Glitch IndexGlitch Index is an oscillator from an unknown origin that is discovered in 2013 as a lua indicator taken from MetaStock days and we are not really sure how far back the original idea goes.
How it Works?
As I found this indicator and looking at it's code in different platform I can see it comes back from a basic idea of getting a price value, calculating it's smoothed average with a set multiplier and getting the difference then presenting it on a simplified scale. It appears to be another interpretation of figuring out price acceleration and velocity. The main logic is calculated as below:
price = priceSet(priceType)
_ma = getAverageName(price, MaMethod, MaPeriod)
rocma = ((_ma - _ma ) * 0.1) + 1
maMul = _ma * rocma
diff = price - maMul
gli_ind = (diff / price) * -10
How to Use?
Glitch Index can be used based on different implementations and along with your already existing trading system as a confirmation. Yoıu can use it as a Long signal when the histogram crosses inner levels or you can use it as an overbough and oversold signals when the histogram crosses above outter levels and gets back in the range between outter and inner levels.
You can customise the settings and set your prefered inner and outter levels in indicator settings along with gradient or static based coloring and modify the code as you see fit. The coloring code is set below:
gli_col = gli_ind > outterLevel ? color.green : gli_ind < -outterLevel ? color.red : gli_ind > innerLevel ? color.rgb(106, 185, 109, 57) : gli_ind < -innerLevel ? color.rgb(233, 111, 111, 40) : color.new(color.yellow, 60)
gradcol = color.from_gradient(gli_ind, -outterLevel, outterLevel, color.red, color.green)
colorSelect = colorType == "Gradient" ? gradcol : gli_col
Osciladores
Cosine smoothed stochasticDescription
The "Cosine Smoothed Stochastic" indicator leverages advanced Fourier Transform techniques to smooth the traditional Stochastic Oscillator. This approach enhances the signal's reliability and reduces noise, providing traders with a more refined and actionable indicator.
The Stochastic Oscillator is a popular momentum indicator that measures the current price relative to the high-low range over a specified period. It helps identify overbought and oversold conditions, signaling potential trend reversals. By smoothing this indicator with Fourier Transform techniques, we aim to reduce false signals and improve its effectiveness.
The indicator comprises three main components:
Cosine Function: A custom function to compute the cosine of an input scaled by a frequency tuner.
Kernel Function: Utilizes the cosine function to create a smooth kernel, constrained to positive values within a specific range.
Kernel Regression and Multi Cosine: Perform kernel regression over a lookback period, with the multi cosine function summing these regressions at varying frequencies for a composite smooth signal.
Additionally, the indicator includes a volume oscillator to complement the smoothed stochastic signals, providing insights into market volume trends.
Features
Fourier Transform Smoothing: Advanced smoothing technique to reduce noise.
Volume Oscillator: Dynamic volume-based oscillator for additional market insights.
Customizable Inputs: Users can configure key parameters like regression lookback period, tuning coefficient, and smoothing length.
Visual Alerts: Buy and sell signals based on smoothed stochastic crossovers.
Usage
The indicator is designed for trend-following and momentum-based trading strategies . It helps identify overbought and oversold conditions, trend reversals, and potential entry and exit points based on smoothed stochastic values and volume trends.
Inputs
Cosine Kernel Setup:
varient: Choose between "Tuneable" and "Stepped" regression types.
lookbackR: Lookback period for regression.
tuning: Tuning coefficient for frequency adjustment.
Stochastic Calculation:
volshow: Toggle to show the volume oscillator.
emalength: Smoothing period for the Stochastic Oscillator.
lookback_period, m1, m2: Parameters for the Stochastic Oscillator lookback and moving averages.
How It Works
Stochastic Oscillator:
Computes the stochastic %K and smoothes it with an EMA.
Further smoothes %K using the multi cosine function.
Volume Oscillator:
Calculates short and long EMAs of volume and derives the oscillator as the percentage difference.
Plots volume oscillator columns with dynamic coloring based on the oscillator's value and change.
Visual Representation:
Plots smoothed stochastic lines with colors indicating bullish, bearish, overbought, and oversold conditions.
Uses plotchar to mark crossovers between current and previous values of d.
Displays overbought and oversold levels with filled regions between them.
Chart Example
To understand the indicator better, refer to the clean and annotated chart provided. The script is used without additional scripts to maintain clarity. The chart includes:
Smoothed Stochastic Lines: Colored according to trend conditions.
Volume Oscillator: Plotted as columns for visual volume trend analysis.
Overbought/Oversold Levels: Clearly marked levels with filled regions between them.
Alert Conditions
The indicator sets up alerts for buy and sell signals when the smoothed stochastic crosses over or under its previous value. These alerts can be used for automated trading systems or manual trading signals.
breakthrough of the indicators method :
Initialization and Inputs:
The indicator starts by defining necessary inputs, such as the lookback period for regression, tuning coefficient, and smoothing parameters for the Stochastic Oscillator and volume oscillator.
Cosine Function and Kernel Creation:
The cosine function is defined to compute the cosine of an input scaled by a frequency tuner.
The kernel function utilizes this cosine function to create a smoothing kernel, which is constrained to positive values within a specific range.
Kernel Regression:
The kernel regression function iterates over the lookback period, calculating weighted sums of the source values using the kernel function. This produces a smoothed value by dividing the accumulated weighted values by the total weights.
Multi Cosine Smoothing:
The multi cosine function combines multiple kernel regressions at different frequencies, summing these results and averaging them to achieve a composite smoothed value.
Stochastic Calculation and Smoothing:
The traditional Stochastic Oscillator is calculated, and its %K value is smoothed using an EMA.
The smoothed %K is further refined using the multi cosine function, resulting in a more reliable and less noisy signal.
Volume Oscillator Calculation:
The volume oscillator calculates short and long EMAs of the volume and derives the oscillator as the percentage difference between these EMAs. The result is plotted with dynamic coloring to indicate volume trends.
Plotting and Alerts:
The indicator plots the smoothed stochastic lines , overbought/oversold levels, and volume oscillator on the chart.
Buy and sell alerts are set up based on crossovers of the smoothed stochastic values, providing traders with actionable signals.
HMA Crossover 1H with RSI, Stochastic RSI, and Trailing StopThe strategy script provided is a trading algorithm designed to help traders make informed buy and sell decisions based on certain technical indicators. Here’s a breakdown of what each part of the script does and how the strategy works:
Key Components:
Hull Moving Averages (HMA):
HMA 5: This is a Hull Moving Average calculated over 5 periods. HMAs are used to smooth out price data and identify trends more quickly than traditional moving averages.
HMA 20: This is another HMA but calculated over 20 periods, providing a broader view of the trend.
Relative Strength Index (RSI):
RSI 14: This is a momentum oscillator that measures the speed and change of price movements over a 14-period timeframe. It helps identify overbought or oversold conditions in the market.
Stochastic RSI:
%K: This is the main line of the Stochastic RSI, which combines the RSI and the Stochastic Oscillator to provide a more sensitive measure of overbought and oversold conditions. It is smoothed with a 3-period simple moving average.
Trading Signals:
Buy Signal:
Generated when the 5-period HMA crosses above the 20-period HMA, indicating a potential upward trend.
Additionally, the RSI must be below 45, suggesting that the market is not overbought.
The Stochastic RSI %K must also be below 39, confirming the oversold condition.
Sell Signal:
Generated when the 5-period HMA crosses below the 20-period HMA, indicating a potential downward trend.
The RSI must be above 60, suggesting that the market is not oversold.
The Stochastic RSI %K must also be above 63, confirming the overbought condition.
Trailing Stop Loss:
This feature helps protect profits by automatically selling the position if the price moves against the trade by 5%.
For sell positions, an additional trailing stop of 100 points is included.
Advanced Gold Scalping Strategy with RSI Divergence# Advanced Gold Scalping Strategy with RSI Divergence
## Overview
This Pine Script implements an advanced scalping strategy for gold (XAUUSD) trading, primarily designed for the 1-minute timeframe. The strategy utilizes the Relative Strength Index (RSI) indicator along with its moving average to identify potential trade setups based on divergences between price action and RSI movements.
