WD Gann: Close Price X Bars Ago with Line or Candle PlotThis indicator is inspired by the principles of WD Gann, a legendary trader known for his groundbreaking methods in time and price analysis. It helps traders track the close price of a security from X bars ago, a technique that is often used to identify key price levels in relation to past price movements. This concept is essential for Gann’s market theories, which emphasize the relationship between time and price.
WD Gann’s analysis often revolved around specific numbers that he considered significant, many of which correspond to squared numbers (e.g., 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521, 1600, 1681, 1764, 1849, 1936). These numbers are believed to represent natural rhythms and cycles in the market. This indicator can help you explore how past price levels align with these significant numbers, potentially revealing key price zones that could act as support, resistance, or reversal points.
Key Features:
- Historical Close Price Calculation: The indicator calculates and displays the close price of a security from X bars ago (where X is customizable). This method aligns with Gann's focus on price relationships over specific time intervals, providing traders with valuable reference points to assess market conditions.
- Customizable Plot Type: You can choose between two plot types for visualizing the historical close price:
- Line Plot: A simple line that represents the close price from X bars ago, ideal for those who prefer a clean and continuous representation.
- Candle Plot: Displays the close price as a candlestick chart, providing a more detailed view with open, high, low, and close prices from X bars ago.
- Candle Color Coding: For the candle plot type, the script color-codes the candles. Green candles appear when the close price from X bars ago is higher than the open price, indicating bullish sentiment; red candles appear when the close is lower, indicating bearish sentiment. This color coding gives a quick visual cue to market sentiment.
- Customizable Number of Bars: You can adjust the number of bars (X) to look back, providing flexibility for analyzing different timeframes. Whether you're conducting short-term or long-term analysis, this input can be fine-tuned to suit your trading strategy.
- Gann Method Application: WD Gann's methods involved analyzing price action over specific time periods to predict future movements. This indicator offers traders a way to assess how the price of a security has behaved in the past in relation to a chosen time interval, a critical concept in Gann's theories.
How to Use:
1. Input Settings:
- Number of Bars (X): Choose the number of bars to look back (e.g., 100, 200, or any custom period).
- Plot Type: Select whether to display the data as a Line or Candles.
2. Interpretation:
- Using the Line plot, observe how the close price from X bars ago compares to the current market price.
- Using the Candles plot, analyze the full price action of the chosen bar from X bars ago, noting how the close price relates to the open, high, and low of that bar.
3. Gann Analysis: Integrate this indicator into your broader Gann-based analysis. By looking at past price levels and their relationship to significant squared numbers, traders can uncover potential key levels of support and resistance or even potential reversal points. The historical close price can act as a benchmark for predicting future market movements.
Suggestions on WD Gann's Emphasis in Trading:
WD Gann’s trading methods were rooted in several key principles that emphasized the relationship between time and price. These principles are vital to understanding how the "Close Price X Bars Ago" indicator fits into his overall analysis:
1. Time Cycles: Gann believed that markets move in cyclical patterns. By studying price levels from specific time intervals, traders can spot these cycles and predict future market behavior. This indicator allows you to see how the close price from X bars ago relates to current market conditions, helping to spot cyclical highs and lows.
2. Price and Time Squaring: A core concept in Gann’s theory is that certain price levels and time periods align, often marking significant reversal points. The squared numbers (e.g., 1, 4, 9, 16, 25, etc.) serve as potential key levels where price and time might "square" to create support or resistance. This indicator helps traders spot these historical price levels and their potential relevance to future price action.
3. Geometric Angles: Gann used angles (like the 45-degree angle) to predict market movements, with the belief that prices move at specific geometric angles over time. This indicator gives traders a reference for past price levels, which could align with key angles, helping traders predict future price movement based on Gann's geometry.
4. Numerology and Key Intervals: Gann paid particular attention to numbers that held significance, including squared numbers and numbers related to the Fibonacci sequence. This indicator allows traders to analyze price levels based on these key numbers, which can help in identifying potential turning points in the market.
5. Support and Resistance Levels: Gann’s methods often involved identifying levels of support and resistance based on past price action. By tracking the close price from X bars ago, traders can identify past support and resistance levels that may become significant again in future market conditions.
Perfect for:
Traders using WD Gann’s methods, such as Gann angles, time cycles, and price theory.
Analysts who focus on historical price levels to predict future price action.
Those who rely on numerology and geometric principles in their trading strategies.
By integrating this indicator into your trading strategy, you gain a powerful tool for analyzing market cycles and price movements in relation to key time intervals. The ability to track and compare the historical close price to significant numbers—like Gann’s squared numbers—can provide valuable insights into potential support, resistance, and reversal points.
Disclaimer:
This indicator is based on the methods and principles of WD Gann and is for educational purposes only. It is not intended as financial advice. Trading involves significant risk, and you should not trade with money that you cannot afford to lose. Past performance is not indicative of future results. The use of this indicator is at your own discretion and risk. Always do your own research and consider consulting a licensed financial advisor before making any investment decisions.
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Pi Cycle Top & Bottom OscillatorThis TradingView script implements the Pi Cycle Top & Bottom Oscillator, a technical indicator designed to identify potential market tops and bottoms using moving average relationships. Here's a detailed breakdown:
Indicator Overview
Purpose: The indicator calculates an oscillator based on the ratio of a 111-day simple moving average (SMA) to double the 350-day SMA. It identifies potential overbought (market tops) and oversold (market bottoms) conditions.
Visualization: The oscillator is displayed in a standalone pane with dynamic color coding to represent different market conditions.
Inputs
111-Day Moving Average Length (length_111): Adjustable parameter for the short-term moving average. Default is 111 days.
350-Day Moving Average Length (length_350): Adjustable parameter for the long-term moving average. Default is 350 days.
Overheat Threshold (upper_threshold): Percentage level above which the market is considered overheated. Default is 100%.
Cooling Down Threshold (lower_threshold): Percentage level below which the market is cooling down. Default is 75%.
Calculation
Moving Averages:
111-day SMA of the closing price.
350-day SMA of the closing price.
Double the 350-day SMA (
𝑚
𝑎
_
2
_
350
=
𝑚
𝑎
_
350
×
2
ma_2_350=ma_350×2).
Oscillator:
Ratio of the 111-day SMA to double the 350-day SMA, expressed as a percentage:
oscillator
=
𝑚
𝑎
_
111
𝑚
𝑎
_
2
_
350
×
100
oscillator=
ma_2_350
ma_111
×100
Market Conditions
Overheated Market (Potential Top): Oscillator >= Overheat Threshold (100% by default). Highlighted in red.
Cooling Down Market (Potential Bottom): Oscillator <= Cooling Down Threshold (75% by default). Highlighted in green.
Normal Market Condition: Oscillator is between these thresholds. Highlighted in blue.
Visual Features
Dynamic Oscillator Plot:
Color-coded to indicate market conditions:
Red: Overheated.
Green: Cooling down.
Blue: Normal condition.
Threshold Lines:
Red Dashed Line: Overheat Threshold.
Green Dashed Line: Cooling Down Threshold.
White Dashed Line: Additional high-value marker at 30 for reference.
Alerts
Overheat Alert: Triggers when the oscillator crosses the overheat threshold, signaling a potential market top.
Cooling Down Alert: Triggers when the oscillator crosses the cooling down threshold, signaling a potential market bottom.
Use Case
This script is particularly useful for traders seeking early signals of market reversals. The thresholds and dynamic color coding provide visual cues and alerts to aid decision-making in identifying overbought or oversold conditions.
VIX OscillatorOVERVIEW
Plots an oscillating value as a percentage, derived from the VIX and VIX3M . This can help identify broader market trends and pivots on higher time frames (ie. 1D), useful when making swing trades.
DATA & MATH
The VIX is a real-time index of expected S&P 500 volatility over the next 30 days, derived from option prices with near-term expirations. Similarly, the VIX3M measures expected volatility over the next 90 days.
Dividing one by the other yields an oscillating value, normalizing the relative strength of the expected volatility. Most commonly the VIX is divided by the VIX3M. However, because the VIX is inversely correlated to market sentiment (typically), this indicator divides the VIX3M by the VIX to visually correlate the plot direction with the anticipated market direction. Further, it subtracts 1.1 from the quotient to visually center the plot, and multiplies that difference by 100 to amplify the value as a percentage:
( VIX3M / VIX - 1.1 ) * 100
This variation makes identifying sentiment extremes easier within a buy-low-sell-high paradigm, where values below zero are bearish and values above zero are bullish.
PLOTS
Two plots are used, maximizing data fidelity and convenience. Candles are used to accurately reflect the quantized math and a Linear Regression is used to simplify contextualization. If you're not familiar with what a Linear Regression is, you can think of it like a better moving average. High / Low zones are also plotted to help identify sentiment extremes.
