Point and Figure (PnF) MACDThis is live and non-repainting Point and Figure Chart MACD 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.
P&F MACD is calculated and shown by using its own P&F engine.
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.
P&F MACD Part
Fast Length: Fast Length for P&F MACD , default value is 12
Slow Length: Fast Length for P&F MACD , default value is 26
Signal Smoothing: Signal Length, default value is 9
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.
There are 2 Alerts:
If PNF MACD line crossover the signal line
If PNF MACD line crossunder the signal line
While adding alert “Once Per Bar Close” option should be chosen.
חפש סקריפטים עבור "美股标普500指数基金中国"
Point and Figure (PnF) CCIThis is live and non-repainting Point and Figure Chart Commodity Channel Index - CCI 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.
Commodity Channel Index – CCI was developed by Donalt Lambert. CCI can be used to identify overbought or oversold, a new trend or warn of extreme conditions. CCI measures the difference between a security's price change and its average price change. High positive readings indicate that prices are well above their average, which is a show of strength. Low negative readings indicate that prices are well below their average, which is a show of weakness.
The Formula for the Commodity Channel Index ( CCI ) Is:
CCI = (Typical Price – L-period SMA of TP) / (0.015 * Mean Deviation)
Mean Deviation = (SumOf 1->L ( |TP – MA| )) / L
L = Length
TP = Typical Price
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.
Upper Band : as default, Upper band is 100
Lower Band : as default, Lower band is -100
There are alerts when P&F CCI moves above Upper Band or moves below Lower Band.
Point and Figure (PnF) Bollinger BandsThis is live and non-repainting Point and Figure Chart Bollinger Bands 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.
P&F Bollinger Bands is calculated and shown by using its own P&F engine. Because of Point and Figure Chart Moving averages are already smoothed, better to use smaller moving average periods, 5 or 10 etc. This period can be chosen by prives movements and characteristics. You can see the consolidation areas and with P&F Breakout signals it’s possible to see the direction. Narrowing bands indicate a consolidation and narrowing does not provide a direction clue. You must look for the next P&F signal to establish direction. But beware of the ‘head fake’. This occurs when prices break a band, then suddenly reverse and move the other way (Trap).
An example for Head Fake:
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 P&F Bollimger Bands:
Length: Base Moving Average Length, default value is 5
StdDev: Standart Deviation, default value ise 2. (Standart deviation is calculated by the engine)
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.
Point and Figure (PnF) RSIThis is live and non-repainting Point and Figure Chart RSI 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.
P&F RSI is calculated and shown by using its own P&F engine.
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.
you can use PNF type RSI or RENKO type RSI.
What is the difference between them?
While calculating PNF type RSI, the script checks last X/O column's closing price but when using RENKO type RSI the scipt calculates RSI on every price changes according to number of boxes. and also with RENKO type RSI, calculation is made for each boxes on price changes.
Important note if you use this PNF script with reversal = 2 then you get RENKO chart. So, with this RENKO chart better to use RENKO type RSI ;)
Point and Figure (PnF) ChartThis is live and non-repainting Point and Figure Charting tool. The tool 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.
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.
Chart Style: There are 3 options for chart style: “Candle”, “Area” or “Don’t show”.
As Area:
As Candle:
X/O Column Style: it can show all columns from opening price or only last Xs/Os.
Color Theme: different themes exist => Green/Red, Yellow/Blue, White/Yellow, Orange/Blue, Lime/Red, Blue/Red
Show Breakouts is the option to show Breakouts
This tool detects & shows following Breakouts:
Triple Top/Bottom,
Triple Top Ascending,
Triple Bottom Descending,
Simple Buy/Sell (Double Top/Bottom),
Simple Buy With Rising Bottom,
Simple Sell With Declining Top
Catapult bullish/bearish
Show Horizontal Count Targets: Finds the congestion or consolidation pattern and if there is breakout then it calculates the Target by using Horizontal Count method (based on the width of congestion pattern). It shows how many column exist on congestion area. There is no guarantee that prices will reach the target.
Show Vertical Count Targets: When Triple Top/Bottom Breakouts occured the script calculates the target by using Vertical Count Method (based on the length of the column). There is no guarantee that prices will reach the target.
For both methods there is auto target cancellation if price goes below congestion bottom or above congestion top.
trend is calculated by EMA of closing price of the P&F
Whipsaw protection:
Last options are “Show info panel” and Labeling Offset. Script shows current box size, reversal, and recommanded minimum and maximum box size. And also it shows the price level to reverse the column (Xs <-> Os) and the price level to add at least 1 more box to column. This is the option to put these labels 10, 20, 30, 50 or 100 bars away from the last bar. Labeling content and color change according to X/O column.
do not hesitate to comment.
Candlesticks ANN for Stock Markets TF : 1WHello, this script consists of training candlesticks with Artificial Neural Networks (ANN).
In addition to the first series, candlesticks' bodies and wicks were also introduced as training inputs.
The inputs are individually trained to find the relationship between the subsequent historical value of all candlestick values 1.(High,Low,Close,Open)
The outputs are adapted to the current values with a simple forecast code.
Once the OHLC value is found, the exponential moving averages of 5 and 20 periods are used.
Reminder : OHLC = (Open + High + Close + Low ) / 4
First version :
Script is designed for S&P 500 Indices,Funds,ETFs, especially S&P 500 Stocks,and for all liquid Stocks all around the World.
NOTE: This script is only suitable for 1W time-frame for Stocks.
The average training error rates are less than 5 per thousand for each candlestick variable. (Average Error < 0.005 )
I've just finished it and haven't tested it in detail.
So let's use it carefully as a supporter.
Best regards !
TNZ - Index above MA Use this indicator to filter stock selection based on the relevant index value being above the selected simple moving average.
For example, only buying the S+P 500 stock if the S+P 500 index value is above the 10 period moving average.
The time frame used is that displayed
Macroeconomic Artificial Neural Networks
This script was created by training 20 selected macroeconomic data to construct artificial neural networks on the S&P 500 index.
No technical analysis data were used.
The average error rate is 0.01.
In this respect, there is a strong relationship between the index and macroeconomic data.
