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.
Cerca negli script per "bands"
Normal Weighted Average PriceIntroducing the "Normal Weighted Average Price" (NWAP) by OmegaTools. This innovative script refines the traditional concept of VWAP by eliminating volume from the equation, offering a unique perspective on price movements and market trends.
The NWAP script is meticulously crafted to provide traders with a straightforward yet powerful tool for analyzing price action. By focusing solely on price data, the NWAP offers a clear, volume-independent view of the market's average price, augmented with bands that denote varying levels of price deviation.
Key Features:
NWAP Core: At the heart of this script is the Normal Weighted Average Price line, offering a pure, volume-excluded average price over your chosen timeframe.
Dynamic Bands: Includes upper and lower bands, plus extreme levels, calculated using the standard deviation from the NWAP. These bands help identify potential overbought and oversold conditions.
Customizable Timeframe: Whether you're a day trader or a long-term investor, the NWAP script allows you to set your preferred analysis period, ensuring relevance to your trading strategy.
Bands Width Adjustment: Tailor the width of the deviation bands with a simple multiplier to fit your risk tolerance and trading style.
Visual Zones: The script visually demarcates premium and discount zones between the bands, aiding in quick assessment of market conditions.
Usage Tips:
Ideal for traders seeking a volume-neutral method to gauge market sentiment and potential reversal points.
Use the NWAP and its bands to refine entry and exit points, especially in markets where volume data may be less reliable or skewed.
Combine with other technical indicators for a comprehensive trading strategy.
The Ultimate Buy and Sell IndicatorThis indicator should be used in conjunction with a solid risk management strategy that does not over-leverage positions and uses stop-losses. You can not rely 100% on the signals provided by this indicator (or any other for that matter).
With that said, this indicator can provide some excellent signals.
It has been designed with a large number of customization options intended for advanced traders, but you do not HAVE to be an advanced user to simply use the indicator. I have tried to make it easy to understand, and this section will provide you with a better understanding of how to use it.
NOTE:
While NOT REQUIRED, I would recommend also finding my indicator called, "Ultimate RSI", which is designed to work together with this indicator (visually). They both contain the same settings and allow you to visualize changes made in this indicator that can not be displayed on the main chart.
This indicator creates it's own candles(bars), so you have to go into your main settings and turn off the "body, border and wick" color settings. Using a dark background is also recommended.
How does it work?
The indicator mainly relies on the RSI indicator with Bollinger Bands for signals. (Though not entirely)
First, there are something that I call "Watch Signals", which are various Bollinger Band crossing events. This could be the price crossing Bollinger Bands or the RSI crossing Bollinger Bands.
There are separate watch signals for buys and sells. Buy watch signals are colored orange to match the BUY signal candle color and Fuchsia (kind of a bright purple) to match SELL signal candles.
In order for most buy or sell signals to be created, there must first be a watch signal. There is a lookback period (or length) for watch signals to be used, and after that many candles (bars) have passed, they will be ignored. You can set a length to look back as well as a time to wait before creating any.
What this means is that if there has previously been (for instance) a sell signal. You can tell it to wait 10 bars before creating any buy watch signals. You can then also tell it that it should look back 10 bars from the current one in order to find any buy watch signals. This means that if you had it set up that way 10 to wait and 10 to validate, it would start allowing buy watch signals 11 bars after a sell, and then once you hit 20 bars, it will start leaving a gap (invisible to you) as the 10 bar lookback period starts moving forward with each new bar. This is useful in order to keep signals more spaced apart as some bad signals come quickly after another one.
Example: You may get a sell signal where the Bollinger bands are tight, then the price easily drops down into the lower band creating a buy watch signal, then you get a "fake" or short pump up and it says buy, but then drops dramatically afterwards. The wait period can ensure that the sell stays in effect longer before a buy is considered by blocking any buy watch signals for a period of time.
After you get a watch signal, the system then looks for various other things to happen to create buy or sell signals. This could be the RSI crossing the (slow) RSI Basis line (from its Bollinger bands), it could be the price crossing its basis line, it could be MACD crosses, it could even be RSI crossing certain levels. All of these are options. If you like the MACD strategy and want it to give you buy and sell signals from just MACD crosses, simply select that option for signals.
It is also able to use the first of any of the options that takes place.
I included an option to force alternating buy and sell signals, rather than showing groups of, or subsequent buy, buy, buy signals, for instance.
Moving on....
You can change the moving average that is used to calculate the RSI. The standard moving average for RSI is the RMA (aka SWMA). Changes to this can dramatically change your signals. You also have the option to change the moving average type used in the Bollinger bands calculation. You can change the length of these as well. The same goes for the Bollinger bands over the Price chart. I added an ATR option for the RSI Bollinger bands to play with, as well. You are able to adjust the standard deviation (multiplier) of the bands as well, which will of course affect the signals.
The ways you can play with signals are nearly infinite, so have fun figuring it out.
The indicator allows for moving averages to be shown as well, with a variety of types to choose from. The standard numbers are 5, 10, 20, 50, 100 and 200, with the addition of a custom moving average of your choice. You can also change the color of this one. You can choose to show them all or any of them you want to show, in any combination, although the TYPE of moving average (SMA, EMA, WMA, etc.) will apply to all of them.
You may also notice the Bollinger Bands over the Price are colored, and become more or less transparent.
The color is derived from the trend of the RSI or the RSI basis (your choice). It looks back at the value however many bars you want and compares the values and that's how it determines if it is trending up or down. Since RSI is a directional momentum indicator, this can be quite useful. If you see the bands are getting darker, this will explain why.
The indicator has a lookback period for determining the widest the bands (which measure volatility) have been over that period of time. This is the baseline. It then will make the bands disappear (by making them more transparent) if the volatility is low. This indicates that a change in volatility is coming and that price isn't really changing much compared to the past (default 500) bars. If they become bright, this is because price has started trending in a direction and volatility is increasing.
I should also note that the candles are colored based on RSI levels.
If you use the Ultimate Companion indicator, you will be able to see the RSI levels (zones) that the colors are based on. As RSI moves into a new range, the candle color will change.
I have created a yellow zone where the candles turn yellow. This is when RSI is between (default) 45 and 55, indicating there is basically no momentum and price is going sideways. This is a good place to get trapped in bad trades, and there is a Yellow RSI Filter to block signals in this area to keep you from entering bad trades.
Green candles indicate values over 55 (getting brighter as RSI rises) and red candles are RSI values under 45 (getting brighter as RSI values get lower). If you see white, this means RSI is either over 80 or under 20. A sharp reversal is almost always imminent at this stage.
When we talk about Buy and Sell Signals, they draw a green or red triangle and it literally says BUY or SELL. There is an option to color the background for added visibility. These signals do not "repaint", what this means is that they can be late. To account for this, I have included a background color that will flash as a warning that a buy or sell could be imminent, although it may fail to break through and set a buy or sell signal. This is simply an advanced warning. The reason is that sometimes a candle may be very large and you won't be told to buy or sell during the candle until the move is completely over and now you're getting in on the next one. That's not a great feeling, so I made it repaint the background color and not repaint the completed signal. You get the best of both worlds.
This indicator also uses complex logic to handle things.
When there is a buy signal, it enters into a state of having been bought, or a "bought state". The same for sells. If Force alternating signals is off, you could have more than one buy in a bought state, or more than one sell in a sell state. There is an option to color the background green during the full duration of a bought state, or red during the full duration of a sold state.
I have added divergence.
This shows that the lows or highs of RSI and PRICE are different. If RSI is making higher highs but the price is not, then the price is likely to follow this bullish divergence, if the opposite happens, it's bearish. It will draw a line on the chart connecting the highs and lows and call it bearish or bullish. You can adjust this as well.
I have an RSI High/Low filter. If the RSI basis (or average) is very high or low, you can block signal from this area since the price is likely to continue in that direction before actually reversing.
You can change the settings of the MACD if you choose to use it for signals, and if you want to see it, you'll have to run that indicator below the chart and match the settings to see what is going on, just like the RSI.
Going back to Watch Signals. You can also choose to require more than one watch signal if you choose. You can skip watch signals, so it will ignore the first or second one, whatever you want to do. You can color the background to show you where watch signals have been skipped.
Regarding the wait period for creating watch signals after a sell or after a buy, you can also color the background to see where these were blocked by the wait period.
Lastly you can choose which type of watch signals to use, or keep them from being shown on the chart. This allows you to study the history of how the asset you are trading behaves and customize the behavior of signals based on your study of it.
Everything in the settings area has tooltips, which will explain what that thing does to help you along this journey.
I hope this indicator (and perhaps Ultimate RSI alongside this) will help you take your trading to the next level.
TrendCylinder (Expo)█ Overview
The TrendCylinder is a dynamic trading indicator designed to capture trends and volatility in an asset's price. It provides a visualization of the current trend direction and upper and lower bands that adapt to volatility changes. By using this indicator, traders can identify potential breakouts or support and resistance levels. While also gauging the volatility to generate trading ranges. The indicator is a comprehensive tool for traders navigating various market conditions by providing a sophisticated blend of trend-following and volatility-based metrics.
█ How It Works
Trend Line: The trend line is constructed using the closing prices with the influence of volatility metrics. The trend line reacts to sudden price changes based on the trend factor and step settings.
