Histogram Trends Strategy by SedkurThis gives to you buy-sell signal with MACD's histogram trends.
Use "Fast and Slow length" and "Trend of Histogram Number" inputs to take less or more signal.
"Trend of Histogram Number" : This means how many histogram bars the trend continues before trading.
ค้นหาในสคริปต์สำหรับ "histogram"
OBV+EMA HistogramHistogram of the difference between On Balance Volume and an EMA of the On Balance Volume (OBV + EMA).
Using a 55 EMA, on the daily timeframe of BTC, bull/bear trends occur when the histogram is above/below the zero line respectively.
Divergences also have a notable effect.
-- Added alert conditions when OBV crosses EMA to signal a possible trend change, for bullish and bearish cases.
Histogram-based price zonesThis indicator provides a new approach to creating price zones that can be used as support and resistance. The approach does not use pivot points or Fibonacci levels. Instead, it uses the frequency of occurence of local maxima and minima to determine zones of interest where price often changed direction.
The algorithm is as follows:
- Gather price data from the last Lookback trading periods
- Calculate rolling minima and rolling maxima along the price points with window size Window size
- Build a histogram from the rolling extrema which are binned into different zones. The number of bins and therefore the width of a zone can be adjusted with the parameter Zone width factor
- Select only the top fullest bins. The number of bins selected for plotting can be controlled with Zone multiplier
The result are a number of boxes that appear on the chart which mark levels of interest to watch for. You can combine multiple instances of this indicator on different settings to find zones that are very relevant.
Shown as an example is the Nasdaq 100 futures ( NQ1! ) on the D timeframe with levels built from the last 100 periods with default settings. The boxes are the only output of the indicator, no signals are created.
DMI-ADX HistogramThe Average Direction Index (ADX) coupled with the Direction Movement Index (DMI), developed by J. Welles Wilder, is a popular indicator that measures trend direction and strength.
The AX line (blue) is used to show the strength of the current trend. It does not tell you the trend direction. The under laid histogram shows relative movements of the price with green showing positive momentum and red showing negative momentum. Use these ADX and DMI together to find trend strength and direction.
- ADX line below 20 indicates that the underlying is in accumulation/distribution.
- ADX line above 20 mean that the underlying is trending with over 60 being very strong.
*When the ADX line is below 20 it is likely to see many reversal signals on the DMI Histogram. It is best to use the DMI signals when the ADX line is above 20 or higher. This is also a good level to play around with.
Motivation
Normally the direction movements are plotted as lines with the DI+ being green and the DI- being red. When the DI+ (green) crosses over DI- (red) this may indicate a buy signal, and vice versa. I found this visual representation made it difficult to see signals as well as lacked the ability to easy see the relative strength of other moves.
I have also noticed that the histogram values will periodically cross the ADX line, but not for very long periods. This could be a useful signal to explore further in the future.
In this image the top indicator is using the normal DI+/- lines, where the bottom indicator is using an absolute histogram.
Risk Distribution HistogramStatistical risk visualization and analysis tool for any ticker 📊
The Risk Distribution Histogram visualizes the statistical distribution of different risk metrics for any financial instrument. It converts risk data into histograms with quartile-based color coding, so that traders can understand their risk, tail-risks, exposure patterns and make data-driven decisions based on empirical evidence rather than assumptions.
The indicator supports multiple risk calculation methods, each designed for different aspects of market analysis, from general volatility assessment to tail risk analysis.
Risk Measurement Methods
Standard Deviation
Captures raw daily price volatility by measuring the dispersion of price movements. Ideal for understanding overall market conditions and timing volatility-based strategies.
Use case: Options trading and volatility analysis.
Average True Range (ATR)
Measures true range as a percentage of price, accounting for gaps and limit moves. Valuable for position sizing across different price levels.
Use case: Position sizing and stop-loss placement.
The chart above illustrates how ATR statistical distribution can be used by looking at the ATR % of price distribution. For example, 90% of the movements are below 5%.
Downside Deviation
Only considers negative price movements, making it ideal for checking downside risk and capital protection rather than capturing upside volatility.
Use case: Downside protection strategies and stop losses.
Drawdown Analysis
Tracks peak-to-trough declines, providing insight into maximum loss potential during different market conditions.
Use case: Risk management and capital preservation.
