)
- Red Background: Momentum falling (negative ATR delta)
- Yellow Tint: Active squeeze zone
---
✅ How to Use It (Futures/Options Focus)
Step-by-Step:
1. Squeeze Detected (Yellow Dot) → Stay alert. Market is coiling.
2. Green Triangle Appears → Momentum is starting to rise.
3. Background Turns Green → Confirmed rising momentum.
4. Blue Label Appears → Confirmed breakout (enter trade if trend aligns).
Directional Bias:
- Use your main chart setup (price action, EMAs, trendlines, etc.) to decide direction (Call or Put, Long or Short).
- ATR Momentum only tells you how strong the move is—not which way.
---
⚙️ Inputs & Settings
- ATR Period: Default 14 (core volatility measure)
- Rolling Lookback: Used to calculate delta (default 5)
- Slope Length: Used to measure acceleration (default 3)
- Squeeze Factor: Default 0.8 — lower = more sensitive squeeze detection
- Breakout Lookback: Checks ATR delta against last X bars (default 10)
---
🧠 Pro Tips
- Works great when paired with EMA stacks, price structure, or breakout patterns.
- Avoid taking trades based only on squeeze or momentum—combine with chart confirmation.
- If background turns red after a breakout, it may be losing momentum—book partials or tighten stops.
---
🧭 Ideal For:
- Nifty/BankNifty Futures
- Option directional trades (call/put buying)
- Index scalping and momentum swing setups
---
Use this tool as your volatility compass—it won't tell you where to go, but it'll tell you when the wind is strong enough to move fast.
End of Manual
EMA Shakeout DetectorEMA Shakeout & Reclaim Zones
Description:
This Pine Script helps traders quickly identify potential shakeout entries based on price action and volume dynamics. Shakeouts often signal strong accumulation, where institutions drive the stock below a key moving average before reclaiming it, creating an opportunity for traders to enter at favorable prices.
How It Works:
1. Volume Surge Filtering:
a. Computes the 51-day Simple Moving Average (SMA) of volume.
b. Identifies days where volume surged 2x above the 51-day average.
c. Filters stocks that had at least two such high-volume days in the last 21 trading days (configurable).
2. Stock Selection Criteria:
a. The stock must be within 25% of its 52-week high.
b. It should have rallied at least 30% from its 52-week low.
Shakeout Conditions:
1. The stock must be trading above the 51-day EMA before the shakeout.
2. A sudden price drop of more than 10% occurs, pushing the stock below the 51-day EMA.
3. A key index (e.g., Nifty 50, S&P 500) must be trading above its 10-day EMA, ensuring overall market strength.
Visualization:
Shakeout zones are highlighted in blue, making it easier to spot potential accumulation areas and study price & volume action in more detail.
This script is ideal for traders looking to identify institutional shakeouts and gain an edge by recognizing high-probability reversal setups.
Econometrica by [SS]This is Econometrica, an indicator that aims to bridge a big gap between the resources available for analysis of fundamental data and its impact on tickers and price action.
I have noticed a general dearth of available indicators that offer insight into how fundamentals impact a ticker and provide guidance on how they these economic factors influence ticker behaviour.
Enter Econometrica. Econometrica is a math based indicator that aims to co-integrate and model indicator price action in relation to critical economic metrics.
Econometrica supports the following US based economic data:
CPI
Non-Farm Payroll
Core Inflation
US Money Supply
US Central Bank Balance Sheet
GDP
PCE
Let's go over the functions of Econometrica.
Creating a Regression Cointegrated Model
The first thing Econometrica does is creates a co-integrated regression, as you see in the main chart, predicting ticker value ranges from fundamental economic data.
You can visualize this in the main chart above, but here are some other examples:
SPY vs Core Inflation:
BA vs PCE:
QQQ vs US Balance Sheet:
The band represents the anticipated range the ticker should theoretically fall in based on the underlying economic value. The indicator will breakdown the relationship between the economic indicator and the ticker more precisely. In the images above, you can see how there are some metrics provided, including Stationairty, lagged correlation, Integrated Correlation and R2. Let's discuss these very briefly:
Stationarity: checks to ensure that the relationship between the economic indicator and ticker is stationary. Stationary data is important for making unbiased inferences and projections, so having data that is stationary is valuable.
Lagged Correlation: This is a very interesting metric. Lagged correlation means whether there is a delay in the economic indicator and the response of the ticker. Typically, you will observed a lagged correlation between an economic indicator and price of a ticker, as it can take some time for economic changes to reach the market. This lagged correlation will provide you with how long it takes for the economic indicator to catch up with the ticker in months.
Integrated Correlation: This metric tells you how good of a fit the regression bands are in relation to the ticker price. A higher correlation, means the model is better at consistent and accurate information about the anticipated range for the ticker in relation to the economic indicator.
R2: Provides information on the variance and degree of model fit. A high R2 value means that the model is capable of explaining a large amount of variance between the economic indicator and the ticker price action.
Explaining the Relationship
Owning to the fact that the indicator is a bit on the mathy side (it has to be to do this kind of task), I have included ability for the indicator to explain and make suggestions based on the underlying data. It can assess the model's fit and make suggestions for tweaking. It can also explain the implications of the data being presented in the model.
Here is an example with QQQ and the US Balance Sheet:
This helps to simplify and interpret the results you are looking at.
Forecasting the Economic Indicator
In addition to assessing the economic indicator's impact on the ticker, the indicator is also capable of forecasting out the economic indicator over the next 25 releases.