Upper & Lower Bands: These bands are not static; they are dynamically adjusted with the calculated standard deviation and Average True Range (ATR) metrics to offer a more flexible, real-world representation of potential price movements, offering an idea of the market's likely trading range.
█ How to Use
Identifying Trends
The trend line can be used to identify the current market trend. If the price is above the trend line, it indicates a bullish trend. Conversely, if the price is below the trend line, it indicates a bearish trend.
Dynamic Support and Resistance
The upper and lower bands (including the trend line) dynamically change with market volatility, acting as moving targets of support and resistance. This helps set up stop-loss or take-profit levels with a higher degree of accuracy.
Breakout vs. Reversion Strategies
Price movements beyond the bands could signify strong trends, making it ideal for breakout strategies.
Fakeouts
If the price touches one of the bands and reverses direction, it could be a fakeout. Traders may choose to trade against the breakout in such scenarios.
█ Settings
Volatility Period: Defines the look-back period for calculating volatility. Higher values adapt the bands more slowly, whereas lower values adapt them more quickly.
Trend Factor: Adjusts the sensitivity of the trend line. Higher values produce a smoother line, while lower values make it more reactive to price changes.
Trend Step: Controls the pace at which the trend line adjusts to sudden price movements. Higher values lead to a slower adjustment and a smoother line, while lower values result in quicker adjustments.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Williams %R with EMA'sThe provided Pine Script code presents a comprehensive technical trading strategy on the TradingView platform, incorporating the Williams %R indicator, exponential moving averages (EMAs), and upper bands for enhanced decision-making. This strategy aims to help traders identify potential buy and sell signals based on various technical indicators, thereby facilitating more informed trading decisions.
The key components of this strategy are as follows:
**Williams %R Indicator:** The Williams %R, also known as the "Willy," is a momentum oscillator that measures overbought and oversold conditions. In this code, the Williams %R is calculated with a user-defined period (default 21) and smoothed using an exponential moving average (EMA).
**Exponential Moving Averages (EMAs):** Two EMAs are computed on the Williams %R values. The "Fast" EMA (default 8) responds quickly to price changes, while the "Slow" EMA (default 21) provides a smoother trend-following signal. Crossovers and divergences between these EMAs can indicate potential buy or sell opportunities.
**Candle Color Detection:** The code also tracks the color of candlesticks, distinguishing between green (bullish) and red (bearish) candles. This information is used in conjunction with other indicators to identify specific trading conditions.
**Additional Upper Bands:** The script introduces upper bands at various levels (-5, -10, -20, -25) to create zones for potential buy and sell signals. These bands are visually represented on the chart and can help traders gauge the strength of a trend.
**Alert Conditions:** The code includes several alert conditions that trigger notifications when specific events occur, such as %R crossing certain levels, candle color changes within predefined upper bands, and EMA crossovers.
**Background Highlighting:** The upper bands and the zero line are visually highlighted with different colors, making it easier for traders to identify critical price levels.
This code is valuable for traders seeking a versatile technical strategy that combines multiple indicators to improve trading decisions. By incorporating the Williams %R, EMAs, candlestick analysis, and upper bands, it offers a holistic approach to technical analysis. Traders can customize the parameters to align with their trading preferences and risk tolerance. The use of alerts ensures that traders are promptly notified of potential trade setups, allowing for timely execution and risk management. Overall, this code serves as a valuable tool for traders looking to make more informed decisions in the dynamic world of financial markets.
VIX Implied MovesKey Features:
Three Timeframe Bands:
Daily: Blue bands showing ±1σ expected move
Weekly: Green bands showing ±1σ expected move
30-Day: Red bands showing ±1σ expected move
Calculation Methodology:
Uses VIX's annualized volatility converted to specific timeframes using square root of time rule
Trading day convention (252 days/year)
Band width = Price × (VIX/100) ÷ √(number of periods)
Visual Features:
Colored semi-transparent backgrounds between bands
Progressive line thickness (thinner for shorter timeframes)
Real-time updates as VIX and ES prices change
Example Calculation (VIX=20, ES=5000):
Daily move = 5000 × (20/100)/√252 ≈ ±63 points
Weekly move = 5000 × (20/100)/√50 ≈ ±141 points
Monthly move = 5000 × (20/100)/√21 ≈ ±218 points
This indicator helps visualize expected price ranges based on current volatility conditions, with wider bands indicating higher market uncertainty. The probabilistic ranges represent 68% confidence levels (1 standard deviation) derived from options pricing.
Fib BB on VWMA*ATRThis TradingView Pine Script is designed to plot Fibonacci Bollinger Bands on a Volume Weighted Moving Average (VWMA) using the Average True Range (ATR). The script takes a higher timeframe (HTF) approach, allowing traders to analyze price action and volatility from a broader market perspective.
🔹 How It Works
Higher Timeframe Data Integration
Users can select a specific timeframe to calculate the VWMA and ATR.
This allows for a more macro perspective, avoiding the noise of lower timeframes.
Volume Weighted Moving Average (VWMA)
Unlike the Simple Moving Average (SMA), VWMA gives higher weight to price movements with larger volume.
Calculation Formula:
𝑉𝑊𝑀𝐴=∑(𝐶𝑙𝑜𝑠𝑒×𝑉𝑜𝑙𝑢𝑚𝑒) / ∑𝑉𝑜𝑙𝑢𝑚𝑒
Since VWMA accounts for volume, it is more reactive to price zones with high buying or selling activity, making it useful for identifying liquidity zones.
ATR-Based Fibonacci Bollinger Bands
The Average True Range (ATR) is used to measure market volatility.
Instead of standard deviation-based Bollinger Bands, Fibonacci multipliers (2.618, 3.0, 3.414) are applied to ATR.
These bands adjust dynamically with market volatility.
🔹 Key Findings from Exploration
Through testing and analysis, this indicator seems to effectively detect supply and demand zones, particularly at the Fibonacci levels of 2.618 to 3.414.
Price frequently reacts at these bands, indicating that they capture key liquidity zones.
Potential Order Block Detection:
The ends of the Fibonacci Bollinger Bands (especially at 2.618, 3.0, and 3.414) tend to align with order blocks—areas where institutional traders previously accumulated or distributed positions.
This is particularly useful for order flow traders who focus on unfilled institutional orders.
🔹 How to Use This Indicator?
Identifying Order Blocks
When price reaches the upper or lower bands, check if there was a strong reaction (rejection or consolidation).
If price rapidly moves away from a band, that level might be an order block.
Spotting Liquidity Pools
VWMA’s nature enhances liquidity detection since it emphasizes high-volume price action.
If a price level repeatedly touches the band without breaking through, it suggests institutional orders may be absorbing liquidity there.
Trend Confirmation
If VWMA is trending upwards and price keeps rejecting the lower bands, it confirms a strong bullish trend.
Conversely, constant rejection from the upper bands suggests a bearish market.
This script is designed for open-source publication and offers traders a refined approach to detecting order blocks and liquidity zones using Fibonacci-based volatility bands.
📌 한글 설명 (상세 설명)
이 트레이딩뷰 파인스크립트는 거래량 가중 이동평균(VWMA)과 평균 실제 범위(ATR)를 활용하여 피보나치 볼린저 밴드를 표시하는 지표입니다.
또한, 고차 타임프레임(HTF) 데이터를 활용하여 시장의 큰 흐름을 분석할 수 있도록 설계되었습니다.
🔹 지표 작동 방식
고차 타임프레임(HTF) 데이터 적용
사용자가 원하는 타임프레임을 선택하여 VWMA와 ATR을 계산할 수 있습니다.
이를 통해 더 큰 시장 흐름을 분석할 수 있으며, 저타임프레임의 노이즈를 줄일 수 있습니다.
거래량 가중 이동평균(VWMA) 적용
VWMA는 단순 이동평균(SMA)보다 거래량이 많은 가격 움직임에 더 큰 가중치를 부여합니다.
계산 공식:
𝑉𝑊𝑀𝐴=∑(𝐶𝑙𝑜𝑠𝑒×𝑉𝑜𝑙𝑢𝑚𝑒) / ∑𝑉𝑜𝑙𝑢𝑚𝑒
거래량이 많이 발생한 가격 구간을 강조하는 특성이 있어, 시장의 유동성 구간을 더 정확히 포착할 수 있습니다.
ATR 기반 피보나치 볼린저 밴드 생성
ATR(Average True Range)를 활용하여 변동성을 측정합니다.
기존의 표준편차 기반 볼린저 밴드 대신, 피보나치 계수(2.618, 3.0, 3.414)를 ATR에 곱하여 밴드를 생성합니다.
이 밴드는 시장 변동성에 따라 유동적으로 조정됩니다.
🔹 탐구 결과: 매물대 및 오더블록 감지
테스트를 통해 Fibonacci 2.618 ~ 3.414 구간에서 매물대 및 오더블록을 포착하는 경향이 있음을 확인했습니다.
가격이 피보나치 밴드(특히 2.618, 3.0, 3.414)에 닿을 때 반응하는 경우가 많음
VWMA의 특성을 통해 오더블록을 감지할 가능성이 높음
🔹 오더블록(Order Block) 감지 원리
Fibonacci 밴드 끄트머리(2.618 ~ 3.414)에서 가격이 강하게 반응
이 영역에서 가격이 강하게 튀어 오르거나(매수 압력) 급락하는(매도 압력) 경우,
→ 기관들이 포지션을 청산하거나 추가 매집하는 구간일 가능성이 큼.