This combination allows you to quickly identify the expected sentiment (bullish / bearish) and its relative value (normal / extreme), which you can then use to anticipate if a trend continuation or pivot is more likely.
INPUTS
Candle colors (rise and fall)
Linear regression colors and length
Zone thresholds and zero line
Cryptocurrency SentimentOverview
This script focuses on calculating and visualizing the sentiment difference between LONG positions and SHORT positions for a selected cryptocurrency pair on the Bitfinex exchange. It provides a clean and clear visual representation of the sentiment, helping traders analyze market behavior.
Key Features
Dynamic Symbol Selection:
The script automatically detects the cryptocurrency symbol from the chart (syminfo.basecurrency) and dynamically constructs the LONGS and SHORTS ticker symbols.
Works seamlessly for pairs like BTCUSD, ETHUSD, and others available on Bitfinex.
Sentiment Calculation:
The sentiment difference is calculated as:
Sentiment Difference=−1×(100− SHORTS/LONGS ×100)
LONGS : The total number of long positions.
SHORTS : The total number of short positions.
If SHORTS is 0, the value is safely skipped to avoid division errors.
Color Coding:
The script visually highlights the sentiment difference:
Green Line: Indicates that LONG positions are dominant (bullish sentiment).
Red Line: Indicates that SHORT positions are dominant (bearish sentiment).
Zero Reference Line:
A gray horizontal line at 0 helps users quickly identify the transition between bullish (above zero) and bearish (below zero) sentiment.
How It Works
Fetching Data:
The script uses request.security to fetch LONGS and SHORTS data at the current chart timeframe (timeframe.period) for the dynamically generated Bitfinex tickers.
Handling Data:
Missing or invalid data (NaN) is filtered out to prevent errors.
Extreme spikes or irregular values are safely avoided.
Visualization:
The sentiment difference is plotted with dynamic color coding:
Green when LONGS > SHORTS (bullish sentiment).
Red when SHORTS > LONGS (bearish sentiment).
Benefits
Market Sentiment Insight: Helps traders quickly identify if the market is leaning towards bullish or bearish sentiment based on actual LONG and SHORT position data.
Dynamic and Adaptive: Automatically adjusts to the selected cryptocurrency symbol on the chart.
Clean Visualization: Focuses solely on sentiment difference with color-coded signals, making it easy to interpret.
Best Use Cases
Trend Confirmation: Use the sentiment difference to confirm trends during bullish or bearish moves.
Market Reversals: Identify potential reversals when sentiment shifts from positive (green) to negative (red) or vice versa.
Sentiment Monitoring: Monitor the overall market bias for cryptocurrencies like BTC, ETH, XRP, etc., in real-time.
Sample Chart Output
Above Zero → Green Line: Bullish sentiment dominates.
Below Zero → Red Line: Bearish sentiment dominates.
Zero Line → Transition point for shifts in sentiment.
Log Regression OscillatorThe Log Regression Oscillator transforms the logarithmic regression curves into an easy-to-interpret oscillator that displays potential cycle tops/bottoms.
🔶 USAGE
Calculating the logarithmic regression of long-term swings can help show future tops/bottoms. The relationship between previous swing points is calculated and projected further. The calculated levels are directly associated with swing points, which means every swing point will change the calculation. Importantly, all levels will be updated through all bars when a new swing is detected.
The "Log Regression Oscillator" transforms the calculated levels, where the top level is regarded as 100 and the bottom level as 0. The price values are displayed in between and calculated as a ratio between the top and bottom, resulting in a clear view of where the price is situated.
The main picture contains the Logarithmic Regression Alternative on the chart to compare with this published script.
Included are the levels 30 and 70. In the example of Bitcoin, previous cycles showed a similar pattern: the bullish parabolic was halfway when the oscillator passed the 30-level, and the top was very near when passing the 70-level.
🔹 Proactive
A "Proactive" option is included, which ensures immediate calculations of tentative unconfirmed swings.
Instead of waiting 300 bars for confirmation, the "Proactive" mode will display a gray-white dot (not confirmed swing) and add the unconfirmed Swing value to the calculation.
The above example shows that the "Calculated Values" of the potential future top and bottom are adjusted, including the provisional swing.
When the swing is confirmed, the calculations are again adjusted, showing a red dot (confirmed top swing) or a green dot (confirmed bottom swing).
🔹 Dashboard
When less than two swings are available (top/bottom), this will be shown in the dashboard.
The user can lower the "Threshold" value or switch to a lower timeframe.
🔹 Notes
Logarithmic regression is typically used to model situations where growth or decay accelerates rapidly at first and then slows over time, meaning some symbols/tickers will fit better than others.
Since the logarithmic regression depends on swing values, each new value will change the calculation. A well-fitted model could not fit anymore in the future.
Users have to check the validity of swings; for example, if the direction of swings is downwards, then the dataset is not fitted for logarithmic regression.
In the example above, the "Threshold" is lowered. However, the calculated levels are unreliable due to the swings, which do not fit the model well.
Here, the combination of downward bottom swings and price accelerates slower at first and faster recently, resulting in a non-fit for the logarithmic regression model.
Note the price value (white line) is bound to a limit of 150 (upwards) and -150 (down)
In short, logarithmic regression is best used when there are enough tops/bottoms, and all tops are around 100, and all bottoms around 0.
Also, note that this indicator has been developed for a daily (or higher) timeframe chart.
🔶 DETAILS
In mathematics, the dot product or scalar product is an algebraic operation that takes two equal-length sequences of numbers (arrays) and returns a single number, the sum of the products of the corresponding entries of the two sequences of numbers.
The usual way is to loop through both arrays and sum the products.
In this case, the two arrays are transformed into a matrix, wherein in one matrix, a single column is filled with the first array values, and in the second matrix, a single row is filled with the second array values.
After this, the function matrix.mult() returns a new matrix resulting from the product between the matrices m1 and m2.
Then, the matrix.eigenvalues() function transforms this matrix into an array, where the array.sum() function finally returns the sum of the array's elements, which is the dot product.
dot(x, y)=>
if x.size() > 1 and y.size() > 1
m1 = matrix.new()
m2 = matrix.new()
m1.add_col(m1.columns(), y)
m2.add_row(m2.rows (), x)
m1.mult (m2)
.eigenvalues()
.sum()
🔶 SETTINGS
Threshold: Period used for the swing detection, with higher values returning longer-term Swing Levels.
Proactive: Tentative Swings are included with this setting enabled.
Style: Color Settings
Dashboard: Toggle, "Location" and "Text Size"
Psychological Levels- Rounding Numbers Psychological Levels Indicator
Overview:
The Psychological Levels Indicator automatically identifies and plots significant price levels based on psychological thresholds, which are key areas where market participants often focus their attention. These levels act as potential support or resistance zones due to human behavioral tendencies to round off numbers. This indicator dynamically adjusts the levels based on the stock's price range and ensures seamless visibility across the chart.
Key Features:
Dynamic Step Sizes:
The indicator adjusts the levels dynamically based on the stock price:
For prices below 500: Levels are spaced at 10.
For prices between 500 and 3000: Levels are spaced at 50, 100, and 1000.
For prices between 3000 and 10,000: Levels are spaced at 100 and 1000.
For prices above 10,000: Levels are spaced at 500 and 1000.
Extended Visibility:
The plotted levels are extended across the entire chart for improved visualization, ensuring traders can easily monitor these critical zones over time.
Customization Options:
Line Color: Choose the color for the levels to suit your charting style.
Line Style: Select from solid, dashed, or dotted lines.
Line Width: Adjust the thickness of the lines for better clarity.
Clean and Efficient Design:
The indicator only plots levels relevant to the visible chart range, avoiding unnecessary clutter and ensuring a clean workspace.
How It Works:
It calculates the relevant step sizes based on the price:
Smaller step sizes for lower-priced stocks.
Larger step sizes for higher-priced stocks.
Primary, secondary, and (if applicable) tertiary levels are plotted dynamically:
Primary Levels: The most granular levels based on the stock price.
Secondary Levels: Higher-order levels for broader significance.
Tertiary Levels: Additional levels for lower-priced stocks to enhance detail.
These levels are plotted across the chart, allowing traders to visualize key psychological areas effortlessly.
Use Cases:
Day Trading: Identify potential intraday support and resistance levels.
Swing Trading: Recognize key price zones where trends may pause or reverse.
Long-Term Investing: Gain insights into significant price zones for entry or exit strategies.
IndicatorsLibrary "Indicators"
cmf(lookback, n_to_smooth)
Calculates the Chaikin's Money Flow.
Parameters:
lookback (simple int)
n_to_smooth (simple int)
Returns: float The Money Flow value.
cmma(lookback, atr_length)
Calculates the CMMA (Close Minus Moving Average) indicator.
