RSI-BBGun-v6.1RSI BB Gun – Operator's Guide
“Eyes on target. Wait for the right moment. Then strike.”
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🎯 Mission Objective
RSI BB Gun identifies extreme market conditions using RSI and Bollinger Bands, then overlays trend and volatility intelligence so you know when the setup is real.
The ❌ is your target acquisition signal—price just moved from an extreme zone back into play. Now you’ve got a clean radar lock.
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📡 How to Operate
🟣 Step 1: Watch for the ❌'s (Black X = RSI & Bollinger Band Extremes Encountered)
• The Purple X means price and RSI are both stretched—and just snapped back into range.
• The target is now in the cross hairs and potentially ready for engagement.
🟥 Step 2: Confirm the Trend
• The thick ribbon tells you if the trend is with you:
o 🟢 Green = Uptrend. Focus on long setups.
o 🔴 Red = Downtrend. Focus on puts or short plays.
• Align with trend. Only engage when the field favors your position.
🔺 Step 3: Evaluate Signal Context
• Green Triangles = price just crossed below lower Bollinger Band (oversold).
• Red Triangles = price crossed above upper Band (overbought).
• Horizontal Lines Disappeared = The bar after the green or red horizontal line disappears means its time. We patiently wait for this as it means the momentum may be changing.
• These are your early indicators—they scout the setup on the GO / NO GO DECISION.
• ❌ + triangle + trend = clean shot.
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☁️ Avoid These Situations
• ❌ in a choppy/no-trend zone = false alarm. Don’t engage.
• Repeated black ❌s without a purple ❌confirmation = low conviction. Let it go.
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🪖 Operator's Mindset
“You don’t chase trades. You stalk them. When the ❌ flashes, the system has found a target. What you do next is up to your discipline, your tools, and your plan.”
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Note: This is a free version. Upcoming paid version includes multi-timeframes working together. Multiple strategies. Volatility meter. Make money and master the BB Gun so that you can elevate to the Snipers weapon.
🔒 Want More Firepower?
Upgraded version coming soon. Unlocks next-gen targeting tools:
• Multi-timeframe RSI intelligence in a live dashboard
• Precision-timed combo signals based on layered volatility + RSI logic
• Advanced trend filters, trade zone overlays, and sniper-level entry indicators
• Ideal for swing traders and options strategists who want clarity under pressure
💥 Budget-friendly. No subscription. Upgrade when you're ready to go Pro.
Tip: Make 4+ trades mastering this setup. Then use a small portion of the trades to gain more features. Always be in a position you cannot lose.
🆚 Why This Beats Standard RSI/BB Tools
Mission Feature Basic Indicators RSI Ribbon Lite
Trend Confirmation ❌ ✅ Ribbon Overlay
Multi-Timeframe Awareness ❌ ✅ 5-Timeframe RSI Grid
Volatility Confirmation ❌ ✅ Weighted ATR Scoring
Combo Signal Alerts ❌ ✅ ❌ Reentry Combo Alerts
TradingView Alerts ❌ ✅ Built-In Radar Ping
#rsi #bb #bollingerbands #hull ma #trend
Wyszukaj w skryptach "弘历投教boll指标代码分析"
BBands Channels with EMAs# **BBands Channels with EMAs Indicator Explanation**
---
## **📌 Feature Overview**
### **1. Bollinger Bands**
- **Basis Line**: 160-period SMA (adjustable)
- **Inner Bands**:
- **Upper**: Basis + 2× Standard Deviation
- **Lower**: Basis - 2× Standard Deviation
- **Outer Bands**:
- **Upper Top**: Basis + 3× Standard Deviation
- **Lower Low**: Basis - 3× Standard Deviation
- **Fill Effect**: Semi-transparent black fill between inner and outer bands
### **2. Exponential Moving Averages (EMAs)**
| Period | Purpose | Line Style |
|--------------|-----------------------------|------------------|
| **EMA 27** | Short-term trend | Thin line |
| **EMA 120** | Short-to-medium-term trend | Medium line |
| **EMA 200** | Medium-term trend | Medium line |
| **EMA 1120** | Ultra-long-term trend | Thick line |
---
## **⚙️ Parameter Settings**
### **Bollinger Bands**
| Parameter | Default | Description |
|---------------|---------|--------------------------------------|
| `length` | 160 | SMA calculation period |
| `mult` | 2.0 | Standard deviation multiplier (inner bands) |
| `multOuter` | 3.0 | Standard deviation multiplier (outer bands) |
| `offset` | 0 | Time offset for plots (±500 bars) |
### **Exponential Moving Averages (EMAs)**
| Parameter | Default | Description |
|-----------------|---------|---------------------------|
| `ema1Length` | 27 | EMA 1 period |
| `ema2Length` | 120 | EMA 2 period |
| `ema3Length` | 200 | EMA 3 period |
| `ema4Length` | 1120 | EMA 4 period |
---
## **📊 Use Cases**
### **1. Trend Confirmation**
- **Bullish Trend**: Price above EMA200 + Bollinger Band expansion
- **Bearish Trend**: Price below EMA200 + Bollinger Band expansion
### **2. Overbought/Oversold Signals**
- **Upper Band Touch**: Price reaches Upper Top → Potential overbought
- **Lower Band Touch**: Price reaches Lower Low → Potential oversold
### **3. Volatility Strategies**
- **Band Squeeze**: Narrowing gap between bands → Breakout warning
- **Band Expansion**: Price breaks outer band → Trend acceleration
---
**✅ Summary**
This indicator combines **Bollinger Bands + Multi-period EMAs** for:
- Trend tracking
- Volatility analysis
- Multi-timeframe strategies
---
# **BBands Channels with EMAs 指標說明**
---
## **📌 功能概述**
### **1. 布林通道 (Bollinger Bands)**
- **基礎線 (Basis Line)**: 160週期SMA（可調整）
- **內通道 (Inner Bands)**:
- 上軌 (Upper): 基礎線 + 2倍標準差
- 下軌 (Lower): 基礎線 - 2倍標準差
- **外通道 (Outer Bands)**:
- 上外軌 (Upper Top): 基礎線 + 3倍標準差
- 下外軌 (Lower Low): 基礎線 - 3倍標準差
- **填充效果**: 內外通道間半透明黑色填充
### **2. 指數移動平均線 (EMAs)**
| 週期 | 用途 | 線條樣式 |
|-------------|-------------------|-----------------|
| **EMA 27** | 短期趨勢 | 細線 |
| **EMA 120** | 中短期趨勢 | 中等線 |
| **EMA 200** | 中期趨勢 | 中等線 |
| **EMA 1120**| 超長期趨勢 | 粗線 |
---
## **⚙️ 參數設定**
### **布林通道 (Bollinger Bands)**
| 參數名 | 預設值 | 說明 |
|-------------|--------|---------------------------|
| `length` | 160 | SMA計算週期 |
| `mult` | 2.0 | 內通道標準差倍數 |
| `multOuter` | 3.0 | 外通道標準差倍數 |
| `offset` | 0 | 線圖時間偏移（±500根K棒） |
### **指數移動平均線 (EMAs)**
| 參數名 | 預設值 | 說明 |
|----------------|---------|-------------------|
| `ema1Length` | 27 | 第一條EMA週期 |
| `ema2Length` | 120 | 第二條EMA週期 |
| `ema3Length` | 200 | 第三條EMA週期 |
| `ema4Length` | 1120 | 第四條EMA週期 |
---
## **📊 應用場景**
### **1. 趨勢確認**
- **多頭趨勢**: 價格在EMA200上方 + 布林通道擴張
- **空頭趨勢**: 價格在EMA200下方 + 布林通道擴張
### **2. 超買超賣信號**
- **觸及外軌**: 價格觸碰Upper Top → 可能超買
- **觸及下軌**: 價格觸碰Lower Low → 可能超賣
### **3. 波動率策略**
- **通道收窄**: 內外通道間距縮小 → 突破預警
- **通道擴張**: 價格突破外軌 → 趨勢加速
---
**✅ 總結**
本指標透過**布林通道+多週期EMA**的組合，適用於：
- 趨勢跟蹤
- 波動率分析
- 多時間框架策略
Multifactor Buy/Sell Strategy V2 | RSI, MACD, ATR, EMA, Boll.BITGET:1INCHUSDT
This Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
### Input Parameters
The script includes multiple customizable parameters:
- RSI, EMA, MACD parameters — for setting periods and signals of MACD and RSI.
- ATR and Bollinger Bands — used for volatility analysis and level determination.
- Minimum Volatility Threshold — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility dataThis Pine Script code for TradingView is a multifactor Buy/Sell indicator that combines several technical factors to generate trading signals based on trend, volatility, and volume conditions. Here’s a breakdown of the main components and functionality:
Indicator Name
- Multifactor Buy/Sell Strategy V2 — an overlay indicator applied directly on the price chart.
Input Parameters
The script includes multiple customizable parameters:
- **RSI, EMA, MACD parameters** — for setting periods and signals of MACD and RSI.
- **ATR and Bollinger Bands** — used for volatility analysis and level determination.
- **Minimum Volatility Threshold** — sets a minimum Bollinger Band width threshold for determining high volatility.
Core Indicators
1. RSI — calculated to identify oversold (below 30) and overbought (above 70) conditions.
2. EMA and MACD — calculates exponential moving averages and MACD histogram to determine trend direction.
3. ATR and Bollinger Bands — used to assess current volatility and establish dynamic upper and lower bands.
Volatility and Volume Analysis
- Determines the current ATR level and Bollinger Band width to evaluate high volatility.
- Calculates the volume moving average to track periods of increased volume during high volatility.
Trend Analysis
The script uses the difference between fast and slow EMAs to define strong trends:
- Uptrend — when the fast EMA is above the slow EMA, the price is above the fast EMA, and the trend is strong.
- Downtrend — when the fast EMA is below the slow EMA, the price is below the fast EMA, and the trend is strong.
Momentum Filter
- Based on the price change over the last three bars and compared against the minimum volatility threshold to identify strong momentum.
Buy and Sell Signal Generation
- Buy Signal: Uptrend with RSI oversold, positive MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
- Sell Signal: Downtrend with RSI overbought, negative MACD histogram, high volatility and volume, strong momentum, and sufficient Bollinger Band width.
Visualization
- Buy and sell signals are displayed as green and red triangles on the chart.
- Plots for fast and slow EMAs, upper and lower bands, and Bollinger Bands.
Alerts
The script includes alert conditions for buy and sell signals, allowing notifications to be sent via email or mobile app.
Information Panel
A small table on the chart displays current volatility
- Volatility Status — indicates high or low volatility.
- Bollinger Band Width — current width as a percentage.
- ATR Ratio — ratio of current ATR to long-term average ATR.
This script is suitable for trading in high-volatility conditions, combining multiple filters and factors to generate precise buy and sell signals.
FibonRSI / ErkOziHello,
This software is a technical analysis script written in the TradingView Pine language. The script creates a trading indicator based on Fibonacci retracement levels and the RSI indicator, providing information about price movements and asset volatility by using Bollinger Bands.
There are many different scripts in the market that draw RSI and Fibonacci retracement levels. However, this script was originally designed by me and shared publicly on TradingView.