과거에 대량 주문이 체결된 가격 구간(= 오더블록)일 수 있음.
VWMA를 통한 유동성 감지
VWMA는 거래량이 집중된 가격을 기준으로 이동하기 때문에, 기관 주문이 많이 들어온 가격대를 강조하는 특징이 있음.
따라서 VWMA와 피보나치 밴드가 만나는 지점은 유동성이 높은 핵심 구간이 될 가능성이 큼.
매물대 및 청산 구간 분석
가격이 밴드에 도달했을 때 강한 반등이 나오는지를 확인 → 오더블록 가능성
가격이 밴드를 여러 번 테스트하면서 돌파하지 못한다면, 해당 지점은 강한 매물대일 가능성
🔹 활용 방법
✅ 오더블록 감지:
가격이 밴드(2.618~3.414)에 닿고 강하게 튕긴다면, 오더블록 가능성
해당 지점에서 거래량 증가 및 강한 반등 발생 시 매수 고려
✅ 유동성 풀 확인:
VWMA와 피보나치 밴드가 만나는 구간에서 반복적으로 거래량이 터진다면, 해당 지점은 기관 유동성 구간일 가능성
✅ 추세 확인:
VWMA가 상승하고 가격이 밴드 하단(지지선)에서 튕긴다면 강한 상승 추세
VWMA가 하락하고 가격이 밴드 상단(저항선)에서 거부당하면 하락 추세 지속
Elastic Volume-Weighted Student-T TensionOverview
The Elastic Volume-Weighted Student-T Tension Bands indicator dynamically adapts to market conditions using an advanced statistical model based on the Student-T distribution. Unlike traditional Bollinger Bands or Keltner Channels, this indicator leverages elastic volume-weighted averaging to compute real-time dispersion and location parameters, making it highly responsive to volatility changes while maintaining robustness against price fluctuations.
This methodology is inspired by incremental calculation techniques for weighted mean and variance, as outlined in the paper by Tony Finch:
📄 "Incremental Calculation of Weighted Mean and Variance" .
Key Features
✅ Adaptive Volatility Estimation – Uses an exponentially weighted Student-T model to dynamically adjust band width.
✅ Volume-Weighted Mean & Dispersion – Incorporates real-time volume weighting, ensuring a more accurate representation of market sentiment.
✅ High-Timeframe Volume Normalization – Provides an option to smooth volume impact by referencing a higher timeframe’s cumulative volume, reducing noise from high-variability bars.
✅ Customizable Tension Parameters – Configurable standard deviation multipliers (σ) allow for fine-tuned volatility sensitivity.
✅ %B-Like Oscillator for Relative Price Positioning – The main indicator is in form of a dedicated oscillator pane that normalizes price position within the sigma ranges, helping identify overbought/oversold conditions and potential momentum shifts.
✅ Robust Statistical Foundation – Utilizes kurtosis-based degree-of-freedom estimation, enhancing responsiveness across different market conditions.
How It Works
Volume-Weighted Elastic Mean (eμ) – Computes a dynamic mean price using an elastic weighted moving average approach, influenced by trade volume, if not volume detected in series, study takes true range as replacement.
Dispersion (eσ) via Student-T Distribution – Instead of assuming a fixed normal distribution, the bands adapt to heavy-tailed distributions using kurtosis-driven degrees of freedom.
Incremental Calculation of Variance – The indicator applies Tony Finch’s incremental method for computing weighted variance instead of arithmetic sum's of fixed bar window or arrays, improving efficiency and numerical stability.
Tension Calculation – There are 2 dispersion custom "zones" that are computed based on the weighted mean and dynamically adjusted standard student-t deviation.
%B-Like Oscillator Calculation – The oscillator normalizes the price within the band structure, with values between 0 and 1:
* 0.00 → Price is at the lower band (-2σ).
* 0.50 → Price is at the volume-weighted mean (eμ).
* 1.00 → Price is at the upper band (+2σ).
* Readings above 1.00 or below 0.00 suggest extreme movements or possible breakouts.
Recommended Usage
For scalping in lower timeframes, it is recommended to use the fixed α Decay Factor, it is in raw format for better control, but you can easily make a like of transformation to N-bar size window like in EMA-1 bar dividing 2 / decayFactor or like an RMA dividing 1 / decayFactor.
The HTF selector catch quite well Higher Time Frame analysis, for example using a Daily chart and using as HTF the 200-day timeframe, weekly or monthly.
Suitable for trend confirmation, breakout detection, and mean reversion plays.
The %B-like oscillator helps gauge momentum strength and detect divergences in price action if user prefer a clean chart without bands, this thanks to pineScript v6 force overlay feature.
Ideal for markets with volume-driven momentum shifts (e.g., futures, forex, crypto).
Customization Parameters
Fixed α Decay Factor – Controls the rate of volume weighting influence for an approximation EWMA approach instead of using sum of series or arrays, making the code lightweight & computing fast O(1).
HTF Volume Smoothing – Instead of a fixed denominator for computing α , a volume sum of the last 2 higher timeframe closed candles are used as denominator for our α weight factor. This is useful to review mayor trends like in daily, weekly, monthly.
Tension Multipliers (±σ) – Adjusts sensitivity to dispersion sigma parameter (volatility).
Oscillator Zone Fills – Visual cues for price positioning within the cloud range.
Posible Interpretations
As market within indicators relay on each individual edge, this are just some key ideas to glimpse how the indicator could be interpreted by the user:
📌 Price inside bands – Market is considered somehow "stable"; price is like resting from tension or "charging batteries" for volume spike moves.
📌 Price breaking outer bands – Potential breakout or extreme movement; watch for reversals or continuation from strong moves. Market is already in tension or generating it.
📌 Narrowing Bands – Decreasing volatility; expect contraction before expansion.
📌 Widening Bands – Increased volatility; prepare for high probability pull-back moves, specially to the center location of the bands (the mean) or the other side of them.
📌 Oscillator is just the interpretation of the price normalized across the Student-T distribution fitting "curve" using the location parameter, our Elastic Volume weighted mean (eμ) fixed at 0.5 value.
Final Thoughts
The Elastic Volume-Weighted Student-T Tension indicator provides a powerful, volume-sensitive alternative to traditional volatility bands. By integrating real-time volume analysis with an adaptive statistical model, incremental variance computation, in a relative price oscillator that can be overlayed in the chart as bands, it offers traders an edge in identifying momentum shifts, trend strength, and breakout potential. Think of the distribution as a relative "tension" rubber band in which price never leave so far alone.
DISCLAIMER:
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The following indicator was made for NON LUCRATIVE ACTIVITIES and must remain as is, following TradingView's regulations. Use of indicator and their code are published for work and knowledge sharing. All access granted over it, their use, copy or re-use should mention authorship(s) and origin(s).
WARNING NOTICE!
THE INCLUDED FUNCTION MUST BE CONSIDERED FOR TESTING. The models included in the indicator have been taken from open sources on the web and some of them has been modified by the author, problems could occur at diverse data sceneries, compiler version, or any other externality.
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Bollinger Breakout Strategy with Direction Control [4H crypto]Bollinger Breakout Strategy with Direction Control - User Guide
This strategy leverages Bollinger Bands, RSI, and directional filters to identify potential breakout trading opportunities. It is designed for traders looking to capitalize on significant price movements while maintaining control over trade direction (long, short, or both). Here’s how to use this strategy effectively:
How the Strategy Works
Indicators Used:
Bollinger Bands:
A volatility-based indicator with an upper and lower band around a simple moving average (SMA). The bands expand or contract based on market volatility.
RSI (Relative Strength Index):
Measures momentum to determine overbought or oversold conditions. In this strategy, RSI is used to confirm breakout strength.
Trade Direction Control:
You can select whether to trade:
Long only: Buy positions.
Short only: Sell positions.
Both: Trade in both directions depending on conditions.
Breakout Conditions:
Long Trade:
The price closes above the upper Bollinger Band.
RSI is above the midline (50), confirming upward momentum.
The "Trade Direction" setting allows either "Long" or "Both."
Short Trade:
The price closes below the lower Bollinger Band.
RSI is below the midline (50), confirming downward momentum.
The "Trade Direction" setting allows either "Short" or "Both."
Risk Management:
Stop-Loss:
Long trades: Set at 2% below the entry price.
Short trades: Set at 2% above the entry price.
Take-Profit:
Calculated using a Risk/Reward Ratio (default is 2:1).
Adjust this in the strategy settings.
Inputs and Customization
Key Parameters:
Bollinger Bands Length: Default is 20. Adjust based on the desired sensitivity.
Multiplier: Default is 2.0. Higher values widen the bands; lower values narrow them.
RSI Length: Default is 14, which is standard for RSI.
Risk/Reward Ratio: Default is 2.0. Increase for more aggressive profit targets, decrease for conservative exits.
Trade Direction:
Options: "Long," "Short," or "Both."
Example: Set to "Long" in a bullish market to focus only on buy trades.
How to Use This Strategy
Adding the Strategy:
Paste the script into TradingView’s Pine Editor and add it to your chart.
Setting Parameters:
Adjust the Bollinger Band settings, RSI, and Risk/Reward Ratio to fit the asset and timeframe you're trading.