Parameters:
lookback (simple int)
atr_length (simple int)
Returns: float The CMMA value.
macd(fast_length, slow_length, n_to_smooth)
Calculates the normalized and scaled MACD.
Parameters:
fast_length (simple int)
slow_length (simple int)
n_to_smooth (simple int)
Returns: A tuple containing .
stochK(length, n_to_smooth)
Calculates a simplified Stochastic Oscillator.
Uses: 100 * ta.sma((close - lowest_low) / (highest_high - lowest_low), n_to_smooth)
Parameters:
length (simple int)
n_to_smooth (simple int)
Returns: float The Stochastic %K value.
williamsR(length)
Calculates the Williams %R using the stochK function.
Uses: -1 * (100 - stoch(length, 1))
Parameters:
length (simple int)
Returns: float The Williams %R value.
Scatter PlotThe Price Volume Scatter Plot publication aims to provide intrabar detail as a Scatter Plot .
🔶 USAGE
A dot is drawn at every intrabar close price and its corresponding volume , as can seen in the following example:
Price is placed against the white y-axis, where volume is represented on the orange x-axis.
🔹 More detail
A Scatter Plot can be beneficial because it shows more detail compared with a Volume Profile (seen at the right of the Scatter Plot).
The Scatter Plot is accompanied by a "Line of Best Fit" (linear regression line) to help identify the underlying direction, which can be helpful in interpretation/evaluation.
It can be set as a screener by putting multiple layouts together.
🔹 Easier Interpretation
Instead of analysing the 1-minute chart together with volume, this can be visualised in the Scatter Plot, giving a straightforward and easy-to-interpret image of intrabar volume per price level.
One of the scatter plot's advantages is that volumes at the same price level are added to each other.
A dot on the scatter plot represents the cumulated amount of volume at that particular price level, regardless of whether the price closed one or more times at that price level.
Depending on the setting "Direction" , which sets the direction of the Volume-axis, users can hoover to see the corresponding price/volume.
🔹 Highest Intrabar Volume Values
Users can display up to 5 last maximum intrabar volume values, together with the intrabar timeframe (Res)
🔹 Practical Examples
When we divide the recent bar into three parts, the following can be noticed:
Price spends most of its time in the upper part, with relative medium-low volume, since the intrabar close prices are mostly situated in the upper left quadrant.
Price spends a shorter time in the middle part, with relative medium-low volume.
Price moved rarely below 61800 (the lowest part), but it was associated with high volume. None of the intrabar close prices reached the lowest area, and the price bounced back.
In the following example, the latest weekly candle shows a rejection of the 45.8 - 48.5K area, with the highest volume at the 45.8K level.
The next three successive candles show a declining maximum intrabar volume, after which the price broke through the 45.8K area.
🔹 Visual Options
There are many visual options available.
🔹 Change Direction
The Scatter Plot can be set in 4 different directions.
🔶 NOTES
🔹 Notes
The script uses the maximum available resources to draw the price/volume dots, which are 500 boxes and 500 labels. When the population size exceeds 1000, a warning is provided ( Not all data is shown ); otherwise, only the population size is displayed.
The Scatter Plot ideally needs a chart which contains at least 100 bars. When it contains less, a warning will be shown: bars < 100, not all data is shown
🔹 LTF Settings
When 'Auto' is enabled ( Settings , LTF ), the LTF will be the nearest possible x times smaller TF than the current TF. When 'Premium' is disabled, the minimum TF will always be 1 minute to ensure TradingView plans lower than Premium don't get an error.
Examples with current Daily TF (when Premium is enabled):
500 : 3 minute LTF
1500 (default): 1 minute LTF
5000: 30 seconds LTF (1 minute if Premium is disabled)
🔶 SETTINGS
Direction: Direction of Volume-axis; Left, Right, Up or Down
🔹 LTF
LTF: LTF setting
Auto + multiple: Adjusts the initial set LTF
Premium: Enable when your TradingView plan is Premium or higher
🔹 Character
Character: Style of Price/Volume dot
Fade: Increasing this number fades dots at lower price/volume
Color
🔹 Linear Regression
Toggle (enable/disable), color, linestyle
Center Cross: Toggle, color
🔹 Background Color
Fade: Increasing this number fades the background color near lower values
Volume: Background color that intensifies as the volume value on the volume-axis increases
Price: Background color that intensifies as the price value on the price-axis increases
🔹 Labels
Size: Size of price/volume labels
Volume: Color for volume labels/axis
Price: Color for price labels/axis
Display Population Size: Show the population size + warning if it exceeds 1000
🔹 Dashboard
Location: Location of dashboard
Size: Text size
Display LTF: Display the intrabar Lower Timeframe used
Highest IB volume: Display up to 5 previous highest Intrabar Volume values
Heat Map Trend (VIDYA MA) [BigBeluga]The Heat Map Trend (VIDYA MA) - BigBeluga indicator is a multi-timeframe trend detection tool based on the Volumetric Variable Index Dynamic Average (VIDYA). This indicator calculates trends using volume momentum, or volatility if volume data is unavailable, and displays the trends across five customizable timeframes. It features a heat map to visualize trends, color-coded candles based on an average of the five timeframes, and a dashboard that shows the current trend direction for each timeframe. This tool helps traders identify trends while minimizing market noise and is particularly useful in detecting faster market changes in shorter timeframes.
🔵 KEY FEATURES & USAGE
◉ Volumetric Variable Index Dynamic Average (VIDYA):
The core of the indicator is the VIDYA moving average, which adjusts dynamically based on volume momentum. If volume data isn't available, the indicator uses volatility instead to smooth the moving average. This allows traders to assess the trend direction with more accuracy, using either volume or volatility, if volume data is not provided, as the basis for the trend calculation.
// VIDYA CALCULATION -----------------------------------------------------------------------------------------
// ATR (Average True Range) and volume calculation
bool volume_check = ta.cum(volume) <= 0
float atrVal = ta.atr(1)
float volVal = volume_check ? atrVal : volume // Use ATR if volume is not available
// @function: Calculate the VIDYA (Volumetric Variable Index Dynamic Average)
vidya(src, len, cmoLen) =>
float cmoVal = ta.sma(ta.cmo(volVal, cmoLen), 10) // Calculate the CMO and smooth it with an SMA
float absCmo = math.abs(cmoVal) // Absolute value of CMO
float alpha = 2 / (len + 1) // Alpha factor for smoothing
var float vidyaVal = 0.0 // Initialize VIDYA
vidyaVal := alpha * absCmo / 100 * src + (1 - alpha * absCmo / 100) * nz(vidyaVal ) // VIDYA formula
◉ Multi-Timeframe Trend Analysis with Heat Map Visualization:
The indicator calculates VIDYA across five customizable timeframes, allowing traders to analyze trends from multiple perspectives. The resulting trends are displayed as a heat map below the chart, where each timeframe is represented by a gradient color. The color intensity reflects the distance of the moving average (VIDYA) from the price, helping traders to identify trends on different timeframes visually. Shorter timeframes in the heat map are particularly useful for detecting faster market changes, while longer timeframes help to smooth out market noise and highlight the general trend.
Trend Direction:
Heat Map Reading:
◉ Dashboard for Multi-Timeframe Trend Directions:
The built-in dashboard displays the trend direction for each of the five timeframes, showing whether the trend is up or down. This quick overview provides traders with valuable insights into the current market conditions across multiple timeframes, helping them to assess whether the market is aligned or if there are conflicting trends. This allows for more informed decisions, especially during volatile periods.
◉ Color-Coded Candles Based on Multi-Timeframe Averages:
Candles are dynamically colored based on the average of the VIDYA across all five timeframes. When the price is in an uptrend, the candles are colored blue, while in a downtrend, they are colored red. If the VIDYA averages suggest a possible trend shift, the candles are displayed in orange to highlight a potential change in momentum. This color coding simplifies the process of identifying the dominant trend and spotting potential reversals.
BTC:
SP500:
◉ UP and DOWN Signals for Trend Direction Changes:
The indicator provides clear UP and DOWN signals to mark trend direction changes. When the average VIDYA crosses above a certain threshold, an UP signal is plotted, indicating a shift to an uptrend. Conversely, when it crosses below, a DOWN signal is shown, highlighting a transition to a downtrend. These signals help traders to quickly identify shifts in market direction and respond accordingly.
🔵 CUSTOMIZATION
VIDYA Length and Momentum Settings:
Adjust the length of the VIDYA moving average and the period for calculating volume momentum. These settings allow you to fine-tune how sensitive the indicator is to market changes, helping to match it with your preferred trading style.
Timeframe Selection:
Select five different timeframes to analyze trends simultaneously. This gives you the flexibility to focus on short-term trends, long-term trends, or a combination of both depending on your trading strategy.
