Average Up and Down Candles Streak with Predicted Next CandleThis indicator is designed to analyze price trends by examining the patterns of up and down streaks (consecutive bullish or bearish candles) over a defined period. It uses this data to provide insights on whether the next candle is likely to be bullish or bearish, and it visually displays relevant information on the chart.
Here’s a breakdown of what the indicator does:
1. Inputs and Parameters
Period (Candles): Defines the number of candles used to calculate the average length of bullish and bearish streaks. For example, if the period is set to 20, the indicator will analyze the past 20 candles to determine average up and down streak lengths.
Bullish/Bearish Bias Signal Toggle: These options allow users to show or hide visual signals (green or red circles) when there’s a bullish or bearish bias in the trend based on the indicator’s calculations.
2. Streak Calculation
The indicator looks at each candle within the period to identify if it closed up (bullish) or down (bearish).
Up Streak: The indicator counts consecutive bullish candles. When there’s a bearish candle, it resets the up streak count.
Down Streak: Similarly, it counts consecutive bearish candles and resets when a bullish candle appears.
Averages: Over the defined period, the indicator calculates the average length of up streaks and average length of down streaks. This provides a baseline to assess whether the current streak is typical or extended.
3. Current and Average Streak Display
The indicator displays the current up and down streak lengths alongside the average streak lengths for comparison. This data appears in a table on the chart, allowing you to see at a glance:
The current streak length (for both up and down trends)
The average streak length for up and down trends over the chosen period
4. Trend Prediction for the Next Candle
Next Candle Prediction: Based on the current streak and its comparison to the average, the indicator predicts the likely direction of the next candle:
Bullish: If the current up streak is shorter than the average up streak, suggesting that the bullish trend could continue.
Bearish: If the current down streak is shorter than the average down streak, indicating that the bearish trend may continue.
Neutral: If the current streak length is near the average, which could signal an upcoming reversal.
This prediction appears in a table on the chart, labeled as “Next Candle.”
5. Previous Candle Analysis
The Previous Candle entry in the table reflects the last completed candle (directly before the current candle) to show whether it was bullish, bearish, or neutral.
This data gives a reference point for recent price action and helps validate the next candle prediction.
6. Visual Signals and Reversal Zones
Bullish/Bearish Bias Signals: The indicator can plot green circles on bullish bias and red circles on bearish bias to highlight points where the trend is likely to continue.
Reversal Zones: If the current streak length reaches or exceeds the average, it suggests the trend may be overextended, indicating a potential reversal zone. The indicator highlights these zones with shaded backgrounds (green for possible bullish reversal, red for bearish) on the chart.
Summary of What You See on the Chart
Bullish and Bearish Bias Signals: Green or red circles mark areas of expected continuation in the trend.
Reversal Zones: Shaded areas in red or green suggest that the trend might be about to reverse.
Tables:
The Next Candle prediction table displays the trend direction of the previous candle and the likely trend of the next candle.
The Streak Information table shows the current up and down streak lengths, along with their averages for easy comparison.
Practical Use
This indicator is helpful for traders aiming to understand trend momentum and potential reversals based on historical patterns. It’s particularly useful for swing trading, where knowing the typical length of bullish or bearish trends can help in timing entries and exits.
Indicators and strategies
VPA Volume Price AverageDescription:
This indicator displays a moving average of volume and its signal line in a separate pane, with conditional highlighting to help interpret buyer and seller pressure. It’s based on two main lines:
Volume Moving Average (red line) : represents the average volume calculated over a configurable number of periods.
Signal Line of the Volume Moving Average (blue line): this is an average of the volume moving average itself, used as a reference for volume trends.
Key Features
Volume Moving Average with Conditional Highlighting:
The volume moving average is plotted as a red line and changes color based on two specific conditions:
The closing price is above its moving average, calculated over a configurable number of periods, indicating a bullish trend.
The volume moving average is greater than the signal line, suggesting an increase in buyer pressure.
When both conditions are met, the volume moving average turns green. If one or both conditions are not met, the line remains red.
Signal Line of the Volume Moving Average:
The signal line is plotted in blue and represents a smoothed version of the volume moving average, useful for identifying long-term volume trends and as a reference for the highlighting condition.
Customizable Periods
The indicator allows you to set the periods for each average to adapt to different timeframes and desired sensitivity:
Period for calculating the volume moving average.
Period for calculating the signal line of the volume moving average.
Period for the price moving average (used in the highlighting condition).
How to Use
This indicator is especially useful for monitoring volume dynamics in detail, with a visual system that highlights conditions of increasing buyer strength when the price is in an uptrend. The green highlight on the volume moving average provides an intuitive signal for identifying potential moments of buyer support.
Try it to gain a clearer and more focused view of volume behavior relative to price movement!
RawCuts_01Library "RawCuts_01"
A collection of functions by:
mutantdog
The majority of these are used within published projects, some useful variants have been included here aswell.
This is volume one consisting mainly of smaller functions, predominantly the filters and standard deviations from Weight Gain 4000.
Also included at the bottom are various snippets of related code for demonstration. These can be copied and adjusted according to your needs.
A full up-to-date table of contents is located at the top of the main script.
WEIGHT GAIN FILTERS
A collection of moving average type filters with adjustable volume weighting.
Based upon the two most common methods of volume weighting.
'Simple' uses the standard method in which a basic VWMA is analogous to SMA.
'Elastic' uses exponential method found in EVWMA which is analogous to RMA.
Volume weighting is applied according to an exponent multiplier of input volume.
0 >> volume^0 (unweighted), 1 >> volume^1 (fully weighted), use float values for intermediate weighting.
Additional volume filter switch for smoothing of outlier events.
DIVA MODULAR DEVIATIONS
A small collection of standard and absolute deviations.
Includes the weightgain functionality as above.
Basic modular functionality for more creative uses.
Optional input (ct) for external central tendency (aka: estimator).
Can be assigned to alternative filter or any float value. Will default to internal filter when no ct input is received.
Some other useful or related functions included at the bottom along with basic demonstration use.
weightgain_sma(src, len, xVol, fVol)
Simple Moving Average (SMA): Weight Gain (Simple Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Standard Simple Moving Average with Simple Weight Gain applied.
weightgain_hsma(src, len, xVol, fVol)
Harmonic Simple Moving Average (hSMA): Weight Gain (Simple Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Harmonic Simple Moving Average with Simple Weight Gain applied.
weightgain_gsma(src, len, xVol, fVol)
Geometric Simple Moving Average (gSMA): Weight Gain (Simple Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Geometric Simple Moving Average with Simple Weight Gain applied.
weightgain_wma(src, len, xVol, fVol)
Linear Weighted Moving Average (WMA): Weight Gain (Simple Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Basic Linear Weighted Moving Average with Simple Weight Gain applied.
weightgain_hma(src, len, xVol, fVol)
Hull Moving Average (HMA): Weight Gain (Simple Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Basic Hull Moving Average with Simple Weight Gain applied.
diva_sd_sma(src, len, xVol, fVol, ct)
Standard Deviation (SD SMA): Diva / Weight Gain (Simple Volume)
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_sma().
Returns:
diva_sd_wma(src, len, xVol, fVol, ct)
Standard Deviation (SD WMA): Diva / Weight Gain (Simple Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_wma().
Returns:
diva_aad_sma(src, len, xVol, fVol, ct)
Average Absolute Deviation (AAD SMA): Diva / Weight Gain (Simple Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_sma().
Returns:
diva_aad_wma(src, len, xVol, fVol, ct)
Average Absolute Deviation (AAD WMA): Diva / Weight Gain (Simple Volume) .
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_wma().