The chart above illustrates tale risk for the asset (TQQQ), showing that it is possible to have drawdowns higher than 20%.
Entropy-Based Risk (EVaR)
Uses information theory to quantify market uncertainty. Higher entropy values indicate more unpredictable price action, valuable for detecting regime changes.
Use case: Advanced risk modeling and tail-risk.
VIX Histogram
Incorporates the market's fear index directly into analysis, showing how current volatility expectations compare to historical patterns. The CAPITALCOM:VIX histogram is independent from the ticker on the chart.
Use case: Volatility trading and market timing.
Visual Features
The histogram uses quartile-based color coding that immediately shows where current risk levels stand relative to historical patterns:
Green (Q1): Low Risk (0-25th percentile)
Yellow (Q2): Medium-Low Risk (25-50th percentile)
Orange (Q3): Medium-High Risk (50-75th percentile)
Red (Q4): High Risk (75-100th percentile)
The data table provides detailed statistics, including:
Count Distribution: Historical observations in each bin
PMF: Percentage probability for each risk level
CDF: Cumulative probability up to each level
Current Risk Marker: Shows your current position in the distribution
Trading Applications
When current risk falls into upper quartiles (Q3 or Q4), it signals conditions are riskier than 50-75% of historical observations. This guides position sizing and portfolio adjustments.
Key applications:
Position sizing based on empirical risk distributions
Monitoring risk regime changes over time
Comparing risk patterns across timeframes
Risk distribution analysis improves trade timing by identifying when market conditions favor specific strategies.
Enter positions during low-risk periods (Q1)
Reduce exposure in high-risk periods (Q4)
Use percentile rankings for dynamic stop-loss placement
Time volatility strategies using distribution patterns
Detect regime shifts through distribution changes
Compare current conditions to historical benchmarks
Identify outlier events in tail regions
Validate quantitative models with empirical data
Configuration Options
Data Collection
Lookback Period: Control amount of historical data analyzed
Date Range Filtering: Focus on specific market periods
Sample Size Validation: Automatic reliability warnings
Histogram Customization
Bin Count: 10-50 bins for different detail levels
Auto/Manual Bin Width: Optimize for your data range
Visual Preferences: Custom colors and font sizes
Implementation Guide
Start with Standard Deviation on daily charts for the most intuitive introduction to distribution-based risk analysis.
Method Selection: Begin with Standard Deviation
Setup: Use daily charts with 20-30 bins
Interpretation: Focus on quartile transitions as signals
Monitoring: Track distribution changes for regime detection
The tool provides comprehensive statistics including mean, standard deviation, quartiles, and current position metrics like Z-score and percentile ranking.
Enjoy, and please let me know your feedback! 😊🥂
Moving Averages HistogramAn interesting idea is to simplify the display of whether ONE fast-moving average crosses FIVE other slower-moving averages using just a histogram.
The idea is to increase the step counter by 1 every time a fast-moving average crosses OVER one of the five slower-moving averages until reaching 5 (highest value) and decrease the step counter by 1 every time the fast-moving average crosses UNDER each one of the five slower moving averages until reaching 0 (lowest value of the histogram).
=== Cut To Chase ===
If the histogram is at the top value 5 (green), it means the FAST moving average is ABOVE ALL slower-moving averages, Hench, the asset is up trending.
If the histogram is at the bottom value 0 (red), it means the FAST moving average is BELOW ALL slower-moving averages, Hench, the asset is down trending.
If the histogram is in the midways between 0 to 5, it means the FAST moving average is starting to cross the slower moving averages which could lead to a trend reversal, up or down, it depends on the direction of the crossing.
=== Notes ===
You can change from a variety of moving averages like RMA, EMA, ALMA, HMA, and so on.
You can reduce the number of slow-moving averages by placing the same length.
You can visualize the moving averages in case you want to see how it works behind, by going to settings and clicking 'Show MA lines'.
Every moving average length can be modified inside settings.
Note that the fast-moving average should have the lowest length.
You can visualize how the moving average is plotted:
MA MTF Momentum HistogramMy own interpretation indicator which i call multi time frame moving averages momentum with NO LAG EMA support (Optional).
The indicator is calculated by subtracting the long-term EMA from the short-term EMA .
This pretty much resembles the MACD moving averages calculation but without the smoothing of the histogram.
Can also be used to find divergences.