Although it affects the whole world,I personally recommend using it under the following conditions: S&P 500 and related ETFs in 1W time-frame (TF = 1W SPX500USD, SP1!, SPY, SPX etc. )
Macroeconomic Parameters
Effective Federal Funds Rate (FEDFUNDS)
Initial Claims (ICSA)
Civilian Unemployment Rate (UNRATE)
10 Year Treasury Constant Maturity Rate (DGS10)
Gross Domestic Product , 1 Decimal (GDP)
Trade Weighted US Dollar Index : Major Currencies (DTWEXM)
Consumer Price Index For All Urban Consumers (CPIAUCSL)
M1 Money Stock (M1)
M2 Money Stock (M2)
2 - Year Treasury Constant Maturity Rate (DGS2)
30 Year Treasury Constant Maturity Rate (DGS30)
Industrial Production Index (INDPRO)
5-Year Treasury Constant Maturity Rate (FRED : DGS5)
Light Weight Vehicle Sales: Autos and Light Trucks (ALTSALES)
Civilian Employment Population Ratio (EMRATIO)
Capacity Utilization (TOTAL INDUSTRY) (TCU)
Average (Mean) Duration Of Unemployment (UEMPMEAN)
Manufacturing Employment Index (MAN_EMPL)
Manufacturers' New Orders (NEWORDER)
ISM Manufacturing Index (MAN : PMI)
Artificial Neural Network (ANN) Training Details :
Learning cycles: 16231
AutoSave cycles: 100
Grid
Input columns: 19
Output columns: 1
Excluded columns: 0
Training example rows: 998
Validating example rows: 0
Querying example rows: 0
Excluded example rows: 0
Duplicated example rows: 0
Network
Input nodes connected: 19
Hidden layer 1 nodes: 2
Hidden layer 2 nodes: 0
Hidden layer 3 nodes: 0
Output nodes: 1
Controls
Learning rate: 0.1000
Momentum: 0.8000 (Optimized)
Target error: 0.0100
Training error: 0.010000
NOTE : Alerts added . The red histogram represents the bear market and the green histogram represents the bull market.
Bars subject to region changes are shown as background colors. (Teal = Bull , Maroon = Bear Market )
I hope it will be useful in your studies and analysis, regards.
Damped Sine Wave Weighted FilterIntroduction
Remember that we can make filters by using convolution, that is summing the product between the input and the filter coefficients, the set of filter coefficients is sometime denoted "kernel", those coefficients can be a same value (simple moving average), a linear function (linearly weighted moving average), a gaussian function (gaussian filter), a polynomial function (lsma of degree p with p = order of the polynomial), you can make many types of kernels, note however that it is easy to fall into the redundancy trap.
Today a low-lag filter who weight the price with a damped sine wave is proposed, the filter characteristics are discussed below.
A Damped Sine Wave
A damped sine wave is a like a sine wave with the difference that the sine wave peak amplitude decay over time.
A damped sine wave
Used Kernel
We use a damped sine wave of period length as kernel.
The coefficients underweight older values which allow the filter to reduce lag.
Step Response
Because the filter has overshoot in the step response we can conclude that there are frequencies amplified in the passband, we could have reached to this conclusion by simply seeing the negative values in the kernel or the "zero-lag" effect on the closing price.
Enough ! We Want To See The Filter !
I should indeed stop bothering you with transient responses but its always good to see how the filter act on simpler signals before seeing it on the closing price. The filter has low-lag and can be used as input for other indicators
Filter with length = 100 as input for the rsi.
The bands trailing stop utility using rolling squared mean average error with length 500 using the filter of length 500 as input.
Approximating A Least Squares Moving Average
A least squares moving average has a linear kernel with certain values under 0, a lsma of length k can be approximated using the proposed filter using period p where p = k + k/4 .
Proposed filter (red) with length = 250 and lsma (blue) with length = 200.
Conclusions
The use of damping in filter design can provide extremely useful filters, in fact the ideal kernel, the sinc function, is also a damped sine wave.
VIX reversion-Buschi
English:
A significant intraday reversion (commonly used: 3 points) on a high (over 20 points) S&P 500 Volatility Index (VIX) can be a sign of a market bottom, because there is the assumption that some of the "big guys" liquidated their options / insurances because the worst is over.
This indicator shows these reversions (3 points as default) when the VIX was over 20 points. The character "R" is then shown directly over the daily column, the VIX need not to be loaded explicitly.
Deutsch:
Eine deutliche Intraday-Umkehr (3 Punkte im Normalfall) bei einem hohen (über 20 Punkte) S&P 500 Volatility Index (VIX) kann ein Zeichen für eine Bodenbildung im Markt sein, weil möglicherweise einige "große Jungs" ihre Optionen / Versicherungen auflösen, weil das schlimmste vorbei ist.
Dieser Indikator zeigt diese Umkehr (Standardwert: 3 Punkte), wenn der VIX vorher über 20 Punkte lag. Der Buchstabe "R" wird dabei direkt über dem Tagesbalken angezeigt, wobei der VIX nicht explizit geladen werden muss.
Relative Price StrengthThe strength of a stock relative to the S&P 500 is key part of most traders decision making process. Hence the default reference security is SPY, the most commonly trades S&P 500 ETF.
Most profitable traders buy stocks that are showing persistence intermediate strength verses the S&P as this has been shown to work. Hence the default period is 63 days or 3 months.
TICK Extremes IndicatorSimple TICK indicator, plots candles and HL2 line
Conditional green/red coloring for highs above 500, 900 and lows above 0, and for lows below -500, -900, and highs above 0
Probably best used for 1 - 5 min timeframes
Always open to suggestions if criteria needs tweaking or if something else would make it more useful or user-friendly!
Market direction and pullback based on S&P 500.A simple indicator based on www.swing-trade-stocks.com The link is also the guide for how to use it.
0 - nothing. If the indicator is showing 0 for a prolonged amount of time, it is likely the market is in "momentum mode" (referred to in the link above).
1 - indicates an uptrend based on SMA and EMA and also a place where a reversal to the upside is likely to occur. You should look only for long trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
-1 - indicates a downtrend based on SMA and EMA and also a place where a reversal to the downside is likely to occur. You should look only for short trades in the stock market when you see a spike upwards and S&P 500 is showing an obvious uptrend.
Net XRP Margin PositionTotal XRP Longs minus XRP Shorts in order to give you the total outstanding XRP margin debt.
ie: If 500,000 XRP has been longed, and 400,000 XRP has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 XRP (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
Net DASH Margin PositionTotal DASH Longs minus DASH Shorts in order to give you the total outstanding DASH margin debt.
ie: If 500,000 DASH has been longed, and 400,000 DASH has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 DASH (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Net NEO Margin PositionTotal NEO Longs minus NEO Shorts in order to give you the total outstanding NEO margin debt.
ie: If 500,000 NEO has been longed, and 400,000 NEO has been shorted, then 500,000 has been bought, and 400,000 sold, leaving us with 100,000 NEO (net) remaining to be sold to give us an overall neutral margin position.
That isn't to say that the net margin position must move towards zero, but it is a sensible reference point, and historical net values may provide useful insights into the current circumstances.
(Anyone know what category this script should be in?)
Everyday 0002 _ MAC 1st Trading Hour WalkoverThis is the second strategy for my Everyday project.
Like I wrote the last time - my goal is to create a new strategy everyday
for the rest of 2016 and post it here on TradingView.
I'm a complete beginner so this is my way of learning about coding strategies.
I'll give myself between 15 minutes and 2 hours to complete each creation.
This is basically a repetition of the first strategy I wrote - a Moving Average Crossover,
but I added a tiny thing.
I read that "Statistics have proven that the daily high or low is established within the first hour of trading on more than 70% of the time."
(source: )
My first Moving Average Crossover strategy, tested on VOLVB daily, got stoped out by the volatility
and because of this missed one nice bull run and a very nice bear run.
