Supply and DemandThis is a "Supply and Demand" script designed to help traders spot potential levels of supply (resistance) and demand (support) in the market by identifying pivot points from past price action.
Differences from Other Scripts:
Unlike many pivot point scripts, this one offers a greater degree of customization and flexibility, allowing users to determine how many ranges of pivot points they wish to plot (up to 10), as well as the number of the most recent ranges to display.
Furthermore, it allows users to restrict the plotting of pivot points to specific timeframes (15 minutes, 30 minutes, 1 hour, 4 hours, and daily) using a toggle input. This is useful for traders who wish to focus on these popular trading timeframes.
This script also uses the color.new function for a more transparent plotting, which is not commonly used in many scripts.
How to Use:
The script provides two user inputs:
"Number of Ranges to Plot (1-10)": This determines how many 10-bar ranges of pivot points the script will calculate and potentially plot.
"Number of Last Ranges to Show (1-?)": This determines how many of the most recent ranges will be displayed on the chart.
"Limit to specific timeframes?": This is a toggle switch. When turned on, the script only plots pivot points if the current timeframe is one of the following: 15 minutes, 30 minutes, 1 hour, 4 hours, or daily.
The pivot points are plotted as circles on the chart, with pivot highs in red and pivot lows in green. The transparency level of these plots can be adjusted in the script.
Market and Conditions:
This script is versatile and can be used in any market, including Forex, commodities, indices, or cryptocurrencies. It's best used in trending markets where supply and demand levels are more likely to be respected. However, like all technical analysis tools, it's not foolproof and should be used in conjunction with other indicators and analysis techniques to confirm signals and manage risk.
A technical analyst, or technician, uses chart patterns and indicators to predict future price movements. The "Supply and Demand" script in question can be an invaluable tool for a technical analyst for the following reasons:
Identifying Support and Resistance Levels : The pivot points plotted by this script can act as potential levels of support and resistance. When the price of an asset approaches these pivot points, it might bounce back (in case of support) or retreat (in case of resistance). These levels can be used to set stop-loss and take-profit points.
Timeframe Analysis : The ability to limit the plotting of pivot points to specific timeframes is useful for multiple timeframe analysis. For instance, a trader might use a longer timeframe to determine the overall trend and a shorter one to decide the optimal entry and exit points.
Customization : The user inputs provided by the script allow a technician to customize the ranges of pivot points according to their unique trading strategy. They can choose the number of ranges to plot and the number of the most recent ranges to display on the chart.
Confirmation of Other Indicators : If a pivot point coincides with a signal from another indicator (for instance, a moving average crossover or a relative strength index (RSI) divergence), it could provide further confirmation of that signal, increasing the chances of a successful trade.
Transparency in Plots : The use of the color.new function allows for more transparent plotting. This feature can prevent the chart from becoming too cluttered when multiple ranges of pivot points are plotted, making it easier for the analyst to interpret the data.
In summary, this script can be used by a technical analyst to pinpoint potential trading opportunities, validate signals from other indicators, and customize the display of pivot points to suit their individual trading style and strategy. Always remember, however, that no single indicator should be used in isolation, and effective risk management strategies should always be employed.
Cerca negli script per "a股板块+沪深两市+股价不超过10元的股票+技术形态好"
No Code SignalsNo Code Signals is an intuitive user interface for users to generate their own signals based on indicators they already have applied to their chart.
This indicator makes use of the new input.source() limits for importing data from external sources (indicators) into 1 indicator.
You are now able to import ANY number of sources from up to 10 different indicators.
Features:
- Import up to 10 unique values from up to 10 different indicators already on your chart!
- Compare those values against other imported indicator values, or chart ohlc values.
- Option to use a defined level instead of an active source.
- 5 Signal Options (Currently)
- Alerts, Each signal has its own alert condition.
- Labeled Signals, to tell which signal is which.
Potential Future Plans:
- More Signals & Analysis Options
- Possibly more imports
- Combining 2 (or more) signals into 1
Here is a Screenshot of a chart with signals, and the Interface creating the signals.
Enjoy!
Sushi Trend [HG]🍣 The Sushi Roll, a trading concept conceived at a restaurant by Mark Fisher.
While the indicator itself goes by Sushi Trend, it is completely backed by the idea of Mark Fisher's Sushi Roll Reversal Pattern. No, it has nothing to do with raw fish, it just so happens that somebody was ordering sushi during the discussion of the idea, and that's how it got its name.
📝 Origin
First mentioned in his book, The Logical Trader --- the idea of the Sushi Roll is to serve as an early warning system to identify reversals in the market. Fisher defines the pattern as a series of 10 bars, split into two different sections, seen as 5 and 5. In order for the pattern to be emitted, the 5 bars to the right must completely engulf the 5 bars to the left. It's not a super complex system and is in fact extremely simple to grasp.
📈 Supertrend Similarities
Instead of displaying the pattern in the way Fisher meant for it to be portrayed (as seen in the photo above), I instead turned it into an indicator similar to that of Supertrend while also inheriting the same concepts from the pattern. I did this because the pattern itself has inconsistencies which can be quite noticeable when trading with it after a while. For example, these patterns can occur even during consolidating periods, and even though the pattern is meant to be recognized during trending markets, the engulfing bars can sometimes be left with indecisive directions.
➡️ The Result
Here is the result, visualized to be better in a trending format. (The indicator will not contain the boxes.)
While Fisher does mention the pattern to include 10 bars, you can actually use this pattern with any number of bars. At the end of the day, it's a concept derived from a discussion at a Japanese restaurant, and a pattern that has been around for years that has seen results. Due to this, I added an input option to control the series of bars for right-bar engulf detection.
To reassure the meaning of the pattern --> "A series of 10 bars" means 5 left bars and 5 right bars. So if you want to check if 5 right bars are engulfing the previous 5 bars (as seen in the photo above), you would want to select 5 in the input settings.
You can learn more about it from the following links
Market Reversals and the Sushi Roll Technique
The Logical Trader
Ignition Cha Cha ChaIgnition Cha Cha Cha (ICCC) is a 3 color coded moving average indicator which numerically quantify the angle of their trends. I have labeled them as fast, medium and slow. The trend colors are Green for bullish, Red for bearish and Grey for sideways. The sideways movement can be user defined for all 3 in the settings under Threshold. If you regard for example anything under 10º as sideways then place 10 in the corresponding threshold and any angle under 10º will give a grey moving average and a grey labeled text. I use this chart in several ways. If you don't want moving averages all over your Chartistic Masterpiece you can turn off the plots and leave the numeric angles which will give you an overview of the trend. Conversely if you want to make the ultimate trend chart you can setup a 4 chart layout, Weekly, Daily, 12 hour and 4 hour and add the indicator with 200/50/25 moving averages and look for confluence. I find the best way for this is turn off the candles and use the moving averages with the numeric labels. You also have the ability to turn off and on different aspects of the indicator so that there is good control over its look. Also I have given the indicator lots of Alert presets for all 3 of the moving averages so you can avoid demented screen-stairing. Please forgive the name, my mother made me do Ballroom dancing lessons as a kid.