Candle and Heat Map Color Customization:
Change the colors of the candles and heat map to fit your personal preferences. This customization allows you to align the visuals of the indicator with your overall chart setup, making it easier to analyze market conditions.
🔵 CONCLUSION
The Heat Trend (VIDYA MA) - BigBeluga indicator provides a comprehensive, multi-timeframe view of market trends, using VIDYA moving averages that adapt to volume momentum or volatility. Its heat map visualization, combined with a dashboard of trend directions and color-coded candles, makes it an invaluable tool for traders looking to understand both short-term market fluctuations and longer-term trends. By showing the overall market direction across multiple timeframes, it helps traders avoid market noise and focus on the bigger picture while being alert to faster shifts in shorter timeframes.
Fancy Oscillator Screener [Daveatt]⬛ OVERVIEW
Building upon LeviathanCapital original RSI Screener (), this enhanced version brings comprehensive technical analysis capabilities to your trading workflow. Through an intuitive grid display, you can monitor multiple trading instruments simultaneously while leveraging powerful indicators to identify market opportunities in real-time.
⬛ FEATURES
This script provides a sophisticated visualization system that supports both cross rates and heat map displays, allowing you to track exchange rates and percentage changes with ease. You can organize up to 40 trading pairs into seven customizable groups, making it simple to focus on specific market segments or trading strategies.
If you overlay on any circle/asset on the chart, you'll see the accurate oscillator value displayed for that asset
⬛ TECHNICAL INDICATORS
The screener supports the following oscillators:
• RSI - the oscillator from the original script version
• Awesome Oscillator
• Chaikin Oscillator
• Stochastic RSI
• Stochastic
• Volume Oscillator
• CCI
• Williams %R
• MFI
• ROC
• ATR Multiple
• ADX
• Fisher Transform
• Historical Volatility
• External : connect your own custom oscillator
⬛ DYNAMIC SCALING
One of the key improvements in this version is the implementation of dynamic chart scaling. Unlike the original script which was optimized for RSI's 0-100 range, this version automatically adjusts its scale based on the selected oscillator.
This adaptation was necessary because different indicators operate on vastly different numerical ranges - for instance, CCI typically ranges from -200 to +200, while Williams %R operates from -100 to 0.
The dynamic scaling ensures that each oscillator's data is properly displayed within its natural range, making the visualization both accurate and meaningful regardless of which indicator you choose to use.
⬛ ALERTS
I've integrated a comprehensive alert system that monitors both overbought and oversold conditions.
Users can now set custom threshold levels for their alerts.
When any asset in your monitored group crosses these thresholds, the system generates an alert, helping you catch potential trading opportunities without constant manual monitoring.
em will help you stay informed of market movements and potential trading opportunities.
I hope you'll find this tool valuable in your trading journey
All the BEST,
Daveatt
DNSE VN301!, SMA & EMA Cross StrategyDiscover the tailored Pinescript to trade VN30F1M Future Contracts intraday, the strategy focuses on SMA & EMA crosses to identify potential entry/exit points. The script closes all positions by 14:25 to avoid holding any contracts overnight.
HNX:VN301!
www.tradingview.com
Setting & Backtest result:
1-minute chart, initial capital of VND 100 million, entering 4 contracts per time, backtest result from Jan-2024 to Nov-2024 yielded a return over 40%, executed over 1,000 trades (average of 4 trades/day), winning trades rate ~ 30% with a profit factor of 1.10.
The default setting of the script:
A decent optimization is reached when SMA and EMA periods are set to 60 and 15 respectively while the Long/Short stop-loss level is set to 20 ticks (2 points) from the entry price.
Entry & Exit conditions:
Long signals are generated when ema(15) crosses over sma(60) while Short signals happen when ema(15) crosses under sma(60). Long orders are closed when ema(15) crosses under sma(60) while Short orders are closed when ema(15) crosses over sma(60).
Exit conditions happen when (whichever came first):
Another Long/Short signal is generated
The Stop-loss level is reached
The Cut-off time is reached (14:25 every day)
*Disclaimers:
Futures Contracts Trading are subjected to a high degree of risk and price movements can fluctuate significantly. This script functions as a reference source and should be used after users have clearly understood how futures trading works, accessed their risk tolerance level, and are knowledgeable of the functioning logic behind the script.
Users are solely responsible for their investment decisions, and DNSE is not responsible for any potential losses from applying such a strategy to real-life trading activities. Past performance is not indicative/guarantee of future results, kindly reach out to us should you have specific questions about this script.
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Khám phá Pinescript được thiết kế riêng để giao dịch Hợp đồng tương lai VN30F1M trong ngày, chiến lược tập trung vào các đường SMA & EMA cắt nhau để xác định các điểm vào/ra tiềm năng. Chiến lược sẽ đóng tất cả các vị thế trước 14:25 để tránh giữ bất kỳ hợp đồng nào qua đêm.
Thiết lập & Kết quả backtest:
Chart 1 phút, vốn ban đầu là 100 triệu đồng, vào 4 hợp đồng mỗi lần, kết quả backtest từ tháng 1/2024 tới tháng 11/2024 mang lại lợi nhuận trên 40%, thực hiện hơn 1.000 giao dịch (trung bình 4 giao dịch/ngày), tỷ lệ giao dịch thắng ~ 30% với hệ số lợi nhuận là 1,10.
Thiết lập mặc định của chiến lược:
Đạt được một mức tối ưu ổn khi SMA và EMA periods được đặt lần lượt là 60 và 15 trong khi mức cắt lỗ được đặt thành 20 tick (2 điểm) từ giá vào.
Điều kiện Mở và Đóng vị thế:
Tín hiệu Long được tạo ra khi ema(15) cắt trên sma(60) trong khi tín hiệu Short xảy ra khi ema(15) cắt dưới sma(60). Lệnh Long được đóng khi ema(15) cắt dưới sma(60) trong khi lệnh Short được đóng khi ema(15) cắt lên sma(60).
Điều kiện đóng vị thể xảy ra khi (tùy điều kiện nào đến trước):
Một tín hiệu Long/Short khác được tạo ra
Giá chạm mức cắt lỗ
Lệnh chưa đóng nhưng tới giờ cut-off (14:25 hàng ngày)
*Tuyên bố miễn trừ trách nhiệm:
Giao dịch hợp đồng tương lai có mức rủi ro cao và giá có thể dao động đáng kể. Chiến lược này hoạt động như một nguồn tham khảo và nên được sử dụng sau khi người dùng đã hiểu rõ cách thức giao dịch hợp đồng tương lai, đã đánh giá mức độ chấp nhận rủi ro của bản thân và hiểu rõ về logic vận hành của chiến lược này.
Người dùng hoàn toàn chịu trách nhiệm về các quyết định đầu tư của mình và DNSE không chịu trách nhiệm về bất kỳ khoản lỗ tiềm ẩn nào khi áp dụng chiến lược này vào các hoạt động giao dịch thực tế. Hiệu suất trong quá khứ không chỉ ra/cam kết kết quả trong tương lai, vui lòng liên hệ với chúng tôi nếu bạn có thắc mắc cụ thể về chiến lược giao dịch này.
Adapted RSI w/ Multi-Asset Regime Detection v1.1The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of an asset's recent price changes to detect overbought or oversold conditions in the price of said asset.
In addition to identifying overbought and oversold assets, the RSI can also indicate whether your desired asset may be primed for a trend reversal or a corrective pullback in price. It can signal when to buy and sell.
The RSI will oscillate between 0 and 100. Traditionally, an RSI reading of 70 or above indicates an overbought condition. A reading of 30 or below indicates an oversold condition.
The RSI is one of the most popular technical indicators. I intend to offer a fresh spin.
Adapted RSI w/ Multi-Asset Regime Detection
Our Adapted RSI makes necessary improvements to the original Relative Strength Index (RSI) by combining multi-timeframe analysis with multi-asset monitoring and providing traders with an efficient way to analyse market-wide conditions across different timeframes and assets simultaneously. The indicator automatically detects market regimes and generates clear signals based on RSI levels, presenting this data in an organised, easy-to-read format through two dynamic tables. Simplicity is key, and having access to more RSI data at any given time, allows traders to prepare more effectively, especially when trading markets that "move" together.
How we calculate the RSI
First, the RSI identifies price changes between periods, calculating gains and losses from one look-back period to the next. This look-back period averages gains and losses over 14 periods, which in this case would be 14 days, and those gains/losses are calculated based on the daily closing price. For example:
Average Gain = Sum of Gains over the past 14 days / 14
Average Loss = Sum of Losses over the past 14 days / 14
Then we calculate the Relative Strength (RS):
RS = Average Gain / Average Loss
Finally, this is converted to the RSI value:
RSI = 100 - (100 / (1 + RS))
Key Features
Our multi-timeframe RSI indicator enhances traditional technical analysis by offering synchronised Daily, Weekly, and Monthly RSI readings with automatic regime detection. The multi-asset monitoring system allows tracking of up to 10 different assets simultaneously, with pre-configured major pairs that can be customised to any asset selection. The signal generation system provides clear market guidance through automatic regime detection and a five-level signal system, all presented through a sophisticated visual interface with dynamic RSI line colouring and customisable display options.
