Bracket IndicatorThis is an indicator that shows tick target above and below the chart. Allows for visualizing continual bracket target moving with price before getting into trade.
So, for example, if you are watching price and wanting to target 10 points above or below. You can set this bracket indicator on the chart and you will be able to in real time see 10 points above/below the current price.
指標和策略
KDJ J Value Strategy (Weekly)This strategy is based on the KDJ indicator at the weekly level, using the changes in the J value to generate buy and sell signals. When the J value drops below -5, it is considered a buy signal; when the J value rises above 90, it is considered a sell signal.
The 950 Bar StrategyNQ 9:50 AM Candle Strategy v3 (Trade at 9:55AM) - 1 Contract
Also called the 950 Standard. The 950 Strategy.
This strategy places its trade at 9:55am each day based on the close of the 9:50am candle. Uses 5min timeframe candles. If candle closes red, or bearish, the strategy goes short. If candle closes green, or bullish, the strategy goes long. Brackets are 150tick TP and 200tick SL.
Squat Ratio IndicatorThe Squat Ratio is a market indicator that measures the relationship between volume and price movement to identify potential reversals or strong trends. It helps traders assess whether a price movement is supported by sufficient volume.
Formula for Squat Ratio
\text{Squat Ratio} = \frac{\text{Current Bar Volume}}{\text{Average Volume of Previous Bars}} \times \frac{\text{Current Bar Range}}{\text{Average Range of Previous Bars}}
Where:
• Current Bar Volume = Volume of the current price bar
• Average Volume = Average volume over a chosen period (e.g., 10 or 20 bars)
• Current Bar Range = (High - Low) of the current bar
• Average Range = Average of the past price ranges
How to Interpret Squat Ratio
1. High Squat Ratio (>1)
• Indicates that price movement is happening with higher volume than usual but is not breaking out significantly.
• Suggests potential accumulation (buyers stepping in) or distribution (sellers offloading).
• Could signal a trend reversal or strong breakout soon.
2. Low Squat Ratio (<1)
• Suggests that the price is moving with low volume, meaning the current move may lack strength.
• Often seen in weak trends or consolidation phases.
Using Squat Ratio in Nifty Trading
• If Nifty moves up with a high Squat Ratio, it may indicate strong buying interest and the potential for a breakout.
• If Nifty falls with a high Squat Ratio, it could mean strong selling pressure and a possible trend reversal.
• It can be used with other indicators like RSI, VWAP, and Delta for better trade confirmation.
Three different momentumThis indicator is a custom-built tool for TradingView that combines three different momentum indicators into one, providing a comprehensive view of market momentum. It allows traders to:
Simultaneously monitor multiple momentum indicators: Instead of switching between different momentum indicators, you can see them all at once on a single chart.
Identify potential trading signals: By observing the convergence or divergence of the three momentum indicators, you can identify potential buy or sell signals.
Customize the indicator: You can adjust the parameters of each momentum indicator to suit your trading style and preferences.
How it Works
The Triple Momentum Indicator calculates and displays three different momentum indicators on the same chart. The specific momentum indicators used can be customized, but some popular options include:
Relative Strength Index (RSI): Measures the speed and change of price movements.
Moving Average Convergence Divergence (MACD): Shows the relationship between two moving averages of a security's price.
Stochastic Oscillator: Tracks the momentum of price by comparing the closing price to the range of prices over a given period.
How to Use It
Add the indicator to your TradingView chart.
Customize the settings: Adjust the parameters of each momentum indicator to your liking.
Interpret the signals: Look for areas where the three momentum indicators converge or diverge. This can indicate potential buy or sell signals.
Advantages
Saves time and effort: You don't have to switch between different momentum indicators.
Provides a comprehensive view of momentum: You can see how different momentum indicators are interacting with each other.
Can help identify potential trading signals: By observing the convergence or divergence of the three momentum indicators, you can identify potential buy or sell signals.