Moving Average Resting Point [theEccentricTrader]█ OVERVIEW
This indicator uses peak and trough prices to calculate the moving average resting point and plots it as a line on the chart. The lookback length is variable and the indicator can plot up to three lines with different lookback lengths and colors.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Support and Resistance
• Support refers to a price level where the demand for an asset is strong enough to prevent the price from falling further.
• Resistance refers to a price level where the supply of an asset is strong enough to prevent the price from rising further.
Support and resistance levels are important because they can help traders identify where the price of an asset might pause or reverse its direction, offering potential entry and exit points. For example, a trader might look to buy an asset when it approaches a support level , with the expectation that the price will bounce back up. Alternatively, a trader might look to sell an asset when it approaches a resistance level , with the expectation that the price will drop back down.
It's important to note that support and resistance levels are not always relevant, and the price of an asset can also break through these levels and continue moving in the same direction.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. As can be seen in the example above, the first swing high or swing low will set the course for the sequence of wave cycles that follow; a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Wave Length
Wave length is here measured in terms of bar distance between the start and end of a wave cycle. For example, if the current wave cycle ends on a swing low the wave length will be the difference in bars between the current swing low and current swing high. In such a case, if the current swing low completes on candle 100 and the current swing high completed on candle 95, we would simply subtract 95 from 100 to give us a wave length of 5 bars.
Average wave length is here measured in terms of total bars as a proportion as total waves. The average wavelength is calculated by dividing the total candles by the total wave cycles.
Wave Height
Wave height is here measured in terms of current range. For example, if the current peak price is 100 and the current trough price is 80, the wave height will be 20.
Amplitude
Amplitude is here measured in terms of current range divided by two. For example if the current peak price is 100 and the current trough price is 80, the amplitude would be calculated by subtracting 80 from 100 and dividing the answer by 2 to give us an amplitude of 10.
Resting Point
The resting point is here calculated by subtracting the current trough price from the current peak price and adding the difference to the current trough price to output the price in the middle of the two prices. Essentially it is the current trough price plus the amplitude. For example, if the current peak price is 100 and the current trough price is 80, the resting point 90.
The moving average resting point is here calculated by subtracting the moving average trough price from the moving average peak price, dividing the answer by two and adding the difference to the moving average trough price.
Frequency
Frequency is here measured in terms of wave cycles per second (Hertz). For example, if the total wave cycle count is 10 and the amount of time it has taken to complete these 10 cycles is 1-year (31,536,000 seconds), the frequency would be calculated by dividing 10 by 31,536,000 to give us a frequency of 0.00000032 Hz.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
█ FEATURES
Inputs
Show MARP 1
Show MARP 2
Show MARP 3
MARP 1 Length
MARP 2 Length
MARP 3 Length
MARP 1 Color
MARP 2 Color
MARP 3 Color
█ HOW TO USE
This indicator can be used like any other moving average indicator to analyse trend direction and momentum, identify potential support and resistance levels, or for filtering trading strategies and developing new ones.
Opening Hour/Closing Hour Indices Statistics: high/low times; 5mVery specific indicator designed for 5min timeframe, to show the statistical timings of the highs and lows of Opening hour (9:30-10am) and Closing hour (3pm-4pm) NY time
~~Shown here on SPX 5min chart. Works all variants of the US indices. SPX and SPY typically show more days of history (non-extended session =>> more bars).
//Purpose:
-To get statistics on the timings of the high and low of the opening hour and the high & low of the closing hour.
//Design & Limitations:
- Designed for the 5minute chart ONLY . Need a sweet spot of 'bucket' size for the statistics: to allow meaningful comparison between times.
-Will also display on 1min chart but NOT the statistics panel, only the realtime data (today's opening hour/ closing hour timings).
-Can be slow to load depending on server load at the time. This is becasue of the multiple usage of looping array functions. Please be patient when loading or changing settings.
//User inputs:
-Standard formatting options: highlight color, table text color. Toggle on/off independently
-Decimal % percision (default = 0, i.e. 23%. If set to 1 => 22.8%)
-Show statistics: Show Opening hour statistics, Show Closing hour statistics
//Notes:
-Days of history shown at top of table; this is the size of the dataset. i.e. 254 here (254 trading days) =>> 254 opening hour highs, 254 closing hour lows etc.
--to illustrate with the above: 18% of those 254 closing hour highs occured on the 15:00 5min candle (i.e. between 15:00 and 15:05).
-SPY or SPX offer the largest history/dataset (circa 254 trading days).
-Note that the final timing in each hour is 10:25am and 15:55pm respectively: this is because the 10:25am 5min candle essentially ends at 10:30am =>> we properly captures the opening hour this way
-Pro+ users will get less data history than Premium users (half as much, due to 10k vs 20k bars history limit).
Correlation prix [SP500, TESLA, BTCBefore you see this post I want to thank all the TradingView team. Every day that passes I learn better and better to use Pine script and I owe this to all those who publish and to the philosophy of TradingView. Thanks from Amos
This trading indicator compares the prices of the S&P 500 Index (SP500), Tesla (TSLA), and Bitcoin (BTC) to find correlations between them. To make the prices of SP500 and Tesla comparable to the price of Bitcoin, the indicator multiplies the closing price of Tesla by 114 and the closing price of the S&P 500 Index by 5.6.
In this way we can superimpose the prices on the BTC chart and see what happens.
Average BTC price/ tesla price = 114, so if we multiply the tesla price by 114 times we can superimpose it on the BTC price
At average BTC/SPX price = 5.6, also in this case we multiply the price of SPX by 5.6 to overlay the graph and see any correlations.
The indicator then calculates the average price between SP500 and Tesla, using the formula (SP500 + Tesla) / 2. This calculation creates a new line on the chart that represents the average price between these two assets.
The BTC_SP_TE variable is then calculated as the average of the closing price of Bitcoin and the previously calculated average price of SP500 and Tesla, using the formula (Btc + SP_TE) / 2. This calculation creates another line on the chart that represents the average price between Bitcoin and the previously calculated average between SP500 and Tesla.
The idea behind calculating these averages is to find correlations and patterns between the prices of these assets, which can help identify potential trading opportunities. By comparing the average prices of different assets, the trader can look for trends and patterns that might not be apparent when looking at each asset individually.
The indicator plots these prices on a chart and fills the area between them with either green or fuchsia, depending on which one is higher. The strategy suggests buying Bitcoin when the average price of SP500 and Tesla is higher than the current price of Bitcoin, and selling when it is lower.
To add visual cues to the trading strategy, the indicator uses the plotchar function to display a small triangle below the chart when it detects a potential buying opportunity. This is done with the following parameters:
Value: BTC_SP_TE < Btc and Btc > Btc1 and Btc1 > Btc , which is a logical expression that checks whether the average price of SP500 and Tesla is less than the current price of Bitcoin (BTC_SP_TE < Btc), and whether the current price of Bitcoin is higher than the price 10 bars ago (Btc > Btc1 ) and higher than the price on the previous bar (Btc1 > Btc ).
Text: "Moyen BTC_SP_Te", which is the text to display inside the marker.
Symbol: "▲", which is the symbol to use for the marker. In this case, it is a small triangle pointing upwards.
Location: location.belowbar, which specifies that the marker should be placed below the bar.
