Trend Surfers - Momentum + ADX + EMAThis script mixes the Lazybear Momentum indicator, ADX indicator, and EMA.
Histogram meaning:
Green = The momentum is growing and the ADX is growing or above your set value
Red = The momentum is growing on the downside and the ADX is growing or above your set value
Orange = The market doesn't have enough momentum or the ADX is not growing or above your value (no trend)
Background meaning:
Blue = The price is above the EMA
Purple = The price is under the EMA
Cross color on 0 line:
Dark = The market might be sideway still
Light = The market is in a bigger move
Tìm kiếm tập lệnh với "histogram"
CFB-Adaptive, Jurik DMX Histogram [Loxx]Jurik DMX Histogram is the ultra-smooth, low lag version of your classic DMI indicator. This is a momentum indicator. You can use this indicator standalone or as part of a system with a moving average and a mean reversion indicator. This indicator has both composite fractal behavior adaptive inputs and fixed inputs. The default is CFB adaptive. Dark green means strong push up, dark red, strong push down. Light green means weak push up, and light red means weak push down.
What is the directional movement index?
The directional movement index (DMI) is an indicator developed by J. Welles Wilder in 1978 that identifies in which direction the price of an asset is moving. The indicator does this by comparing prior highs and lows and drawing two lines: a positive directional movement line ( +DI ) and a negative directional movement line ( -DI ). An optional third line, called the average directional index ( ADX ), can also be used to gauge the strength of the uptrend or downtrend.
When +DI is above -DI , there is more upward pressure than downward pressure in the price. Conversely, if -DI is above +DI , then there is more downward pressure on the price. This indicator may help traders assess the trend direction. Crossovers between the lines are also sometimes used as trade signals to buy or sell.
What is Composite Fractal Behavior ( CFB )?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
Included:
Alerts
Loxx's Expanded Source Types
Signals
Bar coloring
CFB-Adaptive Velocity Histogram [Loxx]CFB-Adaptive Velocity Histogram is a velocity indicator with One-More-Moving-Average Adaptive Smoothing of input source value and Jurik's Composite-Fractal-Behavior-Adaptive Price-Trend-Period input with Dynamic Zones. All Juirk smoothing allows for both single and double Jurik smoothing passes. Velocity is adjusted to pips but there is no input value for the user. This indicator is tuned for Forex but can be used on any time series data.
What is Composite Fractal Behavior ( CFB )?
All around you mechanisms adjust themselves to their environment. From simple thermostats that react to air temperature to computer chips in modern cars that respond to changes in engine temperature, r.p.m.'s, torque, and throttle position. It was only a matter of time before fast desktop computers applied the mathematics of self-adjustment to systems that trade the financial markets.
Unlike basic systems with fixed formulas, an adaptive system adjusts its own equations. For example, start with a basic channel breakout system that uses the highest closing price of the last N bars as a threshold for detecting breakouts on the up side. An adaptive and improved version of this system would adjust N according to market conditions, such as momentum, price volatility or acceleration.
Since many systems are based directly or indirectly on cycles, another useful measure of market condition is the periodic length of a price chart's dominant cycle, (DC), that cycle with the greatest influence on price action.
The utility of this new DC measure was noted by author Murray Ruggiero in the January '96 issue of Futures Magazine. In it. Mr. Ruggiero used it to adaptive adjust the value of N in a channel breakout system. He then simulated trading 15 years of D-Mark futures in order to compare its performance to a similar system that had a fixed optimal value of N. The adaptive version produced 20% more profit!
This DC index utilized the popular MESA algorithm (a formulation by John Ehlers adapted from Burg's maximum entropy algorithm, MEM). Unfortunately, the DC approach is problematic when the market has no real dominant cycle momentum, because the mathematics will produce a value whether or not one actually exists! Therefore, we developed a proprietary indicator that does not presuppose the presence of market cycles. It's called CFB (Composite Fractal Behavior) and it works well whether or not the market is cyclic.
CFB examines price action for a particular fractal pattern, categorizes them by size, and then outputs a composite fractal size index. This index is smooth, timely and accurate
Essentially, CFB reveals the length of the market's trending action time frame. Long trending activity produces a large CFB index and short choppy action produces a small index value. Investors have found many applications for CFB which involve scaling other existing technical indicators adaptively, on a bar-to-bar basis.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
What are Dynamic Zones?