***The indicator uses RSI (Relative Strength Index) and Bollinger Bands (BB) as the basis for the FibonRSI strategy. RSI measures the strength of a price movement, and BB measures the volatility of an asset. The FibonRSI strategy is based on the idea that the Fibonacci ratios and RSI can be used to predict a asset's price retracement levels.
***The script allows for various parameters to be adjusted. Users can specify the price source type and adjust the periods for RSI and Bollinger Bands. The standard deviation number for Bollinger Bands can also be customized.
***The script calculates the current RSI indicator position and the basic, upper, and lower levels of Bollinger Bands. It then calculates and draws the Fibonacci retracement levels. The color of the RSI line is determined by the upper and lower distribution levels of Bollinger Bands. Additionally, the color of the Fibonacci retracement levels can also be customized by the user.
***This script can be used to determine potential buy and sell signals using Fibonacci retracement levels and RSI. For example, when the RSI is oversold and the price is close to a Fibonacci retracement level, it can be interpreted as a buying opportunity. Similarly, when the RSI is overbought and the price is close to a Fibonacci retracement level, it can be interpreted as a selling opportunity.
***The script takes input parameters such as the price source used for calculation, the period for the RSI indicator, the period for the Moving Average in Bollinger Bands, and the number of standard deviations used in Bollinger Bands.
***The script's conditions include elements such as calculating the current position of the RSI indicator, calculating the upper and lower Bollinger Bands, calculating the dispersion factor, and calculating Fibonacci levels.
***The parameters in the code can be adjusted for calculation, including the price type used, the RSI period, the Moving Average period for BB, and the standard deviation count for BB. After this, the current position of the RSI, Moving Average, and standard deviation for BB are calculated. After calculating the upper and lower BB, the levels above and below the average are calculated using a specific dispersion constant.
CONDITIONS FOR THE SCRIPT
current_rsi = ta.rsi(src, for_rsi) // Current position of the RSI indicator
basis = ta.ema(current_rsi, for_ma)
dev = for_mult * ta.stdev(current_rsi, for_ma)
upper = basis + dev
lower = basis - dev
dispersion = 1
disp_up = basis + (upper - lower) * dispersion
disp_down = basis - (upper - lower) * dispersion
// Fibonacci Levels
f100 = basis + (upper - lower) * 1.0
f78 = basis + (upper - lower) * 0.78
f65 = basis + (upper - lower) * 0.65
f50 = basis
f35 = basis - (upper - lower) * 0.65
f23 = basis - (upper - lower) * 0.78
f0 = basis - (upper - lower) * 1.0
***When calculating Fibonacci levels, the distance between the average of BB and the upper and lower BB is used. These levels are 0%, 23.6%, 35%, 50%, 65%, 78.6%, and 100%. Finally, the RSI line that changes color according to a specific RSI position, Fibonacci levels, and BB are visualized. Additionally, the levels of 70, 30, and 50 are also shown.
The script then sets the color of the RSI position according to the EMA and draws Bollinger Bands, RSI, Fibonacci levels, and the 70, 30, and 50 levels.
In conclusion, this script enables traders to analyze market trends and make informed decisions. It can also be customized to suit individual trading strategies.
This script analyzes the RSI indicator using Bollinger Bands and Fibonacci levels. The default settings are 14 periods for RSI, 233 periods and 2 standard deviations for BB. The MA period inside BB is selected as the BB period and is used when calculating Fibonacci levels.
***The reason for selecting these settings is to provide enough time for BB period to confirm a possible trend. Additionally, the MA period inside BB is matched with the BB period and used when calculating Fibonacci levels.
***Fibonacci levels are calculated from the distance between the upper and lower bands of BB and show how RSI movement is related to these levels. Better results can be achieved when RSI periods are set to Fibonacci numbers such as 21, 55, and 89. Therefore, the use of Fibonacci numbers is recommended when adjusting RSI periods. Fibonacci numbers are among the technical analysis tools that can capture the reflection of naturally occurring movements in the market. Therefore, the use of Fibonacci numbers often helps to better track fluctuations in the market.
Finally, the indicator also displays the 70 and 30 levels and the middle level (50) with Fibonacci levels drawn in circles. Changing these settings can help optimize the Fibonacci levels and further improve the indicator.
Thank you in advance for your suggestions and opinions......
BT-Bollinger Bands - Trend FollowingEsse script foi criado para estudo de Backtest.
O script usa as Bandas de Bollinger para indicar o início de uma tendência, a entrada é configurada quando o preço abre abaixo e fecha acima da banda superior ou para venda quando o preço abre acima e fecha abaixo da banda inferior.
Não há um stop fixo e nem alvo fixo a saída se dá quando o preço toca a média da banda.
Você pode usar uma média móvel como filtro combinado com a estratégia.
O Script também pode ser usado com algum serviço de bot como 3commas.io , basta colocar as mensagens de entrada e saída para o bot.
Autor : Credsonb - Nick: M4TR1X_BR
Neste gráfico estou usando as seguintes configurações:
Bandas Bollinger: 7
Desvio Padrão: 1.5
Time Frame: 12hs
Ticker: ETH
This script was created for Backtest study.
script uses Bollinger Bands to indicate the start of a trend, entry is set when price opens below and closes above the upper band or for short when price opens above and closes below the lower band.
There is no fixed stop and no fixed target, the exit occurs when the price touches the average of the band.
You can use a moving average as a filter combined with the strategy.
The Script can also be used with some bot service like 3commas. io , just put the input and output messages to the bot.
Author : Credsonb - Nick: M4TR1X_BR
Mean Reversion & Momentum Hybrid | D_QUANT 📌 Mean Reversion & Momentum Hybrid | D_QUANT
📖 Description:
This indicator combines mean reversion logic, volatility filtering, and percentile-based momentum to deliver clear, context-aware buy/sell signals designed for trend-following and contrarian setups.
At its core, it merges:
A Bollinger Band % Positioning Model (BB%)
A 75th/25th Percentile Momentum System
A Volatility-Adjusted Trend Filter using RMA + ATR
All tied together with a dynamic gradient-style oscillator that visualizes signal strength and persistence over time — making it easy to track high-conviction setups.
Signals only trigger when all three core components align, filtering out noise and emphasizing high-probability turning points or trend continuations.
⚙️ Methodology Overview:
Bollinger Bands % (BB%):
Price is measured as a percentage between upper and lower Bollinger Bands (based on OHLC4). Entries are only considered when price exceeds custom BB% thresholds — emphasizing market extremes.
Volatility-Based Trend Filter (RMA + ATR):
A smoothed RMA baseline is paired with ATR to define trend bias. This ensures signals only occur when price deviates meaningfully beyond recent volatility.
Percentile Momentum Model (75th/25th Rank):
Price is compared against its rolling 75th and 25th percentile. If price breaks these statistical boundaries (adjusted by ATR), it triggers a directional momentum condition.
Signal Consensus Engine:
All three layers must agree — BB% condition, trend filter, and percentile momentum — before a buy or sell signal is plotted.
Gradient Oscillator Visualization:
Signals appear as a fading oscillator line with a gradient-filled area beneath it. The color intensity represents how “fresh” or “strong” the signal is, fading over time if not reconfirmed, offering both clarity and signal aging at a glance.
🔧 User Inputs:
🧠 Core Settings:
Source: Select the price input (default: close)
Bollinger Bands Length: Period for BB basis and deviation
Bollinger Bands Multiplier: Width of the bands
Minimum BB Width (% of Price): Prevents signals during low-volatility chop
📊 BB% Thresholds:
BB% Long Threshold (L): Minimum %B to consider a long
BB% Short Threshold (S): Maximum %B to consider a short
🔍 Trend Filter Parameters:
RMA Length: Period for the smoothed trend baseline
ATR Length: Lookback for ATR in trend deviation filter
⚡️ Momentum Parameters:
Momentum Length: Period for percentile momentum calculation
Mult_75 / Mult_25: ATR-adjusted thresholds for breakout above/below percentile levels
🎨 Visualization:
Bar Coloring: Highlights candles during active signals
Background Coloring: Optional background shading for signals
Show Oscillator Plot: Toggle the gradient-style oscillator
🧪 Use Case:
This indicator works well across all assets for trend identification. It is particularly effective when used on higher timeframes (e.g. 12H, 1D,2D) to capture mean reversion bounces or confirm breakouts backed by percentile momentum and volatility expansion.
⚠️ Notes:
This is not financial advice. Use in combination with proper risk management and confluence from other tools.
Momentum Fusion v1Momentum Fusion v1
Overview
Momentum Fusion v1 (MFusion) is a multi-oscillator indicator that combines several components to analyze market momentum and trend strength. It incorporates modified versions of classic indicators such as PVI (Positive Volume Index), NVI (Negative Volume Index), MFI (Money Flow Index), RSI, Stochastic, and Bollinger Bands Oscillator. The indicator displays a histogram that changes color based on momentum strength and includes "FUSION🔥" signal labels when extreme values are reached.
Indicator Settings
Parameters:
EMA Length – Smoothing period for the moving average (default: 255).
Smoothing Period – Internal calculation smoothing parameter (default: 15).
BB Multiplier – Standard deviation multiplier for Bollinger Bands (default: 2.0).
Show verde / marron / media lines – Toggles the display of auxiliary lines.
Show FUSION🔥 label – Enables/disables signal labels.
Indicator Components
1. PVI (Positive Volume Index)
Formula:
pvi := volume > volume ? nz(pvi ) + (close - close ) / close * sval : nz(pvi )
Description:
PVI increases when volume rises compared to the previous bar and accounts for price percentage change. The stronger the price movement with increasing volume, the higher the PVI value.
2. NVI (Negative Volume Index)
Formula:
nvi := volume < volume ? nz(nvi ) + (close - close ) / close * sval : nz(nvi )
Description:
NVI tracks price movements during declining volume. If the price rises on low volume, it may indicate a "stealth" trend.
3. Money Flow Index (MFI)
Formula:
100 - 100 / (1 + up / dn)
Description:
An oscillator measuring money flow strength. Values above 80 suggest overbought conditions, while values below 20 indicate oversold conditions.
4. Stochastic Oscillator
Formula:
k = 100 * (close - lowest(low, length)) / (highest(high, length) - lowest(low, length))
Description:
A classic stochastic oscillator showing price position relative to the selected period's range.
5. Bollinger Bands Oscillator
Formula:
(tprice - BB midline) / (upper BB - lower BB) * 100
Description:
Indicates the price position relative to Bollinger Bands in percentage terms.
Key Lines & Histogram
1. Verde (Green Line)
Calculation:
verde = marron + oscp (normalized PVI)
Interpretation:
Higher values indicate stronger bullish momentum. A FUSION🔥 signal appears when the value reaches 750+.
2. Marron (Brown Line)
Calculation:
marron = (RSI + MFI + Bollinger Osc + Stochastic / 3) / 2
Interpretation:
A composite oscillator combining multiple indicators. Higher values suggest overbought conditions.
3. Media (Red Line)
Calculation:
media = EMA of marron with smoothing period
Interpretation:
Acts as a signal line for trend confirmation.
4. Histogram
Calculation:
histo = verde - marron
Colors:
Bright green (>100) – Strong bullish momentum.
Light green (>0) – Moderate bullish momentum.
Orange (<0) – Bearish momentum.
