Dix$on's Weighted Volume FlowDixson's Weighted Volume Flow
Dixson's Weighted Volume Flow is a technical indicator designed to analyze and visualize the distribution of buy and sell volume within a given timeframe. It dynamically calculates the proportional allocation of volume based on price action within each bar, providing insights into market sentiment and activity. This indicator displays horizontal volume bars in a separate pane and annotates them with precise volume values.
How It Works
1. Volume Allocation:
- The indicator calculates buy and sell volume using the following formulas:
- Buy Volume = (Close - Low) / (High - Low) Total Volume
- Sell Volume = (High - Close) / (High - Low) Total Volume
- These formulas allocate volume proportionally based on the bar's price range, attributing more volume to buying or selling depending on the relationship between the close, high, and low prices.
2. Dynamic Scaling:
- The buy and sell volumes are scaled relative to their combined total for the period.
- The resulting values determine the length of the horizontal bars, providing a comparative view of buy and sell activity.
3. Bar Visualization:
- Buy Volume Bars: Displayed as green horizontal bars.
- Sell Volume Bars: Displayed as red horizontal bars.
- The lengths of the bars represent the dominance of buy or sell volume, scaled dynamically within the pane.
4. Labels:
- Each bar is annotated with a label showing its calculated buy or sell volume value.
5. Timeframe Adjustment:
- The indicator uses the request.security() function to fetch data from the selected timeframe, allowing users to customize their analysis for intraday, daily, or longer-term trends.
6. Customization Options:
- Enable or disable the indicator using a toggle.
- Adjust colors for the buy/sell bars and text labels to suit your chart theme.
How to Use It
1. Enable the Indicator:
- Activate the indicator using the "Enable/Disable" toggle in the settings.
2. Select a Timeframe:
- Choose the timeframe for analysis (e.g., 1-minute, 1-hour, daily). The indicator fetches volume data specific to the selected timeframe.
3. Interpret the Visualization:
- Compare Bar Lengths:
- Longer buy volume bars (green) indicate stronger buying activity.
- Longer sell volume bars (red) suggest dominant selling pressure.
- Labels:
- Use the labels to view the exact buy and sell volume values for precise analysis.
4. Combine with Other Tools:
- Use the indicator alongside price action analysis, support/resistance levels, or trend indicators to confirm market sentiment and detect potential reversals.
5. Monitor Imbalances:
- Significant disparities between buy and sell volume can signal shifts in market sentiment, such as the end of a trend or the start of a breakout.
Practical Applications
- Trend Confirmation:
- Align the dominance of buy or sell volume with price trends to confirm market direction.
- Reversal Signals:
- Watch for volume imbalances or a sudden shift in the dominance of buy or sell volume to identify potential reversals.
- High-Activity Zones:
- Identify areas with increased volume to anticipate significant price movements or key support/resistance interactions.
Dixson's Weighted Volume Flow provides a clear and systematic way to analyze market activity by visualizing the dynamics of buy and sell volume. It is particularly useful for traders looking to enhance their understanding of volume-based sentiment and its impact on price movements.
Индикаторы и стратегии
hinton_map█ HINTON MAP
This library provides functions to create and display a Hinton Map visualization. A Hinton map uses squares to represent the magnitude and direction of values in a matrix. This library allows you to display multiple ticker/timeframe/indicator combinations on a single chart, using color/boxsize/bnordersize to represent the values used. The values must be from -1.0 to 1.0 in value. 3 different values can be input per square.
Example Usage:
The example below demonstrates how to create a Hinton Map for two symbols (AAPL and MSFT) across three timeframes (1 minute, 5 minutes, and 1 day).
var hintonData = hinton_map.initHintonData(2, 3)
tickers = array.from("AAPL", "MSFT")
timeframes = array.from("1", "5", "1D")
for i = 0 to array.size(tickers) - 1
for j = 0 to array.size(timeframes) - 1
ticker = array.get(tickers, i)
timeframe = array.get(timeframes, j)
= request.security(ticker, timeframe, [close, close , ta.rsi(close, 14)], lookahead = barmerge.lookahead_on)
percent_change = (close_current - close_previous) / close_previous * 100
rsi_deviation = rsi_current - 50
hintonData.unitMatrix.set(i, j, hinton_map.createHintonUnit(
fillValue = percent_change,
borderValue = rsi_deviation,
innerValue = percent_change * rsi_deviation,
boxText = dv.from_string(str.tostring(math.round(percent_change, 2)) + "%"),
tooltipText = dv.from_string(syminfo.ticker + ", " + timeframe + ": " + str.tostring(math.round(percent_change, 2)) + "%, RSI: " + str.tostring(math.round(rsi_current, 2)))
))
hinton_map.drawHintonMap(hintonData)
█ createHintonUnit
Creates a Hinton unit.
• fillValue
Value to determine the fill color hue.
Type: float
Default Value: 0.0
• borderValue
Value to determine the border color hue and width.
Type: float
Default Value: 0.0
• innerValue
Value to determine the inner box color hue.
Type: float
Default Value: 0.0
• boxText
Text to display in the inner box.
Type: dv.DisplayValue
Default Value: na
• tooltipText
Tooltip text for the inner box.
Type: dv.DisplayValue
Default Value: na
Returns: HintonUnit
█ initHintonData
Initializes Hinton map data structure.
• rows
Number of rows.
Type: int
• columns
Number of columns.
Type: int
Returns: HintonData
█ drawHintonMap
Draws a Hinton map.
• hintonData
Hinton map data.
Type: HintonData
• unitSize
Size of each unit in bars.