## Key Components
### 1. RSI Calculation
- Uses a customizable RSI length (default: 60)
- Allows selection of the source for RSI calculation (default: close price)
### 2. Moving Average of RSI
- Supports multiple MA types: SMA, EMA, SMMA (RMA), WMA, VWMA, and Bollinger Bands
- Customizable MA length (default: 3)
- Option to display Bollinger Bands with adjustable standard deviation multiplier
### 3. Divergence Detection
- Implements both bullish and bearish divergence identification
- Uses pivot high and pivot low points to detect divergences
- Allows for customization of lookback periods and range for divergence detection
### 4. Entry Conditions
- Long Entry: Bullish divergence when RSI is below 40
- Short Entry: Bearish divergence when RSI is above 60
### 5. Trade Management
- Stop Loss: Customizable, default set to 11 pips
- Take Profit: Customizable, default set to 33 pips
### 6. Visualization
- Plots RSI line and its moving average
- Displays horizontal lines at 30, 50, and 70 RSI levels
- Shows Bollinger Bands when selected
- Highlights divergences with "Bull" and "Bear" labels on the chart
## Input Parameters
- RSI Length: Adjusts the period for RSI calculation
- RSI Source: Selects the price source for RSI (close, open, high, low, hl2, hlc3, ohlc4)
- MA Type: Chooses the type of moving average applied to RSI
- MA Length: Sets the period for the moving average
- BB StdDev: Adjusts the standard deviation multiplier for Bollinger Bands
- Show Divergence: Toggles the display of divergence labels
- Stop Loss: Sets the stop loss distance in pips
- Take Profit: Sets the take profit distance in pips
## Strategy Logic
1. **RSI Calculation**:
- Computes RSI using the specified length and source
- Calculates the chosen type of moving average on the RSI
2. **Divergence Detection**:
- Identifies pivot points in both price and RSI
- Checks for higher lows in RSI with lower lows in price (bullish divergence)
- Checks for lower highs in RSI with higher highs in price (bearish divergence)
3. **Trade Entry**:
- Enters a long position when a bullish divergence is detected and RSI is below 40
- Enters a short position when a bearish divergence is detected and RSI is above 60
4. **Position Management**:
- Places a stop loss order at the entry price ± stop loss pips (depending on the direction)
- Sets a take profit order at the entry price ± take profit pips (depending on the direction)
5. **Visualization**:
- Plots the RSI and its moving average
- Draws horizontal lines for overbought/oversold levels
- Displays Bollinger Bands if selected
- Shows divergence labels on the chart for identified setups
## Usage Instructions
1. Apply the script to a 1-minute XAUUSD (Gold) chart in TradingView
2. Adjust the input parameters as needed:
- Increase RSI Length for less frequent but potentially more reliable signals
- Modify MA Type and Length to change the sensitivity of the RSI moving average
- Adjust Stop Loss and Take Profit levels based on current market volatility
3. Monitor the chart for Bull (long) and Bear (short) labels indicating potential trade setups
4. Use in conjunction with other analysis and risk management techniques
## Considerations
- This strategy is designed for short-term scalping and may not be suitable for all market conditions
- Always backtest and forward test the strategy before using it with real capital
- The effectiveness of divergence-based strategies can vary depending on market trends and volatility
- Consider using additional confirmation signals or filters to improve the strategy's performance
Remember to adapt the strategy parameters to your risk tolerance and trading style, and always practice proper risk management.
MTF WaveTrend [CryptoSea]The MTF WaveTrend Indicator is a sophisticated tool designed to enhance market analysis through multi-timeframe WaveTrend calculations. This tool is built for traders who seek to identify market momentum and potential reversals with higher accuracy.
In the example below, we can see all the choosen timeframes agree on bearish momentum.
Key Features
Multi-Timeframe WaveTrend Analysis: Tracks WaveTrend values across multiple timeframes to provide a comprehensive view of market momentum.
Customizable Colour Rules: Offers three different colour rules (Traditional, WT1 0 Rule, WT1 & WT2 0 Rule) to suit various trading strategies.
Timeframe Visibility Control: Allows users to enable or disable specific timeframes, providing flexibility in analysis.
Clear Visual Indicators: Uses color-coded squares and labels to clearly display WaveTrend status across different timeframes.
Candle Colouring Option: Includes a setting for neutral candle coloring to enhance chart readability.
This example shows what can happen when all timeframes start alligning with eachother.
How it Works
WaveTrend Calculation: Computes the WaveTrend oscillator by applying a series of exponential moving averages and scaling calculations.
Multi-Timeframe Data Aggregation: Utilizes the `request.security` function to gather and display WaveTrend values from various timeframes without repainting issues.
Conditional Plotting: Displays visual cues only when higher timeframes align with the selected timeframe, ensuring relevant and reliable signals.
Dynamic Colour Rules: Adjusts the indicator colors based on the chosen rule, whether it's a traditional crossover, WT1 crossing zero, or both WT1 & WT2 crossing zero.
Traditional: Colors are determined by the relationship between WT1 and WT2. If WT1 is greater than WT2, it is bullish (bullColour), otherwise bearish (bearColour).
WT1 0 Rule: Colors are based on whether WT1 is above or below zero. WT1 above zero is bullish (bullColour), below zero is bearish (bearColour).
WT1 & WT2 0 Rule: A more complex rule where both WT1 and WT2 need to be above zero for a bullish signal (bullColour) or both below zero for a bearish signal (bearColour). If WT1 and WT2 are not in agreement, a neutral color (neutralColour) is displayed.
This indicator will make sure that the lowest timeframe you can see data from will be the timeframe you are on. This is to avoid false signals as you cannot display 3 x 5 minute candles whilst looking at the 15 minute candle.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of WaveTrend movements across different timeframes.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with multi-timeframe WaveTrend analysis.
Customized Analysis: Adapts to various trading styles with extensive input settings that control the display and sensitivity of WaveTrend data.
The MTF WaveTrend Indicator by is an invaluable addition to a trader's toolkit, offering depth and precision in market trend analysis to navigate complex market conditions effectively.
KNN OscillatorOverview
The KNN Oscillator is an advanced technical analysis tool designed to help traders identify potential trend reversals and market momentum. Using the K-Nearest Neighbors (KNN) algorithm, this oscillator normalizes KNN values to create a dynamic and responsive indicator. The oscillator line changes color to reflect the market sentiment, providing clear visual cues for trading decisions.
Key Features
Dynamic Color Oscillator: The line changes color based on the oscillator value – green for positive, red for negative, and grey for neutral.
Advanced KNN Algorithm: Utilizes the K-Nearest Neighbors algorithm for precise trend detection.
Normalized Values: Ensures the oscillator values are normalized to align with the stock price range, making it applicable to various assets.
Easy Integration: Can be easily added to any TradingView chart for enhanced analysis.
How It Works
The KNN Oscillator leverages the K-Nearest Neighbors algorithm to calculate the average distance of the nearest neighbors over a specified period. These values are then normalized to match the stock price range, ensuring they are comparable across different assets. The oscillator value is derived by taking the difference between the normalized KNN values and the source price. The line's color changes dynamically to provide an immediate visual indication of the market's state:
Green: Positive values indicate upward momentum.
Red: Negative values indicate downward momentum.
Grey: Neutral values indicate a stable or consolidating market.
Usage Instructions
Trend Reversal Detection: Use the color changes to identify potential trend reversals. A shift from red to green suggests a bullish reversal, while a shift from green to red indicates a bearish reversal.
Momentum Analysis: The oscillator's value and color help gauge market momentum. Strong positive values (green) indicate strong upward momentum, while strong negative values (red) indicate strong downward momentum.
Market Sentiment: The dynamic color changes provide an easy-to-understand visual representation of market sentiment, helping traders make informed decisions quickly.
Confirmation Tool: Use the KNN Oscillator in conjunction with other technical indicators to confirm signals and improve the accuracy of your trades.
Scalability: Applicable to various timeframes and asset classes, making it a versatile tool for all types of traders.
ADX and SADX, SDIThe indicator aims to analyze and visualize the Average Directional Index (ADX) and its smoothed versions, along with directional indicators (DI) to help traders identify trend strength and potential buy/sell signals.
Indicator Settings:
The indicator is named "ADX and SADX, SDI" and is set to display prices with a precision of 2 decimal places.
Users can customize the ADX smoothing length, DI length, ADX smoothing period, and DI smoothing period through input variables.
Directional Movement (DM) Calculation:
The function dirmov calculates the positive and negative directional movements (DM) and the smoothed values of the positive directional index (DI+) and negative directional index (DI-).
This is done using the average true range (ATR) to normalize the DM values.
Average Directional Index (ADX) Calculation:
The function adx calculates the ADX, which measures the strength of a trend.
It uses the DI+ and DI- values to compute the ADX value.
Smoothed ADX and DI Calculation:
The ADX values are further smoothed using a simple moving average (SMA).
The DI difference is also smoothed and used to determine the trend direction.
Buy and Sell Signals:
A buy signal is generated when the DI+ crosses above DI- and the smoothed DI difference is increasing.
A sell signal is generated when the DI- crosses above DI+ and the smoothed DI difference is decreasing.
Plotting:
The ADX, smoothed ADX, smoothed DI difference (SPM), DI+, and DI- values are plotted on the chart.
Horizontal lines are drawn to indicate threshold levels (e.g., level 22).
Background and bar colors change based on buy (lime) and sell (maroon) signals to visually indicate these conditions.