Analyzing Signals:
Green line (Upper Band): Signals breakout potential for long trades.
Red line (Lower Band): Signals breakout potential for short trades.
Blue line (Basis): Central Bollinger Band (SMA), helpful for understanding price trends.
Testing the Strategy:
Use the Strategy Tester in TradingView to backtest performance on your chosen asset and timeframe.
Optimizing for Assets:
Forex pairs, cryptocurrencies (like BTC), or stocks with high volatility are ideal for this strategy.
Works best on higher timeframes like 4H or Daily.
Best Practices
Combine with Volume: Confirm breakouts with increased volume for higher reliability.
Avoid Sideways Markets: Use additional trend filters (like ADX) to avoid trades in low-volatility conditions.
Optimize Parameters: Regularly adjust the Bollinger Bands multiplier and RSI settings to match the asset's behavior.
By utilizing this strategy, you can effectively trade breakouts while maintaining flexibility in trade direction. Adjust the parameters to match your trading style and market conditions for optimal results!
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.
IMI and MFI CombinedFor a strategy using the combined IMI (Intraday Momentum Index), MFI (Money Flow Index), and Bollinger Bands on a 1-minute chart of Bank NIFTY (Bank Nifty Index), here's how you can interpret the indicators and define a sell signal strategy:
Strategy Explanation:
IMI (Intraday Momentum Index):
IMI measures the ratio of upward price changes to downward price changes over a specified period, indicating momentum.
In the script, IMI is plotted with a range from 0 to 100. Levels above 75 are considered overbought, and levels below 25 are oversold.
Strategy Condition: A sell signal can be considered when IMI is above 75, indicating a potentially overbought market condition.
MFI (Money Flow Index):
MFI measures the strength of money flowing in and out of a security, using price and volume.
In the script, MFI is plotted with levels at 80 (overbought) and 20 (oversold).
Strategy Condition: A sell signal can be considered when MFI is above 80, suggesting an overbought condition in the market.
Bollinger Bands:
Bollinger Bands consist of a middle band (SMA) and upper/lower bands representing volatility levels around the price.
In the script, Bollinger Bands are plotted with a length of 20 and a standard deviation multiplier of 2.
Strategy Condition: While not explicitly used for generating sell signals in this script, Bollinger Bands can help confirm price volatility and potential reversals when combined with other indicators.
Sell Signal Criteria:
IMI Sell Signal: Look for instances where IMI rises above 75. This indicates that the recent upward price momentum may be reaching an unsustainable level, potentially signaling a reversal or a pullback in prices.
MFI Sell Signal: Look for MFI rising above 80. This suggests that the market has experienced strong buying pressure, possibly leading to an overbought condition where a price correction or reversal might occur.
Implementation Considerations:
Confirmation: Consider waiting for both IMI and MFI to confirm the overbought condition simultaneously before entering a sell trade. This can increase the reliability of the signal.
Risk Management: Use stop-loss orders to manage risk in case the market moves against the anticipated direction after the sell signal is triggered.
Timeframe: This strategy is tailored for a 1-minute chart, meaning signals should be interpreted and acted upon quickly due to the rapid nature of price movements in intraday trading.
By combining these indicators and interpreting their signals, you can develop a systematic approach to identifying potential sell opportunities in the Bank NIFTY index on a 1-minute timeframe. Adjustments to indicator parameters and additional technical analysis may further refine the strategy based on your trading preferences and risk tolerance.
[blackcat] L1 Zero-Lag EMA BandThe Zero-Lag EMA Band is a sophisticated technical analysis tool designed to provide traders with a comprehensive view of market trends. This innovative indicator merges the Zero-Lag EMA, a derivative of the traditional Exponential Moving Average, with Bollinger Bands to create a unique trend indicator that is less laggy and more responsive to market changes.
The Zero-Lag EMA Band is calculated by taking the standard deviation of the price data and adding or subtracting it from the Zero-Lag EMA to create an upper band and a lower band. This process results in a trend band that can help traders identify potential support and resistance levels, providing them with a more accurate assessment of the market's behavior.
The Zero-Lag EMA Band is particularly useful for traders who need to react quickly to market changes. It offers a more timely assessment of potential trend reversals, allowing traders to capitalize on market opportunities and mitigate risk.
The indicator's design is based on the principle of Zero-Lag, which aims to reduce the lag associated with traditional EMAs. This feature makes the Zero-Lag EMA Band a powerful tool for traders who want to stay ahead of the market and make more informed decisions.
In summary, the Zero-Lag EMA Band is a comprehensive and responsive tool for traders looking to identify and capitalize on market trends. It is a valuable addition to any trader's toolkit, offering a more accurate and timely assessment of potential trend reversals and providing a more comprehensive view of the market's behavior.
Certainly! Let's go through the Pine Script code line by line to understand its functionality:
//@version=5
This line specifies the version of Pine Script being used. In this case, it's version 5.
indicator(' L1 Zero-Lag EMA Band', shorttitle='L1 ZLEMA Band', overlay=true)
This line defines the indicator with a title and a short title. The `overlay=true` parameter means that the indicator will be plotted on top of the price data.
length = input.int(21, minval=1, title='Length')
This line creates an input field for the user to specify the length of the EMA. The default value is 21, and the minimum value is 1.
mult = input(1, title='Multiplier')
This line creates an input field for the user to specify the multiplier for the standard deviation, which is used to calculate the bands around the EMA. The default value is 1.
src = input.source(close, title="Source")
This line creates an input field for the user to specify the data source for the EMA calculation. The default value is the closing price of the asset.
// Define the smoothing factor (alpha) for the EMA
alpha = 2 / (length + 1)
This line calculates the smoothing factor alpha for the EMA. It's a common formula for EMA calculation.
// Initialize a variable to store the previous EMA value
var float prevEMA = na
This line initializes a variable to store the previous EMA value. It's initialized as `na` (not a number), which means it's not yet initialized.
// Calculate the zero-lag EMA
emaValue = na(prevEMA) ? ta.sma(src, length) : (src - prevEMA) * alpha + prevEMA
This line calculates the zero-lag EMA. If `prevEMA` is not a number (which means it's the first calculation), it uses the simple moving average (SMA) as the initial EMA. Otherwise, it uses the standard EMA formula.
// Update the previous EMA value
prevEMA := emaValue
This line updates the `prevEMA` variable with the newly calculated EMA value. The `:=` operator is used to update the variable in Pine Script.
// Calculate the upper and lower bands
dev = mult * ta.stdev(src, length)
upperBand = emaValue + dev
lowerBand = emaValue - dev
These lines calculate the upper and lower bands around the EMA. The bands are calculated by adding and subtracting the product of the multiplier and the standard deviation of the source data over the specified length.
// Plot the bands
p0 = plot(emaValue, color=color.new(color.yellow, 0))
p1 = plot(upperBand, color=color.new(color.yellow, 0))
p2 = plot(lowerBand, color=color.new(color.yellow, 0))
fill(p1, p2, color=color.new(color.fuchsia, 80))
These lines plot the EMA value, upper band, and lower band on the chart. The `fill` function is used to color the area between the upper and lower bands. The `color.new` function is used to create a new color with a specified alpha value (transparency).
In summary, this script creates an indicator that displays the zero-lag EMA and its bands on a trading chart. The user can specify the length of the EMA and the multiplier for the standard deviation. The bands are used to identify potential support and resistance levels for the asset's price.
In the context of the provided Pine Script code, `prevEMA` is a variable used to store the previous value of the Exponential Moving Average (EMA). The EMA is a type of moving average that places a greater weight on the most recent data points. Unlike a simple moving average (SMA), which is an equal-weighted average, the EMA gives more weight to the most recent data points, which can help to smooth out short-term price fluctuations and highlight the long-term trend.
The `prevEMA` variable is used to calculate the current EMA value. When the script runs for the first time, `prevEMA` will be `na` (not a number), indicating that there is no previous EMA value to use in the calculation. In such cases, the script falls back to using the simple moving average (SMA) as the initial EMA value.
Here's a breakdown of the role of `prevEMA`:
1. **Initialization**: On the first bar, `prevEMA` is `na`, so the script uses the SMA of the close price over the specified period as the initial EMA value.
2. **Calculation**: On subsequent bars, `prevEMA` holds the value of the EMA from the previous bar. This value is used in the EMA calculation to give more weight to the most recent data points.
3. **Update**: After calculating the current EMA value, `prevEMA` is updated with the new EMA value so it can be used in the next bar's calculation.
The purpose of `prevEMA` is to maintain the state of the EMA across different bars, ensuring that the EMA calculation is not reset to the SMA on each new bar. This is crucial for the EMA to function properly and to avoid the "lag" that can sometimes be associated with moving averages, especially when the length of the moving average is short.
In the provided script, `prevEMA` is used to simulate a zero-lag EMA, but as mentioned earlier, there is no such thing as a zero-lag EMA in the traditional sense. The EMA already has a very minimal lag due to its recursive nature, and any attempt to reduce the lag further would likely not be accurate or reliable for trading purposes.
Please note that the script provided is a conceptual example and may not be suitable for actual trading without further testing and validation.
MESThe Double Bollinger Bands strategy is a trend-following strategy that aims to identify high-probability trading opportunities in trending markets. The strategy involves using two sets of Bollinger Bands with different standard deviation values to identify potential entry and exit points.