As explained in "Stocks & Commodities V15:7 (306-310): Dynamic Zones by Leo Zamansky, Ph .D., and David Stendahl"
Most indicators use a fixed zone for buy and sell signals. Here’ s a concept based on zones that are responsive to past levels of the indicator.
One approach to active investing employs the use of oscillators to exploit tradable market trends. This investing style follows a very simple form of logic: Enter the market only when an oscillator has moved far above or below traditional trading lev- els. However, these oscillator- driven systems lack the ability to evolve with the market because they use fixed buy and sell zones. Traders typically use one set of buy and sell zones for a bull market and substantially different zones for a bear market. And therein lies the problem.
Once traders begin introducing their market opinions into trading equations, by changing the zones, they negate the system’s mechanical nature. The objective is to have a system automatically define its own buy and sell zones and thereby profitably trade in any market — bull or bear. Dynamic zones offer a solution to the problem of fixed buy and sell zones for any oscillator-driven system.
An indicator’s extreme levels can be quantified using statistical methods. These extreme levels are calculated for a certain period and serve as the buy and sell zones for a trading system. The repetition of this statistical process for every value of the indicator creates values that become the dynamic zones. The zones are calculated in such a way that the probability of the indicator value rising above, or falling below, the dynamic zones is equal to a given probability input set by the trader.
To better understand dynamic zones, let's first describe them mathematically and then explain their use. The dynamic zones definition:
Find V such that:
For dynamic zone buy: P{X <= V}=P1
For dynamic zone sell: P{X >= V}=P2
where P1 and P2 are the probabilities set by the trader, X is the value of the indicator for the selected period and V represents the value of the dynamic zone.
The probability input P1 and P2 can be adjusted by the trader to encompass as much or as little data as the trader would like. The smaller the probability, the fewer data values above and below the dynamic zones. This translates into a wider range between the buy and sell zones. If a 10% probability is used for P1 and P2, only those data values that make up the top 10% and bottom 10% for an indicator are used in the construction of the zones. Of the values, 80% will fall between the two extreme levels. Because dynamic zone levels are penetrated so infrequently, when this happens, traders know that the market has truly moved into overbought or oversold territory.
Calculating the Dynamic Zones
The algorithm for the dynamic zones is a series of steps. First, decide the value of the lookback period t. Next, decide the value of the probability Pbuy for buy zone and value of the probability Psell for the sell zone.
For i=1, to the last lookback period, build the distribution f(x) of the price during the lookback period i. Then find the value Vi1 such that the probability of the price less than or equal to Vi1 during the lookback period i is equal to Pbuy. Find the value Vi2 such that the probability of the price greater or equal to Vi2 during the lookback period i is equal to Psell. The sequence of Vi1 for all periods gives the buy zone. The sequence of Vi2 for all periods gives the sell zone.
In the algorithm description, we have: Build the distribution f(x) of the price during the lookback period i. The distribution here is empirical namely, how many times a given value of x appeared during the lookback period. The problem is to find such x that the probability of a price being greater or equal to x will be equal to a probability selected by the user. Probability is the area under the distribution curve. The task is to find such value of x that the area under the distribution curve to the right of x will be equal to the probability selected by the user. That x is the dynamic zone.
Included:
Bar coloring
3 signal variations w/ alerts
Divergences w/ alerts
Loxx's Expanded Source Types
Jurik DMX Histogram [Loxx]Jurik DMX Histogram is the ultra-smooth, low lag version of your classic DMI indicator.
What is the directional movement index?
The directional movement index (DMI) is an indicator developed by J. Welles Wilder in 1978 that identifies in which direction the price of an asset is moving. The indicator does this by comparing prior highs and lows and drawing two lines: a positive directional movement line (+DI) and a negative directional movement line (-DI). An optional third line, called the average directional index (ADX), can also be used to gauge the strength of the uptrend or downtrend.
When +DI is above -DI, there is more upward pressure than downward pressure in the price. Conversely, if -DI is above +DI, then there is more downward pressure on the price. This indicator may help traders assess the trend direction. Crossovers between the lines are also sometimes used as trade signals to buy or sell.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
What is an adaptive cycle, and what is Ehlers Autocorrelation Periodogram Algorithm?