Purpose of the Code:
This Pine Script code is used to create a custom indicator on TradingView that helps traders identify the strength and direction of a trend. The Average Directional Index (ADX) is used to measure trend strength, while the Directional Indicators (DI+ and DI-) are used to determine the direction of the trend. The smoothed versions of these indicators (SADX and SDI) provide additional confirmation and smoothing to reduce noise and false signals. Traders can use the buy and sell signals generated by this indicator to make informed trading decisions based on the trend strength and direction.
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.
RSI Sector analysis
Screening tool that produces a table with the various sectors and their RSI values. The values are shown in 3 rows, each with a user-defined length, and can be averaged out and displayed as a single value. The chart is color coded as well. Each ETF representing a sector can be looked at individually, with the top holdings in each preprogrammed, but users can define their own if they wish. The left most ticker is the "benchmark"; SPY is the benchmark for the various sectors, and the ETF is the benchmark for the tickers within.
Symbols are color coded: light blue text indicates that a symbol has greater RSI values in all three timeframes than the benchmark (the leftmost symbol). Orange text indicates that a symbol has a lower RSI value for all three timeframes. In the first row, light blue text indicates the largest RSI increase from the third row to the first row. Orange text indicates the largest RSI decrease from the third row to the first row.
A blue highlight indicates that the value is the highest among the tickers, excluding the benchmark, and an orange highlight indicates that the value is the lowest among the tickers, also excluding the benchmark. A blue highlight on the ticker indicates that it has the highest average value of the 3 rows, and a orange highlight on the ticker indicates that it has the lowest average value of the 3 rows.
DeQuex Algo BISTIntroduction:
The DeQuex Algo is an advanced technical analysis tool designed to help traders identify high-probability entry and exit points in the Borsa Istanbul (BIST) market. This updated version incorporates an adaptive MACD to reduce false signals and improve the overall reliability of the indicator.
Key Features:
1. Adaptive MACD: The script utilizes an adaptive MACD that dynamically adjusts to market volatility, reducing the occurrence of false signals often associated with traditional MACD implementations.
2. RSI Confirmation: In addition to the adaptive MACD, the DeQuex Algo also considers RSI readings to provide stronger confirmation for buy and sell signals.
3. Signal Types:
- Buy Signal: Triggered when the adaptive MACD crosses above its signal line.
- Sell Signal: Triggered when the adaptive MACD crosses below its signal line.
- Strong Buy Signal: Triggered when both the adaptive MACD and RSI cross above their respective thresholds, indicating a high-probability bullish setup.
- Strong Sell Signal: Triggered when both the adaptive MACD and RSI cross below their respective thresholds, indicating a high-probability bearish setup.
4. Price Bar Highlighting: The script color-codes price bars to provide a visual representation of the current trend. Green bars indicate an uptrend, red bars indicate a downtrend, and purple bars signify a period of consolidation or uncertainty. This feature allows traders to quickly assess the market context at a glance.
5. Customizable Alerts: Users can enable alerts for each signal type, ensuring they never miss a potential trading opportunity.
6. Dynamic Support and Resistance: The DeQuex Algo incorporates dynamic support and resistance levels based on market volatility. These levels are plotted using an innovative approach that combines Donchian channels with a Kalman filter for smoother, more reliable zones.
7. User-Friendly Inputs: The script provides a range of input parameters, allowing traders to fine-tune the indicator's sensitivity and adapt it to their preferred trading style and timeframe.
How to Use:
1. Add the DeQuex Algo indicator to your TradingView chart.
2. Customize the input parameters as desired, or use the default settings.
3. Enable alerts for your preferred signal types.
4. Look for buy and sell signals based on the adaptive MACD and RSI readings, paying attention to the color-coded price bars for additional context.
5. Consider the dynamic support and resistance levels when planning your entries, exits, and stop-loss placements.
Please note that while the DeQuex Algo is designed to identify high-probability setups, no indicator is perfect, and false signals may still occur. Always use proper risk management and consider other factors, such as market sentiment and fundamental analysis, when making trading decisions.
We hope that the DeQuex Algo will be a valuable addition to your trading toolbox, and we welcome any feedback or suggestions for further improvement.
Best regards,
BrandonJames1337
TR:
İşte güncellenmiş DeQuex Algo göstergeniz için önerilen bir açıklama:
Giriş:
DeQuex Algo, yatırımcıların Borsa İstanbul (BIST) piyasasında yüksek olasılıklı giriş ve çıkış noktalarını belirlemelerine yardımcı olmak için tasarlanmış gelişmiş bir teknik analiz aracıdır. Bu güncellenmiş sürüm, yanlış sinyalleri azaltmak ve göstergenin genel güvenilirliğini artırmak için uyarlanabilir bir MACD içerir.
Temel Özellikler:
1. Uyarlanabilir MACD: Komut dosyası, piyasa oynaklığına dinamik olarak ayarlanan ve genellikle geleneksel MACD uygulamalarıyla ilişkili yanlış sinyallerin oluşumunu azaltan uyarlanabilir bir MACD kullanır.
2. RSI Onayı: Uyarlanabilir MACD'ye ek olarak DeQuex Algo, alım ve satım sinyalleri için daha güçlü onay sağlamak üzere RSI okumalarını da dikkate alır.
3. Sinyal Türleri:
- Alış Sinyali: Uyarlanabilir MACD sinyal çizgisinin üzerine çıktığında tetiklenir.
- Satış Sinyali: Uyarlanabilir MACD sinyal çizgisinin altından geçtiğinde tetiklenir.
- Güçlü Alış Sinyali: Hem uyarlanabilir MACD hem de RSI kendi eşiklerinin üzerine çıktığında tetiklenir ve yüksek olasılıklı bir yükseliş düzenine işaret eder.
- Güçlü Satış Sinyali: Hem uyarlanabilir MACD hem de RSI kendi eşiklerinin altına düştüğünde tetiklenir ve yüksek olasılıklı bir düşüş düzenine işaret eder.
4. Fiyat Çubuğu Vurgulama: Komut dosyası, mevcut eğilimin görsel bir temsilini sağlamak için fiyat çubuklarını renk kodlarıyla kodlar. Yeşil çubuklar yükseliş trendini, kırmızı çubuklar düşüş trendini ve mor çubuklar ise konsolidasyon veya belirsizlik dönemini gösterir. Bu özellik, yatırımcıların piyasa bağlamını bir bakışta hızlı bir şekilde değerlendirmelerine olanak tanır.
5. Özelleştirilebilir Uyarılar: Kullanıcılar her sinyal türü için uyarıları etkinleştirerek potansiyel bir alım satım fırsatını asla kaçırmamalarını sağlayabilir.
6. Dinamik Destek ve Direnç: DeQuex Algo, piyasa oynaklığına dayalı dinamik destek ve direnç seviyeleri içerir. Bu seviyeler, daha yumuşak ve daha güvenilir bölgeler için Donchian kanallarını Kalman filtresiyle birleştiren yenilikçi bir yaklaşım kullanılarak çizilir.
7. Kullanıcı Dostu Girişler: Komut dosyası, yatırımcıların göstergenin hassasiyetini ince ayarlamalarına ve tercih ettikleri ticaret tarzına ve zaman dilimine uyarlamalarına olanak tanıyan bir dizi giriş parametresi sağlar.
Nasıl Kullanılır:
1. DeQuex Algo göstergesini TradingView grafiğinize ekleyin.
2. Giriş parametrelerini istediğiniz gibi özelleştirin veya varsayılan ayarları kullanın.
3. Tercih ettiğiniz sinyal türleri için uyarıları etkinleştirin.
4. Ek bağlam için renk kodlu fiyat çubuklarına dikkat ederek uyarlanabilir MACD ve RSI okumalarına dayalı alım ve satım sinyallerini arayın.
5. Girişlerinizi, çıkışlarınızı ve stop-loss yerleşimlerinizi planlarken dinamik destek ve direnç seviyelerini göz önünde bulundurun.
DeQuex Algo yüksek olasılıklı kurulumları belirlemek için tasarlanmış olsa da, hiçbir göstergenin mükemmel olmadığını ve yine de yanlış sinyallerin oluşabileceğini lütfen unutmayın. Alım satım kararları verirken her zaman uygun risk yönetimini kullanın ve piyasa duyarlılığı ve temel analiz gibi diğer faktörleri göz önünde bulundurun.
DeQuex Algo'nun ticaret araç kutunuza değerli bir katkı sağlayacağını umuyor ve daha fazla iyileştirme için her türlü geri bildirim veya öneriyi memnuniyetle karşılıyoruz.
Saygılarımla,
BrandonJames1337
Directional Movement Index DEThis script uses the existing built-in DMI indicator but adds two lines indicating strength of the ADX trend. The original author J. Welles Wilder, indicated a ADX trending strongly above 25 (yellow by default), and ADX trending weaker at a threshold of 20 or below (dashed yellow by default).
The default colours have been changed so that ADX is yellow, +DI is green, and -DI is red.