Returns:
weightgain_ema(src, len, xVol, fVol)
Exponential Moving Average (EMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Exponential Moving Average with Elastic Weight Gain applied.
weightgain_dema(src, len, xVol, fVol)
Double Exponential Moving Average (DEMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Double Exponential Moving Average with Elastic Weight Gain applied.
weightgain_tema(src, len, xVol, fVol)
Triple Exponential Moving Average (TEMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Triple Exponential Moving Average with Elastic Weight Gain applied.
weightgain_rma(src, len, xVol, fVol)
Rolling Moving Average (RMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Rolling Moving Average with Elastic Weight Gain applied.
weightgain_drma(src, len, xVol, fVol)
Double Rolling Moving Average (DRMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Double Rolling Moving Average with Elastic Weight Gain applied.
weightgain_trma(src, len, xVol, fVol)
Triple Rolling Moving Average (TRMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: Triple Rolling Moving Average with Elastic Weight Gain applied.
diva_sd_ema(src, len, xVol, fVol, ct)
Standard Deviation (SD EMA): Diva / Weight Gain: (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_ema().
Returns:
diva_sd_rma(src, len, xVol, fVol, ct)
Standard Deviation (SD RMA): Diva / Weight Gain: (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_rma().
Returns:
weightgain_vidya_rma(src, len, xVol, fVol)
VIDYA v1 RMA base (VIDYA-RMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: VIDYA v1, RMA base with Elastic Weight Gain applied.
weightgain_vidya_ema(src, len, xVol, fVol)
VIDYA v1 EMA base (VIDYA-EMA): Weight Gain (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
Returns: VIDYA v1, EMA base with Elastic Weight Gain applied.
diva_sd_vidya_rma(src, len, xVol, fVol, ct)
Standard Deviation (SD VIDYA-RMA): Diva / Weight Gain: (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_vidya_rma().
Returns:
diva_sd_vidya_ema(src, len, xVol, fVol, ct)
Standard Deviation (SD VIDYA-EMA): Diva / Weight Gain: (Elastic Volume).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
xVol (float) : Volume exponent multiplier (0 = unweighted, 1 = fully weighted).
fVol (bool) : Volume smoothing filter.
ct (float) : Central tendency (optional, na = bypass). Internal: weightgain_vidya_ema().
Returns:
weightgain_sema(src, len, xVol, fVol)
Parameters:
src (float)
len (simple int)
xVol (float)
fVol (bool)
diva_sd_sema(src, len, xVol, fVol)
Parameters:
src (float)
len (simple int)
xVol (float)
fVol (bool)
diva_mad_mm(src, len, ct)
Median Absolute Deviation (MAD MM): Diva (no volume weighting).
Parameters:
src (float) : Source input.
len (int) : Length (number of bars).
ct (float) : Central tendency (optional, na = bypass). Internal: ta.median()
Returns:
source_switch(slct, aux1, aux2, aux3, aux4)
Custom Source Selector/Switch function. Features standard & custom 'weighted' sources with additional aux inputs.
Parameters:
slct (string) : Choose from custom set of string values.
aux1 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.
aux2 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.
aux3 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.
aux4 (float) : Additional input for user-defined source, eg: standard input.source(). Optional, use na to bypass.
Returns: Float value, to be used as src input for other functions.
colour_gradient_ma_div(ma1, ma2, div, bull, bear, mid, mult)
Colour Gradient for plot fill between two moving averages etc, with seperate bull/bear and divergence strength.
Parameters:
ma1 (float) : Input for fast moving average (eg: bullish when above ma2).
ma2 (float) : Input for slow moving average (eg: bullish when below ma1).
div (float) : Input deviation/divergence value used to calculate strength of colour.
bull (color) : Colour when ma1 above ma2.
bear (color) : Colour when ma1 below ma2.
mid (color) : Neutral colour when ma1 = ma2.
mult (int) : Opacity multiplier. 100 = maximum, 0 = transparent.
Returns: Colour with transparency (according to specified inputs)
Price Move Exceed % Threshold & BE Evaluation1Handy to see history or quick back test of moves. Enter a decimal for percentage wanted and choose the time frame wanted . The occurrences of the up or down threshold are plotted in the panel as maroon or green squares and can be read as red or green text in the panel data and on the right hand scale . The last number in the panel is the average move for the chosen period.
My usage is mostly to see what % has been exceeded for break even prices of option trades. Example: in SPY a spread has a break even of 567 when the price is 570; I get the percentage of the $3 move by dividing 3/570 to get 0.0526 ; the results show as described above.
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.
MMAPMarket Maker Aggression & Panic
Here's how it works:
Bollinger Bands: The script calculates and plots the Bollinger Bands, which helps you identify potential aggressive buying or panic selling when the price breaks above or below the bands.
Volume Analysis: It checks for volume spikes compared to the average volume over a specified period. If the volume exceeds a defined threshold, the background color changes to orange, indicating a potential market maker reaction.
Alerts: Alerts are set for volume spikes, aggressive buying (when the price breaks above the upper Bollinger Band), and panic selling (when it drops below the lower Bollinger Band).
Feel free to customize the parameters to fit your trading style!
RTI Thresholds Index | mad_tiger_slayerOverview of the Script
The Relative Trend Index (RTI) Threshold Index is a custom indicator for TradingView that enhances a Relative Trend Index (RTI) . The RTI is designed to reflect the market’s trend strength by comparing the current price to dynamically calculated upper and lower trend boundaries. Additionally, the indicator includes overbought and oversold thresholds, and Trend-coded signals to visually represent market conditions for easier analysis. The RTI Threshold Index is created and meant for long term investments targeted for longer swing trades over a few months to years.
How Do Investors Use the RTI Trend Index?
In the provided chart image, the indicator is displayed on a Bitcoin price chart. Here’s what each visual component represents:
INTENDED USES
The RTI Threshold Index is NOT intended for SCALPING.
With the nature of its components and calculations. This indicator will give false signals when the Timeframe is too low. The best intended use for high-quality signals are above the 12hr timeframes (Note: Coded to be used above 1 Day Timeframes)
The RTI Threshold Index is a TREND-FOLLOWING and MEAN REVERTING INDICATOR . With the explanation below of the image you can see both Trend-Following and Mean Reversion Uses.
A VISUAL REPRESENTATION INTENDED USES
Relative Trend Index Line (Green/Red): The main RTI line changes colors based on long or short conditions, providing an immediate visual cue of the trend direction. This conditional state enter long when the RTI is greater than the long threshold and will not enter short until it is less than the short threshold. (vice versa) When the RTI is less than the short threshold and will not enter long until it is greater than the long threshold.
EMA of RTI: A smoothed version of the RTI in yellow for more stable trend analysis. This EMA can be used for LONGER TERM trends. When the smoothed RTI is above 50, investors can assume that the trend will be in a trending state. Because this is slower than the RTI, you will get slower entries and slower exits.
Threshold Lines: Green and red lines for long and short thresholds, along with dashed lines for overbought and oversold levels. These lines can be calibrated to allow the RTI to enter a long trending or short trending state. The lower the value is for Long Threshold line , it will enter a long trend faster. The higher the value for Short Threshold Line , it will exit faster. We can also set Overbought and Oversold Thresholds. With the RTI entering above the Overbought Threshold line, Investors can assume that the environment is getting heated or is overbought. Same for oversold with the RTI entering below the Oversold Threshold line, Investors can assume that the environment is getting heated or is overbought.
Gradient Background: Shaded overbought and oversold areas improve readability by distinguishing these zones. This coloring of the shaded area tells us the oversold and overbought levels.
Colored Candles: Candles change color based on the RTI condition, aligning the price action visually with the trend status. The Green symbolizes a long state while red symbolizes a short state.
__________________________________________________________________________________
The indicator's primary elements include:
Input Parameters: Configurable settings for trend length, sensitivity, moving average (MA) period, thresholds, and overbought/oversold levels.
RTI Calculation: Computation of trend boundaries and the RTI value based on the price's position within these boundaries.