Red (<-100) – Strong bearish momentum.
Signals & Alerts
1. FUSION🔥 (Strong Momentum)
Condition:
verde >= 750
Visualization:
A "FUSION🔥" label appears below the chart.
Alert:
Can be set to trigger notifications when the condition is met.
2. Background Aura
Condition:
verde > 850
Visualization:
The chart background turns teal, indicating extreme momentum.
Usage Recommendations
FUSION🔥 Signal – Can be used as a long entry point when confirmed by other indicators.
Histogram:
1. Green bars – Potential long entry.
2. Red/orange bars – Potential short entry.
3. Media & Marron Crossover – Can serve as an additional trend filter.
4. Suitable for a 5-15 minute time frame
Conclusion
Momentum Fusion v1 is a powerful tool for momentum analysis, combining multiple indicators into a unified system. It is suitable for:
Trend traders (catching strong movements).
Scalpers (identifying short-term impulses).
Swing traders (filtering entry points).
The indicator features customizable settings and visual signals, making it adaptable to various trading styles.
Multi-Band Comparison (Uptrend)Multi-Band Comparison
Overview:
The Multi-Band Comparison indicator is engineered to reveal critical levels of support and resistance in strong uptrends. In a healthy upward market, the price action will adhere closely to the 95th percentile line (the Upper Quantile Band), effectively “riding” it. This indicator combines a modified Bollinger Band (set at one standard deviation), quantile analysis (95% and 5% levels), and power‑law math to display a dynamic picture of market structure—highlighting a “golden channel” and robust support areas.
Key Components & Calculations:
The Golden Channel: Upper Bollinger Band & Upper Std Dev Band of the Upper Quantile
Upper Bollinger Band:
Calculation:
boll_upper=SMA(close,length)+(boll_mult×stdev)
boll_upper=SMA(close,length)+(boll_mult×stdev) Here, the 20-period SMA is used along with one standard deviation of the close, where the multiplier (boll_mult) is 1.0.
Role in an Uptrend:
In a healthy uptrend, price rides near the 95th percentile line. When price crosses above this Upper Bollinger Band, it confirms strong bullish momentum.
Upper Std Dev Band of the Upper Quantile (95th Percentile) Band:
Calculation:
quant_upper_std_up=quant_upper+stdev
quant_upper_std_up=quant_upper+stdev The Upper Quantile Band, quant_upperquant_upper, is calculated as the 95th percentile of recent price data. Adding one standard deviation creates an extension that accounts for normal volatility around this extreme level.
The Golden Channel:
When the price crosses above the Upper Bollinger Band, the Upper Std Dev Band of the Upper Quantile immediately shifts to gold (yellow) and remains gold until price falls below the Bollinger level. Together, these two lines form the “golden channel”—a visual hallmark of a healthy uptrend where the price reliably hugs the 95th percentile level.
Upper Power‑Law Band
Calculation:
The Upper Power‑Law Band is derived in two steps:
Determine the Extreme Return Factor:
power_upper=Percentile(returns,95%)
power_upper=Percentile(returns,95%) where returns are computed as:
returns=closeclose −1.
returns=close close−1.
Scale the Current Price:
power_upper_band=close×(1+power_upper)
power_upper_band=close×(1+power_upper)
Rationale and Correlation:
By focusing on the upper 5% of returns (reflecting “fat tails”), the Upper Power‑Law Band captures extreme but statistically expected movements. In an uptrend, its value often converges with the Upper Std Dev Band of the Upper Quantile because both measures reflect heightened volatility and extreme price levels. When the Upper Power‑Law Band exceeds the Upper Std Dev Band, it can signal a temporary overextension.
Upper Quantile Band (95% Percentile)
Calculation:
quant_upper=Percentile(price,95%)
quant_upper=Percentile(price,95%) This level represents where 95% of past price data falls below, and in a robust uptrend the price action practically rides this line.
Color Logic:
Its color shifts from a neutral (blackish) tone to a vibrant, bullish hue when the Upper Power‑Law Band crosses above it—signaling extra strength in the trend.
Lower Quantile and Its Support
Lower Quantile Band (5% Percentile):
Calculation:
quant_lower=Percentile(price,5%)
quant_lower=Percentile(price,5%)
Behavior:
In a healthy uptrend, price remains well above the Lower Quantile Band. It turns red only when price touches or crosses it, serving as a warning signal. Under normal conditions it remains bright green, indicating the market is not nearing these extreme lows.
Lower Std Dev Band of the Lower Quantile:
This line is calculated by subtracting one standard deviation from quant_lowerquant_lower and typically serves as absolute support in nearly all conditions (except during gap or near-gap moves). Its consistent role as support provides traders with a robust level to monitor.
How to Use the Indicator:
Golden Channel and Trend Confirmation:
As price rides the Upper Quantile (95th percentile) perfectly in a healthy uptrend, the Upper Bollinger Band (1 stdev above SMA) and the Upper Std Dev Band of the Upper Quantile form a “golden channel” once price crosses above the Bollinger level. When this occurs, the Upper Std Dev Band remains gold until price dips back below the Bollinger Band. This visual cue reinforces trend strength.
Power‑Law Insights:
The Upper Power‑Law Band, which is based on extreme (95th percentile) returns, tends to align with the Upper Std Dev Band. This convergence reinforces that extreme, yet statistically expected, price moves are occurring—indicating that even though the price rides the 95th percentile, it can only stretch so far before a correction or consolidation.
Support Indicators:
Primary and Secondary Support in Uptrends:
The Upper Bollinger Band and the Lower Std Dev Band of the Upper Quantile act as support zones for minor retracements in the uptrend.
Absolute Support:
The Lower Std Dev Band of the Lower Quantile serves as an almost invariable support area under most market conditions.
Conclusion:
The Multi-Band Comparison indicator unifies advanced statistical techniques to offer a clear view of uptrend structure. In a healthy bull market, price action rides the 95th percentile line with precision, and when the Upper Bollinger Band is breached, the corresponding Upper Std Dev Band turns gold to form a “golden channel.” This, combined with the Power‑Law analysis that captures extreme moves, and the robust lower support levels, provides traders with powerful, multi-dimensional insights for managing entries, exits, and risk.
Disclaimer:
Trading involves risk. This indicator is for educational purposes only and does not constitute financial advice. Always perform your own analysis before making trading decisions.
Adaptive Momentum Reversion StrategyThe Adaptive Momentum Reversion Strategy: An Empirical Approach to Market Behavior
The Adaptive Momentum Reversion Strategy seeks to capitalize on market price dynamics by combining concepts from momentum and mean reversion theories. This hybrid approach leverages a Rate of Change (ROC) indicator along with Bollinger Bands to identify overbought and oversold conditions, triggering trades based on the crossing of specific thresholds. The strategy aims to detect momentum shifts and exploit price reversions to their mean.
Theoretical Framework
Momentum and Mean Reversion: Momentum trading assumes that assets with a recent history of strong performance will continue in that direction, while mean reversion suggests that assets tend to return to their historical average over time (Fama & French, 1988; Poterba & Summers, 1988). This strategy incorporates elements of both, looking for periods when momentum is either overextended (and likely to revert) or when the asset’s price is temporarily underpriced relative to its historical trend.
Rate of Change (ROC): The ROC is a straightforward momentum indicator that measures the percentage change in price over a specified period (Wilder, 1978). The strategy calculates the ROC over a 2-period window, making it responsive to short-term price changes. By using ROC, the strategy aims to detect price acceleration and deceleration.
Bollinger Bands: Bollinger Bands are used to identify volatility and potential price extremes, often signaling overbought or oversold conditions. The bands consist of a moving average and two standard deviation bounds that adjust dynamically with price volatility (Bollinger, 2002).
The strategy employs two sets of Bollinger Bands: one for short-term volatility (lower band) and another for longer-term trends (upper band), with different lengths and standard deviation multipliers.
Strategy Construction
Indicator Inputs:
ROC Period: The rate of change is computed over a 2-period window, which provides sensitivity to short-term price fluctuations.
Bollinger Bands:
Lower Band: Calculated with a 18-period length and a standard deviation of 1.7.
Upper Band: Calculated with a 21-period length and a standard deviation of 2.1.
Calculations:
ROC Calculation: The ROC is computed by comparing the current close price to the close price from rocPeriod days ago, expressing it as a percentage.
Bollinger Bands: The strategy calculates both upper and lower Bollinger Bands around the ROC, using a simple moving average as the central basis. The lower Bollinger Band is used as a reference for identifying potential long entry points when the ROC crosses above it, while the upper Bollinger Band serves as a reference for exits, when the ROC crosses below it.
Trading Conditions:
Long Entry: A long position is initiated when the ROC crosses above the lower Bollinger Band, signaling a potential shift from a period of low momentum to an increase in price movement.
Exit Condition: A position is closed when the ROC crosses under the upper Bollinger Band, or when the ROC drops below the lower band again, indicating a reversal or weakening of momentum.
Visual Indicators:
ROC Plot: The ROC is plotted as a line to visualize the momentum direction.
Bollinger Bands: The upper and lower bands, along with their basis (simple moving averages), are plotted to delineate the expected range for the ROC.
Background Color: To enhance decision-making, the strategy colors the background when extreme conditions are detected—green for oversold (ROC below the lower band) and red for overbought (ROC above the upper band), indicating potential reversal zones.
Strategy Performance Considerations
The use of Bollinger Bands in this strategy provides an adaptive framework that adjusts to changing market volatility. When volatility increases, the bands widen, allowing for larger price movements, while during quieter periods, the bands contract, reducing trade signals. This adaptiveness is critical in maintaining strategy effectiveness across different market conditions.
The strategy’s pyramiding setting is disabled (pyramiding=0), ensuring that only one position is taken at a time, which is a conservative risk management approach. Additionally, the strategy includes transaction costs and slippage parameters to account for real-world trading conditions.
Empirical Evidence and Relevance
The combination of momentum and mean reversion has been widely studied and shown to provide profitable opportunities under certain market conditions. Studies such as Jegadeesh and Titman (1993) confirm that momentum strategies tend to work well in trending markets, while mean reversion strategies have been effective during periods of high volatility or after sharp price movements (De Bondt & Thaler, 1985). By integrating both strategies into one system, the Adaptive Momentum Reversion Strategy may be able to capitalize on both trending and reverting market behavior.
Furthermore, research by Chan (1996) on momentum-based trading systems demonstrates that adaptive strategies, which adjust to changes in market volatility, often outperform static strategies, providing a compelling rationale for the use of Bollinger Bands in this context.
Conclusion
The Adaptive Momentum Reversion Strategy provides a robust framework for trading based on the dual concepts of momentum and mean reversion. By using ROC in combination with Bollinger Bands, the strategy is capable of identifying overbought and oversold conditions while adapting to changing market conditions. The use of adaptive indicators ensures that the strategy remains flexible and can perform across different market environments, potentially offering a competitive edge for traders who seek to balance risk and reward in their trading approaches.
References
Bollinger, J. (2002). Bollinger on Bollinger Bands. McGraw-Hill Professional.
Chan, L. K. C. (1996). Momentum, Mean Reversion, and the Cross-Section of Stock Returns. Journal of Finance, 51(5), 1681-1713.