Here is an example of the CPI forecast:
Overall use of the indicator
The indicator is meant to bridge the gap between Technical Analysis and Fundamental Analysis.
Any trader who is attune to fundamentals would benefit from this, as this provides you with objective data on how and to what extent fundamental and economic data impacts tickers.
It can help affirm hypothesis and dispel myths objectively.
It also omits the need from having to perform these types of analyses outside of Tradingview (i.e. in excel, R or Python), as you can get the data in just a few licks of enabling the indicator.
Conclusion
I have tried to make this indicator as user friendly as possible. Though it uses a lot of math, it is fairly straight forward to interpret.
The band plotted can be considered the fair market value or FMV of the ticker based on the underlying economic data, provided the indicator tells you that the relationship is significant (and it will blatantly give you this information verbatim, you don't have to interpret the math stuff).
This is US economic data only. It does not pull economic data from other countries. You can absolutely see how US economic data impacts other markets like the TSX, BANKNIFTY, NIFTY, DAX etc. but the indicator is only pulling US economic data.
That is it!
I hope you enjoy it and find this helpful!
Thanks everyone and safe trades as always 🚀🚀🚀
Trading Capital Management for Option SellingTrading Capital Management for Option Selling
This Pine Script indicator helps manage trading capital allocation for option selling strategies based on price percentile ranking. It provides dynamic allocation recommendations for index options (NIFTY and BANKNIFTY) and individual stock positions.
Key Features:
- Dynamic buying power (BP) allocation based on close price percentile
- Flexible index allocation between NIFTY and BANKNIFTY
- Automated calculation of recommended number of stock positions
- Risk management through position size limits
- Real-time INDIA VIX monitoring
Main Parameters:
1. Window Length: Period for percentile calculation (default: 252 days)
2. Thresholds: Low (30%) and High (70%) percentile thresholds
3. Capital Settings:
- Trading Capital: Total capital available
- Max BP% per Stock: Maximum allocation per stock position
4. Buying Power Range:
- Low Percentile BP%: Base BP usage at low percentile
- High Percentile BP%: Maximum BP usage at high percentile
5. Index Allocation:
- NIFTY/BANKNIFTY split ratio
- Minimum and maximum allocation thresholds
Display:
The indicator shows two tables:
1. Common Metrics:
- Total BP Usage with percentage
- Current INDIA VIX value
- Current Close Price Percentile
2. Capital Allocation:
- Index-wise BP allocation (NIFTY and BANKNIFTY)
- Stock allocation pool
- Recommended number of stock positions with BP per stock
Usage:
This indicator helps traders:
1. Scale positions based on market conditions using price percentile
2. Maintain balanced exposure between indices and stocks
3. Optimize capital utilization while managing risk
4. Adjust position sizing dynamically with market volatility
Relative Strength RatioWhen comparing a stock’s strength against NIFTY 50, the Relative Strength (RS) is calculated to measure how the stock is performing relative to the index. This is different from the RSI but is often used alongside it.
How It Works:
Relative Strength (RS) Calculation:
𝑅
𝑆
=
Stock Price
NIFTY 50 Price
RS=
NIFTY 50 Price
Stock Price
This shows how a stock is performing relative to the NIFTY 50 index.
Relative Strength Ratio Over Time:
If the RS value is increasing, the stock is outperforming NIFTY 50.
If the RS value is decreasing, the stock is underperforming NIFTY 50.
SRT - NK StockTalkSRT stands for Speculation Ratio Territory. It's a technique used in the stock market to identify the top and bottom of an index, which helps define the buying and selling zones.
Here's a brief overview of how it works:
Calculation: The SRT value is calculated by dividing the index value (like Nifty) by the 124-day Simple Moving Average (SMA) on a daily chart.
Range: The SRT value typically ranges between 0.6 (bottom) and 1.5 (top)2.
Investment Strategy:
Buying Zone: Ideal entry points are when the SRT value is between 0.6 and 0.9.
Selling Zone: It's recommended to start booking profits when the SRT value is above 1.3 and exit when it reaches around 1.4
This method helps investors make informed decisions about when to enter or exit the market, aiming for better returns and reduced risks.
Stock Highs Tracker with IndicesThis Pine Script indicator tracks stock highs and compares them with major indices (Nifty, Nifty 500, CNX-SmallCap, and CNX-MidCap). Here’s what it does:
1. Retrieves and Displays Key Price Metrics
All-Time High (ATH): The highest price the stock has ever reached.
52-Week High: The highest price in the last 252 trading days.
Current Price: The stock’s closing price.
2. Calculates Percentage Differences
% from ATH: How much the stock is below its all-time high.
% from 52WKH: How much the stock is below its 52-week high.
3. Fetches and Compares with Indices
It retrieves similar metrics (ATH, 52-Week High, Current Price, % from ATH, % from 52WKH) for:
Nifty 50
Nifty 500
CNX-SmallCap
CNX-MidCap
This helps in assessing whether the stock's movement aligns with broader market trends.
4. Displays Data in a Table
The script creates a table positioned at the top-right corner.
It color-codes different rows for easy readability.
The table compares the stock’s performance against the major indices.
Use Case
Helps traders and investors track stock highs relative to market indices.
Identifies whether the stock is outperforming or underperforming the broader market.