Visual Components: Horizontal threshold lines, plotted RTI values, color-coded candles, and gradient fills for overbought and oversold zones.
1. Input Parameters
The script includes several configurable inputs, allowing users to customize the indicator’s sensitivity and behavior according to market conditions:
Trend Length: Controls the number of data points for trend calculations. Higher values produce a smoother, less responsive trend, while lower values make the trend more sensitive to recent price changes.
Trend Sensitivity: Sets the sensitivity by defining the upper and lower percentiles for the trend boundaries. Higher sensitivity values make the RTI less reactive, while lower values increase responsiveness.
MA length: Defines the period for the Exponential Moving Average (EMA) applied to the RTI, smoothing its output.
longThreshold and shortThreshold: Set the levels for entering long and short positions. The RTI crossing above longThreshold or below shortThreshold signals a long or short condition, respectively.
Overbought and oversold thresholds: When RTI exceeds overbought or falls below oversold, it indicates overbought or oversold market conditions.
2. Relative Trend Index (RTI) Calculation
The RTI is calculated by dynamically setting upper and lower trend boundaries:
Upper Trend and Lower Trend: Calculated by adding and subtracting the standard deviation of the closing price to/from the close, providing a measure of price variation.
upper array and Lower Arrays : Arrays that hold the upper and lower trend values over the specified trend length period.
Sorting and Indexing: After sorting these arrays, the values at specific percentiles (based on trend sensitivity) are selected as UpperTrend and LowerTrend.
RTI formula: The RTI is calculated by normalizing the close price within the range of UpperTrend and LowerTrend. This yields a percentage that reflects the price's relative position within the trend range.
3. Threshold and Signal Lines
Several horizontal lines mark key threshold levels:
midline: A dashed line at 50, marking the RTI midpoint.
overbought and oversold: Dashed lines for the overbought and oversold levels as set by overbought and oversold.
long hline and short hline: Solid lines marking the longThreshold and shortThreshold levels for entering long and short trades. They are colored Green for long threshold and Red for short threshold
4. Long and Short Conditions
The script defines long and short conditions based on the RTI’s position relative to the longThreshold and shortThreshold:
isLong: Set to true when the RTI exceeds longThreshold, signaling a long condition.
isShort: Set to true when the RTI drops below shortThreshold, signaling a short condition. overboughtcandles and oversoldcandles: Boolean variables that indicate when the RTI crosses the overbought or oversold thresholds, enhancing visual feedback.
5. Color Coding
Color-coded elements help to visually indicate the RTI's current state:
rtiColor: Sets the RTI line color based on the long or short condition (green for long, red for short).
obosColor: Colors specific candles in the overbought (yellow) and oversold (purple) regions, adding clarity to these conditions.
6. Plotting and Visualization
The following components display the RTI indicator and its conditions visually:
RTI and EMA Plot: The RTI line is plotted alongside an EMA line for smooth trend observation. The RTI line uses the conditional colors to indicate market conditions.
Background Gradient Fill: Shaded areas between the overbought and oversold levels highlight these zones in the background.
Colored Candles: Candles on the price chart are color-coded based on the RTI condition (green for long, red for short), making it easy to see trend direction changes.
Overbought and Oversold Gradient Fill: Gradient fills are applied to the overbought and oversold regions, creating a visual effect when the RTI reaches extreme levels.
Conclusion
The RTI Threshold Indicator is a powerful tool for assessing trend strength and market conditions. With configurable parameters, it adapts well to various timeframes and market environments, providing investors with a reliable means to identify potential entry and exit points. With configurable parameters, RTI Threshold Indicator can identify market conditions for potential buy and sell zones.
Half Trend Regression [AlgoAlpha]Introducing the Half Trend Regression indicator by AlgoAlpha, a cutting-edge tool designed to provide traders with precise trend detection and reversal signals. This indicator uniquely combines linear regression analysis with ATR-based channel offsets to deliver a dynamic view of market trends. Ideal for traders looking to integrate statistical methods into their analysis to improve trade timing and decision-making.
Key Features
🎨 Customizable Appearance : Adjust colors for bullish (green) and bearish (red) trends to match your charting preferences.
🔧 Flexible Parameters : Configure amplitude, channel deviation, and linear regression length to tailor the indicator to different time frames and trading styles.
📈 Dynamic Trend Line : Utilizes linear regression of high, low, and close prices to calculate a trend line that adapts to market movements.
🚀 Trend Direction Signals : Provides clear visual signals for potential trend reversals with plotted arrows on the chart.
📊 Adaptive Channels : Incorporates ATR-based channel offsets to account for market volatility and highlight potential support and resistance zones.
🔔 Alerts : Set up alerts for bullish or bearish trend changes to stay informed of market shifts in real-time.
How to Use
🛠 Add the Indicator : Add the Half Trend Regression indicator to your chart from the TradingView library. Access the settings to customize parameters such as amplitude, channel deviation, and linear regression length to suit your trading strategy.
📊 Analyze the Trend : Observe the plotted trend line and the filled areas under it. A green fill indicates a bullish trend, while a red fill indicates a bearish trend.
🔔 Set Alerts : Use the built-in alert conditions to receive notifications when a trend reversal is detected, allowing you to react promptly to market changes.
How It Works
The Half Trend Regression indicator calculates linear regression lines for the high, low, and close prices over a specified period to determine the general direction of the market. It then computes moving averages and identifies the highest and lowest points within these regression lines to establish a dynamic trend line. The trend direction is determined by comparing the moving averages and previous price levels, updating as new data becomes available. To account for market volatility, the indicator calculates channels above and below the trend line, offset by a multiple of half the Average True Range (ATR). These channels help visualize potential support and resistance zones. The area under the trend line is filled with color corresponding to the current trend direction—green for bullish and red for bearish. When the trend direction changes, the indicator plots arrows on the chart to signal a potential reversal, and alerts can be set up to notify you. By integrating linear regression and ATR-based channels, the indicator provides a comprehensive view of market trends and potential reversal points, aiding traders in making informed decisions.
Enhance your trading strategy with the Half Trend Regression indicator by AlgoAlpha and gain a statistical edge in the markets! 🌟📊
Multi-Timeframe Supertrend Dashboard - EnhancedOverview
The Multi-Timeframe Supertrend Dashboard is a powerful tool designed to give traders a clear view of market trends across multiple timeframes, all from a single dashboard. This indicator leverages the Supertrend method to calculate buy and sell signals based on the direction of price relative to dynamically calculated support and resistance lines. The dashboard is optimized for dark mode and provides easy-to-interpret color-coded signals for each timeframe.
How It Works
The Supertrend indicator is a trend-following indicator that uses the Average True Range (ATR) to set upper and lower bands around the price, adapting dynamically as volatility changes. When the price is above the Supertrend line, the market is considered in an uptrend, triggering a "BUY" signal. Conversely, when the price falls below the Supertrend line, the market is in a downtrend, triggering a "SELL" signal.
This Multi-Timeframe Supertrend Dashboard calculates Supertrend signals for the following timeframes:
1 minute
5 minutes
15 minutes
1 hour
Daily
Weekly
Monthly
For each timeframe, the dashboard shows either a "BUY" or "SELL" signal, allowing traders to assess whether trends align across timeframes. A "BUY" signal displays in green, and a "SELL" signal displays in red, giving a quick visual reference of the overall trend direction for each timeframe.
Customization Options
ATR Period: Defines the period for the Average True Range (ATR) calculation, which determines how responsive the Supertrend lines are to changes in market volatility.
Multiplier: Sets the sensitivity of the Supertrend bands to price movements. Higher values make the bands less sensitive, while lower values increase sensitivity, allowing quicker reactions to changes in price.