De Bondt, W. F., & Thaler, R. H. (1985). Does the Stock Market Overreact? Journal of Finance, 40(3), 793-805.
Fama, E. F., & French, K. R. (1988). Permanent and Temporary Components of Stock Prices. Journal of Political Economy, 96(2), 246-273.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Wilder, J. W. (1978). New Concepts in Technical Trading Systems. Trend Research.
Uptrick: Volatility Reversion BandsUptrick: Volatility Reversion Bands is an indicator designed to help traders identify potential reversal points in the market by combining volatility and momentum analysis within one comprehensive framework. It calculates dynamic bands around a simple moving average and issues signals when price interacts with these bands. Below is a fully expanded description, structured in multiple sections, detailing originality, usefulness, uniqueness, and the purpose behind blending standard deviation-based and ATR-based concepts. All references to code have been removed to focus on the written explanation only.
Section 1: Overview
Uptrick: Volatility Reversion Bands centers on a moving average around which various bands are constructed. These bands respond to changes in price volatility and can help gauge potential overbought or oversold conditions. Signals occur when the price moves beyond certain thresholds, which may imply a reversal or significant momentum shift.
Section 2: Originality, Usefulness, Uniqness, Purpose
This indicator merges two distinct volatility measurements—Bollinger Bands and ATR—into one cohesive system. Bollinger Bands use standard deviation around a moving average, offering a baseline for what is statistically “normal” price movement relative to a recent mean. When price hovers near the upper band, it may indicate overbought conditions, whereas price near the lower band suggests oversold conditions. This straightforward construction often proves invaluable in moderate-volatility settings, as it pinpoints likely turning points and gauges a market’s typical trading range.
Yet Bollinger Bands alone can falter in conditions marked by abrupt volatility spikes or sudden gaps that deviate from recent norms. Intraday news, earnings releases, or macroeconomic data can alter market behavior so swiftly that standard-deviation bands do not keep pace. This is where ATR (Average True Range) adds an important layer. ATR tracks recent highs, lows, and potential gaps to produce a dynamic gauge of how much price is truly moving from bar to bar. In quieter times, ATR contracts, reflecting subdued market activity. In fast-moving markets, ATR expands, exposing heightened volatility on each new bar.
By overlaying Bollinger Bands and ATR-based calculations, the indicator achieves a broader situational awareness. Bollinger Bands excel at highlighting relative overbought or oversold areas tied to an established average. ATR simultaneously scales up or down based on real-time market swings, signaling whether conditions are calm or turbulent. When combined, this means a price that barely crosses the Bollinger Band but also triggers a high ATR-based threshold is likely experiencing a volatility surge that goes beyond typical market fluctuations. Conversely, a price breach of a Bollinger Band when ATR remains low may still warrant attention, but not necessarily the same urgency as in a high-volatility regime.
The resulting synergy offers balanced, context-rich signals. In a strong trend, the ATR layer helps confirm whether an apparent price breakout really has momentum or if it is just a temporary spike. In a range-bound market, standard deviation-based Bollinger Bands define normal price extremes, while ATR-based extensions highlight whether a breakout attempt has genuine force behind it. Traders gain clarity on when a move is both statistically unusual and accompanied by real volatility expansion, thus carrying a higher probability of a directional follow-through or eventual reversion.
Practical advantages emerge across timeframes. Scalpers in fast-paced markets appreciate how ATR-based thresholds update rapidly, revealing if a sudden price push is routine or exceptional. Swing traders can rely on both indicators to filter out false signals in stable conditions or identify truly notable moves. By calibrating to changes in volatility, the merged system adapts naturally whether the market is trending, ranging, or transitioning between these phases.
In summary, combining Bollinger Bands (for a static sense of standard-deviation-based overbought/oversold zones) with ATR (for a dynamic read on current volatility) yields an adaptive, intuitive indicator. Traders can better distinguish fleeting noise from meaningful expansions, enabling more informed entries, exits, and risk management. Instead of relying on a single yardstick for all market conditions, this fusion provides a layered perspective, encouraging traders to interpret price moves in the broader context of changing volatility.
Section 3: Why Bollinger Bands and ATR are combined
Bollinger Bands provide a static snapshot of volatility by computing a standard deviation range above and below a central average. ATR, on the other hand, adapts in real time to expansions or contractions in market volatility. When combined, these measures offset each other’s limitations: Bollinger Bands add structure (overbought and oversold references), and ATR ensures responsiveness to rapid price shifts. This synergy helps reduce noisy signals, particularly during sudden market turbulence or extended consolidations.
Section 4: User Inputs
Traders can adjust several parameters to suit their preferences and strategies. These typically include:
1. Lookback length for calculating the moving average and standard deviation.
2. Multipliers to control the width of Bollinger Bands.
3. An ATR multiplier to set the distance for additional reversal bands.
4. An option to display weaker signals when the price merely approaches but does not cross the outer bands.
Section 5: Main Calculations
At the core of this indicator are four important steps:
1. Calculate a basis using a simple moving average.
2. Derive Bollinger Bands by adding and subtracting a product of the standard deviation and a user-defined multiplier.
3. Compute ATR over the same lookback period and multiply it by the selected factor.
4. Combine ATR-based distance with the Bollinger Bands to set the outer reversal bands, which serve as stronger signal thresholds.
Section 6: Signal Generation
The script interprets meaningful reversal points when the price:
1. Crosses below the lower outer band, potentially highlighting oversold conditions where a bullish reversal may occur.
2. Crosses above the upper outer band, potentially indicating overbought conditions where a bearish reversal may develop.
Section 7: Visualization
The indicator provides visual clarity through labeled signals and color-coded references:
1. Distinct colors for upper and lower reversal bands.
2. Markers that appear above or below bars to denote possible buying or selling signals.
3. A gradient bar color scheme indicating a bar’s position between the lower and upper bands, helping traders quickly see if the price is near either extreme.
Section 8: Weak Signals (Optional)
For those preferring early cues, the script can highlight areas where the price nears the outer bands. When weak signals are enabled:
1. Bars closer to the upper reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential selling area.
2. Bars closer to the lower reversal zone receive a subtle marker suggesting a less robust, yet still noteworthy, potential buying area.
Section 9: Simplicity, Effectiveness, and Lower Timeframes
Although combining standard deviation and ATR involves sophisticated volatility concepts, this indicator is visually straightforward. Reversal bands and gradient-colored bars make it easy to see at a glance when price approaches or crosses a threshold. Day traders operating on lower timeframes benefit from such clarity because it helps filter out minor fluctuations and focus on more meaningful signals.
Section 10: Adaptability across Market Phases
Because both the standard deviation (for Bollinger Bands) and ATR adapt to changing volatility, the indicator naturally adjusts to various environments:
1. Trending: The additional ATR-based outer bands help distinguish between temporary pullbacks and deeper reversals.
2. Ranging: Bollinger Bands often remain narrower, identifying smaller reversals, while the outer ATR bands remain relatively close to the main bands.
Section 11: Reduced Noise in High-Volatility Scenarios
By factoring ATR into the band calculations, the script widens or narrows the thresholds during rapid market fluctuations. This reduces the amount of false triggers typically found in indicators that rely solely on fixed calculations, preventing overreactions to abrupt but short-lived price spikes.
Section 12: Incorporation with Other Technical Tools
Many traders combine this indicator with oscillators such as RSI, MACD, or Stochastic, as well as volume metrics. Overbought or oversold signals in momentum oscillators can provide additional confirmation when price reaches the outer bands, while volume spikes may reinforce the significance of a breakout or potential reversal.
Section 13: Risk Management Considerations
All trading strategies carry risk. This indicator, like any tool, can and does produce losing trades if price unexpectedly reverses again or if broader market conditions shift rapidly. Prudent traders employ protective measures:
1. Stop-loss orders or trailing stops.
2. Position sizing that accounts for market volatility.
3. Diversification across different asset classes when possible.
Section 14: Overbought and Oversold Identification
Standard Bollinger Bands highlight regions where price might be overextended relative to its recent average. The extended ATR-based reversal bands serve as secondary lines of defense, identifying moments when price truly stretches beyond typical volatility bounds.
Section 15: Parameter Customization for Different Needs
Users can tailor the script to their unique preferences:
1. Shorter lookback settings yield faster signals but risk more noise.
2. Higher multipliers spread the bands further apart, filtering out small moves but generating fewer signals.
3. Longer lookback periods smooth out market noise, often leading to more stable but less frequent trading cues.
Section 16: Examples of Different Trading Styles
1. Day Traders: Often reduce the length to capture quick price swings.
2. Swing Traders: May use moderate lengths such as 20 to 50 bars.
3. Position Traders: Might opt for significantly longer settings to detect macro-level reversals.
Section 17: Performance Limitations and Reality Check
No technical indicator is free from false signals. Sudden fundamental news events, extreme sentiment changes, or low-liquidity conditions can render signals less reliable. Backtesting and forward-testing remain essential steps to gauge whether the indicator aligns well with a trader’s timeframe, risk tolerance, and instrument of choice.
Section 18: Merging Volatility and Momentum
A critical uniqueness of this indicator lies in how it merges Bollinger Bands (standard deviation-based) with ATR (pure volatility measure). Bollinger Bands provide a relative measure of price extremes, while ATR dynamically reacts to market expansions and contractions. Together, they offer an enhanced perspective on potential market turns, ideally reducing random noise and highlighting moments where price has traveled beyond typical bounds.
Section 19: Purpose of this Merger
The fundamental purpose behind blending standard deviation measures with real-time volatility data is to accommodate different market behaviors. Static standard deviation alone can underreact or overreact in abnormally volatile conditions. ATR alone lacks a baseline reference to normality. By merging them, the indicator aims to provide:
1. A versatile dynamic range for both typical and extreme moves.
2. A filter against frequent whipsaws, especially in choppy environments.
3. A visual framework that novices and experts can interpret rapidly.
Section 20: Summary and Practical Tips
Uptrick: Volatility Reversion Bands offers a powerful tool for traders looking to combine volatility-based signals with momentum-derived reversals. It emphasizes clarity through color-coded bars, defined reversal zones, and optional weak signal markers. While potentially useful across all major timeframes, it demands ongoing risk management, realistic expectations, and careful study of how signals behave under different market conditions. No indicator serves as a crystal ball, so integrating this script into an overall strategy—possibly alongside volume data, fundamentals, or momentum oscillators—often yields the best results.
Disclaimer and Educational Use
This script is intended for educational and informational purposes. It does not constitute financial advice, nor does it guarantee trading success. Sudden economic events, low-liquidity times, and unexpected market behaviors can all undermine technical signals. Traders should use proper testing procedures (backtesting and forward-testing) and maintain disciplined risk management measures.
Adaptive Range Scalper - KetBotAIThe Adaptive Scalper is designed to dynamically adjust entry, take-profit (TP), and stop-loss (SL) levels based on the latest market price. It combines multiple tools to provide traders with actionable insights, suitable for a range of trading styles and timeframes.
How the Indicator Works
Dynamic Levels:
- Yellow Dotted Line: Represents the entry level, following the latest price dynamically.
- Green Line: The Take Profit (TP) level, calculated as a multiple of the current price, adapts in real-time.
- Red Line: The Stop Loss (SL) level, placed below the price and also dynamically adjusts.