The background shows the main trend with higher time frame which can be set in the settings.
Aimed to use with Higher time frame (Double or more) but can also work with lower time frame.
How to use the indicator?
==Histogram==
Green: Momentum of asset is positive and increasing.
Lighter Green: Momentum of asset is still positive but decreasing and can revert to negative momentum.
Red: Momentum of asset is negative and increasing.
Lighter Red: Momentum of asset is still negative but increasing and revert to positive momentum.
==Background Color - Main Trend==
Green: HTF (Higher time frame) momentum is positive.
RED: HTF momentum is negative.
Feel free to comment and Follow to stay updated with upcoming scripts: www.tradingview.com
NOTE: BARS ARE COLORED BY DEFAULT WITH HISTOGRAM COLORS! (Can be changed in settings)
Price Volume Trend + Signal and HistogramThis is a script based on PVT + Signal Line, which can be EMA or SMA. It then plots a histogram which is equal to PVT - Signal. This makes it easier to spot divergences.
To better match up the scales, we decided to add a multiplication factor to the histogram. Each asset and even timeframe requires a different multiplication factor, so please experiment to find what suits you.
Credits and special thanks are listed on the source code.
Price/Volume Value HistogramAn interesting implementation of mine to measure an asset changes based on asset price velocity and volume velocity. The indicator acts as asset value calculator. Long and Short.
==Points System Rules==
UPTRENDING
If Current Close is higher than previous Close and Current Volume is bigger than previous Volume: Adds Close Points and Volume Points
Otherwise check
If Current Close is higher than previous Close: Adds Only Close Points
DOWNTRENDING
If Current Close is lower than previous Close and Current Volume is bigger than previous Volume: Reduces Close Points and Volume Points
Otherwise check
If Current Close is lower than previous Close: Reduces Only Close Points
==Plotting==
Result of the values are summed up to a histogram.
Obviously on increasing prices and volume the histogram will be above zero line and on the Bullish side (green color), otherwise, on the Bearish side (red color).
You can't cheat the price movement, it's just what it is.
Optional to smooth it by EMA (set to true by default).
Like if you Like and Enjoy!
Follow for upcoming indicators.
Buying and Selling Smoothed with HistogramBuying and Selling Smoothed with Histogram
Smoothed version with version with a red line representing the selling pressure and a green line which represents the Buying pressure.
If the green line is above the red line it would mean that the Buying pressure is more and vice versa.
The difference between the two is plotted as a Histogram. This is a cumulative value of the buying and selling pressure and provides a easy visual presentation of the dominating pressure.
Linear Regression Histogram [LuxAlgo]This indicator is inspired by traditional statistical histograms. It will return the number of occurrences of price falling within each interval (bins) of the linear regression channel. This can be useful to highlight zones of interest within a trend.
Settings
Length: Number of recent closing prices used for the computation of the linear regression.
Bins Number: Number of intervals constructed from the linear regression channel.
Mult: Multiplicative factor for the RMSE. Controls the width of the linear regression channel.
Src: Input source of the indicator.
Usage
The indicator is constructed by dividing the linear regression channel range into a series of intervals (bins) of equal width. We then count the number of price values falling within each interval.
If a significant number of price values fall within a specific interval then that interval can highlight a potential zone of interest within a trend.
The zone of interest is highlighted in blue.
Percent Change HistogramThis indicator shows you percent changes in a super visual way using a color-coded histogram.
Here's how the colors work:
🟩 Dark green = percent change is growing stronger
🟢 Light green = still positive but losing steam
🟥 Dark red = getting more negative
🔴 Light red = negative but improving
The cool part? You can set any lookback period you want. For example:
24 periods on 1H chart = last 24 hours
30 periods on daily = last month
7 periods on daily = last week
Pro tip: You're not locked to your chart's timeframe! Want to see monthly changes while trading on 5min?
No problem.
You can even stack multiple indicators to watch different intervals simultaneously (daily, weekly, monthly) - super helpful for multi-timeframe analysis.
Perfect for spotting momentum shifts across different timeframes without switching between charts.
Quantum CDV HistogramThis script is an addition to Fixed Quantum Cdv.
It shows vector cdv ratio in columns.
You can select the length as an input to how many bars to look back for the whole calculation.
The green bars represent the bullish values and the red bars the bearish values.