How to Interpret the Dashboard
The Multi-Timeframe Supertrend Dashboard allows traders to see at a glance if trends across multiple timeframes are aligned. Here’s how to interpret the signals:
BUY (Green): The current timeframe’s price is in an uptrend based on the Supertrend calculation.
SELL (Red): The current timeframe’s price is in a downtrend based on the Supertrend calculation.
For example:
If all timeframes display "BUY," the asset is in a strong uptrend across multiple time horizons, which may indicate a bullish market.
If all timeframes display "SELL," the asset is likely in a strong downtrend, signaling a bearish market.
Mixed signals across timeframes suggest market consolidation or differing trends across short- and long-term periods.
Use Cases
Trend Confirmation: Use the dashboard to confirm trends across multiple timeframes before entering or exiting a position.
Quick Market Analysis: Get a snapshot of market conditions across timeframes without having to change charts.
Multi-Timeframe Alignment: Identify alignment across timeframes, which is often a strong indicator of market momentum in one direction.
Dark Mode Optimization
The dashboard has been optimized for dark mode, with white text and contrasting background colors to ensure easy readability on darker TradingView themes.
Weekly Range & Trend (Signed)Weekly Trend & Range is basically calculated every week.
It helps to get a broad idea whether coming week market can be directional , volatile or range bound action. So this helps me to get a hint which style of approach should be given more important on positional basis like directional or non-directional.
I mostly track in NSE:BANKNIFTY , NSE:NIFTY , BSE:SENSEX
For example:
Average range difference of past 4 weeks is bigger in compare to current week range difference means good chance for directional opportunities.
Average range difference of past 4 weeks is lesser in compare to current week range difference means good chance for non-directional opportunities.
Directional or Non-directional hint is been shown in terms of probability . So based on this i plan my week and trades.
Implied Fair Value Gap (IFVG) ICT [TradingFinder] Hidden FVG OTE🔵 Introduction
The Implied Fair Value Gap (IFVG) is distinctive due to its unique three-candlestick formation, which differentiates it from conventional Fair Value Gaps.
Implied fair value represents an estimated worth of an asset—often a business or its goodwill—based on the price likely to be received in a structured transaction between market participants at a specific point in time.
In the ever-evolving world of technical analysis, pinpointing price reversal points and market anomalies can significantly enhance trading strategies and decision-making for traders and investors. Among the advanced concepts gaining traction in this field is the Implied Fair Value Gap (IFVG), introduced by the renowned analyst Inner Circle Trader (ICT).
This tool has proven to be an effective method for identifying hidden supply and demand zones in financial markets, offering a unique edge to traders looking for high-probability setups.
Unlike traditional gaps that are visible on price charts, IFVG is a hidden gap that doesn’t appear explicitly on the chart and thus requires specialized technical analysis tools for accurate identification.
This hidden gap can signal potential price reversals and offers traders insight into high-liquidity areas where price is likely to react. This article will guide you through using the ICT Implied Fair Value Gap Indicator effectively, covering its settings, usage strategies, and key features to help you make informed decisions in the market.
🟣 Bullish Implied FVG
🟣 Bearish Implied FVG
🔵 How to Use
The IFVG indicator is designed to assist traders in recognizing hidden support and resistance zones by identifying Bullish and Bearish IFVG patterns. With this tool, traders can make better-informed decisions about suitable entry and exit points for their trades based on these patterns.
🟣 Bullish Implied Fair Value Gap
This pattern occurs in an uptrend when a large bullish candlestick forms, with the wicks of the previous and following candles overlapping the body of the central candlestick.
This overlap creates a demand zone or a hidden support level, which can act as an ideal entry point for buy trades. Often, when the price returns to this area, it is likely to resume its upward trend, presenting a profitable buying opportunity.
🟣 Bearish Implied Fair Value Gap
This pattern is similar but forms in downtrends. Here, a large bearish candlestick appears on the chart, with the wicks of adjacent candles overlapping its body. This overlap defines a supply zone or a hidden resistance level and serves as a signal for potential sell trades.
When the price returns to this zone, it often continues its downward trend, providing an optimal point for entering sell trades.
The IFVG indicator also includes various filters that traders can use to refine their analysis based on market conditions. These filters, including Very Aggressive, Aggressive, Defensive, and Very Defensive, allow users to customize the IFVG zones' width, offering flexibility according to the trader’s risk tolerance and trading style.
🟣 Example Trading Scenarios
Suppose you’re in a strong uptrend and the IFVG indicator identifies a Bullish IFVG zone. In this scenario, you could consider entering a buy trade when the price retraces to this zone, expecting the uptrend to resume. Conversely, in a downtrend, a Bearish IFVG zone can signal a favorable entry point for short trades when the price revisits this area.
🔵 Settings
Implied Block Validity Period: This parameter specifies the validity period of each identified block, taking into account the number of bars that have passed since its formation. Proper adjustment of this period helps traders focus only on relevant zones, increasing the accuracy of the analysis.
Mitigation Level OB : This option defines the mitigation level for supply and demand blocks (Order Blocks), with settings including Proximal, 50% OB, and Distal.
Depending on the selected level, the indicator will focus on closer, mid-range, or farther points for block identification, allowing traders to adjust for the level of precision required.
Implied Filter : Activating this filter allows traders to apply conditions based on the width of the IFVG zones. With options like Very Aggressive and Very Defensive, traders can control the width of IFVG zones to suit their risk management strategy—whether they prefer high-risk setups or low-risk setups.
Display and Color Settings : This section enables users to customize the appearance of the IFVG zones on their charts. Traders can set different colors for Bullish and Bearish zones, allowing for easier distinction and improved visualization.
Alert Settings : One of the standout features of the IFVG indicator is the alert system. By setting up alerts, users can be notified whenever the price approaches a demand or supply zone.
Alerts can be customized to trigger Once Per Bar (one alert per bar) or Per Bar Close (alert at the close of each bar), ensuring that traders stay updated on critical price movements without needing to monitor the chart continuously.
🔵 Conclusion
The ICT Implied Fair Value Gap (IFVG) indicator is a powerful and sophisticated tool in technical analysis, allowing professional traders to identify hidden supply and demand zones and use them as entry and exit points for buy and sell trades.
This indicator’s automatic detection of IFVG zones helps traders uncover hidden trading opportunities that can enhance their analysis.
While the IFVG indicator offers numerous advantages, it is important to use it in conjunction with other technical analysis tools and sound risk management practices.
IFVG alone does not guarantee profitability in trading; it works best when combined with other indicators such as volume analysis and trend-following indicators for a comprehensive trading strategy.
Dynamic RSI Mean Reversion StrategyDynamic RSI Mean Reversion Strategy
Overview:
This strategy uses an RSI with ATR-Adjusted OB/OS levels in order to enhance the quality of it's mean reversion trades. It also incorporates a form of trend filtering in an effort to minimize downside and maximize upside. The backtest has fewer trades, as it uses substantial filtering to enhance trade quality. As you can see, I didn't cherry pick the results, so the results aren't the most beautiful thing you'll see in your life. I did this to ensure nobody gets misled. If you need a higher frequency of trades, consider removing the trend filter or increasing the length of the EMAs used for trend detection.
Features:
Dynamic OB/OS Levels: Uses ATR to adjust overbought and oversold thresholds dynamically, making the RSI more responsive in varying volatility conditions. This approach enhances signal strength by expanding the RSI range in high volatility and tightening it in low volatility.
Mean Reversion Focus: Designed for mean reversion but incorporates a trend-following filter to reduce countertrend trades. When the RSI is high, it often indicates an uptrend, so a trend filter prevents shorting in these cases and the same goes for downtrends and longing.
Trend Filtering: A moving average cross trend filter checks for the trend direction, with the RSI signal line color-coded to reflect trend shifts. Entries occur when the RSI crosses above or below the dynamic thresholds and is not a countertrend trade.