Calculation
Calculating the DMI can actually be broken down into two parts. First, calculating the +DI and -DI, and second, calculating the ADX. To calculate the +DI and -DI you need to find the +DM and -DM (Directional Movement). +DM and -DM are calculated using the High, Low and Close for each period. You can then calculate the following:
Current High - Previous High = UpMove
Previous Low - Current Low = DownMove
If UpMove > DownMove and UpMove > 0, then +DM = UpMove, else +DM = 0
If DownMove > Upmove and Downmove > 0, then -DM = DownMove, else -DM = 0
Once you have the current +DM and -DM calculated, the +DM and -DM lines can be calculated and plotted based on the number of user defined periods.
+DI = 100 times Exponential Moving Average of (+DM / Average True Range)
-DI = 100 times Exponential Moving Average of (-DM / Average True Range)
Now that -+DX and -DX have been calculated, the last step is calculating the ADX.
ADX = 100 times the Exponential Moving Average of the Absolute Value of (+DI - -DI) / (+DI + -DI)
The basics
DMI has a value between 0 and 100 and is used to measure the strength of the current trend. +DI and -DI are then used to measure direction. When combined, the indicator can provide some valuable insight. A general interpretation would be that during a strong trend (ADX above 25 but dependent on the analyst's interpretation), when the +DI is above the -DI, then a Bullish Market is defined. When -DI is above +DI, then a Bearish Market is at hand.
One thing to be considered is that what DMI values determine, strength or a potential signal, is up to the trader's interpretation. Acceptable values may change depending on the financial instrument being examined, therefore some historical analysis of the instrument in question would be prudent. A technical analyst can make better decisions based on what has occurred in historical examples.
All credit goes to the original script .
Modern Trend IdentifierThis is an update by Lightangel112 to Trendilo (Open-Source).
Thanks @ Lightangel112
The Modern Trend Identifier (MTI) is a sophisticated technical analysis tool designed for traders and analysts seeking to accurately determine market trends. This indicator leverages the Arnaud Legoux Moving Average (ALMA) to smooth price data and calculate percentage changes, providing a clearer and more responsive trend analysis. MTI is engineered to highlight trend direction with visual cues, fill areas between the indicator and its bands, and color bars based on trend direction, making it a powerful tool for identifying market momentum and potential reversals.
Capabilities
Smoothing and Trend Calculation:
Utilizes ALMA to smooth price data, reducing noise and providing a clearer view of the trend.
Calculates percentage changes in price over a user-defined lookback period.
Dynamic Range Adjustment:
Normalizes the ALMA percentage change values to ensure they stay within a -100 to 100 range.
Uses a combination of linear and smoothstep compression to handle extreme values without losing sensitivity.
Trend Direction and Highlighting:
Determines the trend direction based on the relationship between the smoothed ALMA percentage change and dynamically adjusted RMS (Root Mean Square) bands.
Colors the trend line to visually indicate whether the market is in an uptrend, downtrend, or neutral state.
Dynamic Threshold Calculation:
Calculates dynamic thresholds using percentile ranks to adapt to changing market conditions.
Visualization Enhancements:
Fills areas between the ALMA percentage change line and its RMS bands to provide a clear visual indication of the trend strength.
Offers the option to color price bars based on the identified trend direction.
Customizable Settings:
Provides extensive customization options for lookback periods, smoothing parameters, ALMA settings, band multipliers, and more.
Allows users to enable or disable various visual enhancements and customize their appearance.
Use Cases
Trend Identification:
MTI helps traders identify the current market trend, whether it's bullish, bearish, or neutral. This can be particularly useful for trend-following strategies.
Momentum Analysis:
By highlighting areas of strong momentum, MTI enables traders to spot potential breakouts or breakdowns. This can be useful for both entry and exit decisions.
Support and Resistance Levels:
The dynamic threshold bands can act as support and resistance levels. Traders can use these levels to set stop-loss and take-profit orders.
Divergence Detection:
MTI can help in identifying divergences between price and the indicator, which can signal potential trend reversals. This is useful for traders looking to capitalize on trend changes.
Risk Management:
The fill areas and colored bars provide clear visual cues about trend strength and direction, aiding in better risk management. Traders can adjust their positions based on the strength of the trend.
Backtesting:
The extensive customization options allow traders to backtest different settings and parameters to optimize their trading strategies for various market conditions.
Multiple Timeframes:
MTI can be applied to multiple timeframes, from intraday charts to daily, weekly, or monthly charts, making it a versatile tool for traders with different trading styles.
Example Scenarios
Day Trading:
A day trader can use MTI on a 5-minute chart to identify intraday trends. By adjusting the lookback period and smoothing parameters, the trader can quickly spot potential entry and exit points based on short-term momentum changes.
Swing Trading:
A swing trader might apply MTI to a 4-hour chart to identify medium-term trends. The dynamic thresholds can help in setting appropriate stop-loss levels, while the trend direction highlighting aids in making informed decisions about holding or exiting positions.
Position Trading:
For a position trader using a daily chart, MTI can help identify the overarching trend. The trader can use the fill areas and bar coloring to assess the strength of the trend and make decisions about entering or exiting long-term positions.
Market Analysis:
An analyst could use MTI to study historical price movements and identify patterns. By examining how the indicator reacted to past market conditions, the analyst can gain insights into potential future price movements.
In summary, the Modern Trend Identifier (MTI) is a versatile and powerful tool that enhances trend analysis with advanced smoothing techniques, dynamic adjustments, and comprehensive visual cues. It is designed to meet the needs of traders and analysts across various trading styles and timeframes, providing clear and actionable insights into market trends and momentum.
Updated with the following:
Additions and Enhancements in MTI
Grouped Inputs with Descriptive Tooltips:
Inputs are organized into groups for better clarity.
Each input parameter includes a descriptive tooltip.
Dynamic Threshold Calculation:
Added dynamic threshold calculation using percentile ranks to adapt to changing market conditions.
Normalization and Compression:
Added normalization factor to ensure plots are within -100 to 100 range.
Introduced smoothstep function for smooth transition and selectively applied linear and smoothstep compression to values outside -80 to 100 range.
Enhanced Visualization:
Highlighted trend direction with RGB colors.
Enhanced fill areas between the ALMA percentage change line and its RMS bands.
Colored price bars based on the identified trend direction.
RMS Lines Adjustment:
Dynamically adjusted RMS calculation without strict capping.
Ensured RMS lines stay below fill areas to maintain clarity.
Descriptive and Organized Code:
Enhanced code clarity with detailed comments.
Organized code into logical sections for better readability and maintenance.
Key Differences and Improvements.
Input Customization:
Trendilo: Inputs are simple and ungrouped.
MTI: Inputs are grouped and include tooltips for better user guidance.
Trend Calculation:
Trendilo: Uses ALMA and calculates percentage change.
MTI: Enhanced with normalization, compression, and dynamic threshold calculation.
Normalization and Compression:
Trendilo: No normalization or compression applied.
MTI: Normalizes values to -100 to 100 range and applies smoothstep compression to handle extreme values.
Dynamic RMS Adjustment:
Trendilo: Simple RMS calculation.
MTI: Dynamically adjusted RMS calculation to ensure clarity in visualization.
Visual Enhancements:
Trendilo: Basic trend highlighting and filling.
MTI: Enhanced visual cues with RGB colors, dynamic threshold bands, and improved fill areas.
Code Clarity:
Trendilo: Functional but lacks detailed comments and organization.
MTI: Well-organized, extensively commented code for better readability and maintainability.
Chande Momentum Oscillator (CMO) Buy Sell Strategy [TradeDots]The "Chande Momentum Oscillator (CMO) Buy Sell Strategy" leverages the CMO indicator to identify short-term buy and sell opportunities.
HOW DOES IT WORK
The standard CMO indicator measures the difference between recent gains and losses, divided by the total price movement over the same period. However, this version of the CMO has some limitations.
The primary disadvantage of the original CMO is its responsiveness to short-term volatility, making the signals less smooth and more erratic, especially in fluctuating markets. This instability can lead to misleading buy or sell signals.
To address this, we integrated the concept from the Moving Average Convergence Divergence (MACD) indicator. By applying a 9-period exponential moving average (EMA) to the CMO line, we obtained a smoothed signal line. This line acts as a filter, identifying confirmed overbought or oversold states, thereby reducing the number of false signals.
Similar to the MACD histogram, we generate columns representing the difference between the CMO and its signal line, reflecting market momentum. We use this momentum indicator as a criterion for entry and exit points. Trades are executed when there's a convergence of CMO and signal lines during an oversold state, and they are closed when the CMO line diverges from the signal line, indicating increased selling pressure.
APPLICATION
Since the 9-period EMA smooths the CMO line, it's less susceptible to extreme price fluctuations. However, this smoothing also makes it more challenging to breach the original +50 and -50 benchmarks.