Limitations
No indicator is perfect: The Triple Momentum Indicator is just one tool in your trading arsenal. It should not be used in isolation to make trading decisions.
False signals are possible: Like any indicator, the Triple Momentum Indicator can generate false signals.
Requires some knowledge of momentum indicators: To use this indicator effectively, you need to have a basic understanding of how momentum indicators work.
Overall, the Triple Momentum Indicator is a valuable tool for traders who want to get a comprehensive view of market momentum. It can help you identify potential trading signals and make more informed trading decisions.
RSI Deviation & Correlation by DINVESTORQOverview:
This indicator analyzes the Relative Strength Index (RSI) over 252 days, calculating its mean (average) and standard deviation. Based on this, it sets an upper and lower threshold to determine overbought and oversold conditions.
Additionally, it calculates the correlation between RSI and price using a moving average, helping traders understand if RSI is moving in sync with price trends.
Key Features:
✅ RSI Deviation Bands
Upper Limit = RSI Avg + (2 × SD × 2.5)
Lower Limit = RSI Avg - (2 × SD × 2.5)
✅ Trading Signals:
Sell Signal: RSI crosses above the upper limit
Buy Signal: RSI drops below the lower limit
✅ RSI-Price Correlation Moving Average
Uses 50-day correlation between RSI and price
Helps confirm trend strength
✅ Customizable Parameters
RSI Length (Default: 252 Days)
Correlation Period (Default: 50 Days)
✅ Chart Visuals:
Plots RSI (blue), Upper Band (red), Lower Band (green)
Plots RSI-Price Correlation (orange)
Buy/Sell signals appear on chart
TradingView Indicator: RSI Deviation & Correlation Indicator
Overview:
This indicator analyzes the Relative Strength Index (RSI) over 252 days, calculating its mean (average) and standard deviation. Based on this, it sets an upper and lower threshold to determine overbought and oversold conditions.
Additionally, it calculates the correlation between RSI and price using a moving average, helping traders understand if RSI is moving in sync with price trends.
Key Features:
✅ RSI Deviation Bands
Upper Limit = RSI Avg + (2 × SD × 2.5)
Lower Limit = RSI Avg - (2 × SD × 2.5)
✅ Trading Signals:
Sell Signal: RSI crosses above the upper limit
Buy Signal: RSI drops below the lower limit
✅ RSI-Price Correlation Moving Average
Uses 50-day correlation between RSI and price
Helps confirm trend strength
✅ Customizable Parameters
RSI Length (Default: 252 Days)
Correlation Period (Default: 50 Days)
✅ Chart Visuals:
Plots RSI (blue), Upper Band (red), Lower Band (green)
Plots RSI-Price Correlation (orange)
Buy/Sell signals appear on chart
Pine Script for TradingView:
pinescript
Copy
Edit
//version=5
indicator("RSI Deviation & Correlation Indicator", overlay=false)
// User Inputs
length = input.int(252, title="RSI Period")
corr_length = input.int(50, title="Correlation Period")
// RSI Calculation
rsi_value = ta.rsi(close, length)
// Calculate Mean and Standard Deviation of RSI
rsi_avg = ta.sma(rsi_value, length)
rsi_sd = ta.stdev(rsi_value, length) * 2.5
// Define Upper and Lower Limits
upper_limit = rsi_avg + (rsi_sd * 2)
lower_limit = rsi_avg - (rsi_sd * 2)
// Buy and Sell Signals
buy_signal = rsi_value < lower_limit
sell_signal = rsi_value > upper_limit
// Correlation Moving Average between RSI and Price
rsi_price_correlation = ta.correlation(rsi_value, close, corr_length)
// Plot RSI with Bands
plot(rsi_value, title="RSI", color=color.blue)
plot(upper_limit, title="Upper Limit", color=color.red, linewidth=2)
plot(lower_limit, title="Lower Limit", color=color.green, linewidth=2)
plot(rsi_avg, title="Average RSI", color=color.gray, linewidth=2)
// Display Buy/Sell Signals on Chart
plotshape(buy_signal, location=location.bottom, color=color.green, style=shape.labelup, title="BUY Signal", size=size.small)