The green line represents an ema of the bullish value and the red line the ema of the bearish value.
The momentum ema (in purple) represent the cdv ratio (bullish - bearish).
When the momentum ema is at 100% or more it’s a good sell opportunity and when the momentum ema is at or under 100% it’s a good buy opportunity. It is not financial advise. Make sure to make your own analysis. This script help to make entries, but do not enter positions only based on this signal.
In the inputs you can select the emas that you want to display on your histogram.
The original script is the Cumulative Delta Volume by LonesomeTheBlue.
Close Counter HistogramAn interesting experiment to make an indicator act as a counter. I call it CCH - Close Counter Histogram.
It adds 1 when current close is higher than previous close and reduces -1 when current close is lower than previous close.
In the CCH settings you set how many bars to look back and use EMA to smooth the results or disable EMA smoothing.
Disable the EMA smoothing and you'll see the real deal (pure counter).
The higher the GREEN columns the more higher closes and the lower the RED columns the more lower closes.
In case columns are declining above 0 a more darker green will appear.
In case columns are declining below 0 a more darker red will appear.
Supports bar coloring (disabled by default).
Feel free to comment and Like if you like.
Enjoy :)
Z-HistogramIt is possible to approximate the underlying distribution of a random variable by using what is called an "Histogram". In order to construct an histogram one must first split the data into several intervals (also called bins) often of the same size and count the number of values falling within each intervals, the histogram plot is then constructed with the X axis representing the measured variable and the Y axis representing the frequency.
The proposed script aim to estimate the underlying distribution of a rolling z-score by constructing its histogram, here the histogram consist of 13 bins of width 0.5 rolling standard deviations. The length setting define the rolling z-score period, the window setting define the number of past data to be counted, finally using the "Total" option (true by default) will count all the rolling z-scores values since the first bar, in order to use the window setting make sure to uncheck the "Total" option.
DISPLAY
In order to see the entirety of the histogram make sure to double click on the indicator window and to have all the lower panels (text notes, pine editor...etc) hidden, finally make sure to zoom-in in order to see the frequency numbers displayed.
Z-Histogram on BTCUSD 15 min TF, the blue bins represent intervals situated over 0 while red bins represent intervals situated under 0. Here σ represent the X-axis in standard deviations, the histogram start with a bin situated at σ = -3 which count the number of times the rolling z-score was within -3 and -2.5, the histogram end with the bin situated at σ = 3 which count the number of time the rolling z-score was within 3 and 3.5.
It is also possible to look at the shape of the histogram without having the indicator window at full size.
INTERPREATION
An histogram can give really interesting information such as overall trend direction and strength. The direction can be measured by looking at the skewness of the histogram, with a negative skewness (the peak of the histogram situated at the right from the center) representing down-trending variations and positive skewness (the peak of the histogram situated at the left from the center) representing up-trending variations, while a symmetrical histogram could represent a ranging market. The farther away the peak of the histogram is situated from the center, the stronger the trend.
Another interesting characteristic is the tailedness of the histogram, which can give information about the cleanliness of the trend, for example a positive skew and high tailedness would represent a clean up-trend, as it could suggest less variations contrary to the main trend.
An histogram applied to the rolling z-score can give various useful information. As a recall the rolling z-score of the price measure the distance between the closing price and its moving average in term of rolling standard deviations, for example if the rolling z-score is equal to 2 it means that the closing price is currently 2 rolling standard deviations over its moving average.
Lets for example analyze the histogram using INTC 15 min tf with a window of 456 bars and rolling z-score of length = 100 in order to review longer term variations.
We can see from the histogram that the uptrend visible on the chart is represented by the bins situated over 0 having an overall higher frequency than the bins under 0, we can see that the closing price tended to stay between 1 and 1.5 rolling standard deviations over its period 100 moving average. Here bins under 0 accounts for retracements in the trend.
IN SUMMARY
An histogram can give various information regarding the price evolution of a security, the proposed script aim to plot the histogram of a rolling z-score. Now this script might not be too useful but it was fun to make, also it does not mean that an histogram is not an useful tool in the context of trading, the only thing required is a god implementation of it (like volume profiles for example)
In this post we have also reviewed some important statistical concepts such as distributions, z-score, skewness and tailedness, each being extremely important in the quantitative trading field.
Thx for reading !