200-Week EMA % Difference200-Week EMA Percentage Difference Indicator – Understanding Market Stretch & Reversion
What This Indicator Does
Even if an individual stock is delivering strong earnings and solid fundamentals, it is still influenced by overall market sentiment. When the broader market begins reverting to its long-term mean, stocks—no matter how strong—are often pulled down along with it. Unrealized gains can erode if one ignores these macro movements.
The 200-Week EMA Percentage Difference indicator measures how far the price of an asset or index has moved away from its 200-week Exponential Moving Average (EMA) in percentage terms. This provides a reliable gauge of whether the market is overstretched (overbought) or pulling back to support (oversold) relative to a long-term trend.
How It Helps Investors
Identifying Market Extremes:
When the indicator moves into the 50-80% range, historical trends show that broad-based indices like BSE Smallcap, Nifty 500, Nifty Microcap, and Nifty Smallcap 250 have often experienced corrections.
This suggests that the market may be overextended, and investors should exercise caution.
Spotting Support Zones:
Past data indicates that when the percentage difference falls back to around 30%, the market often finds a new support level, leading to fresh buying opportunities.
This can help long-term investors identify favorable entry points.
Mean Reversion & Market Cycles:
The indicator essentially measures how far these indices have stretched from their long-term mean (200-week EMA).
Extreme deviations from the EMA often result in mean reversion, where prices eventually return to more sustainable levels.
How to Use It in Broad-Based Indices
Above 50-80% → Caution Zone: Historically associated with market tops or overheated conditions.
Around 30% → Support Zone: A potential level where corrections stabilize and new market uptrends begin.
By applying this indicator to indices like BSE Smallcap, Nifty 500, Nifty Microcap, and Nifty Smallcap 250, investors can gauge market strength, anticipate corrections, and position themselves strategically for long-term opportunities.
Trend & ADX by Gideon for Indian MarketsThis indicator is designed to help traders **identify strong trends** using the **Kalman Filter** and **ADX** (Average Directional Index). It provides **Buy/Sell signals** based on trend direction and ADX strength. I wanted to create something for Indian markets since there are not much available.
In a nut-shell:
✅ **Buy when the Kalman Filter turns green, and ADX is strong.
❌ **Sell when the Kalman Filter turns red, and ADX is strong.
📌 **Ignore signals if ADX is weak (below threshold).
📊 Use on 5-minute timeframes for intraday trading.
------------------------------------------------------------------------
1. Understanding the Indicator Components**
- **Green Line:** Indicates an **uptrend**.
- **Red Line:** Indicates a **downtrend**.
- The **line color change** signals a potential **trend reversal**.
**ADX Strength Filter**
- The **ADX (orange line)** measures trend strength.
- The **blue horizontal line** marks the **ADX threshold** (default: 20).
- A **Buy/Sell signal is only valid if ADX is above the threshold**, ensuring a strong trend.
**Buy & Sell Signals**
- **Buy Signal (Green Up Arrow)**
- Appears **one candle before** the Kalman line turns green.
- ADX must be **above the threshold** (default: 20).
- Suggests entering a **long position**.
- **Sell Signal (Red Down Arrow)**
- Appears **one candle before** the Kalman line turns red.
- ADX must be **above the threshold** (default: 20).
- Suggests entering a **short position**.
2. Best Settings for 5-Minute Timeframe**
For day trading on the **5-minute chart**, the following settings work best:
- **Kalman Filter Length:** `50`
- **Process Noise (Q):** `0.1`
- **Measurement Noise (R):** `0.01`
- **ADX Length:** `14`
- **ADX Threshold:** `20`
- **(Increase to 25-30 for more reliable signals in volatile markets)**
3. How to Trade with This Indicator**
**Entry Rules**
✅ **Buy Entry**
- Wait for a **green arrow (Buy Signal).
- Kalman Line must **turn green**.
- ADX must be **above the threshold** (strong trend confirmed).
- Enter a **long position** on the next candle.
❌ **Sell Entry**
- Wait for a **red arrow (Sell Signal).
- Kalman Line must **turn red**.
- ADX must be **above the threshold** (strong trend confirmed).
- Enter a **short position** on the next candle.
**Exit & Risk Management**
📌 **Stop Loss**:
- Place stop-loss **below the previous swing low** (for buys) or **above the previous swing high** (for sells).
📌 **Take Profit:
- Use a **Risk:Reward Ratio of 1:2 or 1:3.
- Exit when the **Kalman Filter color changes** (opposite trend signal).
📌 **Avoid Weak Trends**:
- **No trades when ADX is below the threshold** (low trend strength).
4. Additional Tips
- Works best on **liquid assets** like **Bank Nifty, Nifty 50, and large-cap stocks**.
- **Avoid ranging markets** with low ADX values (<20).
- Use alongside **volume analysis and support/resistance levels** for confirmation.
- Experiment with **ADX Threshold (increase for stronger signals, decrease for more trades).**
Best of Luck traders ! 🚀
Price Action + Support/Resistance with LabelsEntry Conditions:
Long Entry (BUY): Based on the bullish engulfing pattern and price being above the resistance level.
Short Entry (SELL): For demonstration, the short entry condition is set as price being below the support level and a bullish candle in the previous bar. You can modify this logic for your own use case.
Stop Loss and Take Profit:
Stoploss is plotted at the calculated stop loss level.
Target is plotted at the calculated take profit level.
Labels:
For long trades, labels are added with "BUY", "STOPLOSS", and "TARGET".