Quick Guide to Use it
Begin by adding the indicator to your chart and configuring your preferred assets in the "Asset Comparison" settings.
Position the two information tables according to your preference.
The main table displays RSI analysis across three timeframes for your current asset, while the asset table shows a comparative analysis of all monitored assets.
Signals are colour-coded for instant recognition, with green indicating bullish conditions and red for bearish conditions. Pay special attention to regime changes and signal transitions, using multi-timeframe confluence to identify stronger signals.
How it Works (Regime Detection & Signals)
When we say 'Regime', a regime is determined by a persistent trend or in this case momentum and by leveraging this for RSI, which is a momentum oscillator, our indicator employs a relatively simple regime detection system that classifies market conditions as either Bullish (RSI > 50) or Bearish (RSI < 50). Our benchmark between a trending bullish or bearish market is equal to 50. By leveraging a simple classification system helps determine the probability of trend continuation and the weight given to various signals. Whilst we could determine a Neutral regime for consolidating markets, we have employed a 'neutral' signal generation which will be further discussed below...
Signal generation occurs across five distinct levels:
Strong Buy (RSI < 15)
Buy (RSI < 30)
Neutral (RSI 30-70)
Sell (RSI > 70)
Strong Sell (RSI > 85)
Each level represents different market conditions and probability scenarios. For instance, extreme readings (Strong Buy/Sell) indicate the highest probability of mean reversion, while neutral readings suggest equilibrium conditions where traders should focus on the overall regime bias (Bullish/Bearish momentum).
This approach offers traders a new and fresh spin on a popular and well-known tool in technical analysis, allowing traders to make better and more informed decisions from the well presented information across multiple assets and timeframes. Experienced and beginner traders alike, I hope you enjoy this adaptation.
RSI + Normalized Fisher Transform with SignalsThis indicator combines three tools for market analysis: the Relative Strength Index (RSI), the RSI's moving average, and the Fisher Transform. RSI is a momentum oscillator that measures the speed and change of price movements, helping identify overbought and oversold conditions. The RSI moving average is a smoothed version of the RSI that filters noise and confirms trends. The Fisher Transform is a mathematical technique that transforms price data into a Gaussian normal distribution, making it easier to identify turning points. It has been normalized to the same scale as the RSI (0-100) for consistency.
Purpose
The goal of this indicator is to identify potential buy and sell opportunities with varying degrees of strength (strong and weak). By combining the RSI, its moving average, and the Fisher Transform, the indicator ensures signals are based on both momentum and reversals, making it highly versatile across different market conditions.
Key Features
This indicator provides strong and weak buy and sell signals. A strong buy occurs when the RSI crosses above its moving average while both the RSI and its moving average are oversold (below the default threshold of 30), and the Fisher Transform reverses direction within the same or prior bar while also being oversold. A weak buy occurs when the Fisher Transform is oversold, and the RSI crosses above its moving average while its value is between the default oversold threshold (30) and 50. A strong sell occurs when the RSI crosses below its moving average while both the RSI and its moving average are overbought (above the default threshold of 70), and the Fisher Transform reverses direction within the same or prior bar while also being overbought. A weak sell occurs when the Fisher Transform is overbought, and the RSI crosses below its moving average while its value is between 50 and the default overbought threshold (70).
The indicator includes customizable thresholds and lengths. Users can adjust the oversold and overbought thresholds to suit their trading style. The RSI length, moving average length, and Fisher Transform length are also customizable. The Fisher Transform is scaled to the RSI’s range of 0-100 to simplify analysis and signal interpretation.
How to Use the Indicator
On the chart, you will see the RSI line in blue, the RSI moving average in orange, and the Fisher Transform in purple. Horizontal lines at the default oversold (30) and overbought (70) levels mark critical zones for signals. Adjust these thresholds in the indicator settings as needed.
Strong buy signals are shown as larger, darker green arrows below the price. Weak buy signals are small lime arrows below the price. Strong sell signals are larger, darker red arrows above the price. Weak sell signals are small fuchsia arrows above the price.
Signal Interpretation
A strong buy indicates a highly favorable buying opportunity. This typically occurs when the asset is in a downtrend but shows signs of reversal, particularly in oversold zones. A weak buy suggests a potential buying opportunity but with less conviction, often when the market is neutral to slightly bearish but showing upward momentum. A strong sell indicates a highly favorable selling opportunity, usually occurring when the asset is in an uptrend but shows signs of reversal, particularly in overbought zones. A weak sell suggests a potential selling opportunity but with less conviction, often in neutral to slightly bullish markets showing downward momentum.
Practical Tips
Avoid using signals in isolation. Combine this indicator with other tools such as trendlines, moving averages, or support/resistance levels for greater accuracy. Adjust the parameters for different assets to match their volatility. For volatile assets, consider wider thresholds like 20/80 for oversold/overbought levels. For less volatile assets, tighter thresholds like 35/65 may be more appropriate. Use higher timeframes to confirm signals before trading on lower timeframes. Be cautious in sideways markets, as both RSI and the Fisher Transform perform better in trending conditions.
Instructions for Adjustments
To change the oversold or overbought levels, open the indicator settings by clicking the gear icon and modify the "Oversold Threshold" and "Overbought Threshold" values. To adjust lengths for RSI and Fisher Transform, update the "RSI Length," "RSI Moving Average Length," and "Fisher Transform Length" settings. If needed, toggle signal visibility by enabling or disabling specific arrows (Strong Buy, Weak Buy, Strong Sell, Weak Sell) in the "Style" tab.
Best Practices
Risk management is essential. Always set appropriate stop-loss levels and position sizes based on your risk tolerance. Backtest the indicator on historical data to understand its performance and behavior for your chosen asset and timeframe. Combining this indicator with volume or volatility analysis (Bollinger Band Width, for example) can help confirm signal validity.
This indicator simplifies decision-making by identifying high-probability trading opportunities using a combination of momentum, trend, and reversals. Follow these instructions to fully utilize its capabilities without needing to analyze the underlying code.
Super CCI By Baljit AujlaThe indicator you've shared is a custom CCI (Commodity Channel Index) with multiple types of Moving Averages (MA) and Divergence Detection. It is designed to help traders identify trends and reversals by combining the CCI with various MAs and detecting different types of divergences between the price and the CCI.
Key Components of the Indicator:
CCI (Commodity Channel Index):
The CCI is an oscillator that measures the deviation of the price from its average price over a specific period. It helps identify overbought and oversold conditions and the strength of a trend.
The CCI is calculated by subtracting a moving average (SMA) from the price and dividing by the average deviation from the SMA. The CCI values fluctuate above and below a zero centerline.
Multiple Moving Averages (MA):
The indicator allows you to choose from a variety of moving averages to smooth the CCI line and identify trend direction or support/resistance levels. The available types of MAs include:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
HMA (Hull Moving Average)
RMA (Running Moving Average)
SMMA (Smoothed Moving Average)
TEMA (Triple Exponential Moving Average)
DEMA (Double Exponential Moving Average)
VWMA (Volume-Weighted Moving Average)
ZLEMA (Zero-Lag Exponential Moving Average)
You can select the type of MA to use with a specified length to help identify the trend direction or smooth out the CCI.
Divergence Detection:
The indicator includes a divergence detection mechanism to identify potential trend reversals. Divergences occur when the price and an oscillator like the CCI move in opposite directions, signaling a potential change in price momentum.
Four types of divergences are detected:
Bullish Divergence: Occurs when the price makes a lower low, but the CCI makes a higher low. This indicates a potential reversal to the upside.
Bearish Divergence: Occurs when the price makes a higher high, but the CCI makes a lower high. This indicates a potential reversal to the downside.
Hidden Bullish Divergence: Occurs when the price makes a higher low, but the CCI makes a lower low. This suggests a continuation of the uptrend.
Hidden Bearish Divergence: Occurs when the price makes a lower high, but the CCI makes a higher high. This suggests a continuation of the downtrend.
Each type of divergence is marked on the chart with arrows and labels to alert traders to potential trading opportunities. The labels include the divergence type (e.g., "Bull Div" for Bullish Divergence) and have customizable text colors.
Visual Representation:
The CCI and its associated moving average are plotted on the indicator panel below the price chart. The CCI is plotted as a line, and its color changes depending on whether it is above or below the moving average:
Green when the CCI is above the MA (indicating bullish momentum).