I hope this is an example of how to create an indicator on TradingView, remember that correlations do not always last, it is possible that when you see the graph this correspondence no longer exists, do your studies and get inspired.
7 Week RuleThe 7 week rule was shared by Gil Morales in his book “Trade Like an O’Neil Disciple”. The rule is described as: Stocks that have shown a tendency to “obey” or “respect” the 10-day moving average for at least 7 weeks in an uptrend should often be sold once the stock violates the 10-day line. A “violation” is defined as a close below the 10-day moving average followed by a move on the next day below the intraday low of the first day.
This indicator makes using the 7 week rule easy. Once a stock has closed above its selected moving average (10SMA by default) for 35 days the 7 week rule is triggered. Once the stock then “violates” the moving average, a sell signal is printed on the chart.
Indicator Customizations
Moving Average Length & Type
Show or Hide Moving Average
Show Running Count of Days Above Selected MA
Highlight When 7 Week Rule Triggers
Option to Show First Day Above MA
Indicator is dynamic and will continue the count if no violation occurs.
Weis V5 zigzag jayySomehow, I deleted version 5 of the zigzag script. Same name. I have added some older notes describing how the Weis Wave works.
I have also changed the date restriction that stopped the script from working after Dec 31, 2022.
What you see here is the Weis zigzag wave plotted directly on the price chart. This script is the companion to the Weis cumulative wave volume script.
What is a Weis wave? David Weis has been recognized as a Wyckoff method analyst he has written two books one of which, Trades About to Happen, describes the evolution of the now-popular Weis wave. The method employed by Weis is to identify waves of price action and to compare the strength of the waves on characteristics of wave strength. Chief among the characteristics of strength is the cumulative volume of the wave. There are other markers that Weis uses as well for example how the actual price difference between the start of the Weis wave from start to finish. Weis also uses time, particularly when using a Renko chart
David Weis did a futures io video which is a popular source of information about his method. (Search David Weis and futures.io. I strongly suggest you also read “Trades About to Happen” by David Weis.
This will get you up and running more quickly when studying charts. However, you should choose the Traditional method to be true to David Weis technique as described in his book "Trades About to Happen" and in the Futures IO Webcast featuring David Weis
. The Weis pip zigzag wave shows how far in terms of bar close price a Weis wave has traveled through the duration of a Weis wave. The Weis zigzag wave is used in combination with the Weis cumulative volume wave. The two waves should be set to the same "wave size".
To use this script, you must set the wave size: Using the traditional Weis method simply enter the desired wave size in the box "How should wave size be calculated", in this example I am using a traditional wave size of .25. Each wave for each security and each timeframe requires its own wave size. Although not the traditional method devised by David Weis a more automatic way to set wave size would be to use Average True Range (ATR). Using ATR is not the true Weis method but it does give you similar waves and, importantly, without the hassle described above. Once the Weis wave size is set then the zigzag wave will be shown with volume. Because Weis used the closing price of a wave to define waves a line Bar highs and bar lows are not captured by the Weis Wave. The default script setting is now cumulative volume waves using an ATR of 7 and a multiplication factor of .5.
To display volume in a way that does not crowd out neighbouring volumes Weis displayed volume as a maximum of 3 digits (usually). Consider two Weis Wave volumes 176,895,570 and 2,654,763,889. To display wave volume as three digits it is necessary to take a number such as 176,895,570 and truncate it. 176,895,570 can be represented as 177 X 10 to the power of 6. The number displayed must also be relative to other numbers in the field. If the highest volume on the page is: 2,654,763,889 and with only three numbers available to display the result the value shown must be 265 (265 X 10 to the power of 7). Since 176,895,570 is an order of magnitude smaller than 2,654,763,889 therefore 175,895,570 must be shown as 18 instead of 177. In this way, the relative magnitudes of the two volumes can be understood. All numbers in the field of view must be truncated by the same order of magnitude to make the relative volumes understandable. The script attempts to calculate the order of magnitude value automatically. If you see a red number in the field of view it means the script has failed to do the calculation automatically and you should use the manual method – use the dialogue box “Calculate truncated wave value automatically or manually”. Scroll down from the automatic method and select manual. Once "manual" is selected the values displayed become the power values or multipliers for each wave.
Using the manual method you will select a “Multiplier” in the next dialogue box. Scan the field and select the largest value in the field of view (visible chart) is the multiplier of interest. If you select a lower number than the maximum value will see at least one red “up”. If you are too high you will see at least one red “down”. Scroll in the direction recommended or the values on the screen will be totally incorrect. With volume truncated to the highest order values, the eye can quickly get a feel for relative volumes. It also reduces the crowding and overlapping of values on the screen. You can opt to show the full volume to help get a sense of the magnitude of the true volumes.
How does the script determine if a Weis wave is continuing to grow or not?
The script evaluates the closing price of each new bar relative to the "Weis wave size". Suppose the current bar closes at a new low close, within the current down wave, at $30.00. If the Weis wave size is $0.10 then the algorithm will remember the $30.00 close and compare it to the close of the next bar. If the bar close price does not close equal to or lower than $30.00 or close equal to or higher than $30.10 then the wave is still a down wave with a current low of $30.00. This is true even if the bar low is less than $30.00 or the bar high is greater than 30.10 – only the bar’s closing price matters. If a bar's closing price climbs back up to a close of $30.11 then because the closing price has moved more than $0.10 (the Weis wave size) then that is a wave reversal with a new up-trending wave. In the above example if there was currently a downward trending wave and the bar closes were as follows $30.00, $30.09, $30.01, $30.05, $30.10 The wave direction would continue to stay downward trending until the close of $30.10 was achieved. As such $30.00 would be the low and the following closes $30.09, $30.01, $30.05 would be allocated to the new upward-trending wave. If however There was a series of bar closes like this $30.00, $30.09, $30.01, $30.05, $29.99 since none of the closes was equal to above the 10-cent reversal target of $30.10 but instead, a new Weis wave low was achieved ($29.99). As such the closes of $30.09, $30.01, $30.05 would all be attributed to the continued down-trending wave with a current low of $29.99, even though the closing price for the interim bars was above $30.00. Now that the Weis Wave low is now 429.99 then, in order to reverse this continued downtrend price will need to close at or above $30.09 on subsequent bar closes assuming now new low bar close is achieved. With large wave sizes, wave direction can be in limbo for many bars before a close either renews wave direction or reverses it and confirms wave direction as either a reversal or a continuation. On the zig-zag, a wave line and its volume will not be "printed" until a wave reversal is confirmed.
The wave attribution is similar when using other methods to define wave size. If ATR is used for wave size instead of a traditional wave constant size such as $0.10 or $2 or 2000 pips or ... then the wave size is calculated based on current ATR instead of the Weis wave constant (Traditional selected value).
I have the option to display pseudo-Ord volume. In truth, Ord used more traditional zig-zag pivots of bar highs and lows. Waves using closes as pivots can have some significant differences. This difference can be lessened by using smaller time frames and larger wave sizes.
There are other options such to display the delta price or pip size of a Weis Wave, the number of bars in a wave, and a few other options.