Stop Losses: Stop losses are set based on ATR distance from the entry price, providing volatility-adjusted protection.
Note:
If you're using this strategy on assets with a higher price, remember to increase the initial capital in the strategy settings. Otherwise, the strategy won't generate any (or many) trades and you'll end up with some inaccurate results.
Recommended Use:
Test it on different assets and timeframes. I’ve found the best results with standard RSI inputs, a relatively slow ATR, and a slower MA cross for trend filtering. Thus, the defaults are set that way. If the trend metrics are too slow, you’ll filter out too many good trades while allowing crummy ones; if too fast, most trades may be filtered out. As always, this has a lot of configurability so experiment to find the balance that works for your trading style.
Globex Trap ZoneGlobex Trap Indicator
A powerful tool designed to identify potential trading opportunities by analyzing the relationship between Globex session ranges and Supply & Demand zones during regular trading hours.
Key Features
Tracks and visualizes Globex session price ranges
Identifies key Supply & Demand zones during regular trading hours
Highlights potential trap areas where price might experience significant reactions
Fully customizable time ranges and visual settings
Clear labeling of Globex highs and lows
How It Works
The indicator tracks two key periods:
Globex Session (Default: 6:00 PM - 9:30 AM)
Monitors overnight price action
Marks session high and low
Helps identify potential range breakouts
Supply & Demand Zone (Default: 8:00 AM - 11:00 AM)
Tracks price action during key market hours
Identifies potential reaction zones
Helps spot institutional trading areas
Best Practices for Using This Indicator
Use on 1-hour timeframe or lower for optimal visualization
Best suited for futures and other instruments traded during Globex sessions
Pay attention to areas where Globex range and Supply/Demand zones overlap
Use in conjunction with your existing trading strategy for confirmation
Recommended minimum of 10 days of historical data for context
Settings Explanation
Globex Session: Customizable time range for overnight trading session
Supply & Demand Zone: Adjustable time range for regular trading hours
Days to Look Back: Number of historical days to display (default: 10)
Visual Settings: Customizable colors and transparency for both zones
Important Notes
All times are based on exchange timezone
The indicator respects overnight sessions and properly handles timezone transitions
Historical data requirements: Minimum 10 days recommended
Performance impact: Optimized for smooth operation with minimal resource usage
Disclaimer
Past performance is not indicative of future results. This indicator is designed to be used as part of a comprehensive trading strategy and should not be relied upon as the sole basis for trading decisions.
Updates and Support
I actively maintain this indicator and welcome feedback from the trading community. Please feel free to leave comments or suggestions for improvements.
Bullish/Bearish Reversal Bars Indicator [Skyrexio]Introduction
Bullish/Bearish Reversal Bars Indicator leverages the combination of candlestick reversal bar pattern and the Williams Alligator indicator to help traders in understanding where there is a high probability of market reversal or correction. Indicator works for both bearish and bullish cases. It visualizes the bearish and bullish reversal bars with red and green dots and also plots the Alligator's lips to make it more convenient for traders to understand if price is above or below lips line (more information in "Methodology and it's justification" paragraph).
Features
Market Facilitation Index(MFI) filter: with the specified parameter in settings user can choose to filter bullish and bearish reversal bars which passed the MFI condition.
Awesome Oscillator(AO) filter: with the specified parameter in settings user can choose to filter bullish and bearish reversal bars which passed the AO condition.
Alerts: user can set up the alert and have notifications when bullish/bearish reversal bar has been printed.
Methodology and it's justification
In the script’s methodology, we apply the concepts of bullish and bearish reversal bars introduced by Bill Williams in his book Trading Chaos. So, what exactly is a bullish or bearish reversal bar? At its core, it’s a candlestick pattern. A bullish reversal bar is a bar that closes in its upper half, while a bearish reversal bar closes in its lower half.
Why is this type of bar significant? Let’s look at the bullish reversal bar as an example. When the price is trending upward, forming higher highs with each candle, and we suddenly see a bullish bar that makes a new high but ultimately closes in its lower half, it signals a shift in control. Bears have taken control toward the end of that candle's period, pushing the price back down. This can be interpreted as a sign of trend weakness and a potential reversal (or at least a correction).
An additional key point is that a reversal bar often indicates a possible end to the trend. Therefore, for a reversal bar to be valid, several preceding candles should show lower highs (for bullish bars) or higher lows (for bearish bars), reinforcing the likelihood of a trend change.
The second step on methodology is the location of the bar related to Williams Alligator. The Williams Alligator Indicator, developed by Bill Williams, is a technical analysis tool that helps traders identify trends and potential turning points in the market. It consists of three lines, often called the jaw, teeth, and lips of the alligator, each representing different moving averages:
Jaw (Blue Line): A slower moving average, typically a 13-period smoothed moving average shifted 8 bars into the future.
Teeth (Red Line): A medium moving average, typically an 8-period smoothed moving average shifted 5 bars into the future.
Lips (Green Line): A faster moving average, usually a 5-period smoothed moving average shifted 3 bars into the future.
When the three lines are spread out and moving in the same direction, it suggests a strong trend (the "alligator" is "awake and feeding"). When they intertwine, the indicator suggests that the market is moving sideways, or in a range, signaling a lack of clear trend (the "alligator" is "sleeping"). Traders use the Alligator Indicator to enter trades in trending markets and avoid trades in choppy, non-trending markets.
If bullish reversal bar's high is not below and bearish reversal bar's low is not above all three Alligator's lines (jaw, lips, teeth) they cannot be interpreted as these types of bars. It can be explained as following: if we are waiting for the bullish reversal bar it shall be reversal from downtrend. If price is not below all three lines it can't be interpret as the downtrend according to this method. The opposite is true for the bearish reversal bar.
All described above are obligatory conditions for reversal bar, now let's discuss two not obligatory conditions. The first one is Market Facilitation Index (MFI) restriction. Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
The second additional filter is Awesome Oscillator. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator that measures market momentum by comparing recent price action to a longer historical context. It helps traders identify potential trend reversals and the strength of trends. Formula:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
If AO is decreasing momentum is bearish, if increasing - bullish. According to Bill Williams approach reversal bars are the potential trades against the trend. As a result we added second filter for bullish reversal bars AO shall be decreasing, for bearish increasing.
How to use indicator
Apply it to desired chart and time frame. It works on every time frame.
Setup the filters with the "Enable MFI" and "Enable AO" checkboxes in the settings. By default they are turned on.
Analyze the price action. Indicator plotted the white line, this is the lips of an Alligator. It will help you to understand how price is moving in comparison to lips line. Indicator will print the green dot and text "BULL" below it current bar is bullish reversal. It will print the red dot and text "BEAR" above it if current bar is interpreted by algorithm as a bearish reversal.
Set up the alerts if it's needed. Indicator has two custom alerts called "Bullish reversal bar has been printed" and "Bearish reversal bar has been printed"
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test indicators before live implementation.