Red when the CCI is below the MA (indicating bearish momentum).
Horizontal lines are drawn at specific levels to help identify key CCI thresholds:
200 and -200 levels indicate extreme overbought or oversold conditions.
75 and -75 levels represent less extreme levels of overbought or oversold conditions.
The 0 level acts as a neutral or baseline level.
A background color fill between the 75 and -75 levels helps highlight the neutral zone.
Customization Options:
CCI Length: You can customize the length of the CCI, which determines the period over which the CCI is calculated.
MA Length: The length of the moving average applied to the CCI can also be adjusted.
MA Type: Choose from a variety of moving averages (SMA, EMA, WMA, etc.) to smooth the CCI.
Divergence Detection: The indicator automatically detects the four types of divergences (bullish, bearish, hidden bullish, hidden bearish) and visually marks them on the chart.
How to Use the Indicator:
Trend Identification: When the CCI is above the selected moving average, it suggests bullish momentum. When the CCI is below the moving average, it suggests bearish momentum.
Overbought/Oversold Conditions: The CCI values above 100 or below -100 indicate overbought and oversold conditions, respectively.
Divergence Analysis: The detection of bullish or bearish divergences can signal potential trend reversals. Hidden divergences may suggest trend continuation.
Trading Signals: You can use the divergence markers (arrows and labels) as potential buy or sell signals, depending on whether the divergence is bullish or bearish.
Practical Application:
This indicator is useful for traders who want to:
Combine the CCI with different moving averages for trend-following strategies.
Identify overbought and oversold conditions using the CCI.
Use divergence detection to anticipate potential trend reversals or continuations.
Have a highly customizable tool for various trading strategies, including trend trading, reversal trading, and divergence-based trading.
Overall, this is a comprehensive tool that combines multiple technical analysis techniques (CCI, moving averages, and divergence) in a single indicator, providing traders with a robust way to analyze price action and spot potential trading opportunities.
TechniTrend: CandleMetrics🟦 Overview
The TechniTrend: CandleMetrics Indicator is a powerful tool designed to give traders an in-depth analysis of candlestick structures. This indicator allows users to identify potential reversal points, trend continuations, and other crucial market behaviors by examining key ratios between candle components—such as body, shadow, and overall range—alongside volume conditions. The advanced filtering options offer flexibility for both novice and experienced traders, enabling tailored setups to suit different trading strategies.
🟦 Key Features
🔸Customizable Ratios: Set thresholds for Body-to-Range, Shadow-to-Range, Upper Shadow-to-Range, and Lower Shadow-to-Range ratios.
🔸Volume-Based Filters: Integrate volume conditions to strengthen the reliability of signals.
🔸Flexible Conditions: Choose whether filters should work independently or in combination, allowing for precise pattern identification.
🔸Visual Markers: Mark potential signals with a distinct background color and symbols on the chart.
🔸Alerts: Receive notifications for each selected condition, ensuring you never miss an opportunity.
🟦 How It Works
The CandleMetrics Indicator operates by analyzing the relationship between different components of each candlestick, combined with volume data to determine the strength of signals. Here’s a detailed breakdown of each feature:
🔸 Body to Range Ratio:
This filter compares the size of the candle's body to its total range (from high to low).
Example Setting: If you’re interested in spotting candles with small bodies relative to their total range, you might set the Body-to-Range Ratio to “Less than 0.3.”
🔸 Shadow to Range Ratio:
This examines the combined size of both shadows (upper and lower) relative to the entire candle range.
Example Setting: Use a Shadow-to-Range Ratio set to “More than 0.8” to find candles with significant wick lengths, suggesting market indecision.
🔸 Upper Shadow to Range Ratio:
This filter assesses the proportion of the upper shadow (wick) in relation to the candle’s full range.
Example Setting: “Less than 0.05” can help identify situations where the upper shadow is minimal, indicating strong downward pressure.
🔸 Lower Shadow to Range Ratio:
It measures the lower shadow compared to the entire candle range.
Example Setting: “More than 0.7” is useful for detecting potential rejection patterns at lower prices, hinting at a possible bullish reversal.
🔸 Volume Filter:
Integrates volume data to verify the reliability of each candle pattern.
Example Setting: Apply a Volume Filter Length of 100 with an SMA type to smooth volume data over a longer period, filtering out short-term noise and focusing on significant volume shifts.
🟦 Combining Filters
The indicator offers an option to Combine Filters. When this setting is enabled, all selected conditions must be met simultaneously for a candle to be marked. If disabled, each condition functions independently, allowing more flexibility in detecting diverse patterns.
🟦 Examples & Use Cases
🔸Example 1: Spotting Reversal Opportunities
I used the following configuration to find potential bullish reversals:
Upper Shadow to Range Ratio: “Less than 0.05” – Looking for candles with almost no upper shadow.
Lower Shadow to Range Ratio: “More than 0.7” – Highlighting candles with a significant lower shadow.
Volume Filter Length: 100 with SMA.
This setup effectively highlights candles where price rejection is happening at lower levels, suggesting a potential trend reversal to the upside.
🔸Example 2: Detecting Market Uncertainty
If you want to focus on candles showing market hesitation, try:
Shadow to Range Ratio: “More than 0.85” – Emphasizing long-wick candles that could indicate indecision.
Disable Combine Filters to allow flexibility, marking any candle meeting the above criteria.
🟦 Detailed Explanation of Each Option
Here’s a clear and concise breakdown of each option for a better understanding:
1. Body to Range Ratio
Purpose: This ratio shows how significant the candle's body is compared to its overall range. A smaller body-to-range ratio can indicate a potential reversal if the market appears indecisive.
How to Use: Increase the ratio to filter for stronger trend candles; decrease it to identify reversal or indecision candles.
2. Shadow to Range Ratio
Purpose: This filter captures the size of both shadows relative to the candle's total range. A larger ratio often points to market hesitation, while a smaller ratio suggests a decisive move.
How to Use: Adjust this filter to focus on candles with long wicks (indecision) or short wicks (decisiveness).
3. Upper Shadow to Range Ratio
Purpose: Helps to identify candles with strong downward moves by focusing on the upper wick length. A small upper shadow can imply sellers' dominance.
How to Use: Lower the ratio to detect candles with minimal upward rejection.
4. Lower Shadow to Range Ratio
Purpose: Targets candles with strong buying pressure by analyzing the lower shadow. A larger lower shadow may indicate a bullish reversal.
How to Use: Increase the ratio to spot rejection candles with significant lower shadows.
5. Volume Filter
Purpose: Adds a volume component to verify the validity of each candlestick pattern. Higher-than-average volume often signifies the strength of a move.
How to Use: Adjust the filter length and type to smooth out volume fluctuations based on your trading timeframe.
🟦 Indicator Alerts
Each filter has its own alert configuration, enabling traders to stay updated on market conditions that meet their selected criteria. You can customize alerts to trigger whenever a condition is met, helping to manage trades even when away from the screen.
Indicator DashboardThis script creates an 'Indicator Dashboard' designed to assist you in analyzing financial markets and making informed decisions. The indicator provides a summary of current market conditions by presenting various technical analysis indicators in a table format. The dashboard evaluates popular indicators such as Moving Averages, RSI, MACD, and Stochastic RSI. Below, we'll explain each part of this script in detail and its purpose:
### Overview of Indicators
1. **Moving Averages (MA)**:
- This indicator calculates Simple Moving Averages (“SMA”) for 5, 14, 20, 50, 100, and 200 periods. These averages provide a visual summary of price movements. Depending on whether the price is above or below the moving average, it determines the market direction as either “Bullish” or “Bearish.”
2. **RSI (Relative Strength Index)**:
- The RSI helps identify overbought or oversold market conditions. Here, the RSI is calculated for a 14-period window, and this value is displayed in the table. Additionally, the 14-period moving average of the RSI is also included.
3. **MACD (Moving Average Convergence Divergence)**:
- The MACD indicator is used to determine trend strength and potential reversals. This script calculates the MACD line, signal line, and histogram. The MACD condition (“Bullish,” “Bearish,” or “Neutral”) is displayed alongside the MACD and signal line values.
4. **Stochastic RSI**:
- Stochastic RSI is used to identify momentum changes in the market. The %K and %D lines are calculated to determine the market condition (“Bullish” or “Bearish”), which is displayed along with the calculated values for %K and %D.
### Table Layout and Presentation
The dashboard is presented in a vertical table format in the top-right corner of the chart. The table contains two columns: “Indicator” and “Status,” summarizing the condition of each technical indicator.
- **Indicator Column**: Lists each of the indicators being tracked, such as SMA values, RSI, MACD, etc.
- **Status Column**: Displays the current status of each indicator, such as “Bullish,” “Bearish,” or specific values like the RSI or MACD.