Type: int
Default Value: 10
• borderWidth
Base width of the inner box border.
Type: int
Default Value: 5
• plusHue
Hue value for positive values (0-360).
Type: float
Default Value: 180
• minusHue
Hue value for negative values (0-360).
Type: float
Default Value: -30
█ HintonUnit
Data for a Hinton unit.
• fillValue
Value to determine the fill color hue.
Type: float
• borderValue
Value to determine the border color hue and width.
Type: float
• innerValue
Value to determine the inner box color hue.
Type: float
• boxText
Text to display in the inner box.
Type: dv.DisplayValue
• tooltipText
Tooltip text for the inner box.
Type: dv.DisplayValue
█ HintonData
Structure to store Hinton map data.
• unitMatrix
Matrix of Hinton units.
Type: matrix
• lineMatrix
Matrix of lines.
Type: matrix
• labelMatrix
Matrix of labels.
Type: matrix
• boxMatrix
Matrix of boxes.
Type: matrix
• fillMatrix
Matrix of line fills.
Type: matrix
Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger B# Enhanced Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands
## Overview
This indicator combines the Kaufman Adaptive Moving Average (KAMA) with Bollinger Bands to create a comprehensive trading system. It provides adaptive trend following capabilities while measuring market volatility and potential reversal points.
## Key Features
- Adaptive moving average that adjusts to market conditions
- Dynamic Bollinger Bands for volatility measurement
- Color-coded KAMA line indicating trend direction
- Integrated buy/sell signals based on multiple confirmations
- Customizable parameters for both KAMA and Bollinger Bands
- Optional bar confirmation wait feature
- Built-in alert conditions for trade signals
## Main Components
### 1. Kaufman Adaptive Moving Average (KAMA)
- Adapts to market volatility using an efficiency ratio
- Changes color based on trend direction (green for uptrend, red for downtrend)
- Adjustable parameters for fine-tuning:
- Base Length: Controls the main calculation period (default: 10)
- Fast EMA Length: For rapid market response (default: 2)
- Slow EMA Length: For stable market conditions (default: 30)
### 2. Bollinger Bands
- Standard deviation-based volatility bands
- Customizable length and standard deviation multiplier
- Includes expansion threshold for volatility measurement
- Components:
- Upper Band: Upper volatility threshold
- Middle Band: Simple moving average
- Lower Band: Lower volatility threshold
## Signal Generation
### Buy Signals
Generated when:
1. KAMA color changes from red to green
2. Price closes above KAMA
3. Price closes above the middle Bollinger Band
4. Signals are marked with:
- Green triangles below the candles
- "B" labels for easy identification
### Sell Signals
Generated when:
1. KAMA color changes from green to red
2. Price closes below KAMA
3. Price closes below the middle Bollinger Band
4. Signals are marked with:
- Red triangles above the candles
- "S" labels for easy identification
## Customizable Parameters
### KAMA Settings
- Base Length (1-50)
- Fast EMA Length (1-10)
- Slow EMA Length (10-50)
- Source Price Selection
- Direction Highlight Toggle
- Bar Confirmation Option
### Bollinger Bands Settings
- Length (default: 20)
- Standard Deviation Multiplier (default: 2.0)
- Expansion Threshold (0.1-3.0)
## Alert Functionality
Built-in alerts for:
- Buy signals with customizable messages
- Sell signals with customizable messages
## Best Practices
### Timeframe Selection
- Works well on multiple timeframes
- Recommended for 15m to 4h charts for optimal signal generation
- Higher timeframes provide more reliable trend signals
### Parameter Optimization
- Adjust KAMA lengths based on trading style:
- Shorter lengths for day trading
- Longer lengths for swing trading
- Fine-tune BB multiplier based on market volatility
- Consider waiting for bar confirmation in volatile markets
### Risk Management
- Use in conjunction with other indicators for confirmation
- Consider market conditions and volatility when trading signals
- Implement proper position sizing and stop-loss levels
## Technical Notes
- Written in Pine Script™ v6
- Overlay indicator (displays on price chart)
- Compatible with all TradingView-supported markets
- Resource-efficient implementation for smooth performance
## Disclaimer
This indicator is provided under the Mozilla Public License 2.0. While it can be a valuable tool for technical analysis, it should not be used as the sole basis for trading decisions. Always combine with proper risk management and additional analysis methods.
Quick scan for signal🙏🏻 Hey TV, this is QSFS, following:
^^ Quick scan for drift (QSFD)
^^ Quick scan for cycles (QSFC)
As mentioned before, ML trading is all about spotting any kind of non-randomness, and this metric (along with 2 previously posted) gonna help ya'll do it fast. This one will show you whether your time series possibly exhibits mean-reverting / consistent / noisy behavior, that can be later confirmed or denied by more sophisticated tools. This metric is O(n) in windowed mode and O(1) if calculated incrementally on each data update, so you can scan Ks of datasets w/o worrying about melting da ice.
^^ windowed mode
Now the post will be divided into several sections, and a couple of things I guess you’ve never seen or thought about in your life:
1) About Efficiency Ratios posted there on TV;
Some of you might say this is the Efficiency Ratio you’ve seen in Perry's book. Firstly, I can assure you that neither me nor Perry, just as X amount of quants all over the world and who knows who else, would say smth like, "I invented it," lol. This is just a thing you R&D when you need it. Secondly, I invite you (and mods & admin as well) to take a lil glimpse at the following screenshot:
^^ not cool...