Bollinger Bands are a technical analysis tool that consists of three lines plotted on a price chart: a simple moving average (SMA) in the middle, and an upper and lower band that are each a certain number of standard deviations away from the SMA. The standard deviation value determines the width of the bands, with a larger deviation resulting in wider bands.
In this indicator, the first set of Bollinger Bands is calculated using a length of 20 bars and a standard deviation of 2, while the second set uses a length of 20 bars and a standard deviation of 3. The bands are plotted on the price chart along with the SMA for each set.
The buy signal is generated when the price falls below the lower band of the second set of Bollinger Bands (the 3-standard deviation band) and then rises above the lower band of the first set (the 2-standard deviation band). This is interpreted as a potential reversal point in a downtrend and a signal to enter a long position.
Conversely, the sell signal is generated when the price rises above the upper band of the second set of Bollinger Bands and then falls below the upper band of the first set. This is interpreted as a potential reversal point in an uptrend and a signal to enter a short position.
To make it easier to identify buy and sell signals on the price chart, the indicator plots triangles above the bars for sell signals and below the bars for buy signals.
Overall, the Double Bollinger Bands strategy can be a useful tool for traders who want to follow trends and identify potential entry and exit points. However, as with any trading strategy, it is important to backtest and thoroughly evaluate its performance before using it in live trading.
Band-Zigzag Based Trend FollowerWe defined new method to derive zigzag last month - which is called Channel-Based-Zigzag . This script is an example of one of the use case of this method.
🎲 Trend Following
Defining a trend following method is simple. Basic rule of trend following is Buy High and Sell Low (Yes, you heard it right). To explain further - methodology involve finding an established trend which is flying high and join the trend with proper risk and optimal stop. Once you get into the trade, you will not exit unless there is change in the trend. Or in other words, the parameters which you used to define trend has reversed and the trend is not valid anymore.
Few examples are:
🎯 Using bands
When price breaks out of upper bands (example, Bollinger Band, Keltener Channel, or Donchian Channel), with a pre determined length and multiplier, we can consider the trend to be bullish and similarly when price breaks down the lower band, we can consider the trend to be bearish.
Here are few examples where I have used bands for identifying trend
Band-Based-Supertrend
Donchian-Channel-Trend-Filter
🎯 Using Pivots
Simple logic using zigzag or pivot points is that when price starts making higher highs and higher lows, we can consider this as uptrend. And when price starts making lower highs and lower lows, we can consider this as downtrend. There are few supertrend implementations I have published in the past based on zigzags and pivot points.
Adoptive-Supertrend-Pivots
Zigzag-Supertrend
Drawbacks of both of these methods is that there will be too many fluctuations in both cases unless we increase the reference length. And if we increase the reference length, we will have higher drawdown.
🎲 Band Based Zigzag Method
Band Based Zigzag will help overcome these issues by combining both the methods.
Here we use bands to define our pivot high and pivot low - this makes sure that we are identifying trend only on breakouts as pivots are only formed on breakouts.
Our method also includes pivot ratio to cross over 1.0 to be able to consider it as trend. This means, we are waiting for price also to make new high high or lower low before making the decision on trend. But, this helps us ignore smaller pivot movements due to the usage of bands.
I have also implemented few tricks such as sticky bands (Bands will not contract unless there is breakout) and Adaptive Bands (Band will not expand unless price is moving in the direction of band). This makes the trend following method very robust.
To avoid fakeouts, we also use percentB of high/low in comparison with price retracement to define breakout.
🎲 The indicator
The output of indicator is simple and intuitive to understand.
🎯 Trend Criteria
Uptrend when last confirmed pivot is pivot high and has higher retracement ratio than PercentB of High. Else, considered as downtrend.
Downtrend when last confirmed pivot is pivot low and has higher retracement ratio than PercentB of High. Else, considered as uptrend.
🎯 Settings
Settings allow you to select the band type and parameters used for calculating zigzag and then trend. Also has few options to hide the display.
Cryptogrithm's Secret Momentum and Volatility IndicatorThis indicator is hard-coded for Bitcoin, but you may try it on other asset classes/coins. I have not updated this indicator in over 3 years, but it seems to still work very well for Bitcoin.
This indicator is NOT for beginners and is directed towards intermediate/advanced traders with a sensibility to agree/disagree with what this indicator is signalling (common sense).
This indicator was developed back in 2018 and I has not been maintained since, which is the reason why I am releasing it. (It still works great though! At the time of this writing of May 2022).
How to use:
Terms:
PA (Price Action): Literally the candlestick formations on your chart (and the trend formation). If you don't know how to read and understand price action, I will make a fast-track video/guide on this later (but in the meanwhile, you need to begin by learning Order-Flow Analysis, please google it first before asking).
CG Level (Cryptogrithm Level/Yellow Line): PA level above = bullish, PA level below = bearish
CG Bands (Cryptogrithm Bands): This is similar to how bollingers work, you can use this the same was as bollinger bands. The only difference is that the CG bands are more strict with the upper and lower levels as it uses different calculations to hug the price tighter allowing it to be more reactive to drastic price changes (earlier signals for oversold/overbought).
CG Upper Band (Red Upper Line): Above this upper bound line means overbought.
CG Middle Band (Light Blue Line): If PA trades above this line, the current PA trend is bullish continuing in the uptrend. If PA trades below this line, the current PA trend is bearish continuing in the downtrend. This band should only be used for short-term trends.
CG Lower Band (Green Lower Line): Below this lower bound line means oversold.
What the CG Level (yellow line) tells you:
PA is trading above CG Level = Bullish
PA is trading below CG Level = Bearish
Distance between CG Level and price = Momentum
What this means is that the further away the price is from the CG Level, the greater the momentum of the current PA trend. An increasing gap between the CG Level and PA indicates the price's strength (momentum) towards the current upward/downward trend. Basically when the PA and CG Level diverge, it means that the momentum is increasing in the current trend and when they converge, the current trend is losing momentum and the direction of the PA trend may flip towards the other direction (momentum flip).
PA+CG Level Momentum:
To use the CG Level as a momentum indicator, you need to pay attention to how the price and the CG level are moving away/closer from each other:
PA + CG Level Diverges = Momentum Increasing
PA + CG Level Converges = Momentum Decreasing
Examples (kind of common sense, but just for clarity):
Case 1: Bullish Divergence (Bullish): The PA is ABOVE and trending AWAY above from the CG Level = very bullish, this means that momentum is increasing towards the upside and larger moves will come (increasing gap between the price and CG Level)
Case 2: Bearish Convergence (Bearish): - The PA is ABOVE the CG Level and trending TOWARDS the CG Level = bearish, there is a possibility that the upward trend is ending. Look to start closing off long positions until case 1 (divergence) occurs again.
Case 3: Neutral - The PA is trading on the CG Level (no clear divergence or convergence between the PA and CG Level) = Indicates a back and forth (tug of war) between bears and bulls. Beware of choppy price patterns as the trend is undecisive until either supply/liquidity is dried out and a winner between bull/bear is chosen. This is a no trade zone, but do as you wish.
Case 4: Bearish Divergence (Bearish): The PA is BELOW and trending AWAY BELOW from the CG Level = very bearish, this means that momentum is increasing towards the downside and larger downward moves will come (increasing gap between the price and CG Level).
Case 5: Bullish Convergence (Bullish): - The PA is BELOW the CG Level and trending TOWARDS the CG Level = bullish, there is a possibility that the downward trend is ending and a trend flip is occuring. Look to start closing off short positions until case 4 (divergence) occurs again.
CG Bands + CG Level: You can use the CG bands instead of the PA candles to get a cleaner interpretation of reading the momentum. I won't go into detail as this is pretty self-explanatory. It is the same explanation as PA+CG Level Momentum, but you are replacing the PA candles with the CG Bands for interpretation. So instead of the PA converging/diverging from the CG Level, the Upper and Lower Bound levels are converging/diverging from the CG level instead.
Convergence: CG Level (yellow line) trades inside the CG bands
Divergence: CG Level (yellow line) trades outside the CG bands
Bullish/Bearish depends on whether the CG Band is trading below or above the CG level. If CG Band is above the CG Level, this is bullish. If CG Band is below the CG level, this is bearish.
Crosses (PA or CG Band crosses with CG level): This typically indicates volatility is incoming.
There are MANY MANY MANY other ways to use this indicator that is not explained here and even other undiscovered methods. Use some common sense as to how this indicator works (it is a momentum indicator and volatility predictor). You can get pretty creative and apply your own methods / knowledge to it and look for patterns that occur. Feel free to comment and share what you came up with!
[CBB] Volatility Squeeze ToyThe main concept and features of this script are adapted from Mark Whistler's book "Volatility Illuminated". I have deviated from the use cases and strategies presented in the book, but the 3 Bollinger Bands use his optimized settings as the default length and standard deviation multiplier. Further insights into Mark's concepts and volatility research were gained by reading and watching some of TV user DadShark's materials (www.tradingview.com).
This script has been through many refinements and feature cycles, and I've added unrelated complimentary features not present in the book. The indicator is better studied than described, and unless you have read the book, any short summary of the material will just make you squint and think about the wrong things.