Nick_OS RangesUNDERSTANDING THE SCRIPT:
TIMEFRAME RESOLUTION:
* You have the option to choose Daily , Weekly , or Monthly
LOOKBACK WINDOW:
* This number represents how far back you want the data to pull from
- Example: "250" would represent the past 250 Days, Weeks, or Months depending on what is selected in the Timeframe Resolution
RANGE 1 nth (Gray lines):
* This number represents the range of the nth biggest day, week, or month in the Lookback Window
- Example: "30" would represent the range of the 30th biggest day in the past 250 days. (If the Lookback Window is "250")
RANGE 2 nth (Blue lines):
* This number represents the range of the nth biggest day, week, or month in the Lookback Window
- Example: "10" would represent the range of the 10th biggest day in the past 250 days. (If the Lookback Window is "250")
RANGE 3 nth (Pink lines):
* This number represents the range of the nth biggest day, week, or month in the Lookback Window
- Example: "3" would represent the range of the 3rd biggest day in the past 250 days. (If the Lookback Window is "250")
YELLOW LINES:
* The yellow lines are the average percentage move of the inputted number in the Lookback Window
SUGGESTED INPUTS:
FOR DAILY:
Lookback Window: 250
Range 1 nth: 30
Range 2 nth: 10
Range 3 nth: 3
FOR WEEKLY:
Lookback Window: 50
Range 1 nth: 10
Range 2 nth: 5
Range 3 nth: 2
FOR MONTHLY:
Lookback Window: 12
Range 1 nth: 3
Range 2 nth: 2
Range 3 nth: 1
TIMEFRAMES TO USE (If You Have TradingView Premium):
Daily: 5 minute timeframe and higher (15 minute timeframe and higher for Futures)
Weekly: 15 minute timeframe and higher
Monthly: Daily timeframe and higher (Monthly still has issues)
TIMEFRAMES TO USE (If You DO NOT Have TradingView Premium):
Daily: 15 minute timeframe and higher
Weekly: 30 minute timeframe and higher
Monthly: Daily timeframe and higher (Monthly still has issues)
IMPORTANT RELATED NOTE:
If you decide to use a higher Lookback Window, the ranges might be off and the timeframes listed above might not apply
ISSUES THAT MIGHT BE RESOLVED IN THE FUTURE
1. If it is a shortened week (No Monday or Friday), then the Weekly Ranges will show the same ranges as last week
2. Monthly ranges will change based on any timeframe used
Stockbee Momentum BurstThis is a script to color code bars based on the bullish- and bearish combination.
Bullish Combination
Percent: Price >= 4% from yesterday and Volume today > Yesterday
Dollar: Price >= 0.9 dollar from open
Base Requirements
- Price > Yesterday's close
- Price > Open
- Price is within 30% of high
- Todays price range >= Yesterdays price range
- Yesterday's move <= 2%
- Volume >= 100 000
Bearish Combination
Percent: Price <= 4% from yesterday and Volume today > Yesterday
Dollar: Price <= 0.9 dollar from open
Base Requirements
- Price < Yesterday's close
- Price < Open
- Price is within 30% of low
- Todays price range >= Yesterdays price range
- Yesterday's move >= -2%
- Minimum volume for each of last 3 days >= 100 000
Momentum Filter
These are based on the 10 and 20 EMA crossover, where the former above would indicate upward momentum and below downward momentum. This can help to narrow down the color code to continuation phases. The linked option will override all other momentum filters, bullish candles will be displayed when EMA 10 > 20 and bearish candles when EMA 10 < 20.
12/26-IT strategyBase of this Strategy is crossover of 12EMA on 26EMA.
Also multiple other criteria has to meet for buy signal, Criterias mentioned below
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There two entry option to select. Either one or both can be selected:
1. Only 12/26 Cross over
a. 12/26 crossover.
b. RSI (14) value to be between a range (RSI is inbuilt, but lower and upper range can be defined in settings)
c. MACD (12, 26) to be positive and above signal line (this is inbuilt)
2. Recent 12/26 Cross over and closing above pivot point(resistance)
a. 12/26 crossover has to be recent, CrossOverLookbackCandles value will look for crossover in # previous candles..
b. RSI (14) value to be between a range (RSI is inbuilt, but lower and upper range can be defined in settings)
c. MACD (12, 26) to be positive and above signal line (this is inbuilt)
d. closing above resistance line
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For Exit we have three options. you can select any SL as per your need, multiple SLs can also be selected
1. Trailing Stop Loss.
Source for TSL is adjustable(open, close, high or low), also you have to mention % below your source TSL has to be placed.
Once closing is below TSL, exit will be triggered.
2. Closing below 7SMA
After 7SMA SL is enabled, 7SMA will be plotted on chart and exit signal will be triggered when closing is below 7SMA.
Choose this option for LESS risk and rewards
3. 12/26 Crossdown
Once 12EMA crossdown below 26EMA, exit will be triggered.
Choose this option for HIGH risk and rewards
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Resistance line is plotted based on left and right candles, if 10(can be changed) is used for both left and right, indicator will look for 10 candles in left and 10 candles in right and if both left and right candle are lower then a line is plotted.
Source has to be selected (close or high)
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Qty mentioned in Buy trigger will be based on BUYVALUE entered
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Multiple Target option is available, if first target is matched how much percentage of qty to be sold can be defined.
If you wish to have only one Target, then exit qty in first target must be 100
TheMas7er scalp (US equity) 5min [promuckaj]This indicator was created according to TheMas7er's trading setup, that he reveal after 18 years of working in the industry. Claims is that this setup should give you good probability to predict the price movement for US equity.
This trading setup is only for New York equity trading session from 09:30 until 4pm. The market in which you should use it are the S&P 500 , Dow Jones, and Nasdaq. Perhaps it will work on some other but for those are good according to tests. It should not used on days with high-impact news, like CPI , FOMC, NFP and so on. The model can still work there but the probability on these days is way lower.
What is the base of this indicator, it marks what is called "The Defining Range"("DR"). This defining range is from 09:30am until 10:30am New York local time, it takes those 12 candles in the 5min chart. Indicator will mark the high and low of this range, including wicks. This will help you to already know at 10:30am, with possible good probability the high or low of the day.
There is also the "Implied Defining Range"("iDR") lines inside the "DR" range, which mark the highest body and the lowest body in the "DR" range.
*The rules (it is very simple to follow):
Chart must be set in 5min timeframe.
At 10:30am you still don't know which one will be the real high or low of the day, but only one will be true.
If price is closing on 5min chart above the "DR" it should give you good probability that the low of the "DR" is the low of the day, and vice versa - if price is closing below the "DR" it should give you good probability that the high of the "DR" is the high of the day.
"iDR" gives you an early indication about what high or low of the day should be. If price is closing above "iDR" you will have an early indication that the low of the "DR" should be the low of the day, and vice versa.
Note that about closing means really closing above or below, not just wicks.
Now, after this you can realize the magnitude of possibility.
You can use any entry model you prefer to trade, it doesn't matter if you use ICT concepts, smart money concepts, volume profile , eliot waves, braking the structure concept or whatever. There are so many possibilities for trading within this rule.
Enjoy!