plotshape(sell_signal, location=location.top, color=color.red, style=shape.labeldown, title="SELL Signal", size=size.small)
// Plot Correlation Moving Average
plot(rsi_price_correlation, title="RSI-Price Correlation", color=color.orange, linewidth=2)
// Alerts for Buy/Sell
alertcondition(buy_signal, title="BUY Alert", message="RSI is below the Lower Limit - BUY Signal")
alertcondition(sell_signal, title="SELL Alert", message="RSI is above the Upper Limit - SELL Signal")
How to Use in TradingView:
1️⃣ Open TradingView and go to the Pine Editor
2️⃣ Paste the above Pine Script
3️⃣ Click Add to Chart
4️⃣ Adjust RSI Length and Correlation Period if needed
5️⃣ Buy/Sell alerts will trigger when conditions match
Trading Strategy:
📉 Sell (Short Entry) when RSI crosses above the upper limit
📈 Buy (Long Entry) when RSI drops below the lower limit
📊 Confirm trends with RSI-Price Correlation:
+1 means RSI and price are moving together
-1 means RSI and price are diverging
Final Notes:
Works best on higher timeframes (Daily, Weekly)
Helps filter overbought/oversold false signals
Can be combined with other indicators (MACD, Bollinger Bands, etc.)
AMD Session Structure Levels# Market Structure & Manipulation Probability Indicator
## Overview
This advanced indicator is designed for traders who want a systematic approach to analyzing market structure, identifying manipulation, and assessing probability-based trade setups. It incorporates four core components:
### 1. Session Price Action Analysis
- Tracks **OHLC (Open, High, Low, Close)** within defined sessions.
- Implements a **dual tracking system**:
- **Official session levels** (fixed from the session open to close).
- **Real-time max/min tracking** to differentiate between temporary spikes and real price acceptance.
### 2. Market Manipulation Detection
- Identifies **manipulative price action** using the relationship between the open and close:
- If **price closes below open** → assumes **upward manipulation**, followed by **downward distribution**.
- If **price closes above open** → assumes **downward manipulation**, followed by **upward distribution**.
- Normalized using **ATR**, ensuring adaptability across different volatility conditions.
### 3. Probability Engine
- Tracks **historical wick ratios** to assess trend vs. reversal conditions.
- Calculates **conditional probabilities** for price moves.
- Uses a **special threshold system (0.45 and 0.03)** for reversal signals.
- Provides **real-time probability updates** to enhance trade decision-making.
### 4. Market Condition Classification
- Classifies market conditions using a **wick-to-body ratio**:
```pine
wick_to_body_ratio = open > close ? upper_wick / (high - low) : lower_wick / (high - low)
```
- **Low ratio (<0.25)** → Likely a **trend day**.
- **High ratio (>0.25)** → Likely a **range day**.
---
## Why This Indicator Stands Out
### ✅ Smarter Level Detection
- Uses **ATR-based dynamic levels** instead of static support/resistance.
- Differentiates **manipulation from distribution** for better decision-making.
- Updates probabilities **in real-time**.
### ✅ Memory-Efficient Design
- Implements **circular buffers** to maintain efficiency:
```pine
var float manipUp = array.new_float(lookbackPeriod, 0.0)
var float manipDown = array.new_float(lookbackPeriod, 0.0)
```
- Ensures **constant memory usage**, even over extended trading sessions.
### ✅ Advanced Probability Calculation
- Utilizes **conditional probabilities** instead of simple averages.
- Incorporates **market context** through wick analysis.
- Provides **actionable signals** via a probability table.
---
## Trading Strategy Guide
### **Best Entry Setups**
✅ Wait for **price to approach manipulation levels**.
✅ Confirm using the **probability table**.