To increase trading opportunities, we've tightened the boundary ranges. Users can customize the target benchmark lines in the settings to adjust for the volatility of the underlying asset.
The 'cool down period' is essentially the number of bars that await before the next signal generation. This feature is employed to dodge the occurrence of multiple signals in a short period.
DEFAULT SETUP
Commission: 0.01%
Initial Capital: $10,000
Equity per Trade: 80%
Signal Cool Down Period: 5
RISK DISCLAIMER
Trading entails substantial risk, and most day traders incur losses. All content, tools, scripts, articles, and education provided by TradeDots serve purely informational and educational purposes. Past performances are not definitive predictors of future results.
Trend Momentum Strength Indicator, Built for Pairs TradingOverview:
This script combines multiple indicators to provide a comprehensive analysis of both trend strength and trend momentum. It is tailored specifically for pairs trading strategies but can also be used for other trading strategies.
Benefit of Comprehensive Analysis:
Having an indicator that evaluates both trend strength and trend momentum is crucial for traders looking to make informed decisions. It allows traders to not only identify the direction and intensity of a trend but also gauge the momentum behind it. This dual capability helps in confirming potential trade opportunities, whether for entering trades with strong trends or considering reversals during overbought or oversold conditions. By integrating both aspects into one tool, traders can gain a holistic view of market dynamics, enhancing their ability to time entries and manage risk effectively.
Features:
* Trend Strength:
Enhanced ADX Formula: The script includes modifications to the standard ADX formula along with DI+ and DI- to provide more responsive trend strength readings.
Directional Indicators: DI+ (green line) indicates positive directional movement, while DI- (red line) indicates negative directional movement.
Trend Momentum:
Modified Stochastic Indicators: The script uses %K and %D indicators, modified and combined with ADX to give a clear indication of trend momentum.
Momentum Strength: This helps determine the strength and direction of the momentum.
Trading Signals:
Combining Indicators: The script combines ADX, DI+, DI-, %K, and %D to generate comprehensive trading signals.
Optimal Entry Points: Designed to identify optimal entry points for trades, particularly in pairs trading.
Colored Area at Bottom:
This area provides two easy-to-read functions:
Color:
Green: Upward momentum (ratio above 1)
Red: Downward momentum (ratio below 1)
Height:
Higher in green: Stronger upward momentum
Lower in red: Stronger downward momentum
Legend:
Green Line: DI+ (Positive)
Red Line: DI- (Negative)
Black Line: ADX
How to Read This Indicator:
1) Trend Direction:
DI+ above DI-: Indicates an upward trend.
DI- above DI+: Indicates a downward trend.
2) Trend Strength:
ADX below 20: Indicates a neutral trend.
ADX between 20 and 25: Indicates a weak trend.
ADX above 25: Indicates a strong trend.
Trading Signals in Pairs Trading:
Neutral Trend: Ideal for pairs trading when no strong trend is detected.
Overbought/Oversold: Uses %K and %D to identify overbought/oversold conditions that support trade decisions.
Entry Signals: Green signals for long positions, red signals for short positions, based on combined criteria of neutral trend strength and supportive momentum.
Application in Pairs Trading:
Neutral trend: In pairs trading strategies, where neutral movement is often sought, this indicator provides signals that are especially relevant during periods of neutral trend strength and supportive momentum, aiding traders in identifying optimal entry
Risk Management: Combining signals from ADX, DI+, DI-, %K, and %D helps traders make more informed decisions regarding entry points, enhancing risk management.
Example Chart (The indicator is on the upper right corner):
Clean Presentation: The chart only includes the necessary elements to demonstrate the indicator’s functionality.
Demonstrates: Overbought/oversold conditions, upward/downward/no momentum, and trading signals with/without specific scenarios.
Custom Signal Oscillator StrategyThe CSO is made to help traders easily test their theories by subtracting the difference between two customizable plots(indicators) without having to search for strategies. The general purpose is to provide a tool to users without coding knowledge.
How to use :
Apply the indicator(s) to test
Go to the CSO strategy input settings and select the desired plots from the added indicators. (The back test will enter long or short depending on the fast signal crosses on the slow signal)
Pull up the strategy tester
Adjust the input settings on the selected indicator(s) to back test
For example, the published strategy is using the basis lines from two Donchian channels with varying length. This can be utilized with multiple overlays on the chart and oscillators that are operating on the same scale with each other. Since chart glows aren't extremely common, a glow option is included to stand out on the chart as the chain operator. A long only option for is also included for versatility.
Fusion MFI RSIHello fellas,
This superb indicator summons two monsters called Relative Strength Index (RSI) and Money Flow Index (MFI) and plays the Yu-Gi-Oh! card "Polymerization" to combine them.
Overview
The Fusion MFI RSI Indicator is an advanced analytical tool designed to provide a nuanced understanding of market dynamics by combining the Relative Strength Index (RSI) and the Money Flow Index (MFI). Enhanced with sophisticated smoothing techniques and the Inverse Fisher Transform (IFT), this indicator excels in identifying key market conditions such as overbought and oversold states, trends, and potential reversal points.
Key Features (Brief Overview)
Fusion of RSI and MFI: Integrates momentum and volume for a comprehensive market analysis.
Advanced Smoothing Techniques: Employs Hann Window, Jurik Moving Average (JMA), T3 Smoothing, and Super Smoother to refine signals.
Inverse Fisher Transform (IFT) Enhances the clarity and distinctiveness of indicator outputs.
Detailed Feature Analysis
Fusion of RSI and MFI
RSI (Relative Strength Index): Developed by J. Welles Wilder Jr., the RSI measures the speed and magnitude of directional price movements. Wilder recommended using a 14-day period and identified overbought conditions above 70 and oversold conditions below 30.
MFI (Money Flow Index): Created by Gene Quong and Avrum Soudack, the MFI combines price and volume to measure trading pressure. It is typically calculated using a 14-day period, with over 80 considered overbought and under 20 as oversold.
Application in Fusion: By combining RSI and MFI, the indicator leverages RSI's sensitivity to price changes with MFI's volume-weighted confirmation, providing a robust analysis tool. This combination is particularly effective in confirming the strength behind price movements, making the signals more reliable.
Advanced Smoothing Techniques
Hann Window: Traditionally used to reduce the abrupt data discontinuities at the edges of a sample, it is applied here to smooth the price data.
Jurik Moving Average (JMA): Known for preserving the timing and smoothness of the data, JMA reduces market noise effectively without significant lag.
T3 Smoothing: Developed to respond quickly to market changes, T3 provides a smoother response to price fluctuations.
Super Smoother: Filters out high-frequency noise while retaining important trends.
Application in Fusion: These techniques are chosen to refine the output of the combined RSI and MFI values, ensuring the indicator remains responsive yet stable, providing clearer and more actionable signals.
Inverse Fisher Transform (IFT):
Developed by John Ehlers, the IFT transforms oscillator outputs to enhance the clarity of extreme values. This is particularly useful in this fusion indicator to make critical turning points more distinct and actionable.
Mathematical Calculations for the Fusion MFI RSI Indicator
RSI (Relative Strength Index)
The RSI is calculated using the following steps:
Average Gain and Average Loss: First, determine the average gain and average loss over the specified period (typically 14 days). This is done by summing all the gains and losses over the period and then dividing each by the period.
Average Gain = (Sum of Gains over the past 14 periods) / 14
Average Loss = (Sum of Losses over the past 14 periods) / 14
Relative Strength (RS): This is the ratio of average gain to average loss.
RS = Average Gain / Average Loss
RSI: Finally, the RSI is calculated using the RS value:
RSI = 100 - (100 / (1 + RS))
MFI (Money Flow Index)
The MFI is calculated using several steps that incorporate both price and volume:
Typical Price: Calculate the typical price for each period.
Typical Price = (High + Low + Close) / 3
Raw Money Flow: Multiply the typical price by the volume for the period.
Raw Money Flow = Typical Price * Volume
Positive and Negative Money Flow: Compare the typical price of the current period to the previous period to determine if the money flow is positive or negative.
If today's Typical Price > Yesterday's Typical Price, then Positive Money Flow = Raw Money Flow; Negative Money Flow = 0
If today's Typical Price < Yesterday's Typical Price, then Negative Money Flow = Raw Money Flow; Positive Money Flow = 0
Money Flow Ratio: Calculate the ratio of the sum of Positive Money Flows to the sum of Negative Money Flows over the past 14 periods.
Money Flow Ratio = (Sum of Positive Money Flows over 14 periods) / (Sum of Negative Money Flows over 14 periods)
MFI: Finally, calculate the MFI using the Money Flow Ratio.