Session candles & reversals / quantifytools— Overview
Like traditional candles, session based candles are a visualization of open, high, low and close values, but based on session time periods instead of typical timeframes such as daily or weekly. Session candles are formed by fetching price at session start (open), highest price during session (high), lowest price during session (low) and price at session end (close). On top of candles, session based moving average is formed and session reversals detected. Session reversals are also backtested, using win rate and magnitude metrics to better understand what to expect from session reversals and which ones have historically performed the best.
By default, following session time periods are used:
Session #1: London (08:00 - 17:00, UTC)
Session #2: New York (13:00 - 22:00, UTC)
Session #3: Sydney (21:00 - 06:00, UTC)
Session #4: Tokyo (00:00 - 09:00, UTC)
Session time periods can be changed via input menu.
— Reversals
Session reversals are patterns that show a rapid change in direction during session. These formations are more familiarly known as wicks or engulfing candles. Following criteria must be met to qualify as a session reversal:
Wick up:
Lower high, lower low, close >= 65% of session range (0% being the very low, 100% being the very high) and open >= 40% of session range.
Wick down:
Higher high, higher low, close <= 35% of session range and open <= 60% of session range.
Engulfing up:
Higher high, lower low, close >= 65% of session range.
Engulfing down:
Higher high, lower low, close <= 35% of session range.
Session reversals are always based on prior corresponding session , e.g. to qualify as a NY session engulfing up, NY session must have a higher high and lower low relative to prior NY session , not just any session that has taken place in between. Session reversals should be viewed the same way wicks/engulfing formations are viewed on traditional timeframe based candles. Essentially, wick reversals (light green/red labels) tell you most of the motion during session was reversed. Engulfing reversals (dark green/red labels) on the other hand tell you all of the motion was reversed and new direction set.
— Backtesting
Session reversals are backtested using win rate and magnitude metrics. A session reversal is considered successful when next corresponding session closes higher/lower than session reversal close . Win rate is formed by dividing successful session reversal count with total reversal count, e.g. 5 successful reversals up / 10 reversals up total = 50% win rate. Win rate tells us what are the odds (historically) of session reversal producing a clean supporting move that was persistent enough to close that way too.
When a session reversal is successful, its magnitude is measured using percentage increase/decrease from session reversal close to next corresponding session high/low . If NY session closes higher than prior NY session that was a reversal up, the percentage increase from prior session close (reversal close) to current session high is measured. If NY session closes lower than prior NY session that was a reversal down, the percentage decrease from prior session close to current session low is measured.
Average magnitude is formed by dividing all percentage increases/decreases with total reversal count, e.g. 10 total reversals up with 1% increase each -> 10% net increase from all reversals -> 10% total increase / 10 total reversals up = 1% average magnitude. Magnitude metric supports win rate by indicating the depth of successful session reversal moves.
To better understand the backtesting calculations and more importantly to verify their validity, backtesting visuals for each session can be plotted on the chart:
All backtesting results are shown in the backtesting panel on top right corner, with highest win rates and magnitude metrics for both reversals up and down marked separately. Note that past performance is not a guarantee of future performance and session reversals as they are should not be viewed as a complete strategy for long/short plays. Always make sure reversal count is sufficient to draw reliable conclusions of performance.
— Session moving average
Users can form a session based moving average with their preferred smoothing method (SMA , EMA , HMA , WMA , RMA) and length, as well as choose which sessions to include in the moving average. For example, a moving average based on New York and Tokyo sessions can be formed, leaving London and Sydney completely out of the calculation.
— Visuals
By default, script hides your candles/bars, although in the case of candles borders will still be visible. Switching to bars/line will make your regular chart visuals 100% hidden. This setting can be turned off via input menu. As some sessions overlap, each session candle can be separately offsetted forward, clearing the overlaps. Users can also choose which session candles to show/hide.
Session periods can be highlighted on the chart as a background color, applicable to only session candles that are activated. By default, session reversals are referred to as L (London), N (New York), S (Sydney) and T (Tokyo) in both reversal labels and backtesting table. By toggling on "Numerize sessions", these will be replaced with 1, 2, 3 and 4. This will be helpful when using a custom session that isn't any of the above.
Visual settings example:
Session candles are plotted in two formats, using boxes and lines as well as plotcandle() function. Session candles constructed using boxes and lines will be clear and much easier on the eyes, but will apply only to first 500 bars due to Tradingview related limitations. Rest of the session candles go back indefinitely, but won't be as clean:
All colors can be customized via input menu.
— Timeframe & session time period considerations
As a rule of thumb, session candles should be used on timeframes at or below 1H, as higher timeframes might not match with session period start/end, leading to incorrect plots. Using 1 hour timeframe will bring optimal results as greatest amount historical data is available without sacrificing accuracy of OHLC values. If you are using a custom session that is not based on hourly period (e.g. 08:00 - 15:00 vs. 08.00 - 15.15) make sure you are using a timeframe that allows correct plots.
Session time periods applied by default are rough estimates and might be out of bounds on some charts, like NYSE listed equities. This is rarely a problem on assets that have extensive trading hours, like futures or cryptocurrency. If a session is out of bounds (asset isn't traded during the set session time period) the script won't plot given session candle and its backtesting metrics will be NA. This can be fixed by changing the session time periods to match with given asset trading hours, although you will have to consider whether or not this defeats the purpose of having candles based on sessions.
— Practical guide
Whether based on traditional timeframes or sessions, reversals should always be considered as only one piece of evidence of price turning. Never react to them without considering other factors that might support the thesis, such as levels and multi-timeframe analysis. In short, same basic charting principles apply with session candles that apply with normal candles. Use discretion.
Example #1 : Focusing efforts on session reversals at distinct support/resistance levels
A reversal against a level holds more value than a reversal by itself, as you know it's a placement where liquidity can be expected. A reversal serves as a confirming reaction for this expectation.
Example #2 : Focusing efforts on highest performing reversals and avoiding poorly performing ones
As you have data backed evidence of session reversal performance, it makes sense to focus your efforts on the ones that perform best. If some session reversal is clearly performing poorly, you would want to avoid it, since there's nothing backing up its validity.
Example #3 : Reversal clusters
Two is better than one, three is better than two and so on. If there are rapid changes in direction within multiple sessions consecutively, there's heavier evidence of a dynamic shift in price. In such case, it makes sense to hold more confidence in price halting/turning.
Traders Reality MainThis indicator serves as the Tradingview equivalent of an MT4 indicator suite.
It differentiates from existing TV indicators in its style and total feature set (most notably PVSRA and PVSRA Override)
It was originally designed for forex markets, and it will work for crypto as well, but it has not been tested on stocks.
List of features:
PVSRA Candles
Market boxes (NY/JP/ HK /UK/ FR and Brinks Boxes)
5/13/50/200/800 EMAs (cloud for 50EMA)
Pivot points (S/M/R 1,2,3; PP )
Yesterday and Last Week price range
Average Daily Range (Weekly and Monthly as well)
Daily Open
PVSRA Override
Psychological High/Low
Vector Candle Zones
All of these are configurable in the indicator settings.
Usage instructions:
PVSRA Candle colors meaning:
Green (bull) and red (bear): Candles with volume >= 200% of the average volume of the 10 previous chart candles, and candles where the product of candle spread x candle volume is >= the highest for the 10 previous chart time candles.