For short trades (if enabled), labels are added with "SELL", "STOPLOSS", and "TARGET".
Labels are placed using label.new at specific locations on the chart (above or below bars).
Alert Conditions:
Alerts are created for both long and short entry signals so you can get notified when the entry conditions are met.
How it works:
BUY label will appear below the bar when a long entry condition is met.
SELL label will appear above the bar when a short entry condition is met.
STOPLOSS and TARGET labels will appear at their respective levels when an entry signal is triggered.
The labels will appear on the chart to give you a clear visual cue of the entry, stop loss, and take profit levels.
How to Use:
Copy the script into your Pine Editor on TradingView and apply it to your chart.
Observe the labels that show up on the chart:
"BUY" will appear below the bar when long conditions are met.
"SELL" will appear above the bar when short conditions are met (if using short logic).
"STOPLOSS" will be plotted at the stop loss level.
"TARGET" will be plotted at the take profit level.
Optional Customization:
You can modify the short entry condition based on your preferred method.
You can adjust the length for the support/resistance calculation, the stopLossRR, and other parameters to fine-tune the strategy for Nifty 50 or any other asset.
Let me know if you have any further questions or need additional modifications!
Metaphor Vigour Ratio### **Script Name:** Metaphor Vigour Ratio
**Short Title:** Metaphor Vigour Ratio
**Author:** Sovit Manjani, CMT
**Description:**
The Metaphor Vigour Ratio (MVRatio) is a powerful Relative Strength Indicator designed for assessing normalized relative strength. It is versatile and can be applied to any script or used to rank symbols based on their intermarket relative strength.
---
### **Features:**
1. **Bullish and Bearish Signals:**
- **Above 100:** Indicates a bullish trend.
- **Below 100:** Indicates a bearish trend.
2. **Trend Analysis with Slope:**
- **Slope Rising:** Suggests bullish momentum.
- **Slope Falling:** Suggests bearish momentum.
3. **Stock Selection Strategy:**
- Identify and rank stocks based on the MVRatio. For example, buy the top 10 stocks of Nifty with the highest MVRatio values for strong performance potential.
---
### **Inputs:**
1. **Fast EMA Period (RSEMAFast):** Default set to 10. Controls the sensitivity of the Fast Moving Average.
2. **Slow EMA Period (RSEMASlow):** Default set to 30. Provides a stable trend base with the Slow Moving Average.
3. **Smooth EMA Period (SmoothEMA):** Default set to 3. Smooths the MVRatio for better clarity.
4. **Close Source:** Default is the closing price, but it can be customized as needed.
5. **Comparative Symbol (ComparativeTickerId):** Default is "NSE:NIFTY," allowing comparison against a benchmark index.
---
### **Calculation Logic:**
1. **Relative Strength (RS):**
- Calculated as the ratio of the base symbol's price to the comparative symbol's price.
2. **Exponential Moving Averages (FastMA and SlowMA):**
- Applied to the RS to smooth and differentiate trends.
3. **Metaphor Vigour Ratio (MVRatio):**
- Computed as the ratio of FastMA to SlowMA, scaled by 100, and further smoothed using SmoothEMA.
---
### **Visualization:**
1. **MVRatio Plot (Blue):**
- Represents the relative strength dynamics.
2. **Reference Line at 100 (Gray):**
- Helps quickly identify bullish (above 100) and bearish (below 100) zones.
---
### **How to Use:**
1. Add the indicator to your chart from TradingView's Pine Script editor.
2. Compare the performance of any symbol relative to a benchmark (e.g., Nifty).
3. Analyze trends, slopes, and ranking based on MVRatio values to make informed trading decisions.
---
**Note:** This indicator is for educational purposes and should be used alongside other analysis methods to make trading decisions.
Sunil 2 Bar Breakout StrategyDetailed Explanation of the Sunil 2 Bar Breakout Strategy
Introduction
The Sunil 2 Bar Breakout Strategy is a simple yet effective price-action-based approach designed to identify breakout opportunities in financial markets. This strategy analyzes the movement of the last three candles to detect momentum and initiates trades in the direction of the breakout. It is equipped with a built-in stop-loss mechanism to protect capital, making it suitable for traders looking for a structured and disciplined trading system.
The strategy works well across different timeframes and asset classes, including indices, stocks, forex, and cryptocurrencies. Its versatility makes it ideal for both intraday and swing trading.
Core Concept
The strategy revolves around two primary conditions: breakout identification and risk management.
Breakout Identification:
Long Trade Setup: The strategy identifies bullish breakouts when:
The current candle's closing price is higher than the previous candle's closing price.
The high of the previous candle is greater than the highs of the two candles before it.
Short Trade Setup: The strategy identifies bearish breakouts when:
The current candle's closing price is lower than the previous candle's closing price.
The low of the previous candle is lower than the lows of the two candles before it.
Risk Management:
Stop-Loss: For each trade, a stop-loss is automatically set:
For long trades, the stop-loss is set to the low of the previous candle.
For short trades, the stop-loss is set to the high of the previous candle.
This ensures that losses are minimized if the breakout fails.
Exit Logic:
The trade is closed automatically when the stop-loss is hit.
This approach maintains discipline and prevents emotional trading.
Strategy Workflow
Entry Criteria:
Long Entry: A long trade is triggered when:
The current close is greater than the previous close.
The high of the previous candle exceeds the highs of the two candles before it.