So I added this single line: if time("60", "1000-1600") regarding when to take exits:
if time("60", "1000-1600")
strategy.exit("Close Long", "Long", profit=2000, loss=500)
strategy.exit("Close Short", "Short", profit=2000, loss=500)
Sweden is UTC+2 so I guess UTC 1000 equals 12.00 in Stockholm. Not sure if this is correct, actually.
Anyway, I hope this means the strategy will only take exits based on price action which occur in the afternoon, when there is a higher probability of a lower volatility.
When I ran the new modified strategy on the same VOLVB daily it didn't get stoped out so easily.
On the other hand I'll have to test this on various stocks .
Reading and learning about how to properly test strategies is on my todo list - all tips on youtube videos or blogs
to read on this topic is very welcome!
Like I said the last time, I'm posting these strategies hoping to learn from the community - so any feedback, advice, or corrections is very much welcome and appreciated!
/pbergden
Double Top/Bottom Screener - Today Only V4//@version=6
indicator("Double Top/Bottom Screener - Today Only", overlay=true, max_lines_count=500)
// Inputs
leftBars = input.int(5, "Left Bars")
rightBars = input.int(5, "Right Bars")
tolerance = input.float(0.02, "Max Difference (e.g., 0.02 for 2 cents)", step=0.01)
atrLength = input.int(14, "ATR Length for Normalized Distance", minval=1)
requiredPeaks = input.int(3, "Required Identical Peaks", minval=2, maxval=5)
// Declarations of persistent variables and arrays
var array resistanceLevels = array.new(0)
var array resistanceCounts = array.new(0)
var array supportLevels = array.new(0)
var array supportCounts = array.new(0)
var array resLines = array.new(0)
var array supLines = array.new(0)
var bool hasDoubleTop = false
var bool hasDoubleBottom = false
var float doubleTopLevel = na
var float doubleBottomLevel = na
var int todayStart = na
var float nearestDoubleLevel = na // Explicitly declared as na by default
// Step 1: Identify Swing Highs/Lows
swingHigh = ta.pivothigh(high, leftBars, rightBars)
swingLow = ta.pivotlow(low, leftBars, rightBars)
// Today's premarket start (04:00 AM ET)
todayStart := timestamp(syminfo.timezone, year, month, dayofmonth, 4, 0, 0)
// Clear arrays and delete lines on the first bar or new day
if barstate.isfirst or (dayofmonth != dayofmonth and time >= todayStart)
// Delete all existing lines only if arrays are not empty
if array.size(resLines) > 0
for i = array.size(resLines) - 1 to 0
line.delete(array.get(resLines, i))
if array.size(supLines) > 0
for i = array.size(supLines) - 1 to 0
line.delete(array.get(supLines, i))
// Clear arrays
array.clear(resistanceLevels)
array.clear(supportLevels)
array.clear(resistanceCounts)
array.clear(supportCounts)
array.clear(resLines)
array.clear(supLines)
// Reset flags and levels
hasDoubleTop := false
hasDoubleBottom := false
doubleTopLevel := na
doubleBottomLevel := na
nearestDoubleLevel := na // Ensure reset on new day
// Add new swings only if today and after premarket
if not na(swingHigh) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualHigh = false
int peakIndex = -1
float prevLevel = na
if array.size(resistanceLevels) > 0
for i = 0 to array.size(resistanceLevels) - 1
prevLevel := array.get(resistanceLevels, i)
if math.abs(swingHigh - prevLevel) <= tolerance
isEqualHigh := true
peakIndex := i
break
if isEqualHigh and peakIndex >= 0
array.set(resistanceCounts, peakIndex, array.get(resistanceCounts, peakIndex) + 1)
if array.get(resistanceCounts, peakIndex) == requiredPeaks
hasDoubleTop := true
doubleTopLevel := prevLevel
else
array.push(resistanceLevels, swingHigh)
array.push(resistanceCounts, 1)
line newResLine = line.new(bar_index - rightBars, swingHigh, bar_index, swingHigh, color=color.red, width=2, extend=extend.none)
array.push(resLines, newResLine)
if not na(swingLow) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualLow = false
int peakIndex = -1
float prevLevel = na
if array.size(supportLevels) > 0
for i = 0 to array.size(supportLevels) - 1
prevLevel := array.get(supportLevels, i)
if math.abs(swingLow - prevLevel) <= tolerance
isEqualLow := true
peakIndex := i
break
if isEqualLow and peakIndex >= 0
array.set(supportCounts, peakIndex, array.get(supportCounts, peakIndex) + 1)
if array.get(supportCounts, peakIndex) == requiredPeaks
hasDoubleBottom := true
doubleBottomLevel := prevLevel
else
array.push(supportLevels, swingLow)
array.push(supportCounts, 1)
line newSupLine = line.new(bar_index - rightBars, swingLow, bar_index, swingLow, color=color.green, width=2, extend=extend.none)
array.push(supLines, newSupLine)
// Monitor and remove broken levels/lines; reset pattern if the equal level breaks
if array.size(resistanceLevels) > 0
for i = array.size(resistanceLevels) - 1 to 0
float level = array.get(resistanceLevels, i)
if close > level
line.delete(array.get(resLines, i))
array.remove(resLines, i)
array.remove(resistanceLevels, i)
array.remove(resistanceCounts, i)
if level == doubleTopLevel
hasDoubleTop := false
doubleTopLevel := na
nearestDoubleLevel := na // Reset if level breaks
if array.size(supportLevels) > 0
for i = array.size(supportLevels) - 1 to 0
float level = array.get(supportLevels, i)
if close < level
line.delete(array.get(supLines, i))
array.remove(supLines, i)
array.remove(supportLevels, i)
array.remove(supportCounts, i)
if level == doubleBottomLevel
hasDoubleBottom := false
doubleBottomLevel := na
nearestDoubleLevel := na // Reset if level breaks
// Limit arrays (after removals)
if array.size(resistanceLevels) > 10
line oldLine = array.shift(resLines)
line.delete(oldLine)
array.shift(resistanceLevels)
array.shift(resistanceCounts)
if array.size(supportLevels) > 10
line oldLine = array.shift(supLines)
line.delete(oldLine)
array.shift(supportLevels)
array.shift(supportCounts)
// Pattern Signal: 1 only if the exact required number of peaks is met
patternSignal = (hasDoubleTop or hasDoubleBottom) ? 1 : 0
// New: Nearest Double Level Price - Only update if pattern is active today and on current day
if time >= todayStart and dayofmonth == dayofmonth // Restrict to today
if patternSignal == 1 // Only set if pattern is active
if hasDoubleTop and not na(doubleTopLevel)
nearestDoubleLevel := doubleTopLevel
if hasDoubleBottom and not na(doubleBottomLevel)
nearestDoubleLevel := na(nearestDoubleLevel) ? doubleBottomLevel : (math.abs(close - doubleBottomLevel) < math.abs(close - nearestDoubleLevel) ? doubleBottomLevel : nearestDoubleLevel)
else
nearestDoubleLevel := na // Reset to na if no pattern today
else
nearestDoubleLevel := na // Reset for all historical bars
// New: Distance to Nearest Level (using ATR for normalization)
var float atr = ta.atr(atrLength)
var float distanceNormalizedATR = na
if not na(nearestDoubleLevel) and not na(atr) and atr > 0
distanceNormalizedATR := math.abs(close - nearestDoubleLevel) / atr
// Outputs
plot(patternSignal, title="Pattern Signal", color=patternSignal == 1 ? color.purple : na, style=plot.style_circles)
plot(nearestDoubleLevel, title="Nearest Double Level Price", color=color.orange)
plot(distanceNormalizedATR, title="Normalized Distance (ATR)", color=color.green)
bgcolor(patternSignal == 1 ? color.new(color.purple, 80) : na)
if patternSignal == 1 and barstate.isconfirmed
alert("Double Pattern detected on " + syminfo.ticker + " at " + str.tostring(close), alert.freq_once_per_bar_close)
if barstate.islast
var table infoTable = table.new(position.top_right, 1, 3, bgcolor=color.new(color.black, 50))
table.cell(infoTable, 0, 0, "Pattern: " + str.tostring(patternSignal), bgcolor=patternSignal == 1 ? color.purple : color.gray)
table.cell(infoTable, 0, 1, "Level: " + str.tostring(nearestDoubleLevel, "#.##"), bgcolor=color.orange)
table.cell(infoTable, 0, 2, "ATR Dist: " + str.tostring(distanceNormalizedATR, "#.##"), bgcolor=color.green)
AMHA + 4 EMAs + EMA50/200 Counter + Avg10CrossesDescription:
This script combines two types of Heikin-Ashi visualization with multiple Exponential Moving Averages (EMAs) and a counting function for EMA50/200 crossovers. The goal is to make trends more visible, measure recurring market cycles, and provide statistical context without generating trading signals.