CandlestickPatternsLibrary "CandlestickPatterns"
zigzag(_low, _high, depth, deviation, backstep)
Parameters:
_low (float)
_high (float)
depth (int)
deviation (int)
backstep (int)
getTrend(trendType, currentClose, zz_downtrend, zz_uptrend, ema14, ema28)
Parameters:
trendType (string)
currentClose (float)
zz_downtrend (bool)
zz_uptrend (bool)
ema14 (float)
ema28 (float)
isInside(currentHigh, currentLow, currentClose, currentOpen, prevHigh, prevLow)
Parameters:
currentHigh (float)
currentLow (float)
currentClose (float)
currentOpen (float)
prevHigh (float)
prevLow (float)
checkMorningStar(open0, high0, low0, close0, open1, high1, low1, close1, open2, high2, low2, close2, innerCandleThreshold, closingMinThreshold, closingMaxThreshold, useDojiFilter, dojiSize, downTrend)
Parameters:
open0 (float)
high0 (float)
low0 (float)
close0 (float)
open1 (float)
high1 (float)
low1 (float)
close1 (float)
open2 (float)
high2 (float)
low2 (float)
close2 (float)
innerCandleThreshold (float)
closingMinThreshold (float)
closingMaxThreshold (float)
useDojiFilter (bool)
dojiSize (float)
downTrend (bool)
checkEveningStar(open0, high0, low0, close0, open1, high1, low1, close1, open2, high2, low2, close2, innerCandleThreshold, closingMinThreshold, closingMaxThreshold, useDojiFilter, dojiSize, upTrend)
Parameters:
open0 (float)
high0 (float)
low0 (float)
close0 (float)
open1 (float)
high1 (float)
low1 (float)
close1 (float)
open2 (float)
high2 (float)
low2 (float)
close2 (float)
innerCandleThreshold (float)
closingMinThreshold (float)
closingMaxThreshold (float)
useDojiFilter (bool)
dojiSize (float)
upTrend (bool)
checkHammerPattern(open, high, low, close, bodyAvg, shadowFactor, downTrend)
Parameters:
open (float)
high (float)
low (float)
close (float)
bodyAvg (float)
shadowFactor (float)
downTrend (bool)
checkInvertedHammerPattern(open, high, low, close, bodyAvg, shadowFactor, downTrend)
Parameters:
open (float)
high (float)
low (float)
close (float)
bodyAvg (float)
shadowFactor (float)
downTrend (bool)
checkHangingManPattern(open, high, low, close, bodyAvg, shadowFactor, upTrend)
Parameters:
open (float)
high (float)
low (float)
close (float)
bodyAvg (float)
shadowFactor (float)
upTrend (bool)
checkShootingStarPattern(open, high, low, close, bodyAvg, shadowFactor, upTrend)
Parameters:
open (float)
high (float)
low (float)
close (float)
bodyAvg (float)
shadowFactor (float)
upTrend (bool)
checkLevels(high0, high1, high2, low0, low1, low2, lookbackPeriod)
Parameters:
high0 (float)
high1 (float)
high2 (float)
low0 (float)
low1 (float)
low2 (float)
lookbackPeriod (int)
Future Trend Channel [ChartPrime]The Future Trend Channel indicator is a dynamic tool for identifying trends and projecting future prices based on channel formations. The indicator uses SMA (Simple Moving Average) and volatility calculations to plot channels that visually represent trends. It also detects moments of lower momentum, indicated by neutral color changes in the channels, and projects future price levels for up to 50 bars ahead.
⯁ KEY FEATURES AND HOW TO USE
⯌ Dynamic Trend Channels :
The indicator draws channels when a trend is identified. It uses a combination of SMA and volatility to determine the direction and strength of the trend. Each channel is visualized with a specific color, where green indicates an uptrend and orange represents a downtrend.
Example of channels during uptrend and downtrend:
⯌ Momentum-Based Color Shifts :
The indicator adapts its channel colors based on momentum changes. When the starting point (Y1) of a channel is higher than its ending point (Y2) during an uptrend, the channel turns neutral, indicating lower momentum and a possible ranging market. The same applies in a downtrend, where the channel turns neutral if Y1 is lower than Y2.
Example of neutral momentum channels:
⯌ Future Price Projection :
At the end of each channel, the indicator generates a projected future price based on the midpoint of the channel. By default, this projection is made 50 bars into the future, but users can adjust the number of bars to their preference.
Example of future price projection:
⯌ Diamond Signals for Valid Trends :
Lime-colored diamonds appear when an uptrend channel is confirmed, while orange diamonds indicate valid downtrend channels. These signals confirm the presence of a strong trend and help identify valid entry and exit points. Neutral channels, which indicate lower momentum, do not show diamond signals.
Example of trend confirmation signals:
⯌ Customizable Settings :
Users can adjust the channel length (how far back the trend is analyzed) and the width (which determines the channel boundaries based on volatility). The future price projection can also be customized to forecast further or fewer bars into the future.
⯁ USER INPUTS
Trend Length : Sets the number of bars used to calculate the trend channels.
Channel Width : Adjusts the width of the channels, based on volatility (ATR multiplier).
Up and Down Colors : Allows customization of the colors used for uptrend and downtrend channels.
Future Bars : Sets the number of bars used for future price projection.
⯁ CONCLUSION
The Future Trend Channel indicator is a versatile tool for identifying and trading trends. With its ability to detect momentum shifts and project future prices, it provides traders with key insights for making more informed decisions. The use of diamond signals for trend validation adds an extra layer of confirmation, helping traders act with greater confidence during volatile or trending markets.
Target Trend [BigBeluga]The Target Trend indicator is a trend-following tool designed to assist traders in capturing directional moves while managing entry, stop loss, and profit targets visually on the chart. Using adaptive SMA bands as the core trend detection method, this indicator dynamically identifies shifts in trend direction and provides structured exit points through customizable target levels.
SP500:
🔵 IDEA
The Target Trend indicator’s concept is to simplify trade management by providing automated visual cues for entries, stops, and targets directly on the chart. When a trend change is detected, the indicator prints an up or down triangle to signal entry direction, plots three customizable target levels for potential exits, and calculates a stop-loss level below or above the entry point. The indicator continuously adapts as price moves, making it easier for traders to follow and manage trades in real time.
When price crosses a target level, the label changes to a check mark, confirming that the target has been achieved. Similarly, if the stop-loss level is hit, the label changes to an "X," and the line becomes dashed, indicating that the stop loss has been activated. This feature provides traders with a clear visual trail of whether their targets or stop loss have been hit, allowing for easier trade tracking and exit strategy management.
🔵 KEY FEATURES & USAGE
SMA Bands for Trend Detection: The indicator uses adaptive SMA bands to identify the trend direction. When price crosses above or below these bands, a new trend is detected, triggering entry signals. The entry point is marked on the chart with a triangle symbol, which updates with each new trend change.
Automated Targets and Stop Loss Management: Upon a new trend signal, the indicator automatically plots three price targets and a stop loss level. These levels provide traders with structured exit points for potential gains and a clear risk limit. The stop loss is placed below or above the entry point, depending on the trend direction, to manage downside risk effectively.
Visual Target and Stop Loss Validation: As price hits each target, the label beside the level updates to a check mark, indicating that the target has been reached. Similarly, if the stop loss is activated, the stop loss label changes to an "X," and the line becomes dashed. This feature visually confirms whether targets or stop losses are hit, simplifying trade management.
The indicator also marks the entry price at each trend change with a label on the chart, allowing traders to quickly see their initial entry point relative to current price and target levels.
🔵 CUSTOMIZATION
Trend Length: Set the lookback period for the trend-detection SMA bands to adjust the sensitivity to trend changes.
Targets Setting: Customize the number and spacing of the targets to fit your trading style and market conditions.
Visual Styles: Adjust the appearance of labels, lines, and symbols on the chart for a clearer view and personalized layout.
🔵 CONCLUSION
The Target Trend indicator offers a streamlined approach to trend trading by integrating entry, target, and stop loss management into a single visual tool. With automatic tracking of target levels and stop loss hits, it helps traders stay focused on the current trend while keeping track of risk and reward with minimal effort.
VWAP Stdev Bands Strategy (Long Only)The VWAP Stdev Bands Strategy (Long Only) is designed to identify potential long entry points in trending markets by utilizing the Volume Weighted Average Price (VWAP) and standard deviation bands. This strategy focuses on capturing upward price movements, leveraging statistical measures to determine optimal buy conditions.
Key Features:
VWAP Calculation: The strategy calculates the VWAP, which represents the average price a security has traded at throughout the day, weighted by volume. This is an essential indicator for determining the overall market trend.