Bollinger Bands:
Provides context for market volatility and potential overbought/oversold zones.
Narrowing bands signal consolidation, while expanding bands indicate increased volatility.
Buy and Sell Signals:
Buy Signal: Triggered when the price crosses above the lower Bollinger Band.
Sell Signal: Triggered when the price crosses below the upper Bollinger Band.
These signals help traders time entries and exits based on momentum shifts.
Risk/Reward Analysis:
Visual shading shows the favorable risk/reward zone between the stop loss and take profit levels.
Timeframe Suggestions
Short-Term Traders (Scalping):
Use on 5-minute to 15-minute charts.
Focus on high-volatility periods for quick entries and exits.
Intraday Traders:
Ideal for 30-minute to 1-hour charts.
Provides more stable signals and less noise.
Swing Traders:
Best suited for 4-hour or daily charts.
Captures broader trends with fewer signals, allowing for larger moves.
Tool Combination
Volume Profile:
Combine with volume-based tools to confirm key support/resistance zones around TP and SL levels.
Trend Indicators:
Use with Moving Averages (e.g., 20-period or 50-period) to identify the broader trend direction.
Example: Only take buy signals in an uptrend and sell signals in a downtrend.
Momentum Oscillators:
Pair with tools like RSI or MACD to avoid entering overbought/oversold conditions.
Support/Resistance Lines:
Manually mark significant levels to confirm alignment with the indicator’s TP and SL zones.
Useful Advice for Traders
Risk Management:
- Always assess the risk/reward ratio; aim for at least 1:2 (risking 1 to gain 2).
- Adjust the multiplier to match your trading style (e.g., higher multiplier for swing trades, lower for scalping).
Avoid Overtrading:
Use the indicator in conjunction with clear rules to avoid false signals during low-volatility periods.
Monitor market volatility:
Pay attention to narrowing Bollinger Bands, which signal consolidations. Avoid trading until a breakout occurs.
Test on Demo Accounts:
Practice using the indicator on a demo account to understand its behavior across different assets and timeframes.
Focus on High-Liquidity Markets:
For the best results, trade highly liquid instruments like major currency pairs, gold, or stock indices.
Summary
The Adaptive Range Indicator dynamically adjusts to market conditions, offering clear entry and exit levels. By combining it with Bollinger Bands and other tools, traders can better navigate market trends and avoid noise. It’s versatile across multiple timeframes and assets, making it a valuable addition to any trader’s toolkit.
Uptrick: Smart BoundariesThis script is an indicator that combines the RSI (Relative Strength Index) and Bollinger Bands to highlight potential points where price momentum and volatility may both be at extreme levels. Below is a detailed explanation of its components, how it calculates signals, and why these two indicators have been merged into one tool. This script is intended solely for educational purposes and for traders who want to explore the combined use of momentum and volatility measures. Please remember that no single indicator guarantees profitable results.
Purpose of This Script
This script is designed to serve as a concise, all-in-one tool for traders seeking to track both momentum and volatility extremes in real time. By overlaying RSI signals with Bollinger Band boundaries, it helps users quickly identify points on a chart where price movement may be highly stretched. The goal is to offer a clearer snapshot of potential overbought or oversold conditions without requiring two separate indicators. Additionally, its optional pyramiding feature enables users to manage how many times they initiate trades when signals repeat in the same direction. Through these combined functions, the script aims to streamline technical analysis by consolidating two popular measures—momentum via RSI and volatility via Bollinger Bands—into a single, manageable interface.
1. Why Combine RSI and Bollinger Bands
• RSI (Relative Strength Index): This is a momentum oscillator that measures the speed and magnitude of recent price changes. It typically ranges between 0 and 100. Traders often watch for RSI crossing into “overbought” or “oversold” levels because it may indicate a potential shift in momentum.
• Bollinger Bands: These bands are plotted around a moving average, using a standard deviation multiplier to create an upper and lower boundary. They help illustrate how volatile the price has been relative to its recent average. When price moves outside these boundaries, some traders see it as a sign the price may be overstretched and could revert closer to the average.
Combining these two can be useful because it blends two different perspectives on market movement. RSI attempts to identify momentum extremes, while Bollinger Bands track volatility extremes. By looking for moments when both conditions agree, the script tries to highlight points where price might be unusually stretched in terms of both momentum and volatility.
2. How Signals Are Generated
• Buy Condition:
- RSI dips below a specified “oversold” level (for example, 30 by default).
- Price closes below the lower Bollinger Band.
When these occur together, the script draws a label indicating a potential bullish opportunity. The underlying reasoning is that momentum (RSI) suggests a stronger-than-usual sell-off, and price is also stretched below the lower Bollinger Band.
• Sell Condition:
- RSI rises above a specified “overbought” level (for example, 70 by default).
- Price closes above the upper Bollinger Band.
When these occur together, a label is plotted for a potential bearish opportunity. The rationale is that momentum (RSI) may be overheated, and the price is trading outside the top of its volatility range.
3. Pyramiding Logic and Trade Count Management
• Pyramiding refers to taking multiple positions in the same direction when signals keep firing. While some traders prefer just one position per signal, others like to scale into a trade if the market keeps pushing in their favor.
• This script uses variables that keep track of how many recent buy or sell signals have fired. If the count reaches a user-defined maximum, no more signals of that type will trigger additional labels. This protects traders from over-committing to one direction if the market conditions remain “extreme” for a prolonged period.
• If you disable the pyramiding feature, the script will only plot one label per side until the condition resets (i.e., until RSI and price conditions are no longer met).
4. Labels and Visual Feedback
• Whenever a buy or sell condition appears, the script plots a label directly on the chart:
- Buy labels under the price bar.
- Sell labels above the price bar.
These labels make it easier to review where both RSI and Bollinger Band conditions align. It can be helpful for visually scanning the chart to see if the signals show any patterns related to market reversals or trend continuations.
• The Bollinger Bands themselves are plotted so traders can see when the price is approaching or exceeding the upper or lower band. Watching the RSI and Bollinger Band plots simultaneously can give traders more context for each signal.
5. Originality and Usefulness
This script provides a distinct approach by merging two well-established concepts—RSI and Bollinger Bands—within a single framework, complemented by optional pyramiding controls. Rather than using each indicator separately, it attempts to uncover moments when momentum signals from RSI align with volatility extremes highlighted by Bollinger Bands. This combined perspective can aid in spotting areas of possible overextension in price. Additionally, the built-in pyramiding mechanism offers a method to manage multiple signals in the same direction, allowing users to adjust how aggressively they scale into trades. By integrating these elements together, the script aims to deliver a tool that caters to diverse trading styles while remaining straightforward to configure and interpret.
6. How to Use the Indicator
• Configure the Inputs:
- RSI Length (the lookback period used for the RSI calculation).
- RSI Overbought and Oversold Levels.
- Bollinger Bands Length and Multiplier (defines the moving average period and the degree of deviation).
- Option to reduce pyramiding.
• Set Alerts (Optional):
- You can create TradingView alerts for when these conditions occur, so you do not have to monitor the chart constantly. Choose the buy or sell alert conditions in your alert settings.
• Integration in a Trading Plan:
- This script alone is not a complete trading system. Consider combining it with other forms of analysis, such as support and resistance, volume profiles, or candlestick patterns. Thorough research, testing on historical data, and risk management are always recommended.
7. No Performance Guarantees
• This script does not promise any specific trading results. It is crucial to remember that no single indicator can accurately predict future market movements all the time. The script simply tries to highlight moments when two well-known indicators both point to an extreme condition.
• Actual trading decisions should factor in a range of market information, including personal risk tolerance and broader market conditions.
8. Purpose and Limitations
• Purpose:
- Provide a combined view of momentum (RSI) and volatility (Bollinger Bands) in a single script.
- Assist in spotting times when price may be at an extreme.
- Offer a configurable system for labeling potential buy or sell points based on these extremes.
• Limitations:
- Overbought and oversold conditions can persist for an extended period in trending markets.
- Bollinger Band breakouts do not always result in immediate reversals. Sometimes price keeps moving in the same direction.
- The script does not include a built-in exit strategy or risk management rules. Traders must handle these themselves.
Additional Disclosures
This script is published open-source and does not rely on any external or private libraries. It does not use lookahead methods or repaint signals; all calculations are performed on the current bar without referencing future data. Furthermore, the script is designed for standard candlestick or bar charts rather than non-standard chart types (e.g., Heikin Ashi, Renko). Traders should keep in mind that while the script can help locate potential momentum and volatility extremes, it does not include an exit strategy or account for factors like slippage or commission. All code comes from built-in Pine Script functions and standard formulas for RSI and Bollinger Bands. Anyone reviewing or modifying this script should exercise caution and incorporate proper risk management when applying it to their own trading.
Calculation Details
The script computes RSI by examining a user-defined number of prior bars (the RSI Length) and determining the average of up-moves relative to the average of down-moves over that period. This ratio is then scaled to a 0–100 range, so lower values typically indicate stronger downward momentum, while higher values suggest stronger upward momentum. In parallel, Bollinger Bands are generated by first calculating a simple moving average (SMA) of the closing price for the user-specified length. The script then measures the standard deviation of closing prices over the same period and multiplies it by the chosen factor (the Bollinger Bands Multiplier) to form the upper and lower boundaries around the SMA. These two measures are checked in tandem: if the RSI dips below a certain oversold threshold and price trades below the lower Bollinger Band, a condition is met that may imply a strong short-term sell-off; similarly, if the RSI surpasses the overbought threshold and price rises above the upper Band, it may indicate an overextended move to the upside. The pyramiding counters track how many of these signals occur in sequence, preventing excessive stacking of labels on the chart if conditions remain extreme for multiple bars.
Conclusion
This indicator aims to provide a more complete view of potential market extremes by overlaying the RSI’s momentum readings on top of Bollinger Band volatility signals. By doing so, it attempts to help traders see when both indicators suggest that the market might be oversold or overbought. The optional reduced pyramiding logic further refines how many signals appear, giving users the choice of a single entry or multiple scaling entries. It does not claim any guaranteed success or predictive power, but rather serves as a tool for those wanting to explore this combined approach. Always be cautious and consider multiple factors before placing any trades.
MACD+RSI+BBDESCRIPTION
The MACD + RSI + Bollinger Bands Indicator is a comprehensive technical analysis tool designed for traders and investors to identify potential market trends and reversals. This script combines three indicators: the Moving Average Convergence Divergence (MACD), the Relative Strength Index (RSI), and Bollinger Bands. Each of these indicators provides unique insights into market behavior.
FEATURES
MACD (Moving Average Convergence Divergence)
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price.
The script calculates the MACD line, the signal line, and the histogram, which visually represents the difference between the MACD line and the signal line.
RSI (Relative Strength Index)
The RSI is a momentum oscillator that measures the speed and change of price movements. It ranges from 0 to 100 and is typically used to identify overbought or oversold conditions.
The script allows users to set custom upper and lower thresholds for the RSI, with default values of 70 and 30, respectively.
Bollinger Bands
Bollinger Bands consist of a middle band (EMA) and two outer bands (standard deviations away from the EMA). They help traders identify volatility and potential price reversals.
The script allows users to customize the length of the Bollinger Bands and the multiplier for the standard deviation.