From his Ehlers' book Cycle Analytics for Traders Advanced Technical Trading Concepts by John F. Ehlers , 2013, page 135:
"Adaptive filters can have several different meanings. For example, Perry Kaufman’s adaptive moving average ( KAMA ) and Tushar Chande’s variable index dynamic average ( VIDYA ) adapt to changes in volatility . By definition, these filters are reactive to price changes, and therefore they close the barn door after the horse is gone.The adaptive filters discussed in this chapter are the familiar Stochastic , relative strength index ( RSI ), commodity channel index ( CCI ), and band-pass filter.The key parameter in each case is the look-back period used to calculate the indicator. This look-back period is commonly a fixed value. However, since the measured cycle period is changing, it makes sense to adapt these indicators to the measured cycle period. When tradable market cycles are observed, they tend to persist for a short while.Therefore, by tuning the indicators to the measure cycle period they are optimized for current conditions and can even have predictive characteristics.
The dominant cycle period is measured using the Autocorrelation Periodogram Algorithm. That dominant cycle dynamically sets the look-back period for the indicators. I employ my own streamlined computation for the indicators that provide smoother and easier to interpret outputs than traditional methods. Further, the indicator codes have been modified to remove the effects of spectral dilation.This basically creates a whole new set of indicators for your trading arsenal."
Included
- Toggle on/off bar coloring
Heiken Ashi Smoothed Net VolumeThis indicator attempts to use Heiken Ashi calculations to smooth the Volume net histogram indicator by RafaelZioni. Long above zero line, short below zero line.
ATR Drift %This script plots an histogram calculated this way:
Get the previous ATR sample, calculated in the specified timeframe
Get the actual open price of the bar in the specified timeframe minus the actual price in the current timeframe
and plots the percent change between the the 2 values
For example, if you select DAY as timeframe for the ATR:
Plots the percent change between:
- ATR(daily) from yesterday
and
- open from today - actual price
Due to Tradingview limitations, only shows the plot if the actual timeframe of the graphic is equal or lower that the ATR selected timeframe
The background changes shows a new ATR sample taking place
I'm testing this for scalping in 5M timeframe with the ATR in 4H
All my published scripts at: es.tradingview.com
5min MACD scalp by JoelThis strategy is inspired by a youtuber called Joel on Crypto. He trades this using Ema, MACD indicators and his own experience. For more information, check out his Best Crypto Scalping Strategy for the 5 Min Time Frame video. I have tried to automate this a little.
Long or Short trades are determined with a crossing of the fast Ema over the slow Ema for Long and the opposite for Short. Trades should only happen close to the crossovers. Then for Long we use the MACD indicator with a 1min TF (I had better results using the 5min) where we look for high peaks in negative values for Long and vice versa for Shorts. These should be significantly higher than other peaks (or if you will lower peaks for a Long).
Hence, the key is to detect high peaks on the histogram, which I try to achieve by checking if the last 2 values were higher than X bars back. If you want to make it even more specific, then you can turn on the additional checkbox which compares the current value to the average value of X bars back, and if it is greater than, say, 50% the value of the average (= 1.5x the average), then it's ok for the trade.
I also noticed that the strategy often bought at the top or bottom, so I added a check that compares whether the last evaluated bar is the first rising bar (for Long) or falling bar (for Short). This can be turned on or off.
Target profit 0,5% and stop loss 0,4% are based on his recommendation. The strategy is set to take only 1 trade at a time , and you can have a back tester table on.
I'm still a pine script beginner, so the strategy is certainly not perfect and could be improved. If you have any tips on how to improve it further, please let me know. I will try to update it when I have time.
I would also like to thank Joel on Crypto for sharing the strategy and @ZenAndTheArtOfTrading for his great library and code (thanks to him we have a back tester table in here), but especially his educational videos on youtube, which taught me a lot about pine script.