MFI = 100 - (100 / (1 + Money Flow Ratio))
Fusion of RSI and MFI
The final Fusion MFI RSI value could be calculated by averaging the IFT-transformed values of RSI and MFI, providing a single oscillator value that reflects both momentum and volume-weighted price action:
Fusion MFI RSI = (MFI weight * MFI) + (RSI weight * RSI)
Suggested Settings and Trading Rules
Original Usage
RSI: Wilder suggested buying when the RSI moves above 30 from below (enter long) and selling when the RSI moves below 70 from above (enter short). He recommended exiting long positions when the RSI reaches 70 or higher and exiting short positions when the RSI falls below 30.
MFI: Quong and Soudack recommended buying when the MFI is below 20 and starts rising (enter long), and selling when it is above 80 and starts declining (enter short). They suggested exiting long positions when the MFI reaches 80 or higher and exiting short positions when the MFI falls below 20.
Fusion Application
Settings: Use a 14-day period for this indicator's calculations to maintain consistency with the original settings suggested by the inventors.
Trading Rules:
Enter Long Signal: Consider entering a long position when both RSI and MFI are below their respective oversold levels and begin to rise. This indicates strong buying pressure supported by both price momentum and volume.
Exit Long Signal: Exit the long position when either RSI or MFI reaches its respective overbought threshold, suggesting a potential reversal or decrease in buying pressure.
Enter Short Signal: Consider entering a short position when both indicators are above their respective overbought levels and begin to decline, suggesting that selling pressure is mounting.
Exit Short Signal: Exit the short position when either RSI or MFI falls below its respective oversold threshold, indicating diminishing selling pressure and a potential upward reversal.
How to Use the Indicator
Select Source and Timeframe: Choose the data source and the timeframe for analysis.
Configure Fusion Settings: Adjust the weights for RSI and MFI.
Choose Smoothing Technique: Select and configure the desired smoothing method to suit the market conditions and personal preference.
Enable Fisherization: Optionally apply the Inverse Fisher Transform to enhance signal clarity.
Customize Visualization: Set up gradient coloring, background plots, and bands according to your preferences.
Interpret the Indicator: Use the Fusion value and visual cues to identify market conditions and potential trading opportunities.
Conclusion
The Fusion MFI RSI Indicator integrates classical and modern technical analysis concepts to provide a comprehensive tool for market analysis. By combining RSI and MFI with advanced smoothing techniques and the Inverse Fisher Transform, this indicator offers enhanced insights, aiding traders in making more informed and timely trading decisions. Customize the settings to align with your trading strategy and leverage this powerful tool to navigate financial markets effectively.
Best regards,
simwai
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Credits to:
@loxx – T3
@everget – JMA
@cheatcountry – Hann Window
Persistent Homology Based Trend Strength OscillatorPersistent Homology Based Trend Strength Oscillator
The Persistent Homology Based Trend Strength Oscillator is a unique and powerful tool designed to measure the persistence of market trends over a specified rolling window. By applying the principles of persistent homology, this indicator provides traders with valuable insights into the strength and stability of uptrends and downtrends, helping to inform better trading decisions.
What Makes This Indicator Original?
This indicator's originality lies in its application of persistent homology , a method from topological data analysis, to financial markets. Persistent homology examines the shape and features of data across multiple scales, identifying patterns that persist as the scale changes. By adapting this concept, the oscillator tracks the persistence of uptrends and downtrends in price data, offering a novel approach to trend analysis.
Concepts Underlying the Calculations:
Persistent Homology: This method identifies features such as clusters, holes, and voids that persist as the scale changes. In the context of this indicator, it tracks the duration and stability of price trends.
Rolling Window Analysis: The oscillator uses a specified window size to calculate the average length of uptrends and downtrends, providing a dynamic view of trend persistence over time.
Threshold-Based Trend Identification: It differentiates between uptrends and downtrends based on specified thresholds for price changes, ensuring precision in trend detection.
How It Works:
The oscillator monitors consecutive changes in closing prices to identify uptrends and downtrends.
An uptrend is detected when the closing price increase exceeds a specified positive threshold.
A downtrend is detected when the closing price decrease exceeds a specified negative threshold.
The lengths of these trends are recorded and averaged over the chosen window size.
The Trend Persistence Index is calculated as the difference between the average uptrend length and the average downtrend length, providing a measure of trend persistence.
How Traders Can Use It:
Identify Trend Strength: The Trend Persistence Index offers a clear measure of the strength and stability of uptrends and downtrends. A higher value indicates stronger and more persistent uptrends, while a lower value suggests stronger and more persistent downtrends.
Spot Trend Reversals: Significant shifts in the Trend Persistence Index can signal potential trend reversals. For instance, a transition from positive to negative values might indicate a shift from an uptrend to a downtrend.
Confirm Trends: Use the Trend Persistence Index alongside other technical indicators to confirm the strength and duration of trends, enhancing the accuracy of your trading signals.
Manage Risk: Understanding trend persistence can help traders manage risk by identifying periods of high trend stability versus periods of potential volatility. This can be crucial for timing entries and exits.
Example Usage:
Default Settings: Start with the default settings to get a feel for the oscillator’s behavior. Observe how the Trend Persistence Index reacts to different market conditions.
Adjust Thresholds: Fine-tune the positive and negative thresholds based on the asset's volatility to improve trend detection accuracy.
Combine with Other Indicators: Use the Persistent Homology Based Trend Strength Oscillator in conjunction with other technical indicators such as moving averages, RSI, or MACD for a comprehensive analysis.
Backtesting: Conduct backtesting to see how the oscillator would have performed in past market conditions, helping you to refine your trading strategy.
Statistical RSI Pivot Reversal Indicator [UAlgo]🔶 Idea
The "Statistical RSI Pivot Reversal Indicator " is designed to enhance traditional RSI analysis by incorporating statistical methods to identify potential reversal points more accurately. The core concept is to detect frequently occurring pivot points in the RSI data, which can indicate strong support or resistance levels. By analyzing the most frequent RSI values at these pivots, the script provides traders with clearer signals for potential market reversals, helping to improve the timing of entry and exit points in their trading strategies.
🔶 Key Features
Enhanced RSI Analysis:
This script calculates the Relative Strength Index (RSI) based on user-defined parameters and identifies pivot points in the RSI data. By analyzing these pivots, it detects the most frequently occurring RSI values at support and resistance levels.
Signal Filtering Options:
Filter buy and sell signals based on whether the RSI is in overbought (above 70) or oversold (below 30) conditions, enhancing the reliability of signals.
Visual and Alert Features:
Visual Signals: The script plots the RSI, the most frequent high and low RSI values, and buy/sell signals on the chart.
Alerts: Set up custom alerts for buy and sell conditions, ensuring you never miss a trading opportunity.
🔶 Disclaimer
The "Statistical RSI Pivot Reversal Indicator " script is intended for educational and informational purposes only.
It does not constitute financial advice or investment recommendations.
Trading financial instruments involves risk, and it is possible to lose more than your initial investment. Past performance is not indicative of future results.
intellect_city - World Cycle - Ath & Atl - Logarithmic - Signal.Indicator Overview
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - The Pi Cycle Top and Bottom Oscillator is an adaptation of the original Pi Cycle Top chart. It compares the 111-Day Moving Average circle and the 2 * 350-Day Moving Average circle of Bitcoin’s Price. These two moving averages were selected as 350 / 111 = 3.153; An approximation of the important mathematical number Pi.
When the 111-Day Moving Average circle reaches the 2 * 350-Day Moving Average circle, it indicates that the market is becoming overheated. That is because the mid time frame momentum reference of the 111-Day Moving Average has caught up with the long timeframe momentum reference of the 2 * 350-Day Moving Average.
Historically this has occurred within 3 days of the very top of each market cycle.
When the 111 Day Moving Average circle falls back beneath the 2 * 350 Day Moving Average circle, it indicates that the market momentum of that cycle is significantly cooling down. The oscillator drops down into the lower green band shown where the 111 Day Moving Average is moving at a 75% discount relative to the 2 * 350 Day Moving Average.
Historically, this has highlighted broad areas of bear market lows.
IMPORTANT: You need to set a LOGARITHMIC graph. (The function is located at the bottom right of the screen)
IMPORTANT: The INTELLECT_city indicator is made for signal purchases of sales, there is also a strategic one from INTELLECT_city
IMPORTANT: The Chart shows all cycles, both buying and selling.
IMPORTANT: Suitable timeframes are 1 daily (recommended) and 1 weekly
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Описание на русском:
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Обзор индикатора
INTELLECT_city - World Cycle - ATH & ATL - Timeframe 1D and 1W - Logarithmic - Signal - Логарифмический - Сигнал - Осциллятор вершины и основания цикла Пи представляет собой адаптацию оригинального графика вершины цикла Пи. Он сравнивает круг 111-дневной скользящей средней и круг 2 * 350-дневной скользящей средней цены Биткойна. Эти две скользящие средние были выбраны как 350/111 = 3,153; Приближение важного математического числа Пи.