So basically, all the Efficiency Ratios that were copypasted to our platform suffer the same bug: dudes don’t know how indexing works in Pine Script. I mean, it’s ok, I been doing the same mistakes as well, but loxx, cmon bro, you... If you guys ever read it, the lines 20 and 22 in da code are dedicated to you xD
2) About the metric;
This supports both moving window mode when Length > 0 and all-data expanding window mode when Length < 1, calculating incrementally from the very first data point in the series: O(n) on history, O(1) on live updates.
Now, why do I SQRT transform the result? This is a natural action since the metric (being a ratio in essence) is bounded between 0 and 1, so it can be modeled with a beta distribution. When you SQRT transform it, it still stays beta (think what happens when you apply a square root to 0.01 or 0.99), but it becomes symmetric around its typical value and starts to follow a bell-shaped curve. This can be easily checked with a normality test or by applying a set of percentiles and seeing the distances between them are almost equal.
Then I noticed that on different moving window sizes, the typical value of the metric seems to slide: higher window sizes lead to lower typical values across the moving windows. Turned out this can be modeled the same way confidence intervals are made. Lines 34 and 35 explain it all, I guess. You can see smth alike on an autocorrelogram. These two match the mean & mean + 1 stdev applied to the metric. This way, we’ve just magically received data to estimate alpha and beta parameters of the beta distribution using the method of moments. Having alpha and beta, we can now estimate everything further. Btw, there’s an alternative parameterization for beta distributions based on data length.
Now what you’ll see next is... u guys actually have no idea how deep and unrealistically minimalistic the underlying math principles are here.
I’m sure I’m not the only one in the universe who figured it out, but the thing is, it’s nowhere online or offline. By calculating higher-order moments & combining them, you can find natural adaptive thresholds that can later be used for anomaly detection/control applications for any data. No hardcoded thresholds, purely data-driven. Imma come back to this in one of the next drops, but the truest ones can already see it in this code. This way we get dem thresholds.
Your main thresholds are: basis, upper, and lower deviations. You can follow the common logic I’ve described in my previous scripts on how to use them. You just register an event when the metric goes higher/lower than a certain threshold based on what you’re looking for. Then you take the time series and confirm a certain behavior you were looking for by using an appropriate stat test. Or just run a certain strategy.
To avoid numerous triggers when the metric jitters around a threshold, you can follow this logic: forget about one threshold if touched, until another threshold is touched.
In general, when the metric gets higher than certain thresholds, like upper deviation, it means the signal is stronger than noise. You confirm it with a more sophisticated tool & run momentum strategies if drift is in place, or volatility strategies if there’s no drift in place. Otherwise, you confirm & run ~ mean-reverting strategies, regardless of whether there’s drift or not. Just don’t operate against the trend—hedge otherwise.
3) Flex;
Extension and limit thresholds based on distribution moments gonna be discussed properly later, but now you can see this:
^^ magic
Look at the thresholds—adaptive and dynamic. Do you see any optimizations? No ML, no DL, closed-form solution, but how? Just a formula based on a couple of variables? Maybe it’s just how the Universe works, but how can you know if you don’t understand how fundamentally numbers 3 and 15 are related to the normal distribution? Hm, why do they always say 3 sigmas but can’t say why? Maybe you can be different and say why?
This is the primordial power of statistical modeling.
4) Thanks;
I really wanna dedicate this to Charlotte de Witte & Marion Di Napoli, and their new track "Sanctum." It really gets you connected to the Source—I had it in my soul when I was doing all this ∞
4-Frame Trend CountThis script tracks the current close vs the close from 4 time frames prior to spot a trend reversal after 9 consecutive up or down moves.
Four Supertrend By Baljit AujlaThis Pine Script is an implementation of a "Four Supertrend" indicator by Baljit Aujla. It calculates and plots four Supertrend indicators based on the Average True Range (ATR) method, allowing for different ATR periods and multipliers for each line.
Here is an explanation of the key components:
Inputs
1:- ATR Periods: Four different periods for ATR, adjustable by the user (defaults: 10, 11, 12, 13).
2:- ATR Multipliers: Four different multipliers for the ATR, adjustable by the user (defaults: 1.0, 2.0, 3.0, 4.0).
3:- Source: The data source used for calculation, default is the average of high and low prices (hl2).
4:- Change ATR Calculation Method: Option to switch between the traditional ATR and a simple moving average of true range (SMA of TR).
5:- Signal Display- Options to show buy/sell signals and highlight trends.
Logic:
The script computes four separate Supertrend lines using the ATR method for each line. For each of the four lines, it calculates an uptrend and downtrend threshold, and the trend direction changes when the close price crosses these thresholds.
For each trend line:
1. Uptrend and Downtrend Calculation: The script uses ATR-based bands above and below the price. The uptrend line is calculated by subtracting the ATR multiplied by a given multiplier from the source price, and the downtrend line is calculated by adding the ATR multiplied by a multiplier to the source price.
2. Trend Reversal Logic: The trend switches based on the price action relative to the uptrend and downtrend lines. If the price moves above the downtrend, it signals a switch to an uptrend, and vice versa for a downtrend.
3. Signal Generation: Buy signals occur when the trend changes from negative to positive (down to up), and sell signals occur when the trend changes from positive to negative (up to down).
Plots:
The script plots:
Uptrend and Downtrend Lines: These are visualized as green and red lines for each trend.
Buy/Sell Signals: Small circles are drawn on the chart when a trend change occurs (buy and sell signals).
Trend Highlighting: Background highlighting is applied to show when the market is in an uptrend (green) or downtrend (red).
Alerts:
The script has commented-out alert conditions (alertcondition), which can be enabled to send notifications when a buy or sell signal occurs, or when a trend change happens.
Enhancements:
1. Background Highlighting: This is an option to visually emphasize uptrends and downtrends by filling the background with respective colors.