VWMACDV2 w/Intraday Intensity Index Histogram & VBCB Hello traders! In this script i tried to combine Kıvanç Özbilgiç's Volume Based Coloured Bars, Volume Weighted Macd V2 and Intraday Intensity Index developed by Dave Bostian and added to Tradingview by Kıvanç Özbilgiç. Let's see what we got here;
VBCB, Paints candlestick bars according to the volume of that bar. Period is 30 by default. If you're trading stocks, 21 should be better.
Volume Weighted Macd V2, "Here in this version; Exponential Moving Averages used and Weighted by Volume instead of using only vwma (Volume Weighted Moving Averages)." Says, Kıvanç Özbilgiç.
III, "A technical indicator that approximates the volume of trading for a specified security in a given day. It is designed to help track the activity of institutional block traders and is calculated by subtracting the day's high and low from double the closing price, divided by the volume and multiplied by the difference between the high and the low."
*Histogram of vwmacd changes color according to the value of III. (Green if positive, yellow if negative value)*
VWMACD also comes with the values of 21,13,3... Which are fibonacci numbers and that's how i use it. You can always go back to the good old 26,12,9.
Other options according to the fibonacci numbers might be= 21,13,5-13,8,3-13,8,5... (For shorter terms of trading)
Trading combined with the bollinger bands is strongly advised for both VWMACD and III. VBCB is just the candy on top :)
Enjoy!
Cosmic AngleThis is a histogram that can display a moving average's angle and also show how volatile the change in angle is.
To use:
Add any moving average indicator to the chart
Click that indicator's More > Add Indicator on (MA)
Select the Cosmic Angle indicator
Adjust the Cosmic Angle 's Price To Bar Ratio value to reflect that of your chart's
Adjust the Cosmic Angle 's Threshold as per your liking (*1)
(*1) This setting affects the bar colors. It represents the minimum difference in degrees between the n and n-1 bars' angle to force a change of color.
Relative Strength of Volume Indicators by DGTThe Relative Strength Index (RSI) , developed by J. Welles Wilder, is a momentum oscillator that measures the speed and change of price movements.
• Traditionally the RSI is considered overbought when above 70 and may be primed for a trend reversal or corrective pullback in price, and oversold or undervalued condition when below 30. During strong trends, the RSI may remain in overbought or oversold for extended periods.
• Signals can be generated by looking for divergences and failure swings. If underlying prices make a new high or low that isn't confirmed by the RSI, this divergence can signal a price reversal. If the RSI makes a lower high and then follows with a downside move below a previous low, a Top Swing Failure has occurred. If the RSI makes a higher low and then follows with an upside move above a previous high, a Bottom Swing Failure has occurred
• RSI can also be used to identify the general trend. In an uptrend or bull market, the RSI tends to remain in the 40 to 90 range with the 40-50 zone acting as support. During a downtrend or bear market the RSI tends to stay between the 10 to 60 range with the 50-60 zone acting as resistance
This study aim to implement Relative Strength concept on most common Volume indicators, such as
• Accumulation Distribution is a volume based indicator designed to measure underlying supply and demand
• Elder's Force Index (EFI) measures the power behind a price movement using price and volume
• Money Flow Index (MFI) measures buying and selling pressure through analyzing both price and volume (used as it is)
• On Balance Volume (OBV) , created by Joe Granville, is a momentum indicator that measures positive and negative volume flow
• Price Volume Trend (PVT) is a momentum based indicator used to measure money flow
Plotting will be performed for regular RSI and RSI of Volume indicator (RSI(VOLX)) selected from the dialog box, where the possibility to apply smoothing is provided as option. Additionally, labels can be added optionally to display the value and name of selected volume indicator
Secondly, ability to present Volume Histogram within the same study along with its Moving Average or Volume Oscillator based on selection
Finally, Volume Based Colored Bars , a study of Kıvanç Özbilgiç is added to emphasis volume changes on top of the bars
Nothing excessively new, the study combines RSI with;
- RSI concept applied to some of the common Volume indicators presented with a highlighted over/under valued threshold area, optional labeling and smoothing,
- added Volume data with additional information and
- colored bars based on volume
Thanks @Vishant_Meshram for the inspiration 🙏
Disclaimer:
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
The script is for informational and educational purposes only. Use of the script does not constitute professional and/or financial advice. You alone have the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Oscillating Snake HistogramWhat's up guys ;) Check out this bad boy, it's like a swiss army knife cuz it gives you information on volatility (size of histogram bars) and direction (color of bars). Enjoy!