Blue (bull) and blue-violet (bear): Candles with volume >= 150% of the average volume of the 10 previous chart candles
PVSRA Override
In order to get reliable bar coloring, we need accurate data. If you're on a chart with low volume on some obscure exchange, you may want to use another exchanges datafeed for the symbol you are on to calculate the PVSRA bar colors with. This lets you do exactly that. By default it's off, but you can turn it on and use INDEX:BTCUSD, or really any other chart you want. You can combine charts too, e.g. use BINANCE:BTCUSDT+COINBASE:BTCUSD.
PVSRA Alerts
Alerts can be made for PVSRA "vector"/"climax" candles:
1. Create Alert (Clock with + sign)
2. Set Condition: "Traders Reality",
3. Select "Alert on Vector Candle",
4. Set it to Once per Bar,
5. choose your notification options.
Market boxes
The market boxes times are configurable and will change depending on the exchange timezone. I recommend to pick your main exchange/chart and adjust the times so that they are correct. Technically you will need to shift the time from the exchanges' timezone to GMT . Default values should be good for UTC based exchanges in current US+UK summer time.
Psychological High/Low
Configurable for Crypto or Forex - draws the perceived Psychological High/Low ranges for the week. Can display historical values too.
Vector Candle Zones
displays unrecovered liquidity left behind on unrecovered vectors. Configurable to take into account candle bodies or candles and wicks.
Recommended additional Tradingview indicator(s):
- TDI - Goldminds, Edited for Market Makers Method by Jakub Donovan
Footnotes
The code was originally by plasmapug, continued development (with permission) is now done by infernix and peshocore and xtech5192 in collaboration with TradersReality.
If you have suggestions or questions, you can message me or leave a comment.
Traders_Reality_LibLibrary "Traders_Reality_Lib"
This library contains common elements used in Traders Reality scripts
calcPvsra(pvsraVolume, pvsraHigh, pvsraLow, pvsraClose, pvsraOpen, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, darkGreyCandleColor, lightGrayCandleColor)
calculate the pvsra candle color and return the color as well as an alert if a vector candle has apperared.
Situation "Climax"
Bars with volume >= 200% of the average volume of the 10 previous chart TFs, or bars
where the product of candle spread x candle volume is >= the highest for the 10 previous
chart time TFs.
Default Colors: Bull bars are green and bear bars are red.
Situation "Volume Rising Above Average"
Bars with volume >= 150% of the average volume of the 10 previous chart TFs.
Default Colors: Bull bars are blue and bear are violet.
Parameters:
pvsraVolume : the instrument volume series (obtained from request.sequrity)
pvsraHigh : the instrument high series (obtained from request.sequrity)
pvsraLow : the instrument low series (obtained from request.sequrity)
pvsraClose : the instrument close series (obtained from request.sequrity)
pvsraOpen : the instrument open series (obtained from request.sequrity)
redVectorColor : red vector candle color
greenVectorColor : green vector candle color
violetVectorColor : violet/pink vector candle color
blueVectorColor : blue vector candle color
darkGreyCandleColor : regular volume candle down candle color - not a vector
lightGrayCandleColor : regular volume candle up candle color - not a vector
@return
adr(length, barsBack)
Parameters:
length : how many elements of the series to calculate on
barsBack : starting possition for the length calculation - current bar or some other value eg last bar
@return adr the adr for the specified lenght
adrHigh(adr, fromDo)
Calculate the ADR high given an ADR
Parameters:
adr : the adr
fromDo : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adrHigh the position of the adr high in price
adrLow(adr, fromDo)
Parameters:
adr : the adr
fromDo : boolean flag, if false calculate traditional adr from high low of today, if true calcualte from exchange midnight
@return adrLow the position of the adr low in price
splitSessionString(sessXTime)
given a session in the format 0000-0100:23456 split out the hours and minutes
Parameters:
sessXTime : the session time string usually in the format 0000-0100:23456
@return
calcSessionStartEnd(sessXTime, gmt)
calculate the start and end timestamps of the session
Parameters:
sessXTime : the session time string usually in the format 0000-0100:23456
gmt : the gmt offset string usually in the format GMT+1 or GMT+2 etc
@return
drawOpenRange(sessXTime, sessXcol, showOrX, gmt)
draw open range for a session
Parameters:
sessXTime : session string in the format 0000-0100:23456
sessXcol : the color to be used for the opening range box shading
showOrX : boolean flag to toggle displaying the opening range
gmt : the gmt offset string usually in the format GMT+1 or GMT+2 etc
@return void
drawSessionHiLo(sessXTime, show_rectangleX, show_labelX, sessXcolLabel, sessXLabel, gmt, sessionLineStyle)
Parameters:
sessXTime : session string in the format 0000-0100:23456
show_rectangleX : show the session high and low lines
show_labelX : show the session label
sessXcolLabel : the color to be used for the hi/low lines and label
sessXLabel : the session label text
gmt : the gmt offset string usually in the format GMT+1 or GMT+2 etc
sessionLineStyle : the line stile for the session high low lines
@return void
calcDst()
calculate market session dst on/off flags
@return indicating if DST is on or off for a particular region
timestampPreviousDayOfWeek(previousDayOfWeek, hourOfDay, gmtOffset, oneWeekMillis)
Timestamp any of the 6 previous days in the week (such as last Wednesday at 21 hours GMT)
Parameters:
previousDayOfWeek : Monday or Satruday
hourOfDay : the hour of the day when psy calc is to start
gmtOffset : the gmt offset string usually in the format GMT+1 or GMT+2 etc
oneWeekMillis : the amount if time for a week in milliseconds
@return the timestamp of the psy level calculation start time
getdayOpen()
get the daily open - basically exchange midnight
@return the daily open value which is float price
newBar(res)
new_bar: check if we're on a new bar within the session in a given resolution
Parameters:
res : the desired resolution
@return true/false is a new bar for the session has started
toPips(val)
to_pips Convert value to pips
Parameters:
val : the value to convert to pips
@return the value in pips
rLabel(ry, rtext, rstyle, rcolor, valid, labelXOffset)
a function that draws a right aligned lable for a series during the current bar
Parameters:
ry : series float the y coordinate of the lable
rtext : the text of the label
rstyle : the style for the lable
rcolor : the color for the label
valid : a boolean flag that allows for turning on or off a lable
labelXOffset : how much to offset the label from the current position
rLabelOffset(ry, rtext, rstyle, rcolor, valid, labelXOffset)
a function that draws a right aligned lable for a series during the current bar
Parameters:
ry : series float the y coordinate of the lable
rtext : the text of the label
rstyle : the style for the lable
rcolor : the color for the label
valid : a boolean flag that allows for turning on or off a lable
labelXOffset : how much to offset the label from the current position
rLabelLastBar(ry, rtext, rstyle, rcolor, valid, labelXOffset)
a function that draws a right aligned lable for a series only on the last bar
Parameters:
ry : series float the y coordinate of the lable
rtext : the text of the label
rstyle : the style for the lable