Short Entry: A short trade is triggered when:
The current close is less than the previous close.
The low of the previous candle is below the lows of the two candles before it.
Stop-Loss Placement:
For long trades, the stop-loss is set at the low of the previous candle.
For short trades, the stop-loss is set at the high of the previous candle.
Trade Management:
Trades are exited automatically if the stop-loss level is hit.
The strategy avoids re-entering trades until new breakout conditions are met.
Default Settings
Position Sizing:
The default position size is set to 1% of the account equity. This ensures proper risk management and prevents overexposure to the market.
Stop-Loss:
Stop-loss levels are automatically calculated based on the previous candle’s high or low.
Timeframes:
The strategy is versatile and works across multiple timeframes. However, it is recommended to test it on 15-minute, 1-hour, and daily charts for optimal performance.
Key Features
Automated Trade Execution:
The strategy handles both trade entry and exit automatically based on pre-defined conditions.
Built-In Risk Management:
The automatic stop-loss placement ensures losses are minimized on failed breakouts.
Works Across Markets:
The strategy is compatible with a wide range of instruments, including indices, stocks, forex, and cryptocurrencies.
Clear Signals:
Entry and exit points are straightforward and based on objective conditions, reducing ambiguity.
Versatility:
Can be used for both day trading and swing trading, depending on the chosen timeframe.
Best Practices for Using This Strategy
Backtesting:
Test the strategy on your chosen instrument and timeframe using TradingView's Strategy Tester to evaluate its performance.
Market Conditions:
The strategy performs best in trending markets or during periods of high volatility. Avoid using it in range-bound or choppy markets.
Position Sizing:
Use the default position size (1% of equity) or adjust based on your risk tolerance and account size.
Instrument Selection:
Focus on instruments with good liquidity and volatility, such as indices (e.g., NIFTY, BANKNIFTY), forex pairs, or major cryptocurrencies (e.g., Bitcoin, Ethereum).
Potential Enhancements
To make the strategy even more robust, consider adding the following optional features:
Stop-Loss Multiplier:
Allow users to customize the stop-loss distance as a multiple of the default level (e.g., 1.5x the low or high of the previous candle).
Take-Profit Levels:
Add user-defined take-profit levels, such as a fixed risk-reward ratio (e.g., 1:2).
Time Filter:
Include an option to restrict trading to specific market hours (e.g., avoid low-liquidity times).
Conclusion
The Sunil 2 Bar Breakout Strategy is an excellent tool for traders looking to capitalize on breakout opportunities while maintaining disciplined risk management. Its simplicity, combined with its effectiveness, makes it suitable for traders of all experience levels. By adhering to the clearly defined rules, traders can achieve consistent results while avoiding emotional trading decisions.
This strategy is a reliable addition to any trader’s toolbox and is designed to work seamlessly across different market conditions and instruments.
Accurate Bollinger Bands mcbw_ [True Volatility Distribution]The Bollinger Bands have become a very important technical tool for discretionary and algorithmic traders alike over the last decades. It was designed to give traders an edge on the markets by setting probabilistic values to different levels of volatility. However, some of the assumptions that go into its calculations make it unusable for traders who want to get a correct understanding of the volatility that the bands are trying to be used for. Let's go through what the Bollinger Bands are said to show, how their calculations work, the problems in the calculations, and how the current indicator I am presenting today fixes these.
--> If you just want to know how the settings work then skip straight to the end or click on the little (i) symbol next to the values in the indicator settings window when its on your chart <--
--------------------------- What Are Bollinger Bands ---------------------------
The Bollinger Bands were formed in the 1980's, a time when many retail traders interacted with their symbols via physically printed charts and computer memory for personal computer memory was measured in Kb (about a factor of 1 million smaller than today). Bollinger Bands are designed to help a trader or algorithm see the likelihood of price expanding outside of its typical range, the further the lines are from the current price implies the less often they will get hit. With a hands on understanding many strategies use these levels for designated levels of breakout trades or to assist in defining price ranges.
--------------------------- How Bollinger Bands Work ---------------------------
The calculations that go into Bollinger Bands are rather simple. There is a moving average that centers the indicator and an equidistant top band and bottom band are drawn at a fixed width away. The moving average is just a typical moving average (or common variant) that tracks the price action, while the distance to the top and bottom bands is a direct function of recent price volatility. The way that the distance to the bands is calculated is inspired by formulas from statistics. The standard deviation is taken from the candles that go into the moving average and then this is multiplied by a user defined value to set the bands position, I will call this value 'the multiple'. When discussing Bollinger Bands, that trading community at large normally discusses 'the multiple' as a multiplier of the standard deviation as it applies to a normal distribution (gaußian probability). On a normal distribution the number of standard deviations away (which trades directly use as 'the multiple') you are directly corresponds to how likely/unlikely something is to happen:
1 standard deviation equals 68.3%, meaning that the price should stay inside the 1 standard deviation 68.3% of the time and be outside of it 31.7% of the time;
2 standard deviation equals 95.5%, meaning that the price should stay inside the 2 standard deviation 95.5% of the time and be outside of it 4.5% of the time;
3 standard deviation equals 99.7%, meaning that the price should stay inside the 3 standard deviation 99.7% of the time and be outside of it 0.3% of the time.
Therefore when traders set 'the multiple' to 2, they interpret this as meaning that price will not reach there 95.5% of the time.