Color-Coding Logic
The histogram color changes based on the following conditions:
Black: If the RSI is above the upper threshold and the closing price is above the upper Bollinger Band, or if the RSI is below the lower threshold and the closing price is below the lower Bollinger Band.
Green (#4caf50): If the RSI is above the upper threshold but the closing price is not above the upper Bollinger Band.
Light Green (#a5d6a7): If the histogram is positive and the RSI is not above the upper threshold.
Red (#f23645): If the RSI is below the lower threshold but the closing price is not below the lower Bollinger Band.
Light Red (#faa1a4): If the histogram is negative and the RSI is not below the lower threshold.
Inputs
Bollinger Bands Settings
Length: The number of periods for the moving average.
Basis MA Type: The type of moving average (SMA, EMA, SMMA, WMA, VWMA).
Source: The price source for the Bollinger Bands calculation.
StdDev: The multiplier for the standard deviation.
RSI Settings
RSI Length: The number of periods for the RSI calculation.
RSI Upper: The upper threshold for the RSI.
RSI Lower: The lower threshold for the RSI.
Source: The price source for the RSI calculation.
MACD Settings
Fast Length: The length for the fast moving average.
Slow Length: The length for the slow moving average.
Signal Smoothing: The length for the signal line smoothing.
Oscillator MA Type: The type of moving average for the MACD calculation.
Signal Line MA Type: The type of moving average for the signal line.
Usage
This indicator is suitable for various trading strategies, including day trading, swing trading, and long-term investing.
Traders can use the MACD histogram to identify potential buy and sell signals, while the RSI can help confirm overbought or oversold conditions.
The Bollinger Bands provide context for price volatility and potential breakout or reversal points.
Example:
From the example, it can clearly see that the Selling Climax and Buying Climax, marked as orange circle when a black histogram occurs.
Conclusion
The MACD + RSI + Bollinger Bands Indicator is a versatile tool that combines multiple technical analysis methods to provide traders with a comprehensive view of market conditions. By utilizing this script, traders can enhance their analysis and improve their decision-making process.
Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
BBTrend w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "BB Trend" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█Introduction and How it is Different
The "BBTrend w SuperTrend decision - Strategy " is a trading strategy designed to identify market trends using Bollinger Bands and SuperTrend indicators. What sets this strategy apart is its use of two Bollinger Bands with different lengths to capture both short-term and long-term market trends, providing a more comprehensive view of market dynamics. Additionally, the strategy includes customizable take profit (TP) and stop loss (SL) settings, allowing traders to tailor their risk management according to their preferences.
BTCUSD 4h Long Performance
█ Strategy, How It Works: Detailed Explanation
The BBTrend strategy employs two key indicators: Bollinger Bands and SuperTrend.
🔶 Bollinger Bands Calculation:
- Short Bollinger Bands**: Calculated using a shorter period (default 20).
- Long Bollinger Bands**: Calculated using a longer period (default 50).
- Bollinger Bands use the standard deviation of price data to create upper and lower bands around a moving average.
Upper Band = Middle Band + (k * Standard Deviation)
Lower Band = Middle Band - (k * Standard Deviation)
🔶 BBTrend Indicator:
- The BBTrend indicator is derived from the absolute differences between the short and long Bollinger Bands' lower and upper values.
BBTrend = (|Short Lower - Long Lower| - |Short Upper - Long Upper|) / Short Middle * 100
🔶 SuperTrend Indicator:
- The SuperTrend indicator is calculated using the average true range (ATR) and a multiplier. It helps identify the market trend direction by plotting levels above and below the price, which act as dynamic support and resistance levels. * @EliCobra makes the SuperTrend Toolkit. He is GOAT.
SuperTrend Upper = HL2 + (Factor * ATR)
SuperTrend Lower = HL2 - (Factor * ATR)
The strategy determines market trends by checking if the close price is above or below the SuperTrend values:
- Uptrend: Close price is above the SuperTrend lower band.
- Downtrend: Close price is below the SuperTrend upper band.
Short: 10 Long: 20 std 2
Short: 20 Long: 40 std 2
Short: 20 Long: 40 std 4
█ Trade Direction
The strategy allows traders to choose their trading direction:
- Long: Enter long positions only.
- Short: Enter short positions only.
- Both: Enter both long and short positions based on market conditions.
█ Usage
To use the "BBTrend - Strategy " effectively:
1. Configure Inputs: Adjust the Bollinger Bands lengths, standard deviation multiplier, and SuperTrend settings.
2. Set TPSL Conditions: Choose the take profit and stop loss percentages to manage risk.
3. Choose Trade Direction: Decide whether to trade long, short, or both directions.
4. Apply Strategy: Apply the strategy to your chart and monitor the signals for potential trades.
█ Default Settings
The default settings are designed to provide a balance between sensitivity and stability:
- Short BB Length (20): Captures short-term market trends.
- Long BB Length (50): Captures long-term market trends.
- StdDev (2.0): Determines the width of the Bollinger Bands.
- SuperTrend Length (10): Period for calculating the ATR.
- SuperTrend Factor (12): Multiplier for the ATR to adjust the SuperTrend sensitivity.
- Take Profit (30%): Sets the level at which profits are taken.
- Stop Loss (20%): Sets the level at which losses are cut to manage risk.
Effect on Performance
- Short BB Length: A shorter length makes the strategy more responsive to recent price changes but can generate more false signals.
- Long BB Length: A longer length provides smoother trend signals but may be slower to react to price changes.
- StdDev: Higher values create wider bands, reducing the frequency of signals but increasing their reliability.
- SuperTrend Length and Factor: Shorter lengths and higher factors make the SuperTrend more sensitive, providing quicker signals but potentially more noise.
- Take Profit and Stop Loss: Adjusting these levels affects the risk-reward ratio. Higher take profit percentages can increase gains but may result in fewer closed trades, while higher stop loss percentages can decrease the likelihood of being stopped out but increase potential losses.
Optimal Length BackTester [YinYangAlgorithms]This Indicator allows for a ‘Optimal Length’ to be inputted within the Settings as a Source. Unlike most Indicators and/or Strategies that rely on either Static Lengths or Internal calculations for the length, this Indicator relies on the Length being derived from an external Indicator in the form of a Source Input.
This may not sound like much, but this application may allows limitless implementations of such an idea. By allowing the input of a Length within a Source Setting you may have an ‘Optimal Length’ that adjusts automatically without the need for manual intervention. This may allow for Traditional and Non-Traditional Indicators and/or Strategies to allow modifications within their settings as well to accommodate the idea of this ‘Optimal Length’ model to create an Indicator and/or Strategy that adjusts its length based on the top performing Length within the current Market Conditions.
This specific Indicator aims to allow backtesting with an ‘Optimal Length’ inputted as a ‘Source’ within the Settings.
This ‘Optimal Length’ may be used to display and potentially optimize multiple different Traditional Indicators within this BackTester. The following Traditional Indicators are included and available to be backtested with an ‘Optimal Length’ inputted as a Source in the Settings:
Moving Average; expressed as either a: Simple Moving Average, Exponential Moving Average or Volume Weighted Moving Average
Bollinger Bands; expressed based on the Moving Average Type
Donchian Channels; expressed based on the Moving Average Type
Envelopes; expressed based on the Moving Average Type
Envelopes Adjusted; expressed based on the Moving Average Type
All of these Traditional Indicators likewise may be displayed with multiple ‘Optimal Lengths’. They have the ability for multiple different ‘Optimal Lengths’ to be inputted and displayed, such as:
Fast Optimal Length
Slow Optimal Length
Neutral Optimal Length
By allowing for the input of multiple different ‘Optimal Lengths’ we may express the ‘Optimal Movement’ of such an expressed Indicator based on different Time Frames and potentially also movement based on Fast, Slow and Neutral (Inclusive) Lengths.
This in general is a simple Indicator that simply allows for the input of multiple different varieties of ‘Optimal Lengths’ to be displayed in different ways using Tradition Indicators. However, the idea and model of accepting a Length as a Source is unique and may be adopted in many different forms and endless ideas.
Tutorial:
You may add an ‘Optimal Length’ within the Settings as a ‘Source’ as followed in the example above. This Indicator allows for the input of a:
Neutral ‘Optimal Length’
Fast ‘Optimal Length’
Slow ‘Optimal Length’
It is important to account for all three as they generally encompass different min/max length values and therefore result in varying ‘Optimal Length’s’.
For instance, say you’re calculating the ‘Optimal Length’ and you use:
Min: 1
Max: 400
This would therefore be scanning for 400 (inclusive) lengths.
As a general way of calculating you may assume the following for which lengths are being used within an ‘Optimal Length’ calculation:
Fast: 1 - 199
Slow: 200 - 400
Neutral: 1 - 400
This allows for the calculation of a Fast and Slow length within the predetermined lengths allotted. However, it likewise allows for a Neutral length which is inclusive to all lengths alloted and may be deemed the ‘Most Accurate’ for these reasons. However, just because the Neutral is inclusive to all lengths, doesn’t mean the Fast and Slow lengths are irrelevant. The Fast and Slow length inputs may be useful for seeing how specifically zoned lengths may fair, and likewise when they cross over and/or under the Neutral ‘Optimal Length’.
This Indicator features the ability to display multiple different types of Traditional Indicators within the ‘Display Type’.
We will go over all of the different ‘Display Types’ with examples on how using a Fast, Slow and Neutral length would impact it:
Simple Moving Average:
In this example above have the Fast, Slow and Neutral Optimal Length formatted as a Slow Moving Average. The first example is on the 15 minute Time Frame and the second is on the 1 Day Time Frame, demonstrating how the length changes based on the Time Frame and the effects it may have.
Here we can see that by inputting ‘Optimal Lengths’ as a Simple Moving Average we may see moving averages that change over time with their ‘Optimal Lengths’. These lengths may help identify Support and/or Resistance locations. By using an 'Optimal Length' rather than a static length, we may create a Moving Average which may be more accurate as it attempts to be adaptive to current Market Conditions.
Bollinger Bands:
Bollinger Bands are a way to see a Simple Moving Average (SMA) that then uses Standard Deviation to identify how much deviation has occurred. This Deviation is then Added and Subtracted from the SMA to create the Bollinger Bands which help Identify possible movement zones that are ‘within range’. This may mean that the price may face Support / Resistance when it reaches the Outer / Inner bounds of the Bollinger Bands. Likewise, it may mean the Price is ‘Overbought’ when outside and above or ‘Underbought’ when outside and below the Bollinger Bands.
By applying All 3 different types of Optimal Lengths towards a Traditional Bollinger Band calculation we may hope to see different ranges of Bollinger Bands and how different lookback lengths may imply possible movement ranges on both a Short Term, Long Term and Neutral perspective. By seeing these possible ranges you may have the ability to identify more levels of Support and Resistance over different lengths and Trading Styles.
Donchian Channels:
Above you’ll see two examples of Machine Learning: Optimal Length applied to Donchian Channels. These are displayed with both the 15 Minute Time Frame and the 1 Day Time Frame.
Donchian Channels are a way of seeing potential Support and Resistance within a given lookback length. They are a way of withholding the High’s and Low’s of a specific lookback length and looking for deviation within this length. By applying a Fast, Slow and Neutral Machine Learning: Optimal Length to these Donchian Channels way may hope to achieve a viable range of High’s and Low’s that one may use to Identify Support and Resistance locations for different ranges of Optimal Lengths and likewise potentially different Trading Strategies.