Logic in Detail:
Adaptive Median Heikin-Ashi (AMHA):
Instead of the classic Heikin-Ashi calculation, this method uses the median of Open, High, Low, and Close. The result smooths out price movements, emphasizes trend direction, and reduces market noise.
Standard Heikin-Ashi Overlay:
Classic HA candles are also drawn in the background for comparison and transparency. Both HA types can be shifted below the chart’s price action using a customizable Offset (Ticks) parameter.
EMA Structure:
Five exponential moving averages (21, 50, 100, 200, 500) are included to highlight different trend horizons. EMA50 and EMA200 are emphasized, as their crossovers are widely monitored as potential trend signals. EMA21 and EMA100 serve as additional structure layers, while EMA500 represents the long-term trend.
EMA50/200 Counter:
The script counts how many bars have passed since the last EMA50/200 crossover. This makes it easy to see the age of the current trend phase. A colored label above the chart displays the current counter.
Average of the Last 10 Crossovers (Avg10Crosses):
The script stores the last 10 completed count phases and calculates their average length. This provides historical context and allows traders to compare the current cycle against typical past behavior.
Benefits for Analysis:
Clearer trend visualization through adaptive Heikin-Ashi calculation.
Multi-EMA setup for quick structural assessment.
Objective measurement of trend phase duration.
Statistical insight from the average cycle length of past EMA50/200 crosses.
Flexible visualization through adjustable offset positioning below the price chart.
Usage:
Add the indicator to your chart.
For a clean look, you may switch your chart type to “Line” or hide standard candlesticks.
Interpret visual signals:
White candles = bullish phases
Orange candles = bearish phases
EMAs = structural trend filters (e.g., EMA200 as a long-term boundary)
The counter label shows the current number of bars since the last cross, while Avg10 represents the historical mean.
Special Feature:
This script is not a trading system. It does not provide buy/sell recommendations. Instead, it serves as a visual and statistical tool for market structure analysis. The unique combination of Adaptive Median Heikin-Ashi, multi-EMA framework, and EMA50/200 crossover statistics makes it especially useful for trend-followers and swing traders who want to add cycle-length analysis to their toolkit.
Double Top/Bottom Screener - Today Only v3 //@version=6
indicator("Double Top/Bottom Screener - Today Only", overlay=true, max_lines_count=500)
// Inputs
leftBars = input.int(5, "Left Bars")
rightBars = input.int(5, "Right Bars")
tolerance = input.float(0.02, "Max Difference (e.g., 0.02 for 2 cents)", step=0.01)
atrLength = input.int(14, "ATR Length for Normalized Distance", minval=1)
requiredPeaks = input.int(3, "Required Identical Peaks", minval=2, maxval=5)
// Declarations of persistent variables and arrays
var array resistanceLevels = array.new(0)
var array resistanceCounts = array.new(0)
var array supportLevels = array.new(0)
var array supportCounts = array.new(0)
var array resLines = array.new(0)
var array supLines = array.new(0)
var bool hasDoubleTop = false
var bool hasDoubleBottom = false
var float doubleTopLevel = na
var float doubleBottomLevel = na
var int todayStart = na
var float nearestDoubleLevel = na // Explicitly declared as na by default
// Step 1: Identify Swing Highs/Lows
swingHigh = ta.pivothigh(high, leftBars, rightBars)
swingLow = ta.pivotlow(low, leftBars, rightBars)
// Today's premarket start (04:00 AM ET)
todayStart := timestamp(syminfo.timezone, year, month, dayofmonth, 4, 0, 0)
// Clear arrays and delete lines on the first bar or new day
if barstate.isfirst or (dayofmonth != dayofmonth and time >= todayStart)
// Delete all existing lines only if arrays are not empty
if array.size(resLines) > 0
for i = array.size(resLines) - 1 to 0
line.delete(array.get(resLines, i))
if array.size(supLines) > 0
for i = array.size(supLines) - 1 to 0
line.delete(array.get(supLines, i))
// Clear arrays
array.clear(resistanceLevels)
array.clear(supportLevels)
array.clear(resistanceCounts)
array.clear(supportCounts)
array.clear(resLines)
array.clear(supLines)
// Reset flags and levels
hasDoubleTop := false
hasDoubleBottom := false
doubleTopLevel := na
doubleBottomLevel := na
nearestDoubleLevel := na // Ensure reset on new day
// Add new swings only if today and after premarket
if not na(swingHigh) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualHigh = false
int peakIndex = -1
float prevLevel = na
if array.size(resistanceLevels) > 0
for i = 0 to array.size(resistanceLevels) - 1
prevLevel := array.get(resistanceLevels, i)
if math.abs(swingHigh - prevLevel) <= tolerance
isEqualHigh := true
peakIndex := i
break
if isEqualHigh and peakIndex >= 0
array.set(resistanceCounts, peakIndex, array.get(resistanceCounts, peakIndex) + 1)
if array.get(resistanceCounts, peakIndex) == requiredPeaks
hasDoubleTop := true
doubleTopLevel := prevLevel
else
array.push(resistanceLevels, swingHigh)
array.push(resistanceCounts, 1)
line newResLine = line.new(bar_index - rightBars, swingHigh, bar_index, swingHigh, color=color.red, width=2, extend=extend.none)
array.push(resLines, newResLine)
if not na(swingLow) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualLow = false
int peakIndex = -1
float prevLevel = na
if array.size(supportLevels) > 0
for i = 0 to array.size(supportLevels) - 1
prevLevel := array.get(supportLevels, i)
if math.abs(swingLow - prevLevel) <= tolerance
isEqualLow := true
peakIndex := i
break
if isEqualLow and peakIndex >= 0
array.set(supportCounts, peakIndex, array.get(supportCounts, peakIndex) + 1)
if array.get(supportCounts, peakIndex) == requiredPeaks
hasDoubleBottom := true
doubleBottomLevel := prevLevel
else
array.push(supportLevels, swingLow)
array.push(supportCounts, 1)
line newSupLine = line.new(bar_index - rightBars, swingLow, bar_index, swingLow, color=color.green, width=2, extend=extend.none)
array.push(supLines, newSupLine)
// Monitor and remove broken levels/lines; reset pattern if the equal level breaks
if array.size(resistanceLevels) > 0
for i = array.size(resistanceLevels) - 1 to 0
float level = array.get(resistanceLevels, i)
if close > level
line.delete(array.get(resLines, i))
array.remove(resLines, i)
array.remove(resistanceLevels, i)