Elliott Wave Oscillator Signals by DGTElliott Wave Principle , developed by Ralph Nelson Elliott, proposes that the seemingly chaotic behaviour of the different financial markets isn’t actually chaotic. In fact the markets moves in predictable, repetitive cycles or waves and can be measured and forecast using Fibonacci numbers. These waves are a result of influence on investors from outside sources primarily the current psychology of the masses at that given time. Elliott wave predicts that the prices of the a traded currency pair will evolve in waves: five impulsive waves and three corrective waves. Impulsive waves give the main direction of the market expansion and the corrective waves are in the opposite direction (corrective wave occurrences and combination corrective wave occurrences are much higher comparing to impulsive waves)
The Elliott Wave Oscillator (EWO) helps identifying where you are in the 5-3 Elliott Waves, mainly the highest/lowest values of the oscillator might indicate a potential bullish/bearish Wave 3. Mathematically expressed, EWO is the difference between a 5-period and 35-period moving average based on the close. In this study instead 35-period, Fibonacci number 34 is implemented for the slow moving average and formula becomes ewo = ema(source, 5) - ema(source, 34)
The application of the Elliott Wave theory in real time trading gets difficult because the charts look messy. This study (EWO-S) simplifies the visualization of EWO and plots labels on probable reversals/corrections. The good part is that all plotting’s are performed on the top of the price chart including a histogram (optional and supported on higher timeframes). Additionally optional Keltner Channels Cloud added to help confirming the price actions.
What to look for:
Plotted labels can be used to follow the Elliott Wave occurrences and most importantly they can be considered as signals for possible trade setup opportunities. Elliott Wave Rules and Fibonacci Retracement/Extensions are suggested to confirm the patters provided by the EWO-S
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
Disclaimer : The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Divergence Histogram for Many IndicatorHello Traders,
This script analyses divergences for 11 predefined indicators and then draws column on the graph. Red columns for negatif divergence (means prices may go down or trend reversal), Lime columns for positive divergences (means prices may go up or trend reversal)
The script uses Pivot Points and on each bar it checks divergence between last Pivot Point and current High/Low and if it finds any divergence then immediately draws column. There is no Latency/Lag.
There are predefined 11 indicators in the script, which are RSI , MACD , MACD Histogram, Stochastic , CCI , Momentum, OBV, Diosc, VWMACD, CMF and MFI.
Smaller Pivot Point Period check smaller areas and if you use smaller numbers it would be more sensitive and may give alerts very often. So you should set it accordingly.
There is "Check Cut-Through in indicators" option, I recomment you to enable it. it checks that there is cut-through in indicators or not, if no cut-through then it's shown as valid divergence.
You should see following one as well if you haven't yet:
Enjoy!
Inflation Rate HistogramThis script is designed to show a histogram of the inflation rate, based on FRED's CPI data. It shows the yearly change in cpiaucsl. As of right now, this script only works correctly on the yearly timeframe (12M). I'm currently looking into a solution to make this script work on all time frames. This script can be useful for comparing growth to inflation, or just if you want to see how inflation was for a certain year. This script really puts the stagflation into perspective.
WMA + MACD strategy with trailing stopHi!
That's my first strategy. I already learn pine, so i will work on it more. Now i search how to make trailing stop working.
"WMA + MACD strategy with traiing stop" is very simple strategy which is designated for stocks market. It is created only to take long positions.
Buy signal is when WMA(120) is below price and macd(10,20,10) histogram is higher than 0.
Position should be automaticly closed when price hits stoploss level.
One transaction should be max 20% of our capital and stoploss is set 3% lower than last closing price.
Point and Figure (PnF) Moving Averages HistogramThis is live and non-repainting Point and Figure Chart Moving Average Histogram tool. The script has it’s own P&F engine and not using integrated function of Trading View.
Point and Figure method is over 150 years old. It consist of columns that represent filtered price movements. Time is not a factor on P&F chart but as you can see with this script P&F chart created on time chart.
P&F chart provide several advantages, some of them are filtering insignificant price movements and noise, focusing on important price movements and making support/resistance levels much easier to identify.