✅ Check the **wick ratio for context**.
✅ Enter when **conditional probability aligns**.
### **Smart Exit Management**
✅ Use **distribution levels** as **profit targets**.
✅ Scale out **when probabilities shift**.
✅ Monitor **wick percentiles** for confirmation.
### **Risk Management**
✅ Size positions based on **probability readings**.
✅ Place stops at **manipulation levels**.
✅ Adjust position size based on **trend vs. range classification**.
---
## Configuration Tips
### **Session Settings**
```pine
sessionTime = input.session("0830-1500", "Session Hours")
weekDays = input.string("23456", "Active Days")
```
- Match these to your **primary trading session**.
- Adjust for different **market opens** if needed.
### **Analysis Parameters**
```pine
lookbackPeriod = input.int(50, "Lookback Period")
low_threshold = input.float(0.25, "Trend/Range Threshold")
```
- **50 periods** is a good starting point but can be optimized per instrument.
- The **0.25 threshold** is ideal for most markets but may need adjustments.
---
## Market Structure Breakdown
### **Trend/Continuation Days**
- **Characteristics:**
✅ Small **opposing wicks** (minimal counter-pressure).
✅ Clean, **directional price movement**.
- **Bullish Trend Day Example:**
✅ Small **lower wicks** (minimal downward pressure).
✅ Strong **closes near the highs** → **Buyers in control**.
- **Bearish Trend Day Example:**
✅ Small **upper wicks** (minimal upward pressure).
✅ Strong **closes near the lows** → **Sellers in control**.
### **Reversal Days**
- **Characteristics:**
✅ **Large opposing wicks** → Failed momentum in the initial direction.
- **Bullish Reversal Example:**
✅ **Large upper wick early**.
✅ **Strong close from the lows** → **Sellers failed to maintain control**.
- **Bearish Reversal Example:**
✅ **Large lower wick early**.
✅ **Weak close from the highs** → **Buyers failed to maintain control**.
---
## Summary
This indicator systematically quantifies market structure by measuring **manipulation, distribution, and probability-driven trade setups**. Unlike traditional indicators, it adapts dynamically using **ATR, historical probabilities, and real-time tracking** to offer a structured, data-driven approach to trading.
🚀 **Use this tool to enhance your decision-making and gain an objective edge in the market!**
Open InterestOpen Interest (OI) refers to the total number of outstanding derivative contracts, such as futures or options, that have not been settled. It represents the total number of active positions in a market that are yet to be closed or offset.
5-Min Trendline Breakout Based on H1 S/R [ABU SETTS]Trail, just wrote and still doing tuning.
What Changed?
Fixed plotshape Size Argument:- Added a switch statement to convert the input string (breakout_label_size) into a const string (label_size).
This ensures the size argument in plotshape receives a valid const string.
Improved Flexibility: - The breakout_label_size input now works correctly with plotshape and label.new.
How to Use
Adjust the Pivot Length, Slope Multiplier, and other inputs to customize the script.
Use the Breakout Label Size dropdown to select the size of the breakout labels (tiny, small, or normal).
Toggle Show Only Confirmed Breakouts to filter out unconfirmed signals.
ROC with closed based coloring & info table [DB]Rate of Change (ROC) Basics
The Rate of Change (ROC) is a momentum oscillator measuring the percentage price change between the current close and the close from N periods ago.
Calculated as: ROC = * 100
Traders use ROC to:
Identify overbought/oversold conditions
Spot momentum shifts
Confirm trend strength
My improvements:
Visual Clarity
Color-Coded Direction: ROC line changes color (green/red/yellow) based on intra-candle momentum shifts.
Direction Table: Instant view of the last change in ROC with the candle close (▲ UP / ▼ DOWN / ▶ FLAT).
Cells for current value and previous change between timeframe bar period.
What you can benefit with this over the regular ROC:
Faster Analysis: The visual cues make direction and strength instantly obvious and it allows for faster decision making while preserving more mental capital.