2. Signal Visibility: You can toggle whether to show the buy/sell signals on the chart.
3. ATR Calculation Method: Option to change the ATR calculation method (using SMA of TR vs the default ATR).
The script is useful for identifying multi-timeframe trends with adjustable parameters and provides both signals and visual markers on the chart to aid in trading decisions.
Issues and Improvements:
The code seems to be truncated, specifically for the last Supertrend line (Line 4). To fully complete the functionality for the fourth line, the logic for up4, down4 and tread4 needs to be finished, similar to the other three lines.
Would you like help finishing the script for the fourth line or improving specific parts of it?
Richs Market StructureThis Pine Script indicator, "Last Bullish High & Lowest Low Tracker with Timeframe Background and Fill", is designed to visually track bullish and bearish trends based on price action on the current chart and a user-defined timeframe. It provides dynamic line plotting, area fills, and background coloring to represent trend alignment between the current chart and the selected timeframe.
Features and Functionalities
Tracks Bullish Highs and Bearish Lows:
The script identifies:
Bullish High: The highest price reached after a bullish (green) candle.
Bearish Low: The lowest price reached after a bearish (red) candle.
It dynamically updates these levels based on the price movements.
Line Plotting:
Current Chart Lines:
The Plotted Bullish High line (green/red) indicates the last bullish high.
The Lowest Low line (green/red) indicates the last bearish low.
Selected Timeframe Lines:
A separate set of lines is plotted for the user-defined timeframe (e.g., daily, weekly):
A Bullish High Line for the selected timeframe (lighter green).
A Lowest Low Line for the selected timeframe (lighter red).
Dynamic Area Fills:
The area between the Plotted Bullish High and Lowest Low is filled:
Green Fill: When both lines are green (indicating a bullish alignment).
Red Fill: When both lines are red (indicating a bearish alignment).
For the selected timeframe:
The area between the timeframe-specific Bullish High and Lowest Low is similarly filled with lighter colors.
Background Color Based on Timeframe Alignment:
The background color represents the trend alignment on the selected timeframe:
Green Background: When the timeframe’s Bullish High is rising and Lowest Low is rising (bullish trend).
Red Background: When the timeframe’s Bullish High is falling and Lowest Low is falling (bearish trend).
What It’s For
This indicator is designed for traders who want to:
Visualize Trends Across Timeframes:
It helps identify when the current chart’s trend aligns with a higher timeframe trend (e.g., daily, weekly).
Useful for multi-timeframe analysis.
Spot Bullish and Bearish Trends:
The color-coded lines and fills clearly show the dominant trend on both the current chart and the selected timeframe.
Plan Trades Based on Trend Alignment:
When the current chart and selected timeframe show the same trend:
Both lines and fills turn green (bullish).
Both lines and fills turn red (bearish).
This alignment is a potential signal for entering long or short trades.
Identify Reversals and Divergences:
Divergence between the current chart and timeframe trends (e.g., green on one, red on the other) may indicate trend weakening or reversal.
Visual Elements
Lines:
Solid lines (current chart): Represent the Plotted Bullish High and Lowest Low.
Dashed/lighter lines (selected timeframe): Represent the timeframe-specific Bullish High and Lowest Low.
Fills:
Green/Red fills highlight trend zones:
On the current chart (darker).
On the selected timeframe (lighter).
Background:
The entire chart background turns green or red based on the selected timeframe’s trend alignment.
Summary
This indicator is ideal for traders who want a clear visual representation of price trends and multi-timeframe alignment. It simplifies trend-following strategies by providing:
Easy-to-interpret fills and background colors.
Clear bullish and bearish zones.
Multi-timeframe trend confirmation.
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.
RS Cycles [QuantVue]The RS Cycles indicator is a technical analysis tool that expands upon traditional relative strength (RS) by incorporating Beta-based adjustments to provide deeper insights into a stock's performance relative to a benchmark index. It identifies and visualizes positive and negative performance cycles, helping traders analyze trends and make informed decisions.
Key Concepts:
Traditional Relative Strength (RS):
Definition: A popular method to compare the performance of a stock against a benchmark index (e.g., S&P 500).
Calculation: The traditional RS line is derived as the ratio of the stock's closing price to the benchmark's closing price.
RS=Stock Price/Benchmark Price
Usage: This straightforward comparison helps traders spot periods of outperformance or underperformance relative to the market or a specific sector.
Beta-Adjusted Relative Strength (Beta RS):
Concept: Traditional RS assumes equal volatility between the stock and benchmark, but Beta RS accounts for the stock's sensitivity to market movements.
Calculation:
Beta measures the stock's return relative to the benchmark's return, adjusted by their respective volatilities.
Alpha is then computed to reflect the stock's performance above or below what Beta predicts:
Alpha=Stock Return−(Benchmark Return×β)
Significance: Beta RS highlights whether a stock outperforms the benchmark beyond what its Beta would suggest, providing a more nuanced view of relative strength.
RS Cycles:
The indicator identifies positive cycles when conditions suggest sustained outperformance:
Short-term EMA (3) > Mid-term EMA (10) > Long-term EMA (50).
The EMAs are rising, indicating positive momentum.
RS line shows upward movement over a 3-period window.
EMA(21) > 0 confirms a broader uptrend.
Negative cycles are marked when the opposite conditions are met:
Short-term EMA (3) < Mid-term EMA (10) < Long-term EMA (50).
The EMAs are falling, indicating negative momentum.
RS line shows downward movement over a 3-period window.
EMA(21) < 0 confirms a broader downtrend.