Multi Asset Histogram [ChartPrime]Multi Asset Histogram Indicator
Overview:
The "Multi Asset Histogram" indicator provides a comprehensive visualization of the performance of multiple assets relative to each other. By calculating a score for each asset and displaying it in a histogram format, this indicator helps traders quickly identify the trends, dominant asset and the average performance of the assets in the selected group.
Key Features:
◆ Multi-Asset Score Calculation:
The indicator calculates a trend score for each selected asset based on the price source (e.g., hl2).
The trend score is determined by comparing the current price to the prices over the past bars back defined by user, adding or subtracting points based on whether the current price is higher or lower than previous prices.
// Score Function
trscore(src) =>
total = 0.0
for i = 1 to 50
total += (src >= nz(src ) ? 1 : -1)
total
◆ Flexible Symbol Input:
Traders can input up to 10 different symbols (e.g., BTCUSD, ETHUSD, etc.) to be included in the histogram analysis.
◆ Dynamic Visualization:
A histogram is plotted for each asset, with bars colored based on the score, providing a clear visual representation of the relative performance.
Color gradients from red to aqua indicate the performance, with red representing negative scores and aqua representing positive scores.
◆ Adaptive Histogram Lines:
The width and placement of histogram lines adapt based on the calculated scores, ensuring clear visualization regardless of the values.
Dashed lines represent the mean score of all assets, helping traders identify the overall market trend.
◆Detailed Labels and Values:
Labels are placed on the histogram to display the exact score for each asset.
Mean value and zero line labels provide additional context for the overall performance.
◆ Visual Scaling Lines:
Zero line and mean line are clearly marked, helping traders understand the distribution and scale of scores.
Scales on the left and right of the histogram indicate the performance range.
◆ Informative Table:
A table is displayed on the chart, showing the dominant asset (the one with the highest score) and the mean score of all assets.
The table updates dynamically to reflect real-time changes in asset performance.
◆ Settings:
Length: The value of number bars back is greater or less than the current value of the source
Source: The price source to be used for score calculation (e.g., hl2).
Symbols: Up to 10 different asset symbols can be input for analysis.
Usage Notes:
This indicator is useful for traders who monitor multiple assets simultaneously and need a quick visual reference to identify the strongest and weakest performers.
The color coding and dynamic labels make it easy to interpret the relative performance and make informed trading decisions.
This indicator is designed to enhance multi-asset analysis by providing a clear, visual representation of each asset's performance relative to the others, making it easier to identify trends and dominant assets in the market.
[blackcat] L1 Close Histogram OscillatorLevel: 1
Background
A histogram is a special chart that is applied to statistical data that is divided into numerically ordered groups. For example groups with close relationships in the vicinity like "Close-ref(Close ,1)", "Close-ref(Close,2)" and so on. A histogram provides a snapshot of all the data so that you can quickly get an overview of the historical data, especially its general shape.In a histogram, the bars are linked - in contrast to a bar chart for categorical data, in which the bars represent categories that are in no particular order and are separated. The height of each bar in a histogram indicates either the number of individuals (called the frequency) in each group or the percentage of individuals (the relative frequency) in each group. Each individual in the data set falls into exactly one bar.
Function
L2 Close Histogram Oscillator is a novel overbought and oversold indicator that estimate the trend state by counting a specific bar relationship nearby. Once nearby bars reach consensus, it may spread to global quickly. The reason why I got this inspiration is because I have been engaged in the research of blockchain consensus mechanism. The market is a complex system, and its consensus depends on the common human characteristics: greed and fear. The trend of the market often also conforms to sociological characteristics. Maybe it's a bit complicated for me to say that. However, if you understand the principle of the spread of rumors and viruses, you can understand the situation where some individuals in the market have local consensus and gradually spread to the overall situation. This is the process of trend formation.
Key Signal
fastcounter --> fast close histogram counters
slowcounter --> slow close histogram counters
attention --> bottom price appears, with height of 10 in white
readybuy --> a small position buy opportunity after first bottom detected, with height of 20 in yellow
buylow --> a small position buy at low price, with height of 30 in lime
longentry --> a confirmed long entry signal by close histogram counter, with height of 40 in green
risk --> oscillator top is reached and trend reversal may happen, with height drop from 100 to 80 in red
Pros and Cons
Pros:
1. since this is based on consensus formation principle, i think this is a leading indicator by spreading local consensus to global
2. it is an oscillator, overbought and oversold can be easily observed.