Quarterly Performance█ OVERVIEW
The Quarterly Performance indicator is designed to visualise and compare the performance of different Quarters of the year. This indicator explores one of the many calendar based anomalies that exist in financial markets.
In the context of financial analysis, a calendar based anomaly refers to patterns or tendencies that are linked to specific time periods, such as days of the week, weeks of the month, or months of the year. This indicator helps explore whether such a calendar based anomaly exists between quarters.
By calculating cumulative quarterly performance and counting the number of quarters with positive returns, it provides a clear snapshot of whether one set of quarters tends to outperform the others, potentially highlighting a calendar based anomaly if a significant difference is observed.
█ FEATURES
Customisable time window through input settings.
Tracks cumulative returns for each quarter separately.
Easily adjust table settings like position and font size via input options.
Clear visual distinction between quarterly performance using different colours.
Built-in error checks to ensure the indicator is applied to the correct timeframe.
█ HOW TO USE
Add the indicator to a chart with a 3 Month (Quarterly) timeframe.
Choose your start and end dates in the Time Settings.
Enable or disable the performance table in the Table Settings as needed.
View the cumulative performance, with Q1 in blue, Q2 in red, Q3 in green and Q4 in purple.
Filtered Trend Levels with FibonacciCurrent Timeframe Check: I added isCurrentTimeframe to only display Fibonacci levels, trend labels, and other elements when the current timeframe matches the chart’s timeframe.
For example, this will show the Fibonacci levels only on a "5-minute" timeframe if timeframe.period == "5" or on a daily chart if timeframe.period == "1D".
Limit to Current Timeframe: All the labels and shapes (for Fibonacci levels, HH/HL, etc.) will only be shown if the isCurrentTimeframe condition is true, which ensures they only appear on the active timeframe.
How to Use:
Change your chart to different time frames (e.g., 5-minute, 1-hour, or daily).
The labels and circles will only show up when the script is applied to that specific timeframe.
This version ensures that only the relevant data for the currently active time frame is displayed, while you can also adjust the Fibonacci levels as needed.
Let me know if this works for you!
Bitcoin Power LawBitcoin power law indicator, based on Giovanni Santostasi work.
It provides a centre line with support and resistant bands
USDT.D + USDT.C ALL TIMEFRAMESThis indicator combines the dominance of USDT (USDT.D) and USDC (USDC.D) to track total stablecoin market share across all timeframes. It displays the combined dominance as candlesticks, providing a clearer view of market liquidity shifts and investor sentiment.
📌 How to Use:
Green candles indicate rising stablecoin dominance (potential risk-off sentiment).
Red candles indicate declining stablecoin dominance (potential risk-on sentiment).
Works on all timeframes, from intraday scalping to macro trend analysis.
This tool is essential for traders looking to analyze stablecoin liquidity flow, identify market turning points, and refine trading strategies based on stablecoin dominance behavior. 🚀
NFP High/Low LevelsChart the last 12 NFP Day High and Low values automatically.
Review and update indicator settings accordingly.
*Feel free to use/edit/improve
*shoutout to DeepSeek for coding help
Machine Learning: kNN Trend PredictorThe kNN Trend Predictor is a machine learning-based indicator that uses the k-Nearest Neighbors (kNN) algorithm for price prediction in trading. By analyzing historical price movements and computing Euclidean distances, the script identifies the closest past price patterns and forecasts potential trends. It provides color-coded trend signals, optional trade entry labels, and alerts for long and short signals.
Share SizeA helpful tool that estimates the amount of times you can trade at your current share size in a small account.
You can adjust the numbers in the settings page!
Moving Averages With Continuous Periods [macp]This script reimagines traditional moving averages by introducing floating-point period calculations, allowing for fractional lengths rather than being constrained to whole numbers. At its core, it provides SMA, WMA, and HMA variants that can work with any decimal length, which proves especially valuable when creating dynamic indicators or fine-tuning existing strategies.