Envelopes / Envelopes Adjusted:
Envelopes are an interesting one in the sense that they both may be perceived as useful; however we deem that with the use of an ‘Optimal Length’ that the ‘Envelopes Adjusted’ may work best. We will start with examples of the Traditional Envelope then showcase the Adjusted version.
Envelopes:
As you may see, a Traditional form of Envelopes even produced with a Machine Learning: Optimal Length may not produce optimal results. Unfortunately this may occur with some Traditional Indicators and they may need some adjustments as you’ll notice with the ‘Envelopes Adjusted’ version. However, even without the adjustments, these Envelopes may be useful for seeing ‘Overbought’ and ‘Oversold’ locations within a Machine Learning: Optimal Length standpoint.
Envelopes Adjusted:
By adding an adjustment to these Envelopes, we may hope to better reflect our Optimal Length within it. This is caused by adding a ratio reflection towards the current length of the Optimal Length and the max Length used. This allows for the Fast and Neutral (and potentially Slow if Neutral is greater) to achieve a potentially more accurate result.
Envelopes, much like Bollinger Bands are a way of seeing potential movement zones along with potential Support and Resistance. However, unlike Bollinger Bands which are based on Standard Deviation, Envelopes are based on percentages +/- from the Simple Moving Average.
We will conclude our Tutorial here. Hopefully this has given you some insight into how useful adding a ‘Optimal Length’ within an external (secondary) Indicator as a Source within the Settings may be. Likewise, how useful it may be for automation sake in the sense that when the ‘Optimal Length’ changes, it doesn’t rely on an alert where you need to manually update it yourself; instead it will update Automatically and you may reap the benefits of such with little manual input needed (aside from the initial setup).
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Logical Trading Indicator V.1Features of the Logical Trading Indicator V.1
ATR-Based Trailing Stop Loss
The Logical Trading Indicator V.1 utilizes the Average True Range (ATR) to implement a dynamic trailing stop loss. You can customize the sensitivity of your alerts by adjusting the ATR Multiple and ATR Period settings.
Higher ATR Multiple values create wider stops, while lower values result in tighter stops. This feature ensures that your trades are protected against adverse price movements. For best practice, use higher values on higher timeframes and lower values on lower term timeframes.
Bollinger Bands
The Logical Trading Indicator V.1 includes Bollinger Bands, which can be customized to use either a Simple Moving Average (SMA) or an Exponential Moving Average (EMA) as the basis.
You can adjust the length and standard deviation multiplier of the Bollinger Bands to fine-tune your strategy. The color of the basis line changes to green when price is above and red when price is below the line to represent the trend.
The bands show a range vs a single band that also represents when the price is in overbought and oversold ranges similar to an RSI. These bands also control the take profit signals.
You also have the ability to change the band colors as well as toggle them off, which only affects the view, they are still active which will still fire the take profit signals.
Momentum Indicator
Our indicator offers a momentum filter option that highlights market momentum directly on the candlesticks, identifying periods of bullish, bearish, or consolidation phases. You can enable or disable this filter as needed, providing valuable insights into market conditions.
By default, you will see the candlestick colors represent the momentum direction as green or red, and consolidation periods as white, but the filter on the BUY and SELL signals is not active. The view options and filter can be toggled on and off in the settings.
Buy and Sell Signals
The Logical Trading Indicator V.1 generates buy and sell signals based on a combination of ATR-based filtering, Bollinger Band basis crossover, and optional momentum conditions if selected in the settings. These signals help you make informed decisions about when to enter or exit a trade. You can also enable a consolidation filter to stay out of trades during tight ranges.
Basically a BUY signal fires when the price closes above the basis line, and the price meets or exceeds the ATR multiple from the previous candle length, which is also editable in the settings.
If the momentum filter is engaged, it will not fire BUY signals when in consolidation periods. It works just the opposite for SELL signals.
Take Profit Signals
We've integrated a Take Profit feature that helps you identify points to exit your trades with profits. The indicator marks Long Take Profit when prices close below the upper zone line of the Bollinger Bands after the previous candle closes inside the band, suggesting an optimal point to exit a long trade or consider a short position.
Conversely, Short Take Profit signals appear when prices close above the lower zone after the previous candle closes inside of it, indicating the right time to exit a short trade or contemplate a long position.
Alerts for Informed Trading
The Logical Trading Indicator V.1 comes equipped with alert conditions for buy signals, sell signals, take profit points, and more. Receive real-time notifications to your preferred devices or platforms to stay updated on market movements and trading opportunities.
VOLD Ratio (Volume Difference Ratio) by TenozenAnother helpful indicator is here! VOLD Ratio is calculated by the net volume of a buying candle, divided by the net volume of a sell candle.
Formula:
buying net volume/selling net volume
It's a simple indicator, but don't underestimate this simplicity. It's a powerful indicator that would help you to decide whether the volume is getting interested in the direction that the market would take. So assume when the market is above the Bollinger Bands, it means that the volume is at a buying extreme, by that, we could expect the market to get back towards the mean, as there is a lot of buying demand that entered the market. How about below the Bollinger Bands? it means that the volume is at a selling extreme, we could expect that there is a lot of volume getting in toward the sellers, so we could take advantage of the opportunity to go for a long. Lastly, the Bollinger Bands would help you guys to determine the liquidity of the market, if the Bollinger Bands get smaller over time, it means there is no interest for the market to enter yet, and if the Bollinger Bands get bigger over time, it means there is interest for the market to enter in the session.
Tips & Reminder:
- We shouldn't use this indicator by itself, make sure to use an Indicator that would help you guys to determine the momentum and the liquidity of the market.
- The higher the timeframe, the slower this indicator would signal an entry, by that use a smaller timeframe... I suggest using a 15M chart for the execution.
- Always trade in the medium-longterm direction if you want to have a high probability trade.
- Be patient in your execution, it's more likely the market would go higher or lower after going in the extreme of the Bollinger Bands.
Well, that's it! Hope you guys enjoy using this indicator, let me know if there is any question or suggestion. Ciao...
Moving Averages + BB & R.VWAP StDev (multi-tf)█ Moving Averages + Bollinger Bands and Rolling Volume Weighted Average Price with Standard Deviation Bands (Multi Timeframe)
Multiple moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines and colors are customizable too.
This script can display:
Moving Averages
Bollinger Bands
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Based on the previous script :
Probability Envelopes (PBE)Introduction
In the world of trading, technical analysis is vital for making informed decisions about the future direction of an asset's price. One such tool is the use of indicators, mathematical calculations that can help traders predict market trends. This article delves into an innovative indicator called the Probability Envelopes Indicator, which offers valuable insights into the potential price levels an asset may reach based on historical data. This in-depth look explores the statistical foundations of the indicator, highlighting its key components and benefits.
Section 1: Calculating Price Movements with Log Returns and Percentages
The Probability Envelopes Indicator provides the option to use either log returns or percentage changes when calculating price movements. Each method has its advantages:
Log Returns: These are calculated as the natural logarithm of the ratio of the current price to the previous price. Log returns are considered more stable and less sensitive to extreme price fluctuations.
Percentage Changes: These are calculated as the percentage difference between the current price and the previous price. They are simpler to interpret and easier to understand for most traders.
Section 2: Understanding Mean, Variance, and Standard Deviation
The Probability Envelopes Indicator utilizes various statistical measures to analyze historical price movements:
Mean: This is the average of a set of numbers. In the context of this indicator, it represents the average price movement for bullish (green) and bearish (red) scenarios.
Variance: This measure represents the dispersion of data points in a dataset. A higher variance indicates a greater spread of data points from the mean. Variance is calculated as the average of the squared differences from the mean.
Standard Deviation: This is the square root of the variance. It is a measure of the amount of variation or dispersion in a dataset. In the context of this indicator, standard deviations are used to calculate the width of the bands around the expected mean.
Section 3: Analyzing Historical Price Movements and Probabilities
The Probability Envelopes Indicator examines historical price movements and calculates probabilities based on their frequency:
The indicator first identifies and categorizes price movements into bullish (green) and bearish (red) scenarios.
It then calculates the probability of each price movement occurring by dividing the frequency of the movement by the total number of occurrences in each category (bullish or bearish).
The expected green and red movements are calculated by multiplying the probabilities by their respective price movements and summing the results.
The total expected movement, or weighted average, is calculated by combining the expected green and red movements and dividing by the total number of occurrences.
Section 4: Constructing the Probability Envelopes
The Probability Envelopes Indicator utilizes the calculated statistics to construct its bands:
The expected mean is calculated using the total expected movement and applied to the current open price.
An exponential moving average (EMA) is used to smooth the expected mean, with the smoothing length determining the degree of responsiveness.
The upper and lower bands are calculated by adding and subtracting the mean green and red movements, respectively, along with their standard deviations multiplied by a user-defined multiplier.
Section 5: Benefits of the Probability Envelopes Indicator
The Probability Envelopes Indicator offers numerous advantages to traders:
Enhanced Decision-Making: By providing probability-based estimations of future price levels, the indicator can help traders make more informed decisions and potentially improve their trading strategies.
Versatility: The indicator is applicable to various financial instruments, such as stocks, forex, commodities, and cryptocurrencies, making it a valuable tool for traders in different markets.
Customization: The indicator's parameters, including the use of log returns, multiplier values, and smoothing length, can be adjusted according to the user's preferences and trading style. This flexibility allows traders to fine-tune the Probability Envelopes Indicator to better suit their needs and goals.
Risk Management: The Probability Envelopes Indicator can be used as a component of a risk management strategy by providing insight into potential price movements. By identifying potential areas of support and resistance, traders can set stop-loss and take-profit levels more effectively.
Visualization: The graphical representation of the indicator, with its clear upper and lower bands, makes it easy for traders to quickly assess the market and potential price levels.
Section 6: Integrating the Probability Envelopes Indicator into Your Trading Strategy
When incorporating the Probability Envelopes Indicator into your trading strategy, consider the following tips:
Confirmation Signals: Use the indicator in conjunction with other technical analysis tools, such as trend lines, moving averages, or oscillators, to confirm the strength and direction of the market trend.
Timeframes: Experiment with different timeframes to find the optimal settings for your trading strategy. Keep in mind that shorter timeframes may generate more frequent signals but may also increase the likelihood of false signals.
Risk Management: Always establish a proper risk management strategy that includes setting stop-loss and take-profit levels, as well as managing your position sizes.
Backtesting: Test the Probability Envelopes Indicator on historical data to evaluate its effectiveness and fine-tune its parameters to optimize your trading strategy.
Section 7: Cons and Limitations of the Probability Envelopes Indicator
While the Probability Envelopes Indicator offers several advantages to traders, it is essential to be aware of its potential cons and limitations. Understanding these can help you make better-informed decisions when incorporating the indicator into your trading strategy.
Lagging Nature: The Probability Envelopes Indicator is primarily based on historical data and price movements. As a result, it may be less responsive to real-time changes in market conditions, and the predicted price levels may not always accurately reflect the market's current state. This lagging nature can lead to late entry and exit signals.