The table also includes rounded indicator values for easier interpretation. This helps traders quickly assess market conditions and make informed decisions based on multiple indicators presented in a single location.
### Detailed Indicator Status Calculations
1. **SMA Status**: For each moving average (5, 14, 20, 50, 100, 200), the script checks if the current price is above or below the SMA. The status is determined as “Bullish” if the price is above the SMA and “Bearish” if below, with the value of the SMA also displayed.
2. **RSI and RSI Average**: The RSI value for a 14-period is displayed along with its 14-period SMA, which provides an average reading of the RSI to smooth out volatility.
3. **MACD Indicator**: The MACD line, signal line, and histogram are calculated using standard parameters (12, 26, 9). The status is shown as “Bullish” when the MACD line is above the signal line, and “Bearish” when it is below. The exact values for the MACD line, signal line, and histogram are also included.
4. **Stochastic RSI**: The %K and %D lines of the Stochastic RSI are used to determine the trend condition. If %K is greater than %D, the condition is “Bullish,” otherwise it is “Bearish.” The actual values of %K and %D are also displayed.
### Conclusion
The 'Indicator Dashboard' provides a comprehensive overview of multiple technical indicators in a single, easy-to-read table. This allows traders to quickly gauge market conditions and make more informed decisions. By consolidating key indicators like Moving Averages, RSI, MACD, and Stochastic RSI into one dashboard, it saves time and enhances the efficiency of technical analysis.
This script is particularly useful for traders who prefer a clean and organized overview of their favorite indicators without needing to plot each one individually on the chart. Instead, all the crucial information is available at a glance in a consolidated format.
Market Session Times and Volume [Market Spotter]Market Session Times and Volume
Market Session Times
Inputs
The inputs tab consists of timezone adjustment which would be the chosen timezone for the plotting of the market sessions based on the market timings.
Further it contains settings for each box to show/hide and change box colour and timings for Asian, London and New York Sessions.
How it works
The indicator primarily works by marking the session highs and lows for the chosen time in the inputs, each of the sessions can be input a custom time value which would plot the box. It helps to identify the important price levels and the trading range for each individual session.
The midpoint of each session is marked with a dashed line. The indicator also marks a developing session while it being formed as well to identify potential secondary levels.
Usage
It can be used to trade session breakouts, false breaks and also divide the daily movement into parts and identify possible patterns while trading.
2. Volumes
Inputs
The volume part has 2 inputs - Smoothing and Normalisation. The smoothing period can simply be used to take in charge volumes of last X bars and normalisation can be used for calculating relative volumes based on last Y bars.
How it works
The indicator takes into account the buy and sell volumes of last X bars and then displays that as a relative smoothed volume which helps to identify longer term build or distribution of volume. It plots the positive volume from 0 to 100 and negative volume from 0 to -100 which has been normalised. The colors identify gradual increase or decrease in volumes
Usage
It can also be used to trade volume spikes well and can identify potential market shifts
Time Change Indicator-AYNETDetailed Scientific Explanation of the Time Change Indicator Code
This Pine Script code implements a financial indicator designed to measure and visualize the percentage change in the closing price of an asset over a specified timeframe. It uses historical data to calculate changes and displays them as a histogram for intuitive analysis. Below is a comprehensive scientific breakdown of the code:
1. User Inputs
The script begins by defining user-configurable parameters, enabling flexibility in analysis:
timeframe: The user selects the timeframe for measuring price changes (e.g., 1 hour, 1 day). This determines the granularity of the analysis.
positive_color and negative_color: Users choose the colors for positive and negative changes, enhancing visual interpretation.
2. Data Retrieval
The script employs request.security to fetch closing price data (close) for the specified timeframe. This function ensures that the indicator adapts to different timeframes, providing consistent results regardless of the chart's base timeframe.
Current Closing Price (current_close):
current_close
=
request.security(syminfo.tickerid, timeframe, close)
current_close=request.security(syminfo.tickerid, timeframe, close)
Retrieves the closing price for the defined timeframe.
Previous Closing Price (prev_close): The script uses a variable (prev_close) to store the previous closing price. This variable is updated dynamically as new data is processed.
3. Price Change Calculation
The script calculates both the absolute and percentage change in closing price:
Absolute Price Change (price_change):
price_change
=
current_close
−
prev_close
price_change=current_close−prev_close
Measures the difference between the current and previous closing prices.
Percentage Change (percent_change):
percent_change
=
price_change
prev_close
×
100
percent_change=
prev_close
price_change
×100
Normalizes the change relative to the previous closing price, making it easier to compare changes across different assets or timeframes.
4. Conditional Logic for Visualization
The script uses a conditional statement to determine the color of each histogram bar:
Positive Change: If price_change > 0, the bar is assigned the user-defined positive_color.
Negative Change: If price_change < 0, the bar is assigned the negative_color.
This differentiation provides a clear visual cue for understanding price movement direction.
5. Visualization
The script visualizes the percentage change using a histogram and enhances the chart with dynamic labels:
Histogram (plot.style_histogram):
Each bar represents the percentage change for a given timeframe.
Bars above the zero line indicate positive changes, while bars below the zero line indicate negative changes.
Zero Line (hline(0)): A reference line at zero provides a baseline for interpreting changes.
Dynamic Labels (label.new):
Each bar is annotated with its exact percentage change value.
The label's position and color correspond to the bar, improving clarity.
6. Algorithmic Flow
Data Fetching: Retrieve the current and previous closing prices for the specified timeframe.
Change Calculation: Compute the absolute and percentage changes between the two prices.
Bar Coloring: Determine the color of the histogram bar based on the change's direction.
Plotting: Visualize the changes as a histogram and add labels for precise data representation.
7. Applications
This indicator has several practical applications in financial analysis:
Volatility Analysis: By visualizing percentage changes, traders can assess the volatility of an asset over specific timeframes.
Trend Identification: Positive and negative bars highlight periods of upward or downward momentum.
Cross-Asset Comparison: Normalized percentage changes enable the comparison of price movements across different assets, regardless of their nominal values.
Market Sentiment: Persistent positive or negative changes may indicate prevailing bullish or bearish sentiment.
8. Scientific Relevance
This script applies fundamental principles of data visualization and time-series analysis:
Statistical Normalization: Percentage change provides a scale-invariant metric for comparing price movements.
Dynamic Data Processing: By updating the prev_close variable with real-time data, the script adapts to new market conditions.
Visual Communication: The use of color and labels improves the interpretability of quantitative data.
Conclusion
This indicator combines advanced Pine Script functions with robust financial analysis techniques to create an effective tool for evaluating price changes. It is highly adaptable, providing users with the ability to tailor the analysis to their specific needs. If additional features, such as smoothing or multi-timeframe analysis, are required, the code can be further extended.
Math Art with Fibonacci, Trigonometry, and Constants-AYNETScientific Explanation of the Code
This Pine Script code is a dynamic visual representation that combines mathematical constants, trigonometric functions, and Fibonacci sequences to generate geometrical patterns on a TradingView chart. The code leverages Pine Script’s drawing functions (line.new) and real-time bar data to create evolving shapes. Below is a detailed scientific explanation of its components:
1. Inputs and User-Defined Parameters
num_points: Specifies the number of points used to generate the geometrical pattern. Higher values result in more complex and smoother shapes.
scale: A scaling factor to adjust the size of the shape.
rotation: A dynamic rotation factor that evolves the shape over time based on the bar index (bar_index).
shape_color: Defines the color of the drawn shapes.
2. Mathematical Constants
The script employs essential mathematical constants:
Phi (ϕ): Known as the golden ratio
(
1
+
5
)
/
2
(1+
5
)/2, which governs proportions in Fibonacci spirals and natural growth patterns.
Pi (π): Represents the ratio of a circle's circumference to its diameter, crucial for trigonometric calculations.
Euler’s Number (e): The base of natural logarithms, incorporated in exponential growth modeling.
3. Geometric and Trigonometric Calculations
Fibonacci-Based Radius: The radius for each point is determined using a Fibonacci-inspired formula:
𝑟
=
scale
×
𝜙
⋅
𝑖
num_points
r=scale×
num_points
ϕ⋅i
Here,
𝑖
i is the point index. This ensures the shape grows proportionally based on the golden ratio.
Angle Calculation: The angular position of each point is calculated as:
𝜃
=
𝑖
⋅
Δ
𝜃
+
rotation
⋅
bar_index
100
θ=i⋅Δθ+rotation⋅
100
bar_index
where
Δ
𝜃
=
2
𝜋
num_points
Δθ=
num_points
2π
. This generates evenly spaced points along a circle, with dynamic rotation.