The most significant improvement lies in the Hull Moving Average implementation. By properly handling floating-point mathematics throughout the calculation chain, this version reduces the overshoot tendencies that often plague integer-based HMAs. The result is a more responsive yet controlled indicator that better captures price action without excessive whipsaw.
The visual aspect incorporates a trend gradient system that can adapt to different trading styles. Rather than using fixed coloring, it offers several modes ranging from simple solid colors to more nuanced three-tone gradients that help identify trend transitions. These gradients are normalized against ATR to provide context-aware visual feedback about trend strength.
From a practical standpoint, the floating-point approach eliminates the subtle discontinuities that occur when integer-based moving averages switch periods. This makes the indicator particularly useful in systems where the MA period itself is calculated from market conditions, as it can smoothly transition between different lengths without artificial jumps.
At the heart of this implementation lies the concept of continuous weights rather than discrete summation. Traditional moving averages treat each period as a distinct unit with integer indexing. However, when we move to floating-point periods, we need to consider how fractional periods should behave. This leads us to some interesting mathematical considerations.
Consider the Weighted Moving Average kernel. The weight function is fundamentally a slope: -x + length where x represents the position in the averaging window. The normalization constant is calculated by integrating (in our discrete case, summing) this slope across the window. What makes this implementation special is how it handles the fractional component - when the length isn't a whole number, the final period gets weighted proportionally to its fractional part.
For the Hull Moving Average, the mathematics become particularly intriguing. The standard HMA formula HMA = WMA(2*WMA(price, n/2) - WMA(price, n), sqrt(n)) is preserved, but now each WMA calculation operates in continuous space. This creates a smoother cascade of weights that better preserves the original intent of the Hull design - to reduce lag while maintaining smoothness.
The Simple Moving Average's treatment of fractional periods is perhaps the most elegant. For a length like 9.7, it weights the first 9 periods fully and the 10th period at 0.7 of its value. This creates a natural transition between integer periods that traditional implementations miss entirely.
The Gradient Mathematics
The trend gradient system employs normalized angular calculations to determine color transitions. By taking the arctangent of price changes normalized by ATR, we create a bounded space between 0 and 1 that represents trend intensity. The formula (arctan(Δprice/ATR) + 90°)/180° maps trend angles to this normalized space, allowing for smooth color transitions that respect market volatility context.
This mathematical framework creates a more theoretically sound foundation for moving averages, one that better reflects the continuous nature of price movement in financial markets. The implementation recognizes that time in markets isn't truly discrete - our sampling might be, but the underlying process we're trying to measure is continuous. By allowing for fractional periods, we're creating a better approximation of this continuous reality.
This floating-point moving average implementation offers tangible benefits for traders and analysts who need precise control over their indicators. The ability to fine-tune periods and create smooth transitions makes it particularly valuable for automated systems where moving average lengths are dynamically calculated from market conditions. The Hull Moving Average calculation now accurately reflects its mathematical formula while maintaining responsiveness, making it a practical choice for both systematic and discretionary trading approaches. Whether you're building dynamic indicators, optimizing existing strategies, or simply want more precise control over your moving averages, this implementation provides the mathematical foundation to do so effectively.
Dynamic Trend Navigator AI [CodingView]Dynamic Trend Navigator AI Strategy Documentation
Strategy Overview
This trend-following algorithm uses proprietary smoothing techniques to identify market trends and execute positions with integrated risk management. Designed for swing trading across various liquid markets.