array.remove(resistanceCounts, i)
if level == doubleTopLevel
hasDoubleTop := false
doubleTopLevel := na
nearestDoubleLevel := na // Reset if level breaks
if array.size(supportLevels) > 0
for i = array.size(supportLevels) - 1 to 0
float level = array.get(supportLevels, i)
if close < level
line.delete(array.get(supLines, i))
array.remove(supLines, i)
array.remove(supportLevels, i)
array.remove(supportCounts, i)
if level == doubleBottomLevel
hasDoubleBottom := false
doubleBottomLevel := na
nearestDoubleLevel := na // Reset if level breaks
// Limit arrays (after removals)
if array.size(resistanceLevels) > 10
line oldLine = array.shift(resLines)
line.delete(oldLine)
array.shift(resistanceLevels)
array.shift(resistanceCounts)
if array.size(supportLevels) > 10
line oldLine = array.shift(supLines)
line.delete(oldLine)
array.shift(supportLevels)
array.shift(supportCounts)
// Pattern Signal: 1 only if the exact required number of peaks is met
patternSignal = (hasDoubleTop or hasDoubleBottom) ? 1 : 0
// New: Nearest Double Level Price - Only update if pattern is active today
if time >= todayStart and dayofmonth == dayofmonth // Restrict to today
if (hasDoubleTop and not na(doubleTopLevel)) or (hasDoubleBottom and not na(doubleBottomLevel))
if hasDoubleTop and not na(doubleTopLevel)
nearestDoubleLevel := doubleTopLevel
if hasDoubleBottom and not na(doubleBottomLevel)
nearestDoubleLevel := na(nearestDoubleLevel) ? doubleBottomLevel : (math.abs(close - doubleBottomLevel) < math.abs(close - nearestDoubleLevel) ? doubleBottomLevel : nearestDoubleLevel)
else
nearestDoubleLevel := na // Reset to na if no pattern today
else
nearestDoubleLevel := na // Reset for historical bars
// New: Distance to Nearest Level (using ATR for normalization)
var float atr = ta.atr(atrLength)
var float distanceNormalizedATR = na
if not na(nearestDoubleLevel) and not na(atr) and atr > 0
distanceNormalizedATR := math.abs(close - nearestDoubleLevel) / atr
// Outputs
plot(patternSignal, title="Pattern Signal", color=patternSignal == 1 ? color.purple : na, style=plot.style_circles)
plot(nearestDoubleLevel, title="Nearest Double Level Price", color=color.orange)
plot(distanceNormalizedATR, title="Normalized Distance (ATR)", color=color.green)
bgcolor(patternSignal == 1 ? color.new(color.purple, 80) : na)
if patternSignal == 1 and barstate.isconfirmed
alert("Double Pattern detected on " + syminfo.ticker + " at " + str.tostring(close), alert.freq_once_per_bar_close)
if barstate.islast
var table infoTable = table.new(position.top_right, 1, 3, bgcolor=color.new(color.black, 50))
table.cell(infoTable, 0, 0, "Pattern: " + str.tostring(patternSignal), bgcolor=patternSignal == 1 ? color.purple : color.gray)
table.cell(infoTable, 0, 1, "Level: " + str.tostring(nearestDoubleLevel, "#.##"), bgcolor=color.orange)
table.cell(infoTable, 0, 2, "ATR Dist: " + str.tostring(distanceNormalizedATR, "#.##"), bgcolor=color.green)
BOCS AdaptiveBOCS Adaptive Strategy - Automated Volatility Breakout System
WHAT THIS STRATEGY DOES:
This is an automated trading strategy that detects consolidation patterns through volatility analysis and executes trades when price breaks out of these channels. Take-profit and stop-loss levels are calculated dynamically using Average True Range (ATR) to adapt to current market volatility. The strategy closes positions partially at the first profit target and exits the remainder at the second target or stop loss.
TECHNICAL METHODOLOGY:
Price Normalization Process:
The strategy begins by normalizing price to create a consistent measurement scale. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). The current close price is then normalized using the formula: (close - lowest_low) / (highest_high - lowest_low). This produces values between 0 and 1, allowing volatility analysis to work consistently across different instruments and price levels.
Volatility Detection:
A 14-period standard deviation is applied to the normalized price series. Standard deviation measures how much prices deviate from their average - higher values indicate volatility expansion, lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() functions to track when volatility reaches peaks and troughs over the detection length period (default 14 bars).
Channel Formation Logic:
When volatility crosses from a high level to a low level, this signals the beginning of a consolidation phase. The strategy records this moment using ta.crossover(upper, lower) and begins tracking the highest and lowest prices during the consolidation. These become the channel boundaries. The duration between the crossover and current bar must exceed 10 bars minimum to avoid false channels from brief volatility spikes. Channels are drawn using box objects with the recorded high/low boundaries.
Breakout Signal Generation:
Two detection modes are available:
Strong Closes Mode (default): Breakout occurs when the candle body midpoint math.avg(close, open) exceeds the channel boundary. This filters out wick-only breaks.
Any Touch Mode: Breakout occurs when the close price exceeds the boundary.
When price closes above the upper channel boundary, a bullish breakout signal generates. When price closes below the lower boundary, a bearish breakout signal generates. The channel is then removed from the chart.
ATR-Based Risk Management:
The strategy uses request.security() to fetch ATR values from a specified timeframe, which can differ from the chart timeframe. For example, on a 5-minute chart, you can use 1-minute ATR for more responsive calculations. The ATR is calculated using ta.atr(length) with a user-defined period (default 14).
Exit levels are calculated at the moment of breakout:
Long Entry Price = Upper channel boundary
Long TP1 = Entry + (ATR × TP1 Multiplier)
Long TP2 = Entry + (ATR × TP2 Multiplier)
Long SL = Entry - (ATR × SL Multiplier)
For short trades, the calculation inverts:
Short Entry Price = Lower channel boundary
Short TP1 = Entry - (ATR × TP1 Multiplier)
Short TP2 = Entry - (ATR × TP2 Multiplier)
Short SL = Entry + (ATR × SL Multiplier)
Trade Execution Logic:
When a breakout occurs, the strategy checks if trading hours filter is satisfied (if enabled) and if position size equals zero (no existing position). If volume confirmation is enabled, it also verifies that current volume exceeds 1.2 times the 20-period simple moving average.