Standard Deviation Bands: Two bands are created above and below the VWAP, calculated using specified standard deviations. These bands act as dynamic support and resistance levels, providing insight into price volatility and potential reversal points.
Trading Logic:
Long Entry Condition: A long position is triggered when the price crosses below the lower standard deviation band and then closes above it, signaling a potential price reversal to the upside.
Profit Target: The strategy allows users to set a predefined profit target, closing the long position once the specified target is reached.
Time Gap Between Orders: A customizable time gap can be specified to prevent multiple orders from being placed in quick succession, allowing for a more controlled trading approach.
Visualization: The VWAP and standard deviation bands are plotted on the chart with distinct colors, enabling traders to visually assess market conditions. The strategy also provides optional plotting of the previous day's VWAP for added context.
Use Cases:
Ideal for traders looking to engage in long-only positions within trending markets.
Suitable for intraday trading strategies or longer-term approaches based on market volatility.
Customization Options:
Users can adjust the standard deviation values, profit target, and time gap to tailor the strategy to their specific trading style and market conditions.
Note: As with any trading strategy, it is important to conduct thorough backtesting and analysis before live trading. Market conditions can change, and past performance does not guarantee future results.
Dynamic Market Correlation Analyzer (DMCA) v1.0Description
The Dynamic Market Correlation Analyzer (DMCA) is an advanced TradingView indicator designed to provide real-time correlation analysis between multiple assets. It offers a comprehensive view of market relationships through correlation coefficients, technical indicators, and visual representations.
Key Features
- Multi-asset correlation tracking (up to 5 symbols)
- Dynamic correlation strength categorization
- Integrated technical indicators (RSI, MACD, DX)
- Customizable visualization options
- Real-time price change monitoring
- Flexible timeframe selection
## Use Cases
1. **Portfolio Diversification**
- Identify highly correlated assets to avoid concentration risk
- Find negatively correlated assets for hedging strategies
- Monitor correlation changes during market events
2. Pairs Trading
- Detect correlation breakdowns for potential trading opportunities
- Track correlation strength for pair selection
- Monitor technical indicators for trade timing
3. Risk Management
- Assess portfolio correlation risk in real-time
- Monitor correlation shifts during market stress
- Identify potential portfolio vulnerabilities
4. **Market Analysis**
- Study sector relationships and rotations
- Analyze cross-asset correlations (e.g., stocks vs. commodities)
- Track market regime changes through correlation patterns
Components
Input Parameters
- **Timeframe**: Custom timeframe selection for analysis
- **Length**: Correlation calculation period (default: 20)
- **Source**: Price data source selection
- **Symbol Selection**: Up to 5 customizable symbols
- **Display Options**: Table position, text color, and size settings
Technical Indicators
1. **Correlation Coefficient**
- Range: -1 to +1
- Strength categories: Strong/Moderate/Weak (Positive/Negative)
2. **RSI (Relative Strength Index)**
- 14-period default setting
- Momentum comparison across assets
3. **MACD (Moving Average Convergence Divergence)**
- Standard settings (12, 26, 9)
- Trend direction indicator
4. **DX (Directional Index)**
- Trend strength measurement
- Based on DMI calculations
Visual Components
1. **Correlation Table**
- Symbol identifiers
- Correlation coefficients
- Correlation strength descriptions
- Price change percentages
- Technical indicator values
2. **Correlation Plot**
- Real-time correlation visualization
- Multiple correlation lines
- Reference levels at -1, 0, and +1
- Color-coded for easy identification
Installation and Setup
1. Load the indicator on TradingView
2. Configure desired symbols (up to 5)
3. Adjust timeframe and calculation length
4. Customize display settings
5. Enable/disable desired components (table, plot, RSI)
Best Practices
1. **Symbol Selection**
- Choose related but distinct assets
- Include a mix of asset classes
- Consider market cap and liquidity
2. **Timeframe Selection**
- Match timeframe to trading strategy
- Consider longer timeframes for strategic analysis
- Use shorter timeframes for tactical decisions
3. **Interpretation**
- Monitor correlation changes over time
- Consider multiple timeframes
- Combine with other technical analysis tools
- Account for market conditions and volatility
Performance Notes
- Calculations update in real-time
- Resource usage scales with number of active symbols
- Historical data availability may affect initial calculations
Version History
- v1.0: Initial release with core functionality
- Multi-symbol correlation analysis
- Technical indicator integration
- Customizable display options
Future Enhancements (Planned)
- Additional technical indicators
- Advanced correlation algorithms
- Enhanced visualization options
- Custom alert conditions
- Statistical significance testing
[Volatility] [Gain & Loss] - OverviewFX:EURUSD
Indicator Overview: Volatility & Gain/Loss - Forex Pair Analysis
This indicator, " —Overview" , is designed for users interested in analyzing the volatility and gain/loss metrics of multiple forex pairs. The tool is especially useful for traders aiming to assess currency pair volatility alongside gain and loss percentages over selected periods. It enables a clearer understanding of pair behavior and aids in decision-making.
Key Features
Customizable Volatility and Gain/Loss Periods : Define your preferred calculation periods and timeframes for both volatility and gain/loss to tailor the indicator to specific trading strategies. Multi-Pair Analysis : This indicator supports up to six forex pairs (default pairs include EURUSD, GBPUSD, USDJPY, USDCHF, AUDUSD, and USDCAD) and allows you to adjust these pairs as needed. Visual Ranking : Forex pairs are sorted by volatility, displaying the highest pairs at the top for quick reference. Top Gain/Loss Highlighting : The pair with the maximum gain and the pair with the maximum loss are highlighted in the table, making it easy to identify the best and worst performers at a glance.
Indicator Settings
Volatility Settings : Period : Adjust the number of periods used in the ATR (Average True Range) calculation. A default period of 14 is set. Timeframe : Select a timeframe (e.g., Daily, Weekly) for volatility calculation to match your analysis preference.
Gain/Loss Settings : Period : Choose the number of periods for gain/loss calculation. The default is set to 1. Timeframe : Select the timeframe for gain/loss calculation, independent of the volatility timeframe.
Symbol Selection : Configure up to six forex pairs. By default, popular forex pairs are pre-loaded but can be customized to include other currency pairs.
Output and Visualization
Table Display : This indicator displays data in a neatly structured table positioned in the top-right corner of your chart. Columns : Includes columns for the Forex Pair, Volatility Percentage, Gain Percentage, and Loss Percentage. Color Coding : Volatility is displayed in a standard color for clear readability. Gain values are highlighted in green, and Loss values are highlighted in red, allowing for quick visual differentiation. Highlighting : Rows representing the pair with the highest gain and the pair with the most significant loss are especially highlighted for emphasis.
How to Use
Volatility Analysis : This metric gives insight into the average price range movements for each pair over the specified period and timeframe, helping you evaluate the potential for rapid price changes. Gain/Loss Tracking : Gain or loss percentages show the pair's recent performance, allowing you to observe whether a currency pair is trending positively or negatively over the chosen period. Comparative Pair Ranking : Use the table to identify pairs with the highest volatility and extremes in gain or loss to guide trading decisions based on market conditions.
Ideal For
Swing Traders and Day Traders looking to understand short-term market fluctuations in currency pairs. Risk Management : Helps traders gauge pairs with higher risk (volatility) and recent performance (gain/loss) for informed position sizing and risk control.
This indicator is a comprehensive tool for visualizing and analyzing key forex pairs, making it an essential addition for traders looking to stay updated on volatility trends and recent price changes.
AutoCorrelation Test [OmegaTools]Overview
The AutoCorrelation Test indicator is designed to analyze the correlation patterns of a financial asset over a specified period. This tool can help traders identify potential predictive patterns by measuring the relationship between sequential returns, effectively assessing the autocorrelation of price movements.