Coordinates: Cartesian coordinates
(
𝑥
,
𝑦
)
(x,y) for each point are derived using:
𝑥
=
𝑟
⋅
cos
(
𝜃
)
,
𝑦
=
𝑟
⋅
sin
(
𝜃
)
x=r⋅cos(θ),y=r⋅sin(θ)
These coordinates describe a polar-to-Cartesian transformation.
4. Dynamic Line Drawing
Connecting Points: For each pair of consecutive points, a line is drawn using:
line.new
(
𝑥
1
,
𝑦
1
,
𝑥
2
,
𝑦
2
)
line.new(x
1
,y
1
,x
2
,y
2
)
The coordinates are adjusted by:
bar_index: Aligns the x-axis to the chart’s time-based bar index.
int() Conversion: Ensures x-coordinates are integers, as required by line.new.
Line Properties:
Color: Set by the user.
Width: Fixed at 1 for simplicity.
5. Real-Time Adaptation
The shapes evolve dynamically as new bars form:
Rotation Over Time: The rotation parameter modifies angles proportionally to bar_index, creating a rotating effect.
Bar Index Alignment: Shapes are positioned relative to the current bar on the chart, ensuring synchronization with market data.
6. Visualization and Applications
This script generates evolving geometrical shapes, which have both aesthetic and educational value. Potential applications include:
Mathematical Visualization: Demonstrating the interplay of Fibonacci sequences, trigonometry, and geometry.
Technical Analysis: Serving as a visual overlay for price movement patterns, highlighting cyclical or wave-like behavior.
Dynamic Art: Creating visually appealing and evolving patterns on financial charts.
Scientific Relevance
This code synthesizes principles from:
Mathematical Analysis: Incorporates constants and formulas central to calculus, trigonometry, and algebra.
Geometry: Visualizes patterns derived from polar coordinates and Fibonacci scaling.
Real-Time Systems: Adapts dynamically to market data, showcasing practical applications of mathematics in financial visualization.
If further optimization or additional functionality is required, let me know! 😊
Renko Periodic Spiral of Archimedes-Secret Geometry - AYNETHow It Works
Dynamic Center:
The spiral is centered on the close price of the chart, with an optional vertical offset (center_y_offset).
Spiral Construction:
The spiral is drawn using segments_per_turn to divide each turn into small line segments.
spacing determines the radial distance between successive turns.
num_turns controls how many full rotations the spiral will have.
Line Drawing:
Each segment is computed using trigonometric functions (cos and sin) to calculate its endpoints.
These segments are drawn sequentially to form the spiral.
Inputs
Center Y Offset: Adjusts the vertical position of the spiral relative to the close price.
Number of Spiral Turns: Total number of full rotations in the spiral.
Spacing Between Turns: Distance between consecutive turns.
Segments Per Turn: Number of segments used to create each turn (higher values make the spiral smoother).
Line Color: Customize the color of the spiral lines.
Line Width: Adjust the thickness of the spiral lines.
Example
If num_turns = 5, spacing = 2, and segments_per_turn = 100:
The spiral will have 5 turns, with a radial distance of 2 between each turn, divided into 100 segments per turn.
Let me know if you have further requests or adjustments to the visualization!
CCI Threshold StrategyThe CCI Threshold Strategy is a trading approach that utilizes the Commodity Channel Index (CCI) as a momentum indicator to identify potential buy and sell signals in financial markets. The CCI is particularly effective in detecting overbought and oversold conditions, providing traders with insights into possible price reversals. This strategy is designed for use in various financial instruments, including stocks, commodities, and forex, and aims to capitalize on price movements driven by market sentiment.
Commodity Channel Index (CCI)
The CCI was developed by Donald Lambert in the 1980s and is primarily used to measure the deviation of a security's price from its average price over a specified period.
The formula for CCI is as follows:
CCI=(TypicalPrice−SMA)×0.015MeanDeviation
CCI=MeanDeviation(TypicalPrice−SMA)×0.015
where:
Typical Price = (High + Low + Close) / 3
SMA = Simple Moving Average of the Typical Price
Mean Deviation = Average of the absolute deviations from the SMA
The CCI oscillates around a zero line, with values above +100 indicating overbought conditions and values below -100 indicating oversold conditions (Lambert, 1980).
Strategy Logic
The CCI Threshold Strategy operates on the following principles:
Input Parameters:
Lookback Period: The number of periods used to calculate the CCI. A common choice is 9, as it balances responsiveness and noise.
Buy Threshold: Typically set at -90, indicating a potential oversold condition where a price reversal is likely.
Stop Loss and Take Profit: The strategy allows for risk management through customizable stop loss and take profit points.
Entry Conditions:
A long position is initiated when the CCI falls below the buy threshold of -90, indicating potential oversold levels. This condition suggests that the asset may be undervalued and due for a price increase.
Exit Conditions:
The long position is closed when the closing price exceeds the highest price of the previous day, indicating a bullish reversal. Additionally, if the stop loss or take profit thresholds are hit, the position will be exited accordingly.
Risk Management:
The strategy incorporates optional stop loss and take profit mechanisms, which can be toggled on or off based on trader preference. This allows for flexibility in risk management, aligning with individual risk tolerances and trading styles.
Benefits of the CCI Threshold Strategy
Flexibility: The CCI Threshold Strategy can be applied across different asset classes, making it versatile for various market conditions.
Objective Signals: The use of quantitative thresholds for entry and exit reduces emotional bias in trading decisions (Tversky & Kahneman, 1974).
Enhanced Risk Management: By allowing traders to set stop loss and take profit levels, the strategy aids in preserving capital and managing risk effectively.
Limitations
Market Noise: The CCI can produce false signals, especially in highly volatile markets, leading to potential losses (Bollinger, 2001).
Lagging Indicator: As a lagging indicator, the CCI may not always capture rapid market movements, resulting in missed opportunities (Pring, 2002).
Conclusion
The CCI Threshold Strategy offers a systematic approach to trading based on well-established momentum principles. By focusing on overbought and oversold conditions, traders can make informed decisions while managing risk effectively. As with any trading strategy, it is crucial to backtest the approach and adapt it to individual trading styles and market conditions.
References
Bollinger, J. (2001). Bollinger on Bollinger Bands. New York: McGraw-Hill.
Lambert, D. (1980). Commodity Channel Index. Technical Analysis of Stocks & Commodities, 2, 3-5.
Pring, M. J. (2002). Technical Analysis Explained. New York: McGraw-Hill.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
Delta Volume-ATR ChangeDelta Volume-ATR Change Indicator
The Delta Volume-ATR Change Indicator is designed to analyze the effectiveness of volume in relation to price volatility by comparing the percentage change in volume with the percentage change in ATR over the last two bars. This indicator provides insights into how volume changes impact price movement, allowing traders to gauge the strength or weakness of market momentum based on volume efficiency.
Formula:
% Volume Change = (Volume - Volume ) / Volume * 100
% ATR Change = (ATR - ATR ) / ATR * 100
Delta = % Volume Change - % ATR Change
The result, Delta, shows the difference between the volume change and ATR change, with positive delta indicating a stronger volume impact and negative delta suggesting weaker volume support relative to price movement.
Features:
Multiple Display Styles: Choose from three visualization styles — Histogram, Line, or Columns — to display delta values in a way that best fits your analysis style.
Delta Smoothing: The smoothed Delta line (using an SMA with customizable length) provides a clearer trend of volume efficiency over time.
Color Coding: Delta bars change color based on direction — green for positive values and red for negative, allowing for quick visual assessment of volume effectiveness.
Applications:
Identify market conditions where high volume is driving price effectively (positive Delta).
Detect instances of low volume efficiency, where price changes may not be fully supported by volume (negative Delta).
Useful for short-term and swing traders looking to understand volume patterns in relation to volatility.
This indicator is a valuable tool for traders seeking to gain insights into volume and volatility interplay, helping improve timing and reliability in market entries and exits.
MMRI Chart (Primary)The **Mannarino Market Risk Indicator (MMRI)** is a financial risk measurement tool created by financial strategist Gregory Mannarino. It’s designed to assess the risk level in the stock market and economy based on current bond market conditions and the strength of the U.S. dollar. The MMRI considers factors like the U.S. 10-Year Treasury Yield and the Dollar Index (DXY), which indicate investor confidence in government debt and the dollar's purchasing power, respectively.
The formula for MMRI uses the 10-Year Treasury Yield multiplied by the Dollar Index, divided by a constant (1.61) to normalize the risk measure. A higher MMRI score suggests increased market risk, while a lower score indicates more stability. Mannarino has set certain thresholds to interpret the MMRI score:
- **Below 100**: Low risk.
- **100–200**: Moderate risk.
- **200–300**: High risk.
- **Above 300**: Extreme risk, indicating market instability and potential downturns.
This tool aims to provide insight into economic conditions that may affect asset classes like stocks, bonds, and precious metals. Mannarino often updates MMRI scores and risk analyses in his public market updates.