Moving averages on Point & Figure charts are based on the average price of each column while bar chart moving averages are based closing price. Average Price means (ClosePrice + OpenPrice) / 2.
Because of there is double smoothing, you should use shorter lengths for moving averages. Double smoothing means: using average price smooths once, using length greater than 2 smooths price second time.
If you are new to Point & Figure Chart then you better get some information about it before using this tool. There are very good web sites and books. Please PM me if you need help about resources.
Options in the Script
Box size is one of the most important part of Point and Figure Charting. Chart price movement sensitivity is determined by the Point and Figure scale. Large box sizes see little movement across a specific price region, small box sizes see greater price movement on P&F chart. There are four different box scaling with this tool: Traditional, Percentage, Dynamic (ATR), or User-Defined
4 different methods for Box size can be used in this tool.
User Defined: The box size is set by user. A larger box size will result in more filtered price movements and fewer reversals. A smaller box size will result in less filtered price movements and more reversals.
ATR: Box size is dynamically calculated by using ATR, default period is 20.
Percentage: uses box sizes that are a fixed percentage of the stock's price. If percentage is 1 and stock’s price is $100 then box size will be $1
Traditional: uses a predefined table of price ranges to determine what the box size should be.
Price Range Box Size
Under 0.25 0.0625
0.25 to 1.00 0.125
1.00 to 5.00 0.25
5.00 to 20.00 0.50
20.00 to 100 1.0
100 to 200 2.0
200 to 500 4.0
500 to 1000 5.0
1000 to 25000 50.0
25000 and up 500.0
Default value is “ATR”, you may use one of these scaling method that suits your trading strategy.
If ATR or Percentage is chosen then there is rounding algorithm according to mintick value of the security. For example if mintick value is 0.001 and box size (ATR/Percentage) is 0.00124 then box size becomes 0.001.
And also while using dynamic box size (ATR or Percentage), box size changes only when closing price changed.
Reversal : It is the number of boxes required to change from a column of Xs to a column of Os or from a column of Os to a column of Xs. Default value is 3 (most used). For example if you choose reversal = 2 then you get the chart similar to Renko chart.
Source: Closing price or High-Low prices can be chosen as data source for P&F charting.
Options for P&F Bollinger Bands:
MA Type: MA type can be EMA or SMA
MA Source: Moving averages on P&F charts are based on the average price of each column. Bar chart moving averages are based on each close price. Average price means “(ClosePrice + OpenPrice) / 2”. You can choose Close Price or Average Price as source. Default is Average Price.
Fast MA Length : Length of Fast Moving average, shorter length than Slow MA
Slow MA Length : Length of Slow Moving average, greater length than Slow MA
There are alerts when Fast MA Crossed over/under Slow MA conditions. While adding alert “Once Per Bar Close” option should be chosen.
BTC Power Law HistogramBased on "Bitcoin’s natural long-term power-law corridor of growth" by Harold Christopher Burger
Donchian HistogramThis Histogram detect the changes in a doncohian channel
for best output , put the TF = or above to the candle size that you use
I did not put signals but is easy
up=crossover(x,0)
down=croosunder(x,0)
Aroon Histogram + CMO [ChuckBanger]This is a combination of Aroon and Chande Momentum Oscillator . I made a histogram of Aroon , aqua line is Chande Momentum and the orange line are a simple moving average of Chande Momentum as a signal line.
One strategy you can use this for is to buy or sell when the signal line crosses the CM line or you can buy and sell when CM line is highest or lowest
You should also study how the indicators work separately:
Aroon Oscillator
www.investopedia.com
Chande Momentum Oscillator
www.investopedia.com
Moving Average Convergence/Divergence Histogram/AreaMoving Average Convergence/Divergence Histogram/Area
MACD Histogram BacktestTesting the trades signaled by the daily MACD histogram to see how they would have performed, compared to regular MACD Crosses. I'm going to take the 'List of trades' and analyse it seperately as some of the profit percentages seem a little off in the tradingview calculation, though it could just be my bad math!
Hi CryptoLove :) Hope this helps your investigation RE:
www.youtube.com
MACD HistogramShort MACD histogram to deal with crypto trade.
Added ability to simulate a test price too.