Key Features
🟢 Dual-layer trend analysis using custom exponential smoothing
🔴 Automated entry/exit signals with visual indicators
⚖️ Position sizing by equity percentage (default 100%)
🛡️ Configurable risk management (profit targets & stop-loss)
📈 Clean visual presentation with real-time signals
Input Parameters
Trend Configuration
Primary Trend Window (9): Short-term trend sensitivity
Secondary Trend Window (30): Long-term market phase reference
Risk Management
Profit Target Points (30): Points from entry for take-profit
Stop-Loss Points (30): Points from entry for risk cutoff
Activate Risk Controls (On/Off): Toggle risk features
How to Use
Apply to Chart
Add to preferred trading instrument (1H+ timeframes recommended)
Default settings work for most markets - adjust parameters as needed
Signal Interpretation
▲ Green Arrow: Bullish trend signal (potential long entry)
▼ Red Arrow: Bearish trend signal (potential short entry)
Green Line: Short-term trend indicator
Red Line: Long-term market phase reference
Position Management
Entries automatically execute on signal confirmation
Exits occur at target/stop levels or counter-signal
Monitor active positions via strategy tester
Risk Considerations
➖ Trend-following systems can underperform in ranging markets
➖ Fixed point targets may require adjustment for volatility
➖ Default 100% position sizing carries high risk - modify according to risk tolerance
➖ Backtest results don't guarantee future performance
Recommended Markets
Forex Majors (EURUSD, GBPUSD)
Equity Indices (SPX, DAX)
Liquid Commodities (Gold, Crude Oil)
Disclaimer
❗ Important Notice
This strategy is for educational purposes only
Past performance ≠ future results
TheCodingView Team not responsible for trading losses
Users must validate strategy in demo environment before live use
Not financial advice - trade at your own risk
Support & Contact
🛠️ Technical Assistance: support@theCodingView.com
🌐 Website: www.theCodingView.com
Best Practices
Start with 50% position sizing
Test across multiple market conditions
Adjust targets/stops according to asset volatility
Combine with fundamental analysis
Monitor drawdowns regularly
Version Notes
v2.0 (Current):
Enhanced smoothing algorithm
Simplified risk management interface
Improved visual clarity
Optimized backtest logic
Enhanced MACD + RSI Buy/Sell Signals### **Enhanced MACD + RSI Buy/Sell Signals Indicator**
This TradingView indicator is designed for **15-minute intraday trading**, providing **stronger and more accurate buy/sell signals** by combining multiple technical indicators: **MACD, RSI, EMA, VWAP, and ATR**.
---
### **Key Components & Logic**
#### **1. MACD (Moving Average Convergence Divergence)**
- Uses **8, 21, 5 MACD settings** (faster than the default 12, 26, 9) for quicker signal detection.
- Buy Signal: **MACD line crosses above the signal line**.
- Sell Signal: **MACD line crosses below the signal line**.
#### **2. RSI (Relative Strength Index)**
- Helps confirm momentum strength.
- Buy only if **RSI is above 30** (prevents buying in weak markets).
- Sell only if **RSI is below 70** (prevents selling too early).
#### **3. 50-Period EMA (Trend Filter)**
- Ensures trades align with the **overall trend**.
- **Buy signals only trigger if price is above the EMA**.
- **Sell signals only trigger if price is below the EMA**.
#### **4. VWAP (Volume Weighted Average Price)**
- Avoids false signals by ensuring price is above/below a volume-based average.
- **Buy only if price is above VWAP** (uptrend confirmation).
- **Sell only if price is below VWAP** (downtrend confirmation).
#### **5. ATR (Average True Range) Filter**
- Ensures trades occur only in **high-volatility conditions**.
- **Buy/Sell signals trigger only when ATR is above a threshold (default: 1.0)**.
---
### **Buy & Sell Signal Conditions**
✅ **Buy Signal (Plotted as Green Arrow Below Price)**
- MACD **bullish crossover** (MACD line crosses above the signal line).
- RSI **above 30** (not in an oversold zone).
- **Price is above the 50 EMA** (strong uptrend).
- **Price is above VWAP** (avoiding false breakouts).
- **ATR is above 1.0** (ensuring enough volatility for a trade).
❌ **Sell Signal (Plotted as Red Arrow Above Price)**
- MACD **bearish crossunder** (MACD line crosses below the signal line).
- RSI **below 70** (not in an overbought zone).