---------------- The Problem With The Math of Bollinger Bands ----------------
In and of themselves the Bollinger Bands are a great tool, but they have become misconstrued with some incorrect sense of statistical meaning, when they should really just be taken at face value without any further interpretation or implication.
In order to explain this it is going to get a bit technical so I will give a little math background and try to simplify things. First let's review some statistics topics (distributions, percentiles, standard deviations) and then with that understanding explore the incorrect logic of how Bollinger Bands have been interpreted/employed.
---------------- Quick Stats Review ----------------
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(If you are comfortable with statistics feel free to skip ahead to the next section)
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-------- I: Probability distributions --------
When you have a lot of data it is helpful to see how many times different results appear in your dataset. To visualize this people use "histograms", which just shows how many times each element appears in the dataset by stacking each of the same elements on top of each other to form a graph. You may be familiar with the bell curve (also called the "normal distribution", which we will be calling it by). The normal distribution histogram looks like a big hump around zero and then drops off super quickly the further you get from it. This shape (the bell curve) is very nice because it has a lot of very nifty mathematical properties and seems to show up in nature all the time. Since it pops up in so many places, society has developed many different shortcuts related to it that speed up all kinds of calculations, including the shortcut that 1 standard deviation = 68.3%, 2 standard deviations = 95.5%, and 3 standard deviations = 99.7% (these only apply to the normal distribution). Despite how handy the normal distribution is and all the shortcuts we have for it are, and how much it shows up in the natural world, there is nothing that forces your specific dataset to look like it. In fact, your data can actually have any possible shape. As we will explore later, economic and financial datasets *rarely* follow the normal distribution.
-------- II: Percentiles --------
After you have made the histogram of your dataset you have built the "probability distribution" of your own dataset that is specific to all the data you have collected. There is a whole complicated framework for how to accurately calculate percentiles but we will dramatically simplify it for our use. The 'percentile' in our case is just the number of data points we are away from the "middle" of the data set (normally just 0). Lets say I took the difference of the daily close of a symbol for the last two weeks, green candles would be positive and red would be negative. In this example my dataset of day by day closing price difference is:
week 1:
week 2:
sorting all of these value into a single dataset I have:
I can separate the positive and negative returns and explore their distributions separately:
negative return distribution =
positive return distribution =
Taking the 25th% percentile of these would just be taking the value that is 25% towards the end of the end of these returns. Or akin the 100%th percentile would just be taking the vale that is 100% at the end of those:
negative return distribution (50%) = -5
positive return distribution (50%) = +4
negative return distribution (100%) = -10
positive return distribution (100%) = +20
Or instead of separating the positive and negative returns we can also look at all of the differences in the daily close as just pure price movement and not account for the direction, in this case we would pool all of the data together by ignoring the negative signs of the negative reruns
combined return distribution =
In this case the 50%th and 100%th percentile of the combined return distribution would be:
combined return distribution (50%) = 4
combined return distribution (100%) = 10
Sometimes taking the positive and negative distributions separately is better than pooling them into a combined distribution for some purposes. Other times the combined distribution is better.
Most financial data has very different distributions for negative returns and positive returns. This is encapsulated in sayings like "Price takes the stairs up and the elevator down".
-------- III: Standard Deviation --------
The formula for the standard deviation (refereed to here by its shorthand 'STDEV') can be intimidating, but going through each of its elements will illuminate what it does. The formula for STDEV is equal to:
square root ( (sum ) / N )
Going back the the dataset that you might have, the variables in the formula above are:
'mean' is the average of your entire dataset
'x' is just representative of a single point in your dataset (one point at a time)
'N' is the total number of things in your dataset.
Going back to the STDEV formula above we can see how each part of it works. Starting with the '(x - mean)' part. What this does is it takes every single point of the dataset and measure how far away it is from the mean of the entire dataset. Taking this value to the power of two: '(x - mean) ^ 2', means that points that are very far away from the dataset mean get 'penalized' twice as much. Points that are very close to the dataset mean are not impacted as much. In practice, this would mean that if your dataset had a bunch of values that were in a wide range but always stayed in that range, this value ('(x - mean) ^ 2') would end up being small. On the other hand, if your dataset was full of the exact same number, but had a couple outliers very far away, this would have a much larger value since the square par of '(x - mean) ^ 2' make them grow massive. Now including the sum part of 'sum ', this just adds up all the of the squared distanced from the dataset mean. Then this is divided by the number of values in the dataset ('N'), and then the square root of that value is taken.
There is nothing inherently special or definitive about the STDEV formula, it is just a tool with extremely widespread use and adoption. As we saw here, all the STDEV formula is really doing is measuring the intensity of the outliers.
--------------------------- Flaws of Bollinger Bands ---------------------------
The largest problem with Bollinger Bands is the assumption that price has a normal distribution. This is assumption is massively incorrect for many reasons that I will try to encapsulate into two points:
Price return do not follow a normal distribution, every single symbol on every single timeframe has is own unique distribution that is specific to only itself. Therefore all the tools, shortcuts, and ideas that we use for normal distributions do not apply to price returns, and since they do not apply here they should not be used. A more general approach is needed that allows each specific symbol on every specific timeframe to be treated uniquely.
The distributions of price returns on the positive and negative side are almost never the same. A more general approach is needed that allows positive and negative returns to be calculated separately.