Here is a limited outline of features and concepts:
1. 3 Bollinger Bands of different length and/or deviation multiplier. Perhaps think of them as representing the various time frames that compression and expansion cycles and events manifest in, and also the expression of range, speed and price distribution within those time frames. You can gain insight into the magnitude of events based on how the three bands interact and stay contained, or not. If volatility is significant enough, all "time frames" represented by the bands will eventually record the event and subsequent price action, but the early signals will come from the spasms of the shortest, most volatile band. Many times the short band will contract again before, or just as it reaches a longer band, but in extreme cases, volatility will explode and all bands at all time frames will erupt in succession. In these cases you will see additional color representing shorter bands (lower time frame volatility in concept) traveling outside of longer bands. It is worth taking a look at the price levels and candles where these volatility bands cross each other.
2. In addition to the mean of the bands, there are a variety of other moving averages available to gauge trend, range, and areas of interest. This is accomplished with variable VWAP, ATR, smoothing, and a special derived loosely from the difference between them.
3. The bands are also used to derive conditions under which volatility is considered compressed, or in "squeeze" . Under these conditions the candles will turn yellow. Depending on your chart settings and indicator settings, these zones can be completely useless or drag on through fairly significant price action. Or, the can give you fantastic levels to watch for breakouts. The point is that volatility is compressed during these conditions, and you should expect the inevitable once this condition ends. Sometimes you can find yourself in a nice fat trend straight away, other times you may blow an account because you gorged your position based on arbitrary bar color. It's not like that. Pay attention to the highest and lowest bars of these squeeze ranges, and carefully observe future price action when it returns to these squeeze ranges. This info is more and more valuable at higher time frames.
The 3 bands, a smoothed long trend VWAP, and the squeeze condition colored bars are all active by default. All features can be shown or hidden on the control panel.
There are some deep market insights to mine if you live with this one for a while. As with any indicator, blunt "buy/sell here" approaches will lead to loss and frustration. however , if you pay attention to squeeze range, band/moving average confluence, high volume and/or large range candles their open/close behavior around these areas and squeeze ranges, you will start to catch the beginning of some powerful momentum moves.
Enjoy!
OB/OS adaptative v1.1# OB/OS Adaptative v1.1 - Multi-Timeframe Adaptive Overbought/Oversold Indicator
## Overview
The `tradingview_indicator_emas.pine` script is a sophisticated multi-timeframe indicator designed to identify dynamic overbought and oversold levels in financial markets. It combines EMA (Exponential Moving Average) crossovers and Bollinger Bands across monthly, weekly, and daily timeframes to create adaptive support and resistance levels that adjust to changing market conditions.
## Core Functionality
### Multi-Timeframe Analysis
The indicator analyzes three timeframes simultaneously:
- **Monthly (M)**: Long-term trend identification
- **Weekly (W)**: Intermediate-term trend identification
- **Daily (D)**: Short-term volatility measurement
### Technical Indicators Used
- **EMA 9 and EMA 20**: For trend identification and momentum assessment
- **Bollinger Bands (20-period)**: For volatility measurement and extreme level identification
- **Price action**: For confirmation of level validity and signal generation
## Key Features
### Adaptive Level Calculation
The indicator dynamically determines overbought and oversold levels based on market structure and trend bias:
#### Monthly Level Logic
- **Bullish Bias** (when monthly open > EMA20):
- Oversold = lower of EMA9 or EMA20
- Overbought = upper of EMA9 or Bollinger Upper Band
- **Bearish/Neutral Bias** (when monthly open ≤ EMA20):
- Oversold = Bollinger Lower Band
- Overbought = upper of EMA20 or EMA9
#### Weekly Level Logic
- **Bullish Bias** (when weekly open > EMA20):
- Oversold = lower of EMA9 or EMA20
- Overbought = Bollinger Upper Band
- **Bearish/Neutral Bias** (when weekly open ≤ EMA20):
- Oversold = Bollinger Lower Band
- Overbought = upper of EMA20 or EMA9
#### Daily Level Logic
- Simple Bollinger Bands:
- Oversold = Bollinger Lower Band
- Overbought = Bollinger Upper Band
### Final Level Determination
The indicator combines all three timeframes through a weighted averaging process:
1. Calculates initial values as the average of monthly, weekly, and daily levels
2. Ensures mathematical consistency by enforcing overbought_final ≥ oversold_final using min/max functions
3. Calculates a midpoint average level as the center of the range
### Visual Elements
- **Dynamic Lines**: Draws horizontal lines for current and previous period overbought, oversold, and average levels
- **Labels**: Places clear textual labels at the start of each period
- **Color Coding**:
- Red for overbought levels (resistance)
- Green for oversold levels (support)
- Blue for average levels (pivot point)
- **Transparency**: Previous period lines use semi-transparent colors to distinguish between current and historical levels
### Update Mechanism
- **Calculation Day**: User-defined day of the week (default: Monday)
- On the specified calculation day, the indicator:
- Updates all levels based on previous bar's data
- Draws new lines extending forward for a user-defined number of days
- Maintains previous period lines for comparison and trend analysis
- Automatically deletes and recreates lines to ensure clean visualization
### Proximity Detection
- Alerts when price approaches overbought/oversold levels (configurable distance in percentage)
- Helps identify potential reversal zones before actual crossovers occur
- Distance thresholds are user-configurable for both overbought and oversold conditions
### Alert Conditions
The indicator provides four distinct alert types:
1. **Cross below oversold**: Triggered when price crosses below the oversold level
2. **Cross above overbought**: Triggered when price crosses above the overbought level
3. **Near oversold**: Triggered when price approaches the oversold level within the configured distance
4. **Near overbought**: Triggered when price approaches the overbought level within the configured distance
### Debug Mode
When enabled, displays comprehensive debug information including:
- Current values for all levels (oversold, overbought, average)
- Timeframe-specific calculations and raw data points
- System status information (current day, calculation day, etc.)
- Lines existence and timing information
- Organized in multiple labels at different price levels to avoid overlap
## Configuration Parameters
| Parameter | Default Value | Description |
|---------|---------------|-------------|
| Short EMA (9) | 9 | Length for short-term EMA calculation |
| Long EMA (20) | 20 | Length for long-term EMA calculation |
| BB Length | 20 | Period for Bollinger Bands calculation |
| Std Dev | 2.0 | Standard deviation multiplier for Bollinger Bands |
| Distance to overbought (%) | 0.5 | Percentage threshold for "near overbought" alerts |
| Distance to oversold (%) | 0.5 | Percentage threshold for "near oversold" alerts |
| Calculation day | Monday | Day of week when levels are recalculated |
| Lookback days | 7 | Number of days to extend previous period lines backward |
| Forward days | 7 | Number of days to extend current period lines forward |
| Show Debug Labels | false | Toggle for comprehensive debug information display |
## Trading Applications
### Primary Use Cases
1. **Reversal Trading**: Identify potential reversal zones when price approaches overbought/oversold levels
2. **Trend Confirmation**: Use the adaptive nature of levels to confirm trend strength and direction
3. **Position Sizing**: Adjust position size based on distance from key levels
4. **Stop Placement**: Use opposite levels as dynamic stop-loss references
### Strategic Advantages
- **Adaptive Nature**: Levels adjust to changing market volatility and trend structure
- **Multi-Timeframe Confirmation**: Signals are validated across multiple timeframes
- **Visual Clarity**: Clear color-coded lines and labels enhance decision-making
- **Proactive Alerts**: "Near" conditions provide early warnings before crossovers
## Implementation Details
### Data Security
Uses `request.security()` function to fetch data from higher timeframes (monthly, weekly) while maintaining proper bar indexing with ` ` offset for open prices.
### Performance Optimization
- Uses `var` keyword to declare persistent variables that maintain state across bars
- Efficient line and label management with proper deletion before recreation
- Conditional execution of debug code to minimize performance impact
### Error Handling
- Comprehensive NA (not available) checks throughout the code
- Graceful degradation when data is unavailable for higher timeframes
- Mathematical safeguards to prevent invalid level calculations
## Conclusion
The OB/OS Adaptative v1.1 indicator represents a sophisticated approach to identifying market extremes by combining multiple technical analysis concepts. Its adaptive nature makes it particularly useful in trending markets where static levels may be less effective. The multi-timeframe approach provides a comprehensive view of market structure, while the visual elements and alert system enhance its practical utility for active traders.
RSI Games 1.2he "RSI Games 1.2" indicator enhances the standard RSI by adding several layers of analysis:
Standard RSI Calculation: It calculates the RSI based on a configurable length (default 14 periods) and a user-selected source (default close price).
RSI Bands: It plots horizontal lines at 70 (red, overbought), 50 (yellow, neutral), and 30 (green, oversold) to easily identify extreme RSI levels.
RSI Smoothing with Moving Averages (MAs) and Bollinger Bands (BBs):
You can apply various types of moving averages (SMA, EMA, SMMA, WMA, VWMA) to smooth the RSI line.
If you choose "SMA + Bollinger Bands," the indicator will also plot Bollinger Bands around the smoothed RSI, providing dynamic overbought/oversold levels based on volatility.
The RSI line itself changes color based on whether it's above (green) or below (red) its smoothing MA.
It also fills the area between the RSI and its smoothing MA, coloring it green when RSI is above and red when below.
Bollinger Band Signals: When Bollinger Bands are enabled, the indicator marks "Buy" signals (green arrow up) when the RSI crosses above the lower Bollinger Band and "Sell" signals (red arrow down) when it crosses below the upper Bollinger Band.