False Signals: As with any technical analysis tool, the Probability Envelopes Indicator can generate false signals. These occur when the indicator suggests a potential price movement, but the market does not follow through. It is crucial to use other technical analysis tools to confirm the signals and minimize the impact of false signals on your trading decisions.
Complex Statistical Concepts: The Probability Envelopes Indicator relies on complex statistical concepts and calculations, which may be challenging to grasp for some traders, particularly beginners. This complexity can lead to misunderstandings and misuse of the indicator if not adequately understood.
Overemphasis on Past Data: While historical data can be informative, relying too heavily on past performance to predict future movements can be limiting. Market conditions can change rapidly, and relying solely on past data may not provide an accurate representation of the current market environment.
No Guarantees: The Probability Envelopes Indicator, like all technical analysis tools, cannot guarantee success. It is essential to approach trading with realistic expectations and understand that no indicator or strategy can provide foolproof results.
To overcome these limitations, it is crucial to combine the Probability Envelopes Indicator with other technical analysis tools and utilize a comprehensive risk management strategy. By doing so, you can better understand the market and increase your chances of success in the ever-changing financial markets.
Section 8: Probability Envelopes Indicator vs. Bollinger Bands
Bollinger Bands and the Probability Envelopes Indicator are both technical analysis tools designed to identify potential support and resistance levels, as well as potential trend reversals. However, they differ in their underlying concepts, calculations, and applications. This section will provide a deep dive into the differences between these two indicators and how they can complement each other in a trading strategy.
Underlying Concepts and Calculations:
Bollinger Bands:
Bollinger Bands are based on a simple moving average (SMA) of the price data, with upper and lower bands plotted at a specified number of standard deviations away from the SMA.
The distance between the bands widens during periods of increased price volatility and narrows during periods of low volatility, indicating potential trend reversals or breakouts.
The standard settings for Bollinger Bands typically involve a 20-period SMA and a 2 standard deviation distance for the upper and lower bands.
Probability Envelopes Indicator:
The Probability Envelopes Indicator calculates the expected price movements based on historical data and probabilities, utilizing mean and standard deviation calculations for both upward and downward price movements.
It generates upper and lower bands based on the calculated expected mean movement and the standard deviation of historical price changes, multiplied by a user-defined multiplier.
The Probability Envelopes Indicator also allows users to choose between using log returns or percentage changes for the calculations, adding flexibility to the indicator.
Key Differences:
Calculation Method: Bollinger Bands are based on a simple moving average and standard deviations, while the Probability Envelopes Indicator uses statistical probability calculations derived from historical price changes.
Flexibility: The Probability Envelopes Indicator allows users to choose between log returns or percentage changes and adjust the multiplier, offering more customization options compared to Bollinger Bands.
Risk Management: Bollinger Bands primarily focus on volatility, while the Probability Envelopes Indicator incorporates probability calculations to provide additional insights into potential price movements, which can be helpful for risk management purposes.
Complementary Use:
Using both Bollinger Bands and the Probability Envelopes Indicator in your trading strategy can offer valuable insights into market conditions and potential price levels.
Bollinger Bands can provide insights into market volatility and potential breakouts or trend reversals based on the widening or narrowing of the bands.
The Probability Envelopes Indicator can offer additional information on the expected price movements based on historical data and probabilities, which can be helpful in anticipating potential support and resistance levels.
Combining these two indicators can help traders to better understand market dynamics and increase their chances of identifying profitable trading opportunities.
In conclusion, while both Bollinger Bands and the Probability Envelopes Indicator aim to identify potential support and resistance levels, they differ significantly in their underlying concepts, calculations, and applications. By understanding these differences and incorporating both tools into your trading strategy, you can gain a more comprehensive understanding of the market and make more informed trading decisions.
In conclusion, the Probability Envelopes Indicator is a powerful and versatile technical analysis tool that offers unique insights into expected price movements based on historical data and probability calculations. It provides traders with the ability to identify potential support and resistance levels, as well as potential trend reversals. When compared to Bollinger Bands, the Probability Envelopes Indicator offers more customization options and incorporates probability-based calculations for a different perspective on market dynamics.
Although the Probability Envelopes Indicator has its limitations and potential cons, such as the reliance on historical data and the assumption that past performance is indicative of future results, it remains a valuable addition to any trader's toolkit. By using the Probability Envelopes Indicator in conjunction with other technical analysis tools, such as Bollinger Bands, traders can gain a more comprehensive understanding of the market and make more informed trading decisions.
Ultimately, the success of any trading strategy relies on the ability to interpret and apply multiple indicators effectively. The Probability Envelopes Indicator serves as a unique and valuable tool in this regard, providing traders with a deeper understanding of the market and its potential price movements. By utilizing this indicator in combination with other tools and techniques, traders can increase their chances of success and optimize their trading strategies.
LibIndicadoresUteisLibrary "LibIndicadoresUteis"
Collection of useful indicators. This collection does not do any type of plotting on the graph, as the methods implemented can and should be used to get the return of mathematical formulas, in a way that speeds up the development of new scripts. The current version contains methods for stochastic return, slow stochastic, IFR, leverage calculation for B3 futures market, leverage calculation for B3 stock market, bollinger bands and the range of change.
estocastico(PeriodoEstocastico)
Returns the value of stochastic
Parameters:
PeriodoEstocastico : Period for calculation basis
Returns: Float with the stochastic value of the period
estocasticoLento(PeriodoEstocastico, PeriodoMedia)
Returns the value of slow stochastic
Parameters:
PeriodoEstocastico : Stochastic period for calculation basis
PeriodoMedia : Average period for calculation basis
Returns: Float with the value of the slow stochastic of the period
ifrInvenenado(PeriodoIFR, OrigemIFR)
Returns the value of the RSI/IFR Poisoned of Guima
Parameters:
PeriodoIFR : RSI/IFR period for calculation basis
OrigemIFR : Source of RSI/IFR for calculation basis
Returns: Float with the RSI/IFR value for the period
calculoAlavancagemFuturos(margem, alavancagemMaxima)
Returns the number of contracts to work based on margin
Parameters:
margem : Margin for contract unit
alavancagemMaxima : Maximum number of contracts to work
Returns: Integer with the number of contracts suggested for trading
calculoAlavancagemAcoes(alavancagemMaxima)
Returns the number of batches to work based on the margin
Parameters:
alavancagemMaxima : Maximum number of batches to work
Returns: Integer with the amount of lots suggested for trading
bandasBollinger(periodoBB, origemBB, desvioPadrao)
Returns the value of bollinger bands
Parameters:
periodoBB : Period of bollinger bands for calculation basis
origemBB : Origin of bollinger bands for calculation basis
desvioPadrao : Standard Deviation of bollinger bands for calculation basis
Returns: Two-position array with upper and lower band values respectively
theRoc(periodoROC, origemROC)
Returns the value of Rate Of Change
Parameters:
periodoROC : Period for calculation basis
origemROC : Source of calculation basis
Returns: Float with the value of Rate Of Change
MTF MA Ribbon and Bands + BB, Gaussian F. and R. VWAP with StDev█ Multi Timeframe Moving Average Ribbon and Bands + Bollinger Bands, Gaussian Filter and Rolling Volume Weighted Average Price with Standard Deviation Bands
Up to 9 moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines, colors and background fill are customizable too.
This script can also display:
Moving Average Bands
Bollinger Bands
Gaussian Filter
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Gaussian Filter
Gaussian filter can be used for smoothing.
It rejects high frequencies (fast movements) better than an EMA and has lower lag.
A Gaussian filter is one whose transfer response is described by the familiar Gaussian bell-shaped curve.
In the case of low-pass filters, only the upper half of the curve describes the filter.
The use of gaussian filters is a move toward achieving the dual goal of reducing lag and reducing the lag of high-frequency components relative to the lag of lower-frequency components.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Made with the help from scripts of: adam24x, VishvaP, loxx and pmk07.
Ultimate IndicatorThis is a combination of all the price chart indicators I frequently switch between. It contains my day time highlighter (for day trading), multi-timeframe long-term trend indicator for current commodity in the bottom right, customizable trend EMA which also has multi-timeframe drawing capabilities, VWAP, customizable indicators with separate settings from the trend indicator including: EMA, HL2 over time, Donchian Channels, Keltner Channels, Bollinger Bands, and Super Trend. The settings for these are right below the trend settings and can have their length and multiplier adjusted. All of those also have multi-timeframe capabilities separate from the trend multi-time settings.
The Day Trade Highlight option will draw faint yellow between 9:15-9:25, red between 9:25-9:45, yellow between 9:45-10:05. There will be one white background at 9:30am to show the opening of the market. while the market is open there will be a very faint blue background. For the end of the day there will be yellow between 15:45-15:50, red between 15:50-16:00, and yellow between 16:00-16:05. During the night hours, there is no coloring. The purpose of this highlight is to show the opening / closing times of the market and the hot times for large moves.
The indicators can also be colored in the following ways:
1. Simple = Makes all colors for the indicator Gray
2. Trend = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction.
3. Trend Adv = Will use the Donchian Channels to get the short-trend direction and by default will color the short-term direction as Blue or Red. Unless using Super Trend, the Donchian Channel is used to find short-term trend direction. If there is a short-term up-trend during a long-term down-trend, the Blue will become Navy. If short-term down-trend during long-term up-trend, the Red will be Brown.
4. Squeeze = Compares the Bollinger Bands width to the Keltner Channels width and will color based on relative squeeze of the market: Teal = no squeeze. Yellow = little squeeze. Red = decent squeeze. White = huge squeeze. if you do not understand this one, try drawing the Bollinger Bands while using the Squeeze color option and it should become more apparent how this works. I also recommend leaving the length and multiplier to the default 20 and 2 if using this setting and only changing the timeframe to get longer/shorter lengths as I've seen that changing the length or multiplier can more or less make it not work at all.
Along with the indicator settings are options to draw lines/labels/fills for the indicator. I enjoy having only fills for a cleaner look.
The Labels option will show Buy/Sell signals when the short-term trend flips to agree with the long-term trend.
The Trend Bars option will do the same as the Labels option but instead will color the bars white when a Buy/Sell option is given.
The Range Bars option shows will color a bar white when the Close of a candle is outside of a respective ranging indicator option (Bollinger or Keltner).
The Trend Bars will draw white candles no matter which indicator selection you make (even "Off"). However, Range Bars will only draw white when either Bollinger or Keltner are selected.
The Donchian Channels and Super Trend are trending indicators and should be used during trending markets. I like to use the MACD in conjunction with these indicators for possibly earlier entries.
The Bollinger Bands and Keltner Channel are ranging indicators and should be used during ranging markets. I like to use the RSI in conjunction with these indicators and will use 60/40 for overbought and oversold areas rather than 70/30. During a range, I wait for an overbought or oversold indication and will buy/sell when it crosses back into the middle area and close my position when it touches the opposite band.
I have a MACD/RSI combination indicator if you'd like that as well :D
As always, trade at your own risk. This is not some secret indicator that will 100% win. As always, the trades you see in the picture use a 1:1.5 or 1:2 risk to reward ratio, for today (August 8, 2022) it won 5/6 times with one trade still open at the end of the day. Manage your account correctly and you'll win in the long term. Hit me up with any questions or suggestions. Happy Trading!