This indicator combines the simplicity of traditional RS with the analytical depth of Beta RS, making highlighting true relative strength and weakness cycles.
Awesome_Accelerator_Zone OscillatorExplanation and Usage Guide for AO_AC_ZONE Oscillator
Indicator Overview
The **AO_AC_ZONE** oscillator is based on the concepts introduced by **Bill Williams** in his book *New Trading Dimensions*. This indicator combines the **Awesome Oscillator (AO)**, **Accelerator Oscillator (AC)**, and a custom **Zone Oscillator**, visualizing them together in a clear, color-coded format.
The Zone Oscillator is derived from the relationship between AO and AC, indicating the market's dominant momentum state (bullish, bearish, or neutral). It also integrates real-time candle coloring to visually align price bars with the Zone's momentum.
---
**Components**
1. **Awesome Oscillator (AO)**:
- AO measures the difference between a 5-period and 34-period Simple Moving Average (SMA) applied to the midpoints of candles.
- It reflects market momentum, where:
- Green bars = increasing momentum
- Red bars = decreasing momentum
2. **Accelerator Oscillator (AC)**:
- AC is calculated as the difference between AO and its 5-period SMA.
- It indicates the acceleration or deceleration of market momentum.
- Fuchsia bars = increasing momentum
- Purple bars = decreasing momentum
3. **Zone Oscillator**:
- The Zone combines AO and AC states:
- **Green Zone**: Both AO and AC are positive (bullish momentum).
- **Red Zone**: Both AO and AC are negative (bearish momentum).
- **Gray Zone**: AO and AC have differing signs (neutral/uncertain momentum).
- Candle colors dynamically match the Zone’s state for enhanced visual clarity.
---
**How to Use the Indicator**
**1. Interpreting the Oscillators**
- **AO**: Use it to detect momentum direction and changes. Pay attention to shifts in bar color:
- **Increasing AO (Aqua)**: Bullish momentum gaining strength.
- **Decreasing AO (Navy)**: Bullish momentum weakening or bearish momentum strengthening.
- **AC**: Provides early signals of momentum shifts.
- If AC changes color ahead of AO, it signals potential trend reversals or accelerations.
**2. Using the Zone Oscillator**
- **Green Zone**:
- Both AO and AC are positive.
- Indicates a strong bullish trend. Look for buying opportunities in line with the trend.
- **Red Zone**:
- Both AO and AC are negative.
- Signals strong bearish momentum. Look for shorting opportunities.
- **Gray Zone**:
- AO and AC are in conflict.
- Represents uncertainty; avoid trading or wait for a clear signal.
---
**Real-Time Application**
**Candle Coloring**
- The indicator modifies candle colors to match the Zone Oscillator's state:
- **Green Candles**: Strong bullish momentum.
- **Red Candles**: Strong bearish momentum.
- **Gray Candles**: Neutral momentum.
**Recommended Strategy (Based on New Trading Dimensions)**:
1. **Identify the Zone**:
- Focus on Green Zones for long entries and Red Zones for short entries.
2. **Look for AO/AC Confirmation**:
- Enter trades in the direction of both AO and AC when they align with the Zone.
- For exits, monitor when AO and AC conflict (Gray Zone).
3. **Use in Combination**:
- Combine this oscillator with fractals or trend indicators to confirm signals.
---
**Benefits**
- Visualizes momentum strength, acceleration, and alignment in one chart.
- Simplifies decision-making by integrating price action with oscillator dynamics.
- Supports faster trade identification and execution by highlighting bullish, bearish, and neutral zones.
---
**Disclaimer**
This indicator is a tool to assist in market analysis. Always incorporate proper risk management and avoid trading during uncertain conditions (Gray Zones). For optimal results, use this oscillator in conjunction with other analysis methods like support/resistance, volume analysis, and trend-following systems.
IV Rank/Percentile with Williams VIX FixDisplay IV Rank / IV Percentile
This indicator is based on William's VixFix, which replicates the VIX—a measure of the implied volatility of the S&P 500 Index (SPX). The key advantage of the VixFix is that it can be applied to any security, not just the SPX.
IV Rank is calculated by identifying the highest and lowest implied volatility (IV) values over a selected number of past periods. It then determines where the current IV lies as a percentage between these two extremes. For example, if over the past five periods the highest IV was 30%, the lowest was 10%, and the current IV is 20%, the IV Rank would be 50%, since 20% is halfway between 10% and 30%.
IV Percentile, on the other hand, considers all past IV values—not just the highest and lowest—and calculates the percentage of these values that are below the current IV. For instance, if the past five IV values were 30%, 10%, 11%, 15%, and 17%, and the current IV is 20%, the IV Rank remains at 50%. However, the IV Percentile is 80% because 4 out of the 5 past values (80%) are below the current IV of 20%.
Real-Time Custom Candle Range Color Indicator
The script allows the user to input a custom range value (default set to 100 points) through the userDefinedRange variable. This value determines the minimum range required for a candle to change color.
Calculating Candle Range:
The script calculates the range of each candle by subtracting the low from the high price.
Determining Bullish or Bearish Candles:
It checks whether the close price is higher than the open price to determine if a candle is bullish (isBullish variable).
Coloring Candles:
Based on the custom range input, the script changes the color of the candles:
If the candle's range is greater than or equal to the custom range and it is bullish, the candle color is set to blue (bullishColor).
If the range condition is met and the candle is bearish, the color is set to orange (bearishColor).
If the range condition is not met, the color is set to na (not applicable).
Plotting Colored Candles:
The plotcandle function is used to plot candles with colors based on the custom range and bullish/bearish conditions. The candles will have a higher z-order to be displayed in front of default candles.