If all conditions are met:
strategy.entry() opens a position using the user-defined number of contracts
strategy.exit() immediately places a stop loss order
The code monitors price against TP1 and TP2 levels on each bar
When price reaches TP1, strategy.close() closes the specified number of contracts (e.g., if you enter with 3 contracts and set TP1 close to 1, it closes 1 contract). When price reaches TP2, it closes all remaining contracts. If stop loss is hit first, the entire position exits via the strategy.exit() order.
Volume Analysis System:
The strategy uses ta.requestUpAndDownVolume(timeframe) to fetch up volume, down volume, and volume delta from a specified timeframe. Three display modes are available:
Volume Mode: Shows total volume as bars scaled relative to the 20-period average
Comparison Mode: Shows up volume and down volume as separate bars above/below the channel midline
Delta Mode: Shows net volume delta (up volume - down volume) as bars, positive values above midline, negative below
The volume confirmation logic compares breakout bar volume to the 20-period SMA. If volume ÷ average > 1.2, the breakout is classified as "confirmed." When volume confirmation is enabled in settings, only confirmed breakouts generate trades.
INPUT PARAMETERS:
Strategy Settings:
Number of Contracts: Fixed quantity to trade per signal (1-1000)
Require Volume Confirmation: Toggle to only trade signals with volume >120% of average
TP1 Close Contracts: Exact number of contracts to close at first target (1-1000)
Use Trading Hours Filter: Toggle to restrict trading to specified session
Trading Hours: Session input in HHMM-HHMM format (e.g., "0930-1600")
Main Settings:
Normalization Length: Lookback bars for high/low calculation (1-500, default 100)
Box Detection Length: Period for volatility peak/trough detection (1-100, default 14)
Strong Closes Only: Toggle between body midpoint vs close price for breakout detection
Nested Channels: Allow multiple overlapping channels vs single channel at a time
ATR TP/SL Settings:
ATR Timeframe: Source timeframe for ATR calculation (1, 5, 15, 60, etc.)
ATR Length: Smoothing period for ATR (1-100, default 14)
Take Profit 1 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 2.0)
Take Profit 2 Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 3.0)
Stop Loss Multiplier: Distance from entry as multiple of ATR (0.1-10.0, default 1.0)
Enable Take Profit 2: Toggle second profit target on/off
VISUAL INDICATORS:
Channel boxes with semi-transparent fill showing consolidation zones
Green/red colored zones at channel boundaries indicating breakout areas
Volume bars displayed within channels using selected mode
TP/SL lines with labels showing both price level and distance in points
Entry signals marked with up/down triangles at breakout price
Strategy status table showing position, contracts, P&L, ATR values, and volume confirmation status
HOW TO USE:
For 2-Minute Scalping:
Set ATR Timeframe to "1" (1-minute), ATR Length to 12, TP1 Multiplier to 2.0, TP2 Multiplier to 3.0, SL Multiplier to 1.5. Enable volume confirmation and strong closes only. Use trading hours filter to avoid low-volume periods.
For 5-15 Minute Day Trading:
Set ATR Timeframe to match chart or use 5-minute, ATR Length to 14, TP1 Multiplier to 2.0, TP2 Multiplier to 3.5, SL Multiplier to 1.2. Volume confirmation recommended but optional.
For Hourly+ Swing Trading:
Set ATR Timeframe to 15-30 minute, ATR Length to 14-21, TP1 Multiplier to 2.5, TP2 Multiplier to 4.0, SL Multiplier to 1.5. Volume confirmation optional, nested channels can be enabled for multiple setups.
BACKTEST CONSIDERATIONS:
Strategy performs best during trending or volatility expansion phases
Consolidation-heavy or choppy markets produce more false signals
Shorter timeframes require wider stop loss multipliers due to noise
Commission and slippage significantly impact performance on sub-5-minute charts
Volume confirmation generally improves win rate but reduces trade frequency
ATR multipliers should be optimized for specific instrument characteristics
COMPATIBLE MARKETS:
Works on any instrument with price and volume data including forex pairs, stock indices, individual stocks, cryptocurrency, commodities, and futures contracts. Requires TradingView data feed that includes volume for volume confirmation features to function.
KNOWN LIMITATIONS:
Stop losses execute via strategy.exit() and may not fill at exact levels during gaps or extreme volatility
request.security() on lower timeframes requires higher-tier TradingView subscription
False breakouts inherent to breakout strategies cannot be completely eliminated
Performance varies significantly based on market regime (trending vs ranging)
Partial closing logic requires sufficient position size relative to TP1 close contracts setting
RISK DISCLOSURE:
Trading involves substantial risk of loss. Past performance of this or any strategy does not guarantee future results. This strategy is provided for educational purposes and automated backtesting. Thoroughly test on historical data and paper trade before risking real capital. Market conditions change and strategies that worked historically may fail in the future. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions.
ACKNOWLEDGMENT & CREDITS:
This strategy is built upon the channel detection methodology created by AlgoAlpha in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns and sharing this innovative technique with the TradingView community. The enhancements added to the original concept include automated trade execution, multi-timeframe ATR-based risk management, partial position closing by contract count, volume confirmation filtering, and real-time position monitoring.