Когда круг 111-дневной скользящей средней достигает круга 2 * 350-дневной скользящей средней, это указывает на то, что рынок перегревается. Это происходит потому, что опорный моментум среднего временного интервала 111-дневной скользящей средней догнал опорный момент импульса длинного таймфрейма 2 * 350-дневной скользящей средней.
Исторически это происходило в течение трех дней после вершины каждого рыночного цикла.
Когда круг 111-дневной скользящей средней опускается ниже круга 2 * 350-дневной скользящей средней, это указывает на то, что рыночный импульс этого цикла значительно снижается. Осциллятор опускается в нижнюю зеленую полосу, показанную там, где 111-дневная скользящая средняя движется со скидкой 75% относительно 2 * 350-дневной скользящей средней.
Исторически это высветило широкие области минимумов медвежьего рынка.
ВАЖНО: Выставлять нужно ЛОГАРИФМИЧЕСКИЙ график. (Находиться функция с правой нижней части экрана)
ВАЖНО: Индикатор INTELLECT_city сделан для сигнальных покупок продаж, есть также и стратегический от INTELLECT_сity
ВАЖНО: На Графике видны все циклы, как на покупку так и на продажу.
ВАЖНО: Подходящие таймфреймы 1 дневной (рекомендовано) и 1 недельный
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Beschreibung - Deutsch
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Indikatorübersicht
INTELLECT_city – Weltzyklus – ATH & ATL – Zeitrahmen 1T und 1W – Logarithmisch – Signal – Der Pi-Zyklus-Top- und Bottom-Oszillator ist eine Anpassung des ursprünglichen Pi-Zyklus-Top-Diagramms. Er vergleicht den 111-Tage-Gleitenden-Durchschnittskreis und den 2 * 350-Tage-Gleitenden-Durchschnittskreis des Bitcoin-Preises. Diese beiden gleitenden Durchschnitte wurden als 350 / 111 = 3,153 ausgewählt; eine Annäherung an die wichtige mathematische Zahl Pi.
Wenn der 111-Tage-Gleitenden-Durchschnittskreis den 2 * 350-Tage-Gleitenden-Durchschnittskreis erreicht, deutet dies darauf hin, dass der Markt überhitzt. Das liegt daran, dass der Momentum-Referenzwert des 111-Tage-Gleitenden-Durchschnitts im mittleren Zeitrahmen den Momentum-Referenzwert des 2 * 350-Tage-Gleitenden-Durchschnitts im langen Zeitrahmen eingeholt hat.
Historisch gesehen geschah dies innerhalb von 3 Tagen nach dem Höhepunkt jedes Marktzyklus.
Wenn der Kreis des 111-Tage-Durchschnitts wieder unter den Kreis des 2 x 350-Tage-Durchschnitts fällt, deutet dies darauf hin, dass die Marktdynamik dieses Zyklus deutlich nachlässt. Der Oszillator fällt in das untere grüne Band, in dem der 111-Tage-Durchschnitt mit einem Abschlag von 75 % gegenüber dem 2 x 350-Tage-Durchschnitt verläuft.
Historisch hat dies breite Bereiche mit Tiefstständen in der Baisse hervorgehoben.
WICHTIG: Sie müssen ein logarithmisches Diagramm festlegen. (Die Funktion befindet sich unten rechts auf dem Bildschirm)
WICHTIG: Der INTELLECT_city-Indikator dient zur Signalisierung von Käufen oder Verkäufen, es gibt auch einen strategischen Indikator von INTELLECT_city
WICHTIG: Das Diagramm zeigt alle Zyklen, sowohl Kauf- als auch Verkaufszyklen.
WICHTIG: Geeignete Zeitrahmen sind 1 täglich (empfohlen) und 1 wöchentlich
Multiple Oscillator Conditions Final [siulian] v2This tool is created to gather multiple oscilators condition under the same umbrela and back-test your idea.
Basically the only intention of this tool is to used in combination with a back-tester indicator ( or manually ) where you get the entry based on the cumulative signals provided by this tool.
For example you can to combine RSI , MACD, CCI, Keltner Channels or whatever indicator you think it might give you an edge for an entry signal.
You can combine up to 7 indicators either by comparing them with a static value or with another indicator (for example you can compare RSI with RSI MA, Volume with Volume MA, etc)
There are two lines which will be printed.
1) Result(blue line) - it will print 1 when all the condition are met ( the same can be used for back-testing tools)
2) Condition Met count(yellow line) - which will count how many conditions from the ones selected are triggered ( for example you have 6 indicators that are matching the conditions and you still want to take a trade even if the condition number 7 is not met)
Alarms can be setup to check if more than defined conditions are present.
As a demo in the above image i have put several condition in order to possible catch bottoms.
Please understand this is just an example on how to integrate multiple condition into a single entity and should not be used as is.
1) price should close below KC
2) CCI < - 100
3) RSI < 30
4) Vol > Vol MA
Past performance do not guarantee future performance.
Advanced Awesome Oscillator [CryptoSea]Advanced AO Analysis Indicator
The Advanced AO Analysis indicator is a sophisticated tool designed to evaluate the Awesome Oscillator (AO) in search of regular and hidden divergences that signal potential price reversals. By tracking the intensity and duration of the AO's movements, this indicator aids traders in pinpointing critical points in price action.
Key Features
Divergence Detection: Identifies both regular and hidden bullish and bearish divergences, providing early signs of potential market reversals.
Customizable Lookback Periods: Allows users to set specific lookback windows to define the strength and relevance of detected divergences.
Adaptive Oscillator Display: Features customizable display options for the AO, enabling users to view data in different modes suited to their analysis needs.
Alert System: Includes configurable alerts to notify users of potential divergence formations, helping traders respond promptly.
How it Works
AO Calculation: Computes the AO as the difference between short-term and long-term moving averages of the midpoints of bars, highlighting momentum shifts.
Pivot Point Analysis: Utilizes advanced algorithms to find low and high pivot points based on the oscillator values, crucial for spotting trend reversals.
Range Validation: Verifies that divergences occur within a predefined range from pivot points, ensuring their validity and strength.
Visualisation: Plots AO values and potential divergences directly on the chart, aiding in quick visual analysis.
Application
Strategic Decision-Making: Assists traders in making informed decisions by providing detailed analysis of AO movements and divergence.
Trend Confirmation: Reinforces trading strategies by confirming potential reversals with pivot point detection and divergence analysis.
Behavioural Insight: Offers insights into market dynamics and sentiment by analyzing the depth and duration of AO cycles above and below zero.
The Advanced AO Analysis indicator equips traders with a powerful analytical tool for studying the Awesome Oscillator in-depth, enhancing their ability to spot and act on divergence-based trading opportunities in the cryptocurrency markets.
Williams %R OB/OS Candle Coloring### Description for TradingView Publication
**Title:** Williams %R OB/OS Candle Coloring
**Description:**
This Pine Script indicator enhances the visibility of market conditions by changing the color of the candlesticks based on the Williams %R values. It helps traders quickly identify overbought and oversold conditions without the need to display the Williams %R line or any additional bands.
**How It Works:**
- The script calculates the Williams %R value using a specified lookback period (default is 14 days).
- It then compares the Williams %R value against predefined overbought and oversold levels.
- **Overbought Condition:** When the Williams %R value is greater than the upper band level (-20 by default), the candlestick color changes to blue.
- **Oversold Condition:** When the Williams %R value is less than the lower band level (-80 by default), the candlestick color changes to yellow.
**How to Use:**
1. **Input Parameters:**
- **Length:** The lookback period for calculating Williams %R (default is 14).
- **Upper Band Level:** The threshold for overbought conditions (default is -20).
- **Lower Band Level:** The threshold for oversold conditions (default is -80).
2. **Candlestick Coloring:**
- Blue candles indicate potential overbought conditions.
- Yellow candles indicate potential oversold conditions.
This indicator is designed to provide a visual cue directly on the price chart, making it easier for traders to spot extreme market conditions at a glance.
**Concepts Underlying the Calculation:**
Williams %R, developed by Larry Williams, is a momentum indicator that measures overbought and oversold levels. It compares the current closing price to the highest high and lowest low over a specified period. By using color-coded candles, traders can quickly assess market conditions and make informed decisions without the need to interpret an additional indicator line.
This script is particularly useful for traders who prefer a clean chart but still want to leverage the insights provided by the Williams %R indicator.