Displaying High and Low Price Points:
Triangular shapes are plotted at the high and low price levels using the plotshape function, with colors representing bullish (blue) and bearish (orange) conditions.
In trading, this indicator can help traders visually identify candles that meet a specific range criteria, potentially signaling strength or weakness in price movements. By customizing the range parameter, traders can adapt the indicator to different market conditions and trading strategies. It can be used in conjunction with other technical analysis tools to make informed trading decisions based on candlestick patterns and price movements.
Quantum Transform - AynetQuantum Transform Trading Indicator: Explanation
This script is called a "Quantum Transform Trading Indicator" and aims to enhance market analysis by applying complex mathematical models. Written in Pine Script, the indicator includes the following elements:
1. General Structure
Quantum Parameters: Inspired by physical and mathematical concepts (Planck constant ℏ, wave function Ψ, time τ, etc.), it uses specific parameters.
Transformation Functions: Applies various mathematical operations to transform price data in different ways.
Signal Generation: Produces signals for long and short positions.
Visualization: Displays different price transformations and signals on the chart.
2. Core Parameters
The parameters allow users to control various transformations:
Planck Constant (ℏ): A scaling factor for wave modulation.
Wave (Ψ): Controls oscillation in price data.
Time (τ): The length of the lookback period for calculations.
Relativity (γ): Power factor in the Lorentz transformation.
Phase Shift (β): Manages phase shift in transformations.
Frequency (ω): Represents the frequency of price movements.
Dimensions (∇): Enables multi-dimensional field analysis.
3. Functions
a) Relativistic Transform
Inspired by the theory of relativity.
Calculates the Lorentz factor using the rate of price change.
Transforms price data to amplify the relativity effect.
b) Phase Transform
Calculates the phase of price data and applies wave modulation.
Creates phase and amplitude modulation based on the bar index.
c) Resonance Transform
Calculates resonance effects using natural frequency and oscillations.
Highlights periodic behaviors of price movements.
d) Field Transform
Applies multi-dimensional field calculations.
Combines strength, wave, and coherence aspects of price data.
e) Chaos Transform
Implements a chaos effect based on sensitivity analysis.
Simulates chaotic behaviors of price movements.
4. Main Calculations
Quantum Price: The average of all transformation functions.
Bands:
Upper Band: The highest level of quantum price.
Lower Band: The lowest level of quantum price.
Mid Band: The average of upper and lower bands.
Momentum: Calculates the rate of change in quantum price.
5. Signal Generation
Long Signal:
Triggered when the phase price crosses above the field price.
Momentum must be positive, and the price above the mid-band.
Short Signal:
Triggered when the phase price crosses below the field price.
Momentum must be negative, and the price below the mid-band.
Signal strength is calculated relative to the momentum moving average.
6. Visualization
Each transformation is displayed in a unique color.
Bands and Momentum: Visualize price behavior.
Signal Icons: Show buy/sell signals using up/down arrows on the chart.
7. Information Panel
A table in the top-right corner of the chart displays:
The current values of each transformation.
Signal strength (as a percentage).
The type of signal (⬆: Long, ⬇: Short).
Applications
Trend Following: Analyze trends with complex transformations.
Resonance and Chaos Analysis: Understand dynamic behaviors of price.
Signal Strategies: Create strong and reliable buy/sell signals.
If you have any additional questions or customization requests regarding this indicator, feel free to ask!
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.
SMA Buy/Sell Strategy with Significant Slope and Dynamic TP/SLDescription:
This strategy uses a simple moving average (SMA) to detect trading opportunities based on the slope and proximity of price action. It ensures trades are only executed during significant trends, reducing false signals caused by sideways movements. The strategy incorporates dynamic risk management with an initial ambitious Take Profit (TP) and a Trailing Stop Loss (SL) to protect profits.
Key Features:
Trend Detection with SMA:
Two SMAs are calculated: one on High values and one on Low values.
Signals are generated when the price crosses these SMAs, ensuring:
Buy: Price closes above the SMA on High, with a significant upward slope.
Sell: Price closes below the SMA on Low, with a significant downward slope.
Slope Significance Check:
The slope of the SMA is calculated over a configurable period.
Only trends with a slope variation exceeding a user-defined percentage threshold are considered significant.
Dynamic Risk Management:
Ambitious Initial TP: Positions target a high percentage gain upon entry.
Trailing SL: Automatically adjusts as the price moves in favor of the trade, locking in profits.
Automatic Position Management:
Opposing signals close existing positions to avoid conflicting trades.
Configurable position size for risk control.
Parameters:
SMA Period: Number of candles for calculating the SMA.
Initial Take Profit (%): Percentage gain for the initial TP.
Trailing Stop Loss (%): Percentage for trailing SL based on the current price.
Slope Threshold (%): Minimum percentage change in SMA slope to confirm trend significance.
How It Works:
Buy Signal:
The price closes above the SMA on High values.
The slope of the SMA (on High) is positive and exceeds the slope threshold.
Sell Signal:
The price closes below the SMA on Low values.
The slope of the SMA (on Low) is negative and exceeds the slope threshold.
Exits:
A position closes at the Take Profit level, Trailing Stop Loss, or when an opposing signal is generated.
Use Case:
This strategy is ideal for trending markets where price action respects moving averages. It can be used on any timeframe or asset but is particularly effective in markets with clear directional movements.
Recommended Settings:
Timeframe: Works well on higher timeframes (e.g., 1H, 4H, Daily).
Slope Threshold (%): Default is 5%, adjust based on market volatility.
Initial TP and Trailing SL: Tailor to your risk/reward preferences.