rcolor : the color for the label
valid : a boolean flag that allows for turning on or off a lable
labelXOffset : how much to offset the label from the current position
drawLine(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, labelXOffset, validTimeFrame)
a function that draws a line and a label for a series
Parameters:
xSeries : series float the y coordinate of the line/label
res : the desired resolution controlling when a new line will start
tag : the text for the lable
xColor : the color for the label
xStyle : the style for the line
xWidth : the width of the line
xExtend : extend the line
isLabelValid : a boolean flag that allows for turning on or off a label
labelXOffset : how much to offset the label from the current position
validTimeFrame : a boolean flag that allows for turning on or off a line drawn
drawLineDO(xSeries, res, tag, xColor, xStyle, xWidth, xExtend, isLabelValid, labelXOffset, validTimeFrame)
a function that draws a line and a label for the daily open series
Parameters:
xSeries : series float the y coordinate of the line/label
res : the desired resolution controlling when a new line will start
tag : the text for the lable
xColor : the color for the label
xStyle : the style for the line
xWidth : the width of the line
xExtend : extend the line
isLabelValid : a boolean flag that allows for turning on or off a label
labelXOffset : how much to offset the label from the current position
validTimeFrame : a boolean flag that allows for turning on or off a line drawn
drawPivot(pivotLevel, res, tag, pivotColor, pivotLabelColor, pivotStyle, pivotWidth, pivotExtend, isLabelValid, validTimeFrame, levelStart, pivotLabelXOffset)
draw a pivot line - the line starts one day into the past
Parameters:
pivotLevel : series of the pivot point
res : the desired resolution
tag : the text to appear
pivotColor : the color of the line
pivotLabelColor : the color of the label
pivotStyle : the line style
pivotWidth : the line width
pivotExtend : extend the line
isLabelValid : boolean param allows to turn label on and off
validTimeFrame : only draw the line and label at a valid timeframe
levelStart : basically when to start drawing the levels
pivotLabelXOffset : how much to offset the label from its current postion
@return the pivot line series
getPvsraFlagByColor(pvsraColor, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, lightGrayCandleColor)
convert the pvsra color to an internal code
Parameters:
pvsraColor : the calculated pvsra color
redVectorColor : the user defined red vector color
greenVectorColor : the user defined green vector color
violetVectorColor : the user defined violet vector color
blueVectorColor : the user defined blue vector color
lightGrayCandleColor : the user defined regular up candle color
@return pvsra internal code
updateZones(pvsra, direction, boxArr, maxlevels, pvsraHigh, pvsraLow, pvsraOpen, pvsraClose, transperancy, zoneupdatetype, zonecolor, zonetype, borderwidth, coloroverride, redVectorColor, greenVectorColor, violetVectorColor, blueVectorColor, lightGrayCandleColor)
a function that draws the unrecovered vector candle zones
Parameters:
pvsra : internal code
direction : above or below the current pa
boxArr : the array containing the boxes that need to be updated
maxlevels : the maximum number of boxes to draw
pvsraHigh : the pvsra high value series
pvsraLow : the pvsra low value series
pvsraOpen : the pvsra open value series
pvsraClose : the pvsra close value series
transperancy : the transparencfy of the vecor candle zones
zoneupdatetype : the zone update type
zonecolor : the zone color if overriden
zonetype : the zone type
borderwidth : the width of the border
coloroverride : if the color overriden
redVectorColor : the user defined red vector color
greenVectorColor : the user defined green vector color
violetVectorColor : the user defined violet vector color
blueVectorColor : the user defined blue vector color
lightGrayCandleColor : the user defined regular up candle color
cleanarr(arr)
clean an array from na values
Parameters:
arr : the array to clean
@return if the array was cleaned
calcPsyLevels(oneWeekMillis, showPsylevels, psyType, sydDST)
calculate the psy levels
4 hour res based on how mt4 does it
mt4 code
int Li_4 = iBarShift(NULL, PERIOD_H4, iTime(NULL, PERIOD_W1, Li_0)) - 2 - Offset;
ObjectCreate("PsychHi", OBJ_TREND, 0, Time , iHigh(NULL, PERIOD_H4, iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4)), iTime(NULL, PERIOD_W1, 0), iHigh(NULL, PERIOD_H4,
iHighest(NULL, PERIOD_H4, MODE_HIGH, 2, Li_4)));
so basically because the session is 8 hours and we are looking at a 4 hour resolution we only need to take the highest high an lowest low of 2 bars
we use the gmt offset to adjust the 0000-0800 session to Sydney open which is at 2100 during dst and at 2200 otherwize. (dst - spring foward, fall back)
keep in mind sydney is in the souther hemisphere so dst is oposite of when london and new york go into dst
Parameters:
oneWeekMillis : a constant value
showPsylevels : should psy levels be calculated
psyType : the type of Psylevels - crypto or forex
sydDST : is Sydney in DST
@return
Mega Pendulum IndicatorThe MPI (Mega Pendulum Indicator) is a fusion between the Pendulum Indicator and the Swing Indicator and is used with specific trading rules.
The MPI is a semi-bounded oscillator comprised of two lines. The first bounded line is the Pendulum Indicator which oscillates between 0 and 100 but generally oscillates between 20 and 80. The second semi-bounded line is the Swing Indicator which generally oscillates between -10 and 10.
The conditions for trading the Mega Pendulum Indicator are as follows:
* Buy: Whenever the Pendulum indicator crosses over its signal line (a 5-period moving average) and at the same time, the Swing Indicator must cross over -10 after having been below it.
* Sell: Whenever the Pendulum indicator crosses below its signal line (a 5-period moving average) and at the same time, the Swing Indicator must cross under -10 after having been above it.
Stochastic of Two-Pole SuperSmoother [Loxx]Stochastic of Two-Pole SuperSmoother is a Stochastic Indicator that takes as input Two-Pole SuperSmoother of price. Includes gradient coloring and Discontinued Signal Lines signals with alerts.
What is Ehlers ; Two-Pole Super Smoother?
From "Cycle Analytics for Traders Advanced Technical Trading Concepts" by John F. Ehlers
A SuperSmoother filter is used anytime a moving average of any type would otherwise be used, with the result that the SuperSmoother filter output would have substantially less lag for an equivalent amount of smoothing produced by the moving average. For example, a five-bar SMA has a cutoff period of approximately 10 bars and has two bars of lag. A SuperSmoother filter with a cutoff period of 10 bars has a lag a half bar larger than the two-pole modified Butterworth filter.Therefore, such a SuperSmoother filter has a maximum lag of approximately 1.5 bars and even less lag into the attenuation band of the filter. The differential in lag between moving average and SuperSmoother filter outputs becomes even larger when the cutoff periods are larger.
Market data contain noise, and removal of noise is the reason for using smoothing filters. In fact, market data contain several kinds of noise. I’ll group one kind of noise as systemic, caused by the random events of trades being exercised. A second kind of noise is aliasing noise, caused by the use of sampled data. Aliasing noise is the dominant term in the data for shorter cycle periods.