Double Top/Bottom Screener - Today Only v2 //@version=6
indicator("Double Top/Bottom Screener - Today Only", overlay=true, max_lines_count=500)
// Inputs
leftBars = input.int(5, "Left Bars")
rightBars = input.int(5, "Right Bars")
tolerance = input.float(0.02, "Max Difference (e.g., 0.02 for 2 cents)", step=0.01)
atrLength = input.int(14, "ATR Length for Normalized Distance", minval=1)
requiredPeaks = input.int(3, "Required Identical Peaks", minval=2, maxval=5)
// Declarations of persistent variables and arrays
var array resistanceLevels = array.new(0)
var array resistanceCounts = array.new(0)
var array supportLevels = array.new(0)
var array supportCounts = array.new(0)
var array resLines = array.new(0)
var array supLines = array.new(0)
var bool hasDoubleTop = false
var bool hasDoubleBottom = false
var float doubleTopLevel = na
var float doubleBottomLevel = na
var int todayStart = na
// Step 1: Identify Swing Highs/Lows
swingHigh = ta.pivothigh(high, leftBars, rightBars)
swingLow = ta.pivotlow(low, leftBars, rightBars)
// Today's premarket start (04:00 AM ET)
todayStart := timestamp(syminfo.timezone, year, month, dayofmonth, 4, 0, 0)
// Clear arrays and delete lines on the first bar or new day
if barstate.isfirst or (dayofmonth != dayofmonth and time >= todayStart)
// Delete all existing lines only if arrays are not empty
if array.size(resLines) > 0
for i = array.size(resLines) - 1 to 0
line.delete(array.get(resLines, i))
if array.size(supLines) > 0
for i = array.size(supLines) - 1 to 0
line.delete(array.get(supLines, i))
// Clear arrays
array.clear(resistanceLevels)
array.clear(supportLevels)
array.clear(resistanceCounts)
array.clear(supportCounts)
array.clear(resLines)
array.clear(supLines)
// Reset flags
hasDoubleTop := false
hasDoubleBottom := false
doubleTopLevel := na
doubleBottomLevel := na
// Add new swings only if today and after premarket
if not na(swingHigh) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualHigh = false
int peakIndex = -1
float prevLevel = na
if array.size(resistanceLevels) > 0
for i = 0 to array.size(resistanceLevels) - 1
prevLevel := array.get(resistanceLevels, i)
if math.abs(swingHigh - prevLevel) <= tolerance
isEqualHigh := true
peakIndex := i
break
if isEqualHigh and peakIndex >= 0
array.set(resistanceCounts, peakIndex, array.get(resistanceCounts, peakIndex) + 1)
if array.get(resistanceCounts, peakIndex) == requiredPeaks
hasDoubleTop := true
doubleTopLevel := prevLevel
else
array.push(resistanceLevels, swingHigh)
array.push(resistanceCounts, 1)
line newResLine = line.new(bar_index - rightBars, swingHigh, bar_index, swingHigh, color=color.red, width=2, extend=extend.none)
array.push(resLines, newResLine)
if not na(swingLow) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualLow = false
int peakIndex = -1
float prevLevel = na
if array.size(supportLevels) > 0
for i = 0 to array.size(supportLevels) - 1
prevLevel := array.get(supportLevels, i)
if math.abs(swingLow - prevLevel) <= tolerance
isEqualLow := true
peakIndex := i
break
if isEqualLow and peakIndex >= 0
array.set(supportCounts, peakIndex, array.get(supportCounts, peakIndex) + 1)
if array.get(supportCounts, peakIndex) == requiredPeaks
hasDoubleBottom := true
doubleBottomLevel := prevLevel
else
array.push(supportLevels, swingLow)
array.push(supportCounts, 1)
line newSupLine = line.new(bar_index - rightBars, swingLow, bar_index, swingLow, color=color.green, width=2, extend=extend.none)
array.push(supLines, newSupLine)
// Monitor and remove broken levels/lines; reset pattern if the equal level breaks
if array.size(resistanceLevels) > 0
for i = array.size(resistanceLevels) - 1 to 0
float level = array.get(resistanceLevels, i)
if close > level
line.delete(array.get(resLines, i))
array.remove(resLines, i)
array.remove(resistanceLevels, i)
array.remove(resistanceCounts, i)
if level == doubleTopLevel
hasDoubleTop := false
doubleTopLevel := na
if array.size(supportLevels) > 0
for i = array.size(supportLevels) - 1 to 0
float level = array.get(supportLevels, i)
if close < level
line.delete(array.get(supLines, i))
array.remove(supLines, i)
array.remove(supportLevels, i)
array.remove(supportCounts, i)
if level == doubleBottomLevel
hasDoubleBottom := false
doubleBottomLevel := na
// Limit arrays (after removals)
if array.size(resistanceLevels) > 10
line oldLine = array.shift(resLines)
line.delete(oldLine)
array.shift(resistanceLevels)
array.shift(resistanceCounts)
if array.size(supportLevels) > 10
line oldLine = array.shift(supLines)
line.delete(oldLine)
array.shift(supportLevels)
array.shift(supportCounts)
// Pattern Signal: 1 only if the exact required number of peaks is met
patternSignal = (hasDoubleTop or hasDoubleBottom) ? 1 : 0
// New: Nearest Double Level Price
var float nearestDoubleLevel = na
if hasDoubleTop and not na(doubleTopLevel)
nearestDoubleLevel := doubleTopLevel
if hasDoubleBottom and not na(doubleBottomLevel)
nearestDoubleLevel := na(nearestDoubleLevel) ? doubleBottomLevel : (math.abs(close - doubleBottomLevel) < math.abs(close - nearestDoubleLevel) ? doubleBottomLevel : nearestDoubleLevel)
// New: Distance to Nearest Level (using ATR for normalization)
var float atr = ta.atr(atrLength)
var float distanceNormalizedATR = na
if not na(nearestDoubleLevel) and not na(atr) and atr > 0
distanceNormalizedATR := math.abs(close - nearestDoubleLevel) / atr
// Optional Bounce Signal (for reference)
bounceSignal = 0
if array.size(resistanceLevels) > 0
for i = 0 to array.size(resistanceLevels) - 1
float level = array.get(resistanceLevels, i)
if low <= level and high >= level and close < level
bounceSignal := 1
if array.size(supportLevels) > 0
for i = 0 to array.size(supportLevels) - 1
float level = array.get(supportLevels, i)
if high >= level and low <= level and close > level
bounceSignal := 1
// Outputs
plot(patternSignal, title="Pattern Signal", color=patternSignal == 1 ? color.purple : na, style=plot.style_circles)
plot(bounceSignal, title="Bounce Signal", color=bounceSignal == 1 ? color.yellow : na, style=plot.style_circles)
plot(nearestDoubleLevel, title="Nearest Double Level Price", color=color.orange)
plot(distanceNormalizedATR, title="Normalized Distance (ATR)", color=color.green)
bgcolor(patternSignal == 1 ? color.new(color.purple, 80) : na)
if patternSignal == 1 and barstate.isconfirmed
alert("Double Pattern detected on " + syminfo.ticker + " at " + str.tostring(close), alert.freq_once_per_bar_close)
if barstate.islast
var table infoTable = table.new(position.top_right, 1, 4, bgcolor=color.new(color.black, 50))
table.cell(infoTable, 0, 0, "Pattern: " + str.tostring(patternSignal), bgcolor=patternSignal == 1 ? color.purple : color.gray)
table.cell(infoTable, 0, 1, "Bounce: " + str.tostring(bounceSignal), bgcolor=bounceSignal == 1 ? color.yellow : color.gray)
table.cell(infoTable, 0, 2, "Level: " + str.tostring(nearestDoubleLevel, "#.##"), bgcolor=color.orange)
table.cell(infoTable, 0, 3, "ATR Dist: " + str.tostring(distanceNormalizedATR, "#.##"), bgcolor=color.green)