---
### ภาษาไทย:
**คำอธิบาย:**
สคริปต์ Pine Script ตัวนี้ช่วยเพิ่มการมองเห็นสภาวะตลาดโดยการเปลี่ยนสีของแท่งเทียนตามค่าของ Williams %R ช่วยให้เทรดเดอร์สามารถระบุสภาวะการซื้อเกินและขายเกินได้อย่างรวดเร็วโดยไม่ต้องแสดงเส้น Williams %R หรือเส้นระดับเพิ่มเติมใดๆ
**วิธีการทำงาน:**
- สคริปต์คำนวณค่าของ Williams %R โดยใช้ช่วงเวลาที่กำหนด (เริ่มต้นที่ 14 วัน)
- จากนั้นเปรียบเทียบค่าของ Williams %R กับระดับการซื้อเกินและขายเกินที่กำหนดไว้
- **สภาวะการซื้อเกิน:** เมื่อค่าของ Williams %R มากกว่าระดับ Upper Band (-20 เริ่มต้น) สีของแท่งเทียนจะเปลี่ยนเป็นสีน้ำเงิน
- **สภาวะการขายเกิน:** เมื่อค่าของ Williams %R น้อยกว่าระดับ Lower Band (-80 เริ่มต้น) สีของแท่งเทียนจะเปลี่ยนเป็นสีเหลือง
**วิธีการใช้งาน:**
1. **ค่าพารามิเตอร์:**
- **Length:** ช่วงเวลาที่ใช้คำนวณ Williams %R (เริ่มต้นที่ 14)
- **Upper Band Level:** ระดับการซื้อเกิน (เริ่มต้นที่ -20)
- **Lower Band Level:** ระดับการขายเกิน (เริ่มต้นที่ -80)
2. **การเปลี่ยนสีแท่งเทียน:**
- แท่งเทียนสีน้ำเงินระบุถึงสภาวะการซื้อเกิน
- แท่งเทียนสีเหลืองระบุถึงสภาวะการขายเกิน
อินดิเคเตอร์นี้ถูกออกแบบมาเพื่อให้สัญญาณภาพตรงบนกราฟราคาช่วยให้เทรดเดอร์สามารถมองเห็นสภาวะตลาดได้อย่างชัดเจนและทำการตัดสินใจได้ง่ายขึ้น
**แนวคิดที่อยู่เบื้องหลังการคำนวณ:**
Williams %R ที่พัฒนาโดย Larry Williams เป็นอินดิเคเตอร์โมเมนตัมที่วัดระดับการซื้อเกินและขายเกิน มันเปรียบเทียบราคาปิดปัจจุบันกับราคาสูงสุดและต่ำสุดในช่วงเวลาที่กำหนด โดยใช้แท่งเทียนที่มีการเปลี่ยนสี เทรดเดอร์สามารถประเมินสภาวะตลาดและทำการตัดสินใจได้อย่างรวดเร็วโดยไม่ต้องตีความเส้นอินดิเคเตอร์เพิ่มเติม
สคริปต์นี้มีประโยชน์โดยเฉพาะสำหรับเทรดเดอร์ที่ต้องการกราฟที่สะอาดแต่ยังต้องการใช้ข้อมูลเชิงลึกจากอินดิเคเตอร์ Williams %R
Enhanced Reversal DetectionScript Description:
The "Enhanced Reversal Detection" indicator is a powerful tool designed to identify potential market reversals across various financial instruments. It incorporates a sophisticated algorithm that analyzes price action along with key technical indicators such as the Relative Strength Index (RSI), Bollinger Bands, and Moving Average (MA).
How to Use:
Adjustable Parameters: The indicator offers a range of adjustable parameters to cater to different trading preferences and market conditions.
RSI Length: Adjusts the length of the RSI calculation to fine-tune sensitivity.
Overbought Level: Sets the threshold for identifying overbought conditions on the RSI scale.
Oversold Level: Sets the threshold for identifying oversold conditions on the RSI scale.
Bollinger Bands Length: Determines the length of the Bollinger Bands calculation.
Bollinger Bands Multiplier: Adjusts the standard deviation multiplier for the Bollinger Bands, influencing band width.
Moving Average Length: Defines the length of the Moving Average calculation to capture trend direction.
Min Bars Between Signals: Sets the minimum number of bars required between consecutive reversal signals.
ADX Length: Adjusts the length of the Average Directional Index (ADX) calculation.
ADX Threshold: Defines the threshold value for ADX, serving as a filter for reversal signals.
Signal Generation: The indicator generates signals for both bullish and bearish reversals based on predefined criteria. A bullish reversal signal is triggered when the closing price exceeds the lower Bollinger Band and RSI falls below the oversold threshold. Conversely, a bearish reversal signal occurs when the closing price falls below the upper Bollinger Band and RSI surpasses the overbought threshold.
Alerts: Traders can opt to receive alerts for bullish and bearish reversal signals, enabling them to stay informed of potential trading opportunities even when away from the platform.
Publication Readiness:
To ensure readiness for publication in the TradingView public library, the script has been meticulously crafted and documented:
The code is extensively commented to provide clear explanations of parameters, calculations, and signal generation logic.
Best coding practices have been followed to enhance readability and maintainability.
Rigorous testing has been conducted to validate the accuracy and reliability of signal generation across various market conditions.
The script adheres to TradingView's guidelines and policies for script publication, ensuring compliance with platform standards and user expectations.
With its comprehensive features and user-friendly design, the "Enhanced Reversal Detection" indicator is poised to become a valuable asset for traders seeking to identify high-probability reversal opportunities in the financial markets.
Cosine Kernel Regressions [QuantraSystems]Cosine Kernel Regressions
Introduction
The Cosine Kernel Regressions indicator (CKR) uses mathematical concepts to offer a unique approach to market analysis. This indicator employs Kernel Regressions using bespoke tunable Cosine functions in order to smoothly interpret a variety of market data, providing traders with incredibly clean insights into market trends.
The CKR is particularly useful for traders looking to understand underlying trends without the 'noise' typical in raw price movements. It can serve as a standalone trend analysis tool or be combined with other indicators for more robust trading strategies.
Legend
Fast Trend Signal Line - This is the foreground oscillator, it is colored upon the earliest confirmation of a change in trend direction.
Slow Trend Signal Line - This oscillator is calculated in a similar manner. However, it utilizes a lower frequency within the cosine tuning function, allowing it to capture longer and broader trends in one signal. This allows for tactical trading; the user can trade smaller moves without losing sight of the broader trend.
Case Study
In this case study, the CKR was used alongside the Triple Confirmation Kernel Regression Oscillator (KRO)
Initially, the KRO indicated an oversold condition, which could be interpreted as a signal to enter a long position in anticipation of a price rebound. However, the CKR’s fast trend signal line had not yet confirmed a positive trend direction - suggesting that entering a trade too early and without confirmation could be a mistake.
Waiting for a confirmed positive trend from the CKR proved beneficial for this trade. A few candles after the oversold signal, the CKR's fast trend signal line shifted upwards, indicating a strong upward momentum. This was the optimal entry point suggested by the CKR, occurring after the confirmation of the trend change, which significantly reduced the likelihood of entering during a false recovery or continuation of the downtrend.
This is one of the many uses of the CKR - by timing entries using the fast signal line , traders could avoid unnecessary losses by preventing premature entries.
Methodology
The methodology behind CKR is a multi-layered approach and utilizes many ‘base’ indicators.
Relative Strength Index
Stochastic Oscillator
Bollinger Band Percent
Chande Momentum Oscillator
Commodity Channel Index
Fisher Transform
Volume Zone Oscillator
The calculated output from each indicator is standardized and scaled before being averaged. This prevents any single indicator from overpowering the resulting signal.
// ╔════════════════════════════════╗ //
// ║ Scaling/Range Adjustment ║ //
// ╚════════════════════════════════╝ //
RSI_ReScale (_res ) => ( _res - 50 ) * 2.8
STOCH_ReScale (_stoch ) => ( _stoch - 50 ) * 2
BBPCT_ReScale (_bbpct ) => ( _bbpct - 0.5 ) * 120
CMO_ReScale (_chandeMO ) => ( _chandeMO * 1.15 )
CCI_ReScale (_cci ) => ( _cci / 2 )
FISH_ReScale (_fish1 ) => ( _fish1 * 30 )
VZO_ReScale (_VP, _TV ) => (_VP / _TV) * 110
These outputs are then fed into a customized cosine kernel regression function, which smooths the data, and combines all inputs into a single coherent output.
// ╔════════════════════════════════╗ //
// ║ COSINE KERNEL REGRESSIONS ║ //
// ╚════════════════════════════════╝ //
// Define a function to compute the cosine of an input scaled by a frequency tuner
cosine(x, z) =>
// Where x = source input
// y = function output
// z = frequency tuner
var y = 0.
y := math.cos(z * x)
Y
// Define a kernel that utilizes the cosine function
kernel(x, z) =>
var y = 0.
y := cosine(x, z)
math.abs(x) <= math.pi/(2 * z) ? math.abs(y) : 0. // cos(zx) = 0
// The above restricts the wave to positive values // when x = π / 2z
The tuning of the regression is adjustable, allowing users to fine-tune the sensitivity and responsiveness of the indicator to match specific trading strategies or market conditions. This robust methodology ensures that CKR provides a reliable and adaptable tool for market analysis.