Background Coloring: The background of the indicator pane changes to light green when RSI is below 30 (oversold) and light red when RSI is above 70 (overbought), visually highlighting extreme conditions.
Divergence Detection: This is a key feature. The indicator automatically identifies and labels:
Regular Bullish Divergence: Price makes a lower low, but RSI makes a higher low. This often signals a potential reversal to the upside.
Regular Bearish Divergence: Price makes a higher high, but RSI makes a lower high. This often signals a potential reversal to the downside.
Hidden Bullish Divergence: Price makes a higher low, but RSI makes a lower low. This can indicate a continuation of an uptrend.
Hidden Bearish Divergence: Price makes a lower high, but RSI makes a higher high. This can indicate a continuation of a downtrend.
Divergences are visually marked with labels and can trigger alerts.
Candle Trend PowerThe Candle Trend Power is a custom technical indicator designed for advanced trend analysis and entry signal generation. It combines multiple smoothing methods, candle transformations, and volatility bands to visually and analytically enhance your trading decisions.
🔧 Main Features:
📉 Custom Candle Types
It transforms standard OHLC candles into one of several advanced types:
Normal Candles, Heikin-Ashi, Linear Regression, Rational Quadratic (via kernel filtering), McGinley Dynamic Candles
These transformations help traders better see trend continuations and reversals by smoothing out market noise.
🧮 Smoothing Method for Candle Data
Each OHLC value can be optionally smoothed using:
EMA, SMA, SMMA (RMA), WMA, VWMA, HMA, Mode (Statistical mode) Or no smoothing at all.
This flexibility is useful for customizing to different market conditions.
📊 Volatility Bands
Volatility-based upper and lower bands are calculated using:
Band = price ± (price% + ATR * multiplier)
They help identify overbought/oversold zones and potential reversal points.
📍 Candle Color Logic
Each candle is colored:
Cyan (#00ffff) if it's bullish and stronger than the previous candle
Red (#fd0000) if it's bearish and weaker
Alternating bar index coloring improves visual clarity.
📈 Trend Momentum Labels
The script includes a trend strength estimation using a smoothed RSI:
If the candle is bullish, it shows a BUY label with the overbought offset.
If bearish, it shows a SELL label with the oversold offset.
These labels are dynamic and placed next to the bar.
📍 Signal Markers
It also plots triangles when the price crosses the volatility bands:
Triangle up for potential long
Triangle down for potential short
✅ Use Case Summary
This script is mainly used for:
Visual trend confirmation with enhanced candles
Volatility-based entry signals
RSI-based trend momentum suggestions
Integrating different smoothing & transformation methods to fine-tune your strategy
It’s a flexible tool for both manual traders and automated system developers who want clear, adaptive signals across different market conditions.
💡 What's Different
🔄 Candle Type Transformations
⚙️ Custom Candle Smoothing
📉 Candle's Multi-level Volatility Bands
🔺 Dynamic Entry Signals (Buy/Sell Labels)
❗Important Note:
This script is provided for educational purposes and does not constitute financial advice. Traders and investors should conduct their research and analysis before making any trading decisions.
True Amplitude Envelopes (TAE)The True Envelopes indicator is an adaptation of the True Amplitude Envelope (TAE) method, based on the research paper " Improved Estimation of the Amplitude Envelope of Time Domain Signals Using True Envelope Cepstral Smoothing " by Caetano and Rodet. This indicator aims to create an asymmetric price envelope with strong predictive power, closely following the methodology outlined in the paper.
Due to the inherent limitations of Pine Script, the indicator utilizes a Kernel Density Estimator (KDE) in place of the original Cepstral Smoothing technique described in the paper. While this approach was chosen out of necessity rather than superiority, the resulting method is designed to be as effective as possible within the constraints of the Pine environment.
This indicator is ideal for traders seeking an advanced tool to analyze price dynamics, offering insights into potential price movements while working within the practical constraints of Pine Script. Whether used in dynamic mode or with a static setting, the True Envelopes indicator helps in identifying key support and resistance levels, making it a valuable asset in any trading strategy.
Key Features:
Dynamic Mode: The indicator dynamically estimates the fundamental frequency of the price, optimizing the envelope generation process in real-time to capture critical price movements.
High-Pass Filtering: Uses a high-pass filtered signal to identify and smoothly interpolate price peaks, ensuring that the envelope accurately reflects significant price changes.
Kernel Density Estimation: Although implemented as a workaround, the KDE technique allows for flexible and adaptive smoothing of the envelope, aimed at achieving results comparable to the more sophisticated methods described in the original research.
Symmetric and Asymmetric Envelopes: Provides options to select between symmetric and asymmetric envelopes, accommodating various trading strategies and market conditions.
Smoothness Control: Features adjustable smoothness settings, enabling users to balance between responsiveness and the overall smoothness of the envelopes.
The True Envelopes indicator comes with a variety of input settings that allow traders to customize the behavior of the envelopes to match their specific trading needs and market conditions. Understanding each of these settings is crucial for optimizing the indicator's performance.
Main Settings
Source: This is the data series on which the indicator is applied, typically the closing price (close). You can select other price data like open, high, low, or a custom series to base the envelope calculations.
History: This setting determines how much historical data the indicator should consider when calculating the envelopes. A value of 0 will make the indicator process all available data, while a higher value restricts it to the most recent n bars. This can be useful for reducing the computational load or focusing the analysis on recent market behavior.
Iterations: This parameter controls the number of iterations used in the envelope generation algorithm. More iterations will typically result in a smoother envelope, but can also increase computation time. The optimal number of iterations depends on the desired balance between smoothness and responsiveness.
Kernel Style: The smoothing kernel used in the Kernel Density Estimator (KDE). Available options include Sinc, Gaussian, Epanechnikov, Logistic, and Triangular. Each kernel has different properties, affecting how the smoothing is applied. For example, Gaussian provides a smooth, bell-shaped curve, while Epanechnikov is more efficient computationally with a parabolic shape.
Envelope Style: This setting determines whether the envelope should be Static or Dynamic. The Static mode applies a fixed period for the envelope, while the Dynamic mode automatically adjusts the period based on the fundamental frequency of the price data. Dynamic mode is typically more responsive to changing market conditions.
High Q: This option controls the quality factor (Q) of the high-pass filter. Enabling this will increase the Q factor, leading to a sharper cutoff and more precise isolation of high-frequency components, which can help in better identifying significant price peaks.
Symmetric: This setting allows you to choose between symmetric and asymmetric envelopes. Symmetric envelopes maintain an equal distance from the central price line on both sides, while asymmetric envelopes can adjust differently above and below the price line, which might better capture market conditions where upside and downside volatility are not equal.
Smooth Envelopes: When enabled, this setting applies additional smoothing to the envelopes. While this can reduce noise and make the envelopes more visually appealing, it may also decrease their responsiveness to sudden market changes.
Dynamic Settings
Extra Detrend: This setting toggles an additional high-pass filter that can be applied when using a long filter period. The purpose is to further detrend the data, ensuring that the envelope focuses solely on the most recent price oscillations.
Filter Period Multiplier: This multiplier adjusts the period of the high-pass filter dynamically based on the detected fundamental frequency. Increasing this multiplier will lengthen the period, making the filter less sensitive to short-term price fluctuations.
Filter Period (Min) and Filter Period (Max): These settings define the minimum and maximum bounds for the high-pass filter period. They ensure that the filter period stays within a reasonable range, preventing it from becoming too short (and overly sensitive) or too long (and too sluggish).
Envelope Period Multiplier: Similar to the filter period multiplier, this adjusts the period for the envelope generation. It scales the period dynamically to match the detected price cycles, allowing for more precise envelope adjustments.
Envelope Period (Min) and Envelope Period (Max): These settings establish the minimum and maximum bounds for the envelope period, ensuring the envelopes remain adaptive without becoming too reactive or too slow.
Static Settings
Filter Period: In static mode, this setting determines the fixed period for the high-pass filter. A shorter period will make the filter more responsive to price changes, while a longer period will smooth out more of the price data.
Envelope Period: This setting specifies the fixed period used for generating the envelopes in static mode. It directly influences how tightly or loosely the envelopes follow the price action.
TAE Smoothing: This controls the degree of smoothing applied during the TAE process in static mode. Higher smoothing values result in more gradual envelope curves, which can be useful in reducing noise but may also delay the envelope’s response to rapid price movements.
Visual Settings
Top Band Color: This setting allows you to choose the color for the upper band of the envelope. This band represents the resistance level in the price action.
Bottom Band Color: Similar to the top band color, this setting controls the color of the lower band, which represents the support level.
Center Line Color: This is the color of the central price line, often referred to as the carrier. It represents the detrended price around which the envelopes are constructed.
Line Width: This determines the thickness of the plotted lines for the top band, bottom band, and center line. Thicker lines can make the envelopes more visible, especially when overlaid on price data.
Fill Alpha: This controls the transparency level of the shaded area between the top and bottom bands. A lower alpha value will make the fill more transparent, while a higher value will make it more opaque, helping to highlight the envelope more clearly.
The envelopes generated by the True Envelopes indicator are designed to provide a more precise and responsive representation of price action compared to traditional methods like Bollinger Bands or Keltner Channels. The core idea behind this indicator is to create a price envelope that smoothly interpolates the significant peaks in price action, offering a more accurate depiction of support and resistance levels.