In addition to the issues of the normal distribution assumption, the standard deviation formula (as shown above in the quick stats review) is essentially just a tame measurement of outliers (a more aggressive form of outlier measurement might be taking the differences to the power of 3 rather than 2). Despite this being a bit of a philosophical question, does the measurement of outlier intensity as defined by the STDEV formula really measure what we want to know as traders when we're experiencing volatility? Or would adjustments to that formula better reflect what we *experience* as volatility when we are actively trading? This is an open ended question that I will leave here, but I wanted to pose this question because it is a key part of what how the Bollinger Bands work that we all assume as a given.
Circling back on the normal distribution assumption, the standard deviation formula used in the calculation of the bands only encompasses the deviation of the candles that go into the moving average and have no knowledge of the historical price action. Therefore the level of the bands may not really reflect how the price action behaves over a longer period of time.
------------ Delivering Factually Accurate Data That Traders Need------------
In light of the problems identified above, this indicator fixes all of these issue and delivers statistically correct information that discretionary and algorithmic traders can use, with truly accurate probabilities. It takes the price action of the last 2,000 candles and builds a huge dataset of distributions that you can directly select your percentiles from. It also allows you to have the positive and negative distributions calculated separately, or if you would like, you can pool all of them together in a combined distribution. In addition to this, there is a wide selection of moving averages directly available in the indicator to choose from.
Hedge funds, quant shops, algo prop firms, and advanced mechanical groups all employ the true return distributions in their work. Now you have access to the same type of data with this indicator, wherein it's doing all the lifting for you.
------------------------------ Indicator Settings ------------------------------
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---- Moving average ----
Select the type of moving average you would like and its length
---- Bands ----
The percentiles that you enter here will be pulled directly from the return distribution of the last 2,000 candles. With the typical Bollinger Bands, traders would select 2 standard deviations and incorrectly think that the levels it highlights are the 95.5% levels. Now, if you want the true 95.5% level, you can just enter 95.5 into the percentile value here. Each of the three available bands takes the true percentile you enter here.
---- Separate Positive & Negative Distributions----
If this box is checked the positive and negative distributions are treated indecently, completely separate from each other. You will see that the width of the top and bottom bands will be different for each of the percentiles you enter.
If this box is unchecked then all the negative and positive distributions are pooled together. You will notice that the width of the top and bottom bands will be the exact same.
---- Distribution Size ----
This is the number of candles that the price return is calculated over. EG: to collect the price return over the last 33 candles, the difference of price from now to 33 candles ago is calculated for the last 2,000 candles, to build a return distribution of 2000 points of price differences over 33 candles.
NEGATIVE NUMBERS(<0) == exact number of candles to include;
EG: setting this value to -20 will always collect volatility distributions of 20 candles
POSITIVE NUMBERS(>0) == number of candles to include as a multiple of the Moving Average Length value set above;
EG: if the Moving Average Length value is set to 22, setting this value to 2 will use the last 22*2 = 44 candles for the collection of volatility distributions
MORE candles being include will generally make the bands WIDER and their size will change SLOWER over time.
I wish you focus, dedication, and earnest success on your journey.
Happy trading :)
JJ Psychological Levels (125 Increments)Psychological Levels Indicator
Description:
The Psychological Levels Indicator is a versatile tool designed for traders to identify key price levels that often act as support or resistance zones in the market. These levels are plotted at regular intervals, customizable by the user, starting from a base price level. This is particularly useful for spotting psychological price points that traders and investors frequently monitor.
Key Features:
1.Dynamic Psychological Levels:
- The script calculates and displays horizontal lines at price levels separated by customizable increments (default: 125 points).
- These levels are dynamically adjusted to the visible range of the chart.
2. Customizable Inputs:
- Starting Level: Set the base level from which increments are calculated (e.g., 0 or 1000).
- Step Size: Define the interval between levels (e.g., 125 for indices like Bank NIFTY).
3. Visual Representation:
- Horizontal lines are drawn at each psychological level, helping traders quickly identify key zones.
- Labels are placed next to each level, displaying the corresponding price for easy reference.
4. Application Across Instruments:
- This indicator works seamlessly with various asset classes, including stocks, indices, forex, and cryptocurrencies.
How to Use:
1.Identify Key Price Zones:
- Use the plotted psychological levels to spot areas where price action is likely to react.
- Levels such as 1125, 1250, and 1375 (for a step size of 125) are visually highlighted.
2. Plan Trades Around Key Levels:
- These levels can act as support/resistance or breakout points, providing opportunities for entry, exit, and stop-loss placement.
3. Customizable Settings:
- Adjust the starting level and step size to tailor the indicator to your trading instrument or strategy.
Why Psychological Levels Matter:
Psychological levels are widely followed by traders and often coincide with key market turning points due to their significance in human behavior and market psychology. They are frequently used by institutional traders, making them valuable reference points for intraday and swing trading.
Custom Settings:
- **Starting Level:** Default: `0`
- **Step Size:** Default: `125`
Disclaimer:
This indicator is a technical analysis tool and is not intended to provide financial advice. Always combine it with other indicators and perform your due diligence before making trading decisions.
Swing Structure Scanner [LuxAlgo]The Swing Structure Scanner Indicator is a dashboard type indicator which displays a Consolidated "High/Low-Only" view of swing structure, with the capability to retrieve and display swing points from up to 6 different tickers and timeframes at once.
🔶 USAGE
This indicator displays swing structure data from up to 6 unique tickers or timeframes; Each graph represents the current swing structure retrieved from the requested chart/s.