Cons:
1. the model is not complex enough to depict market behavior exactly.
2. sideways and chop market will make this indicator's output hard to read.
Remarks
This is rare! I combined my previous theory of developing cellular automata with the market to produce such a weird indicator. I hope to inspire everyone and study market behavior in a deeper level.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Statistical Histogram with configurable bins and Data WindowCreates a Histogram for Statistical Analysis of any source.
Input Parameters:
Sample Source: Select your source here, can be any numerical source.
Sample Period: Sample size for Mean and Standard Deviation Calculations.
Enable Cumulative Mode: Will attempt to calculate the bin for every sample in the entire dataset.
Window Period: Used only in Window Mode (Enable Cumulative Mode unchecked), Calculates the bin for the past Window Period sample size.
Bin Label Spacing: Adjust horizontal spacing of Bin Labels below the histogram for easier viewing.
Center Bin: Selects the center Bin, usually set to (0 - Bin Width) < Sample <= 0 standard deviations or (z_score)
Bin Width: Selects the Bin Width in standard deviations.
How you can use it:
View characteristics of dataset such as unimodal/bimodal and skewness to determine preferred statistical analysis.
Additional Reference:
en.wikipedia.org
en.wikipedia.org
Credits:
Thanks goes out to www.tradingview.com , for cleaning up some of the code and www.tradingview.com for the original idea.
Usage Tips:
When adjusting the bin parameters, center bin and bin width, verify that the total sum of the bins (Sum Frequency in the Data Window) is close to the Total Samples. If your Sum Frequency is drastically lower it means you need to adjust your center bin and/or bin width to capture more of the data available.
MACD histogram divergence by Rexio v1Hi everyone!
I wrote this indicator for intraday trading and it cannot be use only by itself you need to at least draw some S/R lines to make it useful. It is based at MACD histogram and gives signal when it sees divergence on MACD's Histogram when macd's histogram switchs trend. Im using it to playing with a trend most of the time looking. It highlights candles which can give good singnals to play with a trend (its based on ema200 and RSI overbought and oversold zones).
Im not a computer programist nor professional trader so it is only for educational purposes only.
TRIX Histogram R1-12 by JustUncleLCreated by request.
Description:
This study is an implementation of the Standard TRIX indicator (a momentum oscillator), shown in coloured histogram format by default, with optional Bar colouring of TRIX zero cross overs. Other options include showing TRIX as a line graph instead of histogram and an optional TRIX signal line with difference histogram (to highlight signal line crosses).
References:
forex-indicators.net
"TRIX MA" by munkeefonix
1st Gray Cross Signals ━ Histogram SQZMOM [whvntr][LazyBear]This is the Histogram Version of one of my other indicators named: SQZ Momentum + 1st Gray Cross Signals (with arrows) Which is a modification of "Squeeze Momentum Indicator" by user: "LazyBear". In that indicator of his he described, and suggested, the use of his gray cross signals to find points of interest for trading based on the direction of momentum when the first gray cross appears... I have programmed these points, and highlighted them, for ease of use. The 1st gray cross strategy, he said , is from John F. Carter's book, Chapter 11, "Mastering the Trade".
Here we have the Histogram version, with background highlights only, and nothing on the chart, in true SQZ Momentum style.
Disclaimer: using this indicator, or any indicator anywhere, involves risk when trading and isn't a guarantee of 100% accurate results.
OMA (One More Average) RSI Histogram [Loxx]OMA (One More Average) RSI Histogram is an RSI histogram built using the OMA adaptive moving average. This is meant to filter out the noise from regular RSI. You'll notice that it rarely signals, but the signals that do show up are perfectly set up for mean reversion/trend ATR-based trading.
What is the One More Moving Average (OMA)?
The usual story goes something like this : which is the best moving average? Everyone that ever started to do any kind of technical analysis was pulled into this "game". Comparing, testing, looking for new ones, testing ...
The idea of this one is simple: it should not be itself, but it should be a kind of a chameleon - it should "imitate" as much other moving averages as it can. So the need for zillion different moving averages would diminish. And it should have some extra, of course:
How to use
Green means buy
Red means sell
Included
Bar coloring