One of the critical aspects of this approach is the use of a high-pass filtered signal to identify these peaks. The high-pass filter serves as an effective method of detrending the price data, isolating the rapid fluctuations in price that are often lost in standard trend-following indicators. By filtering out the lower frequency components (i.e., the trend), the high-pass filter reveals the underlying oscillations in the price, which correspond to significant peaks and troughs. These oscillations are crucial for accurately constructing the envelope, as they represent the most responsive elements of the price movement.
The algorithm works by first applying the high-pass filter to the source price data, effectively detrending the series and isolating the high-frequency price changes. This filtered signal is then used to estimate the fundamental frequency of the price movement, which is essential for dynamically adjusting the envelope to current market conditions. By focusing on the peaks identified in the high-pass filtered signal, the algorithm generates an envelope that is both smooth and adaptive, closely following the most significant price changes without overfitting to transient noise.
Compared to traditional envelopes and bands, such as Bollinger Bands and Keltner Channels, the True Envelopes indicator offers several advantages. Bollinger Bands, which are based on standard deviations, and Keltner Channels, which use the average true range (ATR), both tend to react to price volatility but do not necessarily follow the peaks and troughs of the price with precision. As a result, these traditional methods can sometimes lag behind or fail to capture sudden shifts in price momentum, leading to either false signals or missed opportunities.
In contrast, the True Envelopes indicator, by using a high-pass filtered signal and a dynamic period estimation, adapts more quickly to changes in price behavior. The envelopes generated by this method are less prone to the lag that often affects standard deviation or ATR-based bands, and they provide a more accurate representation of the price's immediate oscillations. This can result in better predictive power and more reliable identification of support and resistance levels, making the True Envelopes indicator a valuable tool for traders looking for a more responsive and precise approach to market analysis.
In conclusion, the True Envelopes indicator is a powerful tool that blends advanced theoretical concepts with practical implementation, offering traders a precise and responsive way to analyze price dynamics. By adapting the True Amplitude Envelope (TAE) method through the use of a Kernel Density Estimator (KDE) and high-pass filtering, this indicator effectively captures the most significant price movements, providing a more accurate depiction of support and resistance levels compared to traditional methods like Bollinger Bands and Keltner Channels. The flexible settings allow for extensive customization, ensuring the indicator can be tailored to suit various trading strategies and market conditions.
Charan_Trading_IndicatorCharan_Trading_Indicator Overview:
The Charan_Trading_Indicator combines several technical analysis tools, including Bollinger Bands, RSI (Relative Strength Index), VWAP (Volume-Weighted Average Price), and ATR (Average True Range), to provide buy and sell signals. The script incorporates multiple strategies, such as crack snap setups, overbought/oversold levels, and trend continuation indicators, all tailored for precise market entry and exit points.
Key Components:
RSI (Relative Strength Index):
The indicator uses RSI to detect overbought (RSI > 70) and oversold (RSI < 30) market conditions.
Alerts are triggered when prices are within the specified buy/sell range and RSI crosses these thresholds.
Bollinger Bands:
Bollinger Bands are calculated based on a configurable moving average and standard deviation.
The script identifies potential buy signals when the price dips below the lower Bollinger Band and recovers, and sell signals when the price exceeds the upper Bollinger Band and retraces.
Crack Snap Strategies:
The indicator incorporates multiple variations of the crack snap strategy:
Buy Signals: Triggered when price opens below the lower Bollinger Band and closes above it, alongside certain conditions in previous candles.
Sell Signals: Triggered when price opens above the upper Bollinger Band and closes below it, with similar candle patterns.
Variations such as 3-candle (3C) and 4-candle (4C) versions refine the crack snap setups for more robust signals.
Isolated Candle Conditions:
The indicator tracks isolated candles, where the entire candle lies above or below the Bollinger Bands, to identify potential reversal points.
Trend Continuation Signals:
Conditions based on the candle range and previous highs/lows allow the indicator to generate signals for trend continuation:
Buy signals when price breaks above the previous two highs.
Sell signals when price breaks below the previous two lows.
VWAP (Volume-Weighted Average Price):
The indicator integrates VWAP to give additional support and resistance levels, ensuring signals align with volume trends.
ATR-Based Stop Loss:
For both buy and sell conditions, the script plots stop-loss levels based on the ATR (Average True Range), giving dynamic risk management levels.
Buy/Sell Ranges:
The user can set minimum and maximum price ranges for buy and sell signals, ensuring that the indicator only generates alerts within desired price ranges.
How It Works:
Buy Signals: The script generates buy signals based on multiple conditions, including the crack snap strategy, oversold RSI levels, and trend continuation setups. When these conditions are met, green triangles appear below the price bars, and an alert is triggered.
Sell Signals: Sell signals are triggered when the opposite conditions are met (overbought RSI, crack snap sell setups, trend breaks), and red triangles appear above the price bars.
Visual Indicators: The script plots upper and lower Bollinger Bands, stop loss levels, and VWAP on the chart, providing a comprehensive view of market conditions and support/resistance levels.
This indicator is versatile, combining multiple technical tools for robust decision-making in trading. It generates alerts, plots visual markers, and integrates risk management, making it a well-rounded tool for technical analysis.
This indicator is versatile, combining multiple technical tools for robust decision-making in trading. It generates alerts, plots visual markers, and integrates risk management, making it a well-rounded tool for technical analysis.
Larry Connors %b Strategy (Bollinger Band)Larry Connors’ %b Strategy is a mean-reversion trading approach that uses Bollinger Bands to identify buy and sell signals based on the %b indicator. This strategy was developed by Larry Connors, a renowned trader and author known for his systematic, data-driven trading methods, particularly those focusing on short-term mean reversion.
The %b indicator measures the position of the current price relative to the Bollinger Bands, which are volatility bands placed above and below a moving average. The strategy specifically targets times when prices are oversold within a long-term uptrend and aims to capture rebounds by buying at relatively low points and selling at relatively high points.
Strategy Rules
The basic rules of the %b Strategy are:
1. Trend Confirmation: The closing price must be above the 200-day moving average. This filter ensures that trades are made in alignment with a longer-term uptrend, thereby avoiding trades against the primary market trend.
2. Oversold Conditions: The %b indicator must be below 0.2 for three consecutive days. The %b value below 0.2 indicates that the price is near the lower Bollinger Band, suggesting an oversold condition.
3. Entry Signal: Enter a long position at the close when conditions 1 and 2 are met.
4. Exit Signal: Exit the position when the %b value closes above 0.8, signaling an overbought condition where the price is near the upper Bollinger Band.
How the Strategy Works
This strategy operates on the premise of mean reversion, which suggests that extreme price movements will revert to the mean over time. By entering positions when the %b value indicates an oversold condition (below 0.2) in a confirmed uptrend, the strategy attempts to capture short-term price rebounds. The exit rule (when %b is above 0.8) aims to lock in profits once the price reaches an overbought condition, often near the upper Bollinger Band.
Who Was Larry Connors?
Larry Connors is a well-known figure in the world of financial markets and trading. He co-authored several influential trading books, including “Short-Term Trading Strategies That Work” and “High Probability ETF Trading.” Connors is recognized for his quantitative approach, focusing on systematic, rules-based strategies that leverage historical data to validate trading edges.
His work primarily revolves around short-term trading strategies, often using technical indicators like RSI (Relative Strength Index), Bollinger Bands, and moving averages. Connors’ methodologies have been widely adopted by traders seeking structured approaches to exploit short-term inefficiencies in the market.
Risks of the Strategy
While the %b Strategy can be effective, particularly in mean-reverting markets, it is not without risks:
1. Mean Reversion Assumption: The strategy is based on the assumption that prices will revert to the mean. In trending or sharply falling markets, this reversion may not occur, leading to sustained losses.
2. False Signals in Choppy Markets: In volatile or sideways markets, the strategy may generate multiple false signals, resulting in whipsaw trades that can erode capital through frequent small losses.
3. No Stop Loss: The basic implementation of the strategy does not include a stop loss, which increases the risk of holding losing trades longer than intended, especially if the market continues to move against the position.
4. Performance During Market Crashes: During major market downturns, the strategy’s buy signals could be triggered frequently as prices decline, compounding losses without the presence of a risk management mechanism.
Scientific References and Theoretical Basis
The %b Strategy relies on the concept of mean reversion, which has been extensively studied in finance literature. Studies by Avellaneda and Lee (2010) and Bouchaud et al. (2018) have demonstrated that mean-reverting strategies can be profitable in specific market environments, particularly when combined with volatility filters like Bollinger Bands. However, the same studies caution that such strategies are highly sensitive to market conditions and often perform poorly during periods of prolonged trends.
Bollinger Bands themselves were popularized by John Bollinger and are widely used to assess price volatility and detect potential overbought and oversold conditions. The %b value is a critical part of this analysis, as it standardizes the position of price relative to the bands, making it easier to compare conditions across different securities and time frames.
Conclusion
Larry Connors’ %b Strategy is a well-known mean-reversion technique that leverages Bollinger Bands to identify buying opportunities in uptrending markets when prices are temporarily oversold. While the strategy can be effective under the right conditions, traders should be aware of its limitations and risks, particularly in trending or highly volatile markets. Incorporating risk management techniques, such as stop losses, could help mitigate some of these risks, making the strategy more robust against adverse market conditions.