Each swing graph displays the current live swing point positioning relative to the previous swing points. By analyzing the different formations, patterns can more easily be recognized and found across multiple tickers or timeframes at once.
This indicator serves as a nifty tool for confluence recognition, whether that's confluence throughout market tickers, or confluence through higher timeframes on the same ticker.
Alternatively, viewing the relative positioning of each swing point to each other, should give a clearer idea when higher lows or lower highs are formed. This can potentially indicate a newly forming trend, as well as serving as a warning to watch for breakouts.
The swing length can be changed to align with each individual's strategy, as well as a display look back can be adjusted to show more or less swing points at one time.
The display is fairly customizable, it is not fixed to 6 symbols at all times and can be minimized to only display the number of symbols needed; Additionally, the display can be set to vertical mode or horizontal(default) to utilize as needed.
Note: Hover over the swing point in the dashboard to get a readout of the exact price level of the swing point.
🔶 SETTINGS
Swing Length: Set the swing length for the structure calculations.
Swing Display Lookback: Sets the number of swing points (Pairs) to display in each Swing Graph display.
Symbols: Sets the Timeframe and Symbol for each Swing Graph.
Vertical Display: Display the Swing Graphs up and down, rather than side to side.
Scaling Factor: Scales the entire indicator up or down, to fit your needs.
Option Time ValueThis TradingView script calculates and visualizes the time value of an option (Call or Put) based on its market price and intrinsic value. The time value represents the premium paid for the option above its intrinsic value, and it is a key metric for analyzing the cost of holding an option.
This script is suitable for traders analyzing options on indices or stocks, such as the NIFTY 50, and supports both Call and Put options. By dynamically extracting the strike price and option type from the input symbol, it adapts seamlessly to the selected instrument.
Key Features:
Dynamic Instrument Selection:
Users can input the underlying asset (e.g., NSE:NIFTY) and the specific option instrument (e.g., NSE:NIFTY250327C24000 for a Call or NSE:NIFTY250327P24000 for a Put).
Automatic Option Type Detection:
The script detects whether the option is a Call or a Put by parsing the input symbol for the characters "C" (Call) or "P" (Put).
Dynamic Strike Price Extraction:
The strike price is dynamically extracted from the input option symbol, eliminating the need for hardcoding and reducing user errors.
Key Metrics Plotted:
Time Value: The premium paid above the intrinsic value, plotted in blue.
Intrinsic Value: The calculated intrinsic value of the option, plotted in green.
Seamless Integration:
Designed for ease of use and integration into existing TradingView setups.
Automatically adjusts to the timeframe and pricing data of the selected instruments.
Options Cumulative Chart AnalysysThis Pine Script is a comprehensive tool designed for traders analyzing options data on TradingView. It aggregates multiple symbols to calculate and visualize cumulative performance, providing essential insights for decision-making.
Key Features:
Symbol and Strike Price Configuration:
Supports up to four configurable symbols (e.g., NIFTY options).
Allows defining buy/sell actions, quantities, and entry premiums for each symbol.
Customizable Chart Display:
Plot candlesticks and line charts for cumulative data.
Configurable Exponential Moving Averages (EMAs) for technical analysis.
Entry and price lines with customizable colors.
Timeframe Management:
Supports higher timeframe (HTF) candles.
Ensures compatibility with the current chart timeframe to maintain accuracy.
Dynamic Coloring and Visualization:
Red, green, and gray color schemes for body and wicks of candlesticks based on price movements.
Customizable positive and negative color schemes.
Table for Data Representation:
Displays an info table showing symbols, quantities, entry prices, and latest traded prices (LTP).
Adjustable table position, overlay, and styling.
Premium and Profit/Loss Calculations:
Calculates cumulative open, high, low, and close prices considering premiums and quantities.
Tracks the profit and loss dynamically based on cumulative premiums and market prices.
Alerts and Notifications:
Alerts triggered on specific conditions, such as when the profit/loss turns negative.
Modular Functions:
Functions for calculating high/low/open/close values, combining premiums, and drawing candlesticks.
Utilities for symbol management and security requests.
Custom Settings:
Includes a wide range of input options for customization:
Timeframes, EMA lengths, colors, table configurations, and more.
Error Handling:
Validates timeframe inputs to ensure compatibility and prevent runtime errors.
This script is designed for advanced traders looking for a customizable tool to analyze cumulative options data efficiently. By leveraging its modular design and visual elements, users can make informed trading decisions with a holistic view of market movements.
Option vs Index Performance**Indicator Name:** Option vs Index Performance
**Description:**
This indicator helps traders analyze the relative performance of options compared to their underlying index (e.g., Nifty 50). It evaluates and highlights zones based on two key metrics:
1. **Bar-to-Bar Performance:** Compares the percentage movement of the option price against the index movement on a bar-by-bar basis.
- **Green Zone**: Option outperforms the index.
- **Yellow Zone**: Option moves in sync with the index.
- **Red Zone**: Option underperforms the index.
2. **Swing Alignment:** Tracks the swing structure of the index (higher highs, higher lows) and compares it with the option chart. The indicator checks if the option's swings align with or deviate from the index's swing pattern.
The final output combines both conditions, providing clear visual zones below the chart:
- **Green**: Overperformance and alignment with the index.
- **Yellow**: Neutral performance or partial alignment.
- **Red**: Underperformance or misalignment with the index.
Use this tool on option charts to quickly identify opportunities and assess whether the option's movement is in line with the broader market trend.