By utilizing this strategy, traders can capitalize on significant market trends while dynamically managing risk. Test it on historical data to optimize the parameters for your preferred market!
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.
libTFLibrary "libTF"
libTF: Find higher/lower TF automatically
This library to find higher/lower TF from current timeframe(timeframe.period) for Pine Script version6(or higher).
Basic Algorithm
Using a timeframe scale Array and timeframe.in_seconds() function to find higher/lower timeframe.
Return value is na if could not find TF in the timeframe scale.
The timeframe scale could be changed by the parameter 'scale'(CSV).
How to use
1. Set higher/lower TF
higher()/lower() function returns higher/lower TF.
Default timeframe scale is "1, 5, 15, 60, 240, 1D, 1M, 3M, 12M".
example:
htf1 = higher()
htf2 = higher(htf1)
ltf1 = lower()
ltf2 = lower(ltf1)
2. Set higher/lower TF using your timeframe scale
The timeframe scale could be changed by the parameter.
example:
myscale="1,60,1D,1M,12M"
htf1 = higher(timeframe.period,myscale)
htf2 = higher(htf1,myscale)
ltf1 = lower(timeframe.period,myscale)
ltf2 = lower(ltf1,myscale)
3. How to use with request.*() function
na value is set if no higher/lower TF in timeframe scale.
It returns current timeframe's value, when na value as timeframe parameter in request.*().
As bellow, if it should be na when timeframe is na.
example:
return_value_request_htf1 = na(htf1)?na:request.security(syminfo.tickerid,htf1,timeframe.period)
return_value_request_ltf1 = na(ltf1)?na:request.security(syminfo.tickerid,ltf1,timeframe.period)
higher(tf, scale)
higher: find higher TF from TF string.
Parameters:
tf (string) : default value is timeframe.period.
scale (string) : TF scale in CSV. default is "1,5,15,60,240,1D,1W,1M,3M,12M".
Returns: higher TF string.
lower(tf, scale)
lower: find lower TF from TF string.
Parameters:
tf (string) : default value is timeframe.period.
scale (string) : TF scale in CSV. defalut is "1,5,15,60,240,1D,1W,1M,3M,12M".
Returns: lower TF string.
Market GhostGhost Candles: Volume-Based Transparency Indicator
Before adding the indicator to the chart, hide the chart candles (the chart would get blank) otherwise no changes will be visible on your chart due to the display of the original candles (transparencies won't be visible because the full-opaque candles cover them)
This unique indicator dynamically adjusts the transparency of candles based on their volume relative to the past X candles. Candles with low volume become more transparent, while those with higher volume appear more opaque, creating a smooth gradient effect. This allows for a visual representation of market activity where low-volume candles "fade" into the background, making high-volume candles stand out more clearly.
Customizable Lookback Period: Adjust the lookback period (X candles) to suit your analysis.
Volume-Based Visualization: A smooth gradient of transparency helps to visualize volume strength relative to recent market activity.
Unique Aesthetic: Adds a unique, "ghostly" aesthetic to the chart, ideal for identifying volume trends without the clutter of traditional indicators.
This script is perfect for traders who want to visually highlight volume strength while maintaining a clean, easy-to-read chart.
Azlan MA Silang PLUS++Overview
Azlan MA Silang PLUS++ is an advanced moving average crossover trading indicator designed for traders who want to jump back into the market when they missed their first opportunity to take a trade. It implements a sophisticated dual moving average system with customizable settings and re-entry signals, making it suitable for both trend following and swing trading strategies.
Key Features
• Dual Moving Average System with multiple MA types (EMA, SMA, WMA, LWMA)
• Customizable price sources for each moving average
• Smart re-entry system with configurable maximum re-entries
• Visual signals with background coloring and shape markers
• Comprehensive alert system for both initial and re-entry signals
• Flexible parameter customization through input options
Input Parameters
Moving Average Configuration
• MA1 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA2 Type: Choice between SMA, EMA, WMA, LWMA (default: EMA)
• MA1 Length: Minimum value 1 (default: 8)
• MA2 Length: Minimum value 1 (default: 15)
• MA1 & MA2 Shift: Offset values for moving averages
• Price Sources: Configurable for each MA (Open, High, Low, Close, HL/2, HLC/3, HLCC/4)
Re-entry System
• Enable/Disable re-entry signals
• Maximum re-entries allowed (default: 3)
Technical Implementation
Price Source Calculation
The script implements a flexible price source system through the price_source() function:
• Supports standard OHLC values
• Includes compound calculations (HL/2, HLC/3, HLCC/4)
• Defaults to close price if invalid source specified
Moving Average Types
Implements four MA calculations:
1. SMA (Simple Moving Average)
2. EMA (Exponential Moving Average)
3. WMA (Weighted Moving Average)
4. LWMA (Linear Weighted Moving Average)
Signal Generation Logic
Initial Signals
• Buy Signal: MA1 crosses above MA2 with price above both MAs
• Sell Signal: MA1 crosses below MA2 with price below both MAs
Re-entry Signals
Re-entry system activates when:
1. Price crosses under MA1 in buy mode (or over in sell mode)
2. Price returns to cross back over MA1 (or under for sells)
3. Position relative to MA2 confirms trend direction
4. Number of re-entries hasn't exceeded maximum allowed
Visual Components
• MA1: Blue line (width: 2)
• MA2: Red line (width: 2)
• Background Colors:
o Green (60% opacity): Bullish conditions
o Red (60% opacity): Bearish conditions
• Signal Markers:
o Initial Buy/Sell: Up/Down arrows with "BUY"/"SELL" labels
o Re-entry Buy/Sell: Up/Down arrows with "RE-BUY"/"RE-SELL" labels
Alert System
Generates alerts for:
• Initial buy/sell signals
• Re-entry opportunities
• Alerts include ticker and timeframe information
• Configured for once-per-bar-close frequency
Usage Tips
1. Moving Average Selection
o Shorter periods (MA1) capture faster moves
o Longer periods (MA2) identify overall trend
o EMA responds faster to price changes than SMA
2. Re-entry System
o Best used in strong trending markets
o Limit maximum re-entries based on market volatility
o Monitor price action around MA1 for potential re-entry points
3. Risk Management
o Use additional confirmation indicators
o Set appropriate stop-loss levels
o Consider market conditions when using re-entry signals
Code Structure
The script follows a modular design with distinct sections:
1. Input parameter definitions
2. Helper functions for price and MA calculations
3. Main signal generation logic
4. Visual elements and plotting
5. Alert system implementation
This organization makes the code maintainable and easy to modify for custom needs.