Double Top/Bottom Screener - Today Only//@version=6
indicator("Double Top/Bottom Screener - Today Only", overlay=true, max_lines_count=500)
// Inputs
leftBars = input.int(5, "Left Bars")
rightBars = input.int(5, "Right Bars")
tolerance = input.float(0.02, "Max Difference (e.g., 0.02 for 2 cents)", step=0.01)
atrLength = input.int(14, "ATR Length for Normalized Distance", minval=1)
requiredPeaks = input.int(3, "Required Identical Peaks", minval=2, maxval=5)
// Declarations of persistent variables and arrays
var array resistanceLevels = array.new(0)
var array resistanceCounts = array.new(0)
var array supportLevels = array.new(0)
var array supportCounts = array.new(0)
var array resLines = array.new(0)
var array supLines = array.new(0)
var bool hasDoubleTop = false
var bool hasDoubleBottom = false
var float doubleTopLevel = na
var float doubleBottomLevel = na
var int todayStart = na
// Step 1: Identify Swing Highs/Lows
swingHigh = ta.pivothigh(high, leftBars, rightBars)
swingLow = ta.pivotlow(low, leftBars, rightBars)
// Today's premarket start (04:00 AM ET)
todayStart := timestamp(syminfo.timezone, year, month, dayofmonth, 4, 0, 0)
// Clear arrays and delete lines on the first bar or new day
if barstate.isfirst or (dayofmonth != dayofmonth and time >= todayStart)
// Delete all existing lines
for i = array.size(resLines) - 1 to 0
line.delete(array.get(resLines, i))
for i = array.size(supLines) - 1 to 0
line.delete(array.get(supLines, i))
// Clear arrays
array.clear(resistanceLevels)
array.clear(supportLevels)
array.clear(resistanceCounts)
array.clear(supportCounts)
array.clear(resLines)
array.clear(supLines)
// Reset flags
hasDoubleTop := false
hasDoubleBottom := false
doubleTopLevel := na
doubleBottomLevel := na
// Add new swings only if today and after premarket
if not na(swingHigh) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualHigh = false
int peakIndex = -1
float prevLevel = na
if array.size(resistanceLevels) > 0
for i = 0 to array.size(resistanceLevels) - 1
prevLevel := array.get(resistanceLevels, i)
if math.abs(swingHigh - prevLevel) <= tolerance
isEqualHigh := true
peakIndex := i
break
if isEqualHigh and peakIndex >= 0
array.set(resistanceCounts, peakIndex, array.get(resistanceCounts, peakIndex) + 1)
if array.get(resistanceCounts, peakIndex) == requiredPeaks
hasDoubleTop := true
doubleTopLevel := prevLevel
else
array.push(resistanceLevels, swingHigh)
array.push(resistanceCounts, 1)
line newResLine = line.new(bar_index - rightBars, swingHigh, bar_index, swingHigh, color=color.red, width=2, extend=extend.none)
array.push(resLines, newResLine)
if not na(swingLow) and time >= todayStart and dayofmonth == dayofmonth
bool isEqualLow = false
int peakIndex = -1
float prevLevel = na
if array.size(supportLevels) > 0
for i = 0 to array.size(supportLevels) - 1
prevLevel := array.get(supportLevels, i)
if math.abs(swingLow - prevLevel) <= tolerance
isEqualLow := true
peakIndex := i
break
if isEqualLow and peakIndex >= 0
array.set(supportCounts, peakIndex, array.get(supportCounts, peakIndex) + 1)
if array.get(supportCounts, peakIndex) == requiredPeaks
hasDoubleBottom := true
doubleBottomLevel := prevLevel
else
array.push(supportLevels, swingLow)
array.push(supportCounts, 1)
line newSupLine = line.new(bar_index - rightBars, swingLow, bar_index, swingLow, color=color.green, width=2, extend=extend.none)
array.push(supLines, newSupLine)
// Monitor and remove broken levels/lines; reset pattern if the equal level breaks
if array.size(resistanceLevels) > 0
for i = array.size(resistanceLevels) - 1 to 0
float level = array.get(resistanceLevels, i)
if close > level
line.delete(array.get(resLines, i))
array.remove(resLines, i)
array.remove(resistanceLevels, i)
array.remove(resistanceCounts, i)
if level == doubleTopLevel
hasDoubleTop := false
doubleTopLevel := na
if array.size(supportLevels) > 0
for i = array.size(supportLevels) - 1 to 0
float level = array.get(supportLevels, i)
if close < level
line.delete(array.get(supLines, i))
array.remove(supLines, i)
array.remove(supportLevels, i)
array.remove(supportCounts, i)
if level == doubleBottomLevel
hasDoubleBottom := false
doubleBottomLevel := na
// Limit arrays (after removals)
if array.size(resistanceLevels) > 10
line oldLine = array.shift(resLines)
line.delete(oldLine)
array.shift(resistanceLevels)
array.shift(resistanceCounts)
if array.size(supportLevels) > 10
line oldLine = array.shift(supLines)
line.delete(oldLine)
array.shift(supportLevels)
array.shift(supportCounts)
// Pattern Signal: 1 only if the exact required number of peaks is met
patternSignal = (hasDoubleTop or hasDoubleBottom) ? 1 : 0
// New: Nearest Double Level Price
var float nearestDoubleLevel = na
if hasDoubleTop and not na(doubleTopLevel)
nearestDoubleLevel := doubleTopLevel
if hasDoubleBottom and not na(doubleBottomLevel)
nearestDoubleLevel := na(nearestDoubleLevel) ? doubleBottomLevel : (math.abs(close - doubleBottomLevel) < math.abs(close - nearestDoubleLevel) ? doubleBottomLevel : nearestDoubleLevel)
// New: Distance to Nearest Level (using ATR for normalization)
var float atr = ta.atr(atrLength)
var float distanceNormalizedATR = na
if not na(nearestDoubleLevel) and not na(atr) and atr > 0
distanceNormalizedATR := math.abs(close - nearestDoubleLevel) / atr
// Optional Bounce Signal (for reference)
bounceSignal = 0
if array.size(resistanceLevels) > 0
for i = 0 to array.size(resistanceLevels) - 1
float level = array.get(resistanceLevels, i)
if low <= level and high >= level and close < level
bounceSignal := 1
if array.size(supportLevels) > 0
for i = 0 to array.size(supportLevels) - 1
float level = array.get(supportLevels, i)
if high >= level and low <= level and close > level
bounceSignal := 1
// Outputs
plot(patternSignal, title="Pattern Signal", color=patternSignal == 1 ? color.purple : na, style=plot.style_circles)
plot(bounceSignal, title="Bounce Signal", color=bounceSignal == 1 ? color.yellow : na, style=plot.style_circles)
plot(nearestDoubleLevel, title="Nearest Double Level Price", color=color.orange)
plot(distanceNormalizedATR, title="Normalized Distance (ATR)", color=color.green)
bgcolor(patternSignal == 1 ? color.new(color.purple, 80) : na)
if patternSignal == 1 and barstate.isconfirmed
alert("Double Pattern detected on " + syminfo.ticker + " at " + str.tostring(close), alert.freq_once_per_bar_close)
if barstate.islast
var table infoTable = table.new(position.top_right, 1, 4, bgcolor=color.new(color.black, 50))
table.cell(infoTable, 0, 0, "Pattern: " + str.tostring(patternSignal), bgcolor=patternSignal == 1 ? color.purple : color.gray)
table.cell(infoTable, 0, 1, "Bounce: " + str.tostring(bounceSignal), bgcolor=bounceSignal == 1 ? color.yellow : color.gray)
table.cell(infoTable, 0, 2, "Level: " + str.tostring(nearestDoubleLevel, "#.##"), bgcolor=color.orange)
table.cell(infoTable, 0, 3, "ATR Dist: " + str.tostring(distanceNormalizedATR, "#.##"), bgcolor=color.green)