Autocorrelation analysis is useful in identifying the consistency of directional trends (upward or downward) and potential cyclical behavior. This indicator provides an insight into whether recent price movements are likely to continue in a similar direction (positive correlation) or reverse (negative correlation).
Key Features
Multi-Period Autocorrelation: The indicator calculates autocorrelation across three periods, offering a granular view of price movement consistency over time.
Customizable Length & Sensitivity: Adjustable parameters allow users to tailor the length of analysis and sensitivity for detecting correlation.
Visual Aids: Three separate autocorrelation plots are displayed, along with an average correlation line. Dotted horizontal lines mark the thresholds for positive and negative correlation, helping users quickly assess potential trend continuation or reversal.
Interpretive Table: A table summarizing correlation status for each period helps traders make quick, informed decisions without needing to interpret the plot details directly.
Parameters
Source: Defines the price source (default: close) for calculating autocorrelation.
Length: Sets the analysis period, ranging from 10 to 2000 (default: 200).
Sensitivity: Adjusts the threshold sensitivity for defining correlation as positive or negative (default: 2.5).
Interpretation
Above 50 + Sensitivity: Indicates Positive Correlation. The price movements over the selected period are likely to continue in the same direction, potentially signaling a trend continuation.
Below 50 - Sensitivity: Indicates Negative Correlation. The price movements show a likelihood of reversing, which could signal an upcoming trend reversal.
Between 50 ± Sensitivity: Indicates No Correlation. Price movements are less predictable in direction, with no clear trend continuation or reversal tendency.
How It Works
The indicator calculates the logarithmic returns of the selected source price over each length period.
It then compares returns over consecutive periods, categorizing them as either "winning" (consistent direction) or "losing" (inconsistent direction) movements.
The result for each period is displayed as a percentage, with values above 50% indicating a higher degree of directional consistency (positive or negative).
A table updates with descriptive labels (Positive Correlation, Negative Correlation, No Correlation) for each tested period, providing a quick overview.
Visual Elements
Plots:
AutoCorrelation Test : Displays autocorrelation for the closest period (lag 1).
AutoCorrelation Test : Displays autocorrelation for the second period (lag 2).
AutoCorrelation Test : Displays autocorrelation for the third period (lag 3).
Average: Displays the simple moving average of the three test periods for a smoothed view of overall correlation trends.
Horizontal Lines:
No Correlation (50%): A baseline indicating neutral correlation.
Positive/Negative Correlation Thresholds: Dotted lines set at 50 ± Sensitivity, marking the thresholds for significant correlation.
Usage Guide
Adjust Parameters:
Select the Source to define which price metric (e.g., close, open) will be analyzed.
Set the Length based on your preferred analysis window (e.g., shorter for intraday trends, longer for swing trading).
Modify Sensitivity to fine-tune the thresholds based on market volatility and personal trading preference.
Interpret Table and Plots:
Use the table to quickly check the correlation status of each lag period.
Analyze the plots for changes in correlation. If multiple lags show positive correlation above the sensitivity threshold, a trend continuation may be expected. Conversely, negative values suggest a potential reversal.
Integrate with Other Indicators:
For enhanced insights, consider using the AutoCorrelation Test indicator in conjunction with other trend or momentum indicators.
This indicator offers a powerful method to assess market conditions, identify potential trend continuations or reversals, and better inform trading decisions. Its customization options provide flexibility for various trading styles and timeframes.
Moving AveragesWhile this "Moving Averages" indicator may not revolutionize technical analysis, it certainly offers a valuable and efficient solution for traders seeking to streamline their chart analysis process. This all-in-one tool addresses a common frustration among traders: the need to constantly search for and compare different types and lengths of moving averages.
Key Features
The indicator allows for the configuration of up to 5 moving averages simultaneously, providing a comprehensive view of price trends. Users can choose from 7 types of moving averages for each line, including SMA, EMA, WMA, VWMA, HMA, SMMA, and TMA. This variety ensures that traders can apply their preferred moving average types without the need for multiple indicators.
Each moving average can be fully customized in terms of length, color, line style, and thickness, allowing for clear visual differentiation. However, what sets this indicator apart is its "Smart Opacity" feature. When activated, this option dynamically adjusts the transparency of the moving average lines based on their direction, with ascending lines appearing more opaque and descending lines more transparent. This subtle yet effective visual cue aids in quickly identifying trend changes and potential trading signals.
Advantages
The primary benefit of this indicator lies in its convenience. By consolidating multiple moving averages into a single, customizable tool, it saves traders valuable time and reduces chart clutter. The Smart Opacity feature, while not groundbreaking, does offer an intuitive way to visualize trend strength and direction at a glance.
Moreover, the indicator's flexibility makes it suitable for various trading styles and experience levels. Whether you're a novice trader learning to interpret basic trend signals or an experienced analyst fine-tuning a complex strategy, this tool can adapt to your needs.
In conclusion, while this "Moving Averages" indicator may not be a game-changer in the world of technical analysis, it represents a thoughtful refinement of a fundamental trading tool. By focusing on user convenience and visual clarity, it offers a practical solution for traders looking to optimize their chart analysis process and make more informed trading decisions.
DeNoised Momentum [OmegaTools]The DeNoised Momentum by OmegaTools is a versatile tool designed to help traders evaluate momentum, acceleration, and noise-reduction levels in price movements. Using advanced mathematical smoothing techniques, this script provides a "de-noised" view of momentum by applying filters to reduce market noise. This helps traders gain insights into the strength and direction of price trends without the distractions of market volatility. Key components include a DeNoised Moving Average (MA), a Momentum line, and Acceleration bars to identify trend shifts more clearly.
Features:
- Momentum Line: Measures the percentage change of the de-noised source price over a specified look-back period, providing insights into trend direction.
- Acceleration (Ret) Bars: Visualizes the rate of change of the source price, helping traders identify momentum shifts.
- Normal and DeNoised Moving Averages: Two moving averages, one based on close price (Normal MA) and the other on de-noised data (DeNoised MA), enable a comparison of smoothed trends versus typical price movements.
- DeNoised Price Data Plot: Displays the current de-noised price, color-coded to indicate the relationship between the Normal and DeNoised MAs, which highlights bullish or bearish conditions.
Script Inputs:
- Length (lnt): Sets the period for calculations (default: 21). It influences the sensitivity of the momentum and moving averages. Higher values will smooth the indicator further, while lower values increase sensitivity to price changes.
The Length does not change the formula of the DeNoised Price Data, it only affects the indicators calculated on it.
Indicator Components:
1. Momentum (Blue/Red Line):
- Calculated using the log of the percentage change over the specified period.
- Blue color indicates positive momentum; red indicates negative momentum.
2. Acceleration (Gray Columns):
- Measures the short-term rate of change in momentum, shown as semi-transparent gray columns.
3. Moving Averages:
- Normal MA (Purple): A standard simple moving average (SMA) based on the close price over the selected period.
- DeNoised MA (Gray): An SMA of the de-noised source, reducing the effect of market noise.
4. DeNoised Price Data:
- Represented as colored circles, with blue indicating that the Normal MA is above the DeNoised MA (bullish) and red indicating the opposite (bearish).
Usage Guide:
1. Trend Identification:
- Use the Momentum line to assess overall trend direction. Positive values indicate upward momentum, while negative values signal downward momentum.
- Compare the Normal and DeNoised MAs: when the Normal MA is above the DeNoised MA, it indicates a bullish trend, and vice versa for bearish trends.
2. Entry and Exit Signals:
- A change in the Momentum line's color from blue to red (or vice versa) may indicate potential entry or exit points.
- Observe the DeNoised Price Data circles for early signs of a trend reversal based on the interaction between the Normal and DeNoised MAs.
3. Volatility and Noise Reduction:
- By utilizing the DeNoised MA and de-noised price data, this indicator helps filter out minor fluctuations and focus on larger price movements, improving decision-making in volatile markets.