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
Trend FinderEnglish
Trend Finder is an indicator designed to identify breakouts and breakdowns based on specified timeframes. It monitors the previous high and low prices and changes the bar color when the current close price surpasses these levels.
Features
Customizable Timeframes: Set your preferred high/low and close resolutions.
Visual Alerts: Bars turn lime green on breakout above the previous high and red on breakdown below the previous low.
Alert Conditions: Receive notifications when significant price movements occur.
日本語
Trend Finderは、指定した時間枠に基づいてブレイクアウトとブレイクダウンを識別するためのインジケーターです。前日の高値と安値を監視し、現在の終値がこれらのレベルを超えたときにバーの色を変更します。
特徴
カスタマイズ可能な時間枠 高値/安値と終値の解像度を設定可能。
視覚的アラート 前日の高値を超えるとバーがライムグリーンに、安値を下回ると赤に変化。
アラート条件 重要な価格変動時に通知を受け取れます。
Chart Example
Disclaimer
This indicator is for educational purposes only and should not be considered as financial advice. Always perform your own analysis before making trading decisions.
Breaks and Retests - Free990Strategy Description: "Breaks and Retests - Free990"
The "Breaks and Retests - Free990" strategy is based on identifying breakout and retest opportunities for potential entries in both long and short trades. The idea is to detect price breakouts above resistance levels or below support levels, and subsequently identify retests that confirm the breakout levels. The strategy offers an automated approach to enter trades after a breakout followed by a retest, which serves as a confirmation of trend continuation.
Key Components:
Support and Resistance Detection:
The strategy calculates pivot levels based on historical price movements to define support and resistance areas. A lookback range is used to determine these key levels.
Breakouts and Retests:
The system identifies when a breakout occurs above a resistance level or below a support level.
It then waits for a retest of the previously broken level as confirmation, which is often a better entry opportunity.
Trade Direction Selection:
Users can choose between "Long Only," "Short Only," or "Both" directions for trading based on their market view.
Stop Loss and Trailing Stop:
An initial stop loss is placed at a defined percentage away from the entry.
The trailing stop loss is activated after the position gains a specified percentage in profit.
Long Entry:
A long entry is triggered if the price breaks above a resistance level and subsequently retests that level successfully.
The entry condition checks if the breakout was confirmed and if a retest was valid.
The long entry is only executed if the user-selected direction is either "Long Only" or "Both."
Short Entry:
A short entry is triggered if the price breaks below a support level and subsequently retests that level.
The short entry is only executed if the user-selected direction is either "Short Only" or "Both."
sell_condition checks whether the support has been broken and whether the retest condition is valid.
An initial stop loss is placed when the trade is opened to limit the risk if the trade moves against the position.
The stop loss is calculated based on a user-defined percentage (stop_loss_percent) of the entry price.
pinescript
Copy code
stop_loss_price := strategy.position_avg_price * (1 - stop_loss_percent / 100)
For long positions, the stop loss is placed below the entry price.
For short positions, the stop loss is placed above the entry price.
Trailing Stop:
When a position achieves a certain profit threshold (profit_threshold_percent), the trailing stop mechanism is activated.
For long positions, the trailing stop follows the highest price reached, ensuring that some profit is locked in if the price reverses.
For short positions, the trailing stop follows the lowest price reached.
Code Logic for Trailing Stop:
Exit Execution:
The strategy exits the position when the price hits the calculated stop loss level.
This includes both the initial stop loss and the trailing stop that adjusts as the trade progresses.
Code Logic for Exit:
Summary:
Breaks and Retests - Free990 uses support and resistance levels to identify breakouts, followed by retests for confirmation.
Entry Points: Triggered when a breakout is confirmed and a retest occurs, for both long and short trades.
Exit Points:
Initial Stop Loss: Limits risk for both long and short trades.
Trailing Stop Loss: Locks in profits as the price moves in favor of the position.
This strategy aims to capture the momentum after breakouts and minimize losses through effective use of stop loss and trailing stops. It gives the flexibility of selecting trade direction and ensures trades are taken with confirmation through the retest, which helps to reduce false breakouts.
Original Code by @HoanGhetti
MTF ADX TableThis Indicator displays a table on the chart with the Average Directional Index (ADX) values for two different timeframes. It calculates the ADX using a custom formula and shows the ADX values along with their corresponding timeframes. The table's position, font size, and background color can be customized, and the timeframes are labeled with "ADX" appended to their unit (e.g., "5m ADX", "1D ADX"). The table updates dynamically with the latest ADX values for each timeframe. The indicator also provides a rating, based of the thresholds settings