- **Price is below the 50 EMA** (downtrend confirmation).
- **Price is below VWAP** (avoiding weak downtrends).
- **ATR is above 1.0** (ensuring enough movement for profitability).
---
### **Why This Works Well for 15-Minute Charts**
✅ **Faster MACD settings** reduce lag and react quicker to price changes.
✅ **EMA + VWAP** ensures **trend alignment** and prevents false signals.
✅ **ATR filter** removes low-volatility signals, increasing accuracy.
✅ **Simple buy/sell signals** make it easy to read and execute trades.
---
### **How to Use This Indicator**
1. Apply it to a **15-minute** timeframe.
2. Wait for a **green label (BUY)** or **red label (SELL)** on the chart.
3. Confirm signals with **support/resistance levels** for extra reliability.
4. Use a **1:2 risk-reward ratio** for trade exits.
This strategy ensures **higher accuracy, fewer false trades, and stronger trend-based entries**. 🚀
EMA Crossover Backtest [BarScripts]This indicator lets you backtest an EMA crossover strategy with built-in risk management and trade tracking. It simulates long and short trades based on EMA crossovers, allowing you to fine-tune entry conditions, stop-loss placement, and reward/risk settings.
🔹 How It Works:
Long Entry: Fast EMA crosses above Slow EMA, and price closes above Fast EMA.
Short Entry: Fast EMA crosses below Slow EMA, and price closes below Fast EMA.
Stop Loss: Set based on previous bars or a fixed amount.
Take Profit: Adjustable reward/risk ratio.
Higher Timeframe Confluence: Confirms trades based on a larger timeframe.
Trade Hours Filter: Limits trades to specific time windows.
🔹 Key Features:
✅ Shows Entry & Exit Points with visual trade lines.
✅ Customizable EMA Lengths to fit any strategy.
✅ P&L Tracking & Statistics to measure performance.
✅ Position Sizing Options: Fixed position, fixed risk, or percentage of balance.
✅ Commissions Tracking (based on total trades, not contracts).
Use this tool to fine-tune your EMA crossover strategy and see how it performs over time! 🚀
💬 Let me know your feedback—suggest improvements, report issues, or request new features!
MACD + RSI Buy/Sell Signals### **MACD + RSI Buy/Sell Signals Indicator for TradingView**
This TradingView indicator helps traders identify **buy and sell opportunities** using a combination of **MACD (Moving Average Convergence Divergence) and RSI (Relative Strength Index)**.
---
### **Indicator Components**
1. **MACD (Moving Average Convergence Divergence)**
- Uses **12-period EMA (fast)** and **26-period EMA (slow)** to calculate the MACD line.
- A **9-period EMA** of the MACD line is used as the **signal line**.
- A **bullish crossover** (MACD line crossing above the signal line) suggests a buy signal.
- A **bearish crossover** (MACD line crossing below the signal line) suggests a sell signal.
2. **RSI (Relative Strength Index)**
- Uses a **14-period RSI** to measure momentum.
- An RSI value above **30** confirms a **buy signal** when the MACD crossover happens.
- An RSI value below **70** confirms a **sell signal** when the MACD crossunder happens.
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### **Buy & Sell Signals**
- **Buy Signal:**
- When the **MACD line crosses above the signal line**, and RSI is above **30** (indicating upward momentum).
- Plotted as a **green label** below the price bars.
- **Sell Signal:**
- When the **MACD line crosses below the signal line**, and RSI is below **70** (indicating downward momentum).
- Plotted as a **red label** above the price bars.
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### **Usage Guidelines**
- Best suited for **intraday and swing trading** on **higher timeframes** like **15 minutes, 1 hour, or daily charts**.
- Works well in **trending markets** but may generate false signals in **sideways markets**.
- Can be combined with **support/resistance levels** for higher accuracy.
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This indicator provides **clear visual signals** on the chart to help traders **easily identify potential entry and exit points**.