It is easy to think of market data as being a continuous waveform, but it is not. Using the closing price as representative for that bar constitutes one sample point. It doesn’t matter if you are using an average of the high and low instead of the close, you are still getting one sample per bar. Since sampled data is being used, there are some dSP aspects that must be considered. For example, the shortest analysis period that is possible (without aliasing)2 is a two-bar cycle.This is called the Nyquist frequency, 0.5 cycles per sample.A perfect two-bar sine wave cycle sampled at the peaks becomes a square wave due to sampling. However, sampling at the cycle peaks can- not be guaranteed, and the interference between the sampling frequency and the data frequency creates the aliasing noise.The noise is reduced as the data period is longer. For example, a four-bar cycle means there are four samples per cycle. Because there are more samples, the sampled data are a better replica of the sine wave component. The replica is better yet for an eight-bar data component.The improved fidelity of the sampled data means the aliasing noise is reduced at longer and longer cycle periods.The rate of reduction is 6 dB per octave. My experience is that the systemic noise rarely is more than 10 dB below the level of cyclic information, so that we create two conditions for effective smoothing of aliasing noise:
1. It is difficult to use cycle periods shorter that two octaves below the Nyquist frequency.That is, an eight-bar cycle component has a quantization noise level 12 dB below the noise level at the Nyquist frequency. longer cycle components therefore have a systemic noise level that exceeds the aliasing noise level.
2. A smoothing filter should have sufficient selectivity to reduce aliasing noise below the systemic noise level. Since aliasing noise increases at the rate of 6 dB per octave above a selected filter cutoff frequency and since the SuperSmoother attenuation rate is 12 dB per octave, the Super- Smoother filter is an effective tool to virtually eliminate aliasing noise in the output signal.
What are DSL Discontinued Signal Line?
A lot of indicators are using signal lines in order to determine the trend (or some desired state of the indicator) easier. The idea of the signal line is easy : comparing the value to it's smoothed (slightly lagging) state, the idea of current momentum/state is made.
Discontinued signal line is inheriting that simple signal line idea and it is extending it : instead of having one signal line, more lines depending on the current value of the indicator.
"Signal" line is calculated the following way :
When a certain level is crossed into the desired direction, the EMA of that value is calculated for the desired signal line
When that level is crossed into the opposite direction, the previous "signal" line value is simply "inherited" and it becomes a kind of a level
This way it becomes a combination of signal lines and levels that are trying to combine both the good from both methods.
In simple terms, DSL uses the concept of a signal line and betters it by inheriting the previous signal line's value & makes it a level.
Included:
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
Adaptive Two-Pole Super Smoother Entropy MACD [Loxx]Adaptive Two-Pole Super Smoother Entropy (Math) MACD is an Ehlers Two-Pole Super Smoother that is transformed into an MACD oscillator using entropy mathematics. Signals are generated using Discontinued Signal Lines.
What is Ehlers; Two-Pole Super Smoother?
From "Cycle Analytics for Traders Advanced Technical Trading Concepts" by John F. Ehlers
A SuperSmoother filter is used anytime a moving average of any type would otherwise be used, with the result that the SuperSmoother filter output would have substantially less lag for an equivalent amount of smoothing produced by the moving average. For example, a five-bar SMA has a cutoff period of approximately 10 bars and has two bars of lag. A SuperSmoother filter with a cutoff period of 10 bars has a lag a half bar larger than the two-pole modified Butterworth filter.Therefore, such a SuperSmoother filter has a maximum lag of approximately 1.5 bars and even less lag into the attenuation band of the filter. The differential in lag between moving average and SuperSmoother filter outputs becomes even larger when the cutoff periods are larger.
Market data contain noise, and removal of noise is the reason for using smoothing filters. In fact, market data contain several kinds of noise. I’ll group one kind of noise as systemic, caused by the random events of trades being exercised. A second kind of noise is aliasing noise, caused by the use of sampled data. Aliasing noise is the dominant term in the data for shorter cycle periods.
It is easy to think of market data as being a continuous waveform, but it is not. Using the closing price as representative for that bar constitutes one sample point. It doesn’t matter if you are using an average of the high and low instead of the close, you are still getting one sample per bar. Since sampled data is being used, there are some dSP aspects that must be considered. For example, the shortest analysis period that is possible (without aliasing)2 is a two-bar cycle.This is called the Nyquist frequency, 0.5 cycles per sample.A perfect two-bar sine wave cycle sampled at the peaks becomes a square wave due to sampling. However, sampling at the cycle peaks can- not be guaranteed, and the interference between the sampling frequency and the data frequency creates the aliasing noise.The noise is reduced as the data period is longer. For example, a four-bar cycle means there are four samples per cycle. Because there are more samples, the sampled data are a better replica of the sine wave component. The replica is better yet for an eight-bar data component.The improved fidelity of the sampled data means the aliasing noise is reduced at longer and longer cycle periods.The rate of reduction is 6 dB per octave. My experience is that the systemic noise rarely is more than 10 dB below the level of cyclic information, so that we create two conditions for effective smoothing of aliasing noise:
1. It is difficult to use cycle periods shorter that two octaves below the Nyquist frequency.That is, an eight-bar cycle component has a quantization noise level 12 dB below the noise level at the Nyquist frequency. longer cycle components therefore have a systemic noise level that exceeds the aliasing noise level.
2. A smoothing filter should have sufficient selectivity to reduce aliasing noise below the systemic noise level. Since aliasing noise increases at the rate of 6 dB per octave above a selected filter cutoff frequency and since the SuperSmoother attenuation rate is 12 dB per octave, the Super- Smoother filter is an effective tool to virtually eliminate aliasing noise in the output signal.
What are DSL Discontinued Signal Line?
A lot of indicators are using signal lines in order to determine the trend (or some desired state of the indicator) easier. The idea of the signal line is easy : comparing the value to it's smoothed (slightly lagging) state, the idea of current momentum/state is made.
Discontinued signal line is inheriting that simple signal line idea and it is extending it : instead of having one signal line, more lines depending on the current value of the indicator.
"Signal" line is calculated the following way :
When a certain level is crossed into the desired direction, the EMA of that value is calculated for the desired signal line
When that level is crossed into the opposite direction, the previous "signal" line value is simply "inherited" and it becomes a kind of a level
This way it becomes a combination of signal lines and levels that are trying to combine both the good from both methods.
In simple terms, DSL uses the concept of a signal line and betters it by inheriting the previous signal line's value & makes it a level.
Included:
Bar coloring
Alerts
Signals
Loxx's Expanded Source Types
STD/Clutter-Filtered, Variety FIR Filters [Loxx]STD/Clutter-Filtered, Variety FIR Filters is a FIR filter explorer. The following FIR Digital Filters are included.
Rectangular - simple moving average
Hanning
Hamming
Blackman
Blackman/Harris
Linear weighted
Triangular
There are 10s of windowing functions like the ones listed above. This indicator will be updated over time as I create more windowing functions in Pine.
Uniform/Rectangular Window
The uniform window (also called the rectangular window) is a time window with unity amplitude for all time samples and has the same effect as not applying a window.
Use this window when leakage is not a concern, such as observing an entire transient signal.
The uniform window has a rectangular shape and does not attenuate any portion of the time record. It weights all parts of the time record equally. Because the uniform window does not force the signal to appear periodic in the time record, it is generally used only with functions that are already periodic within a time record, such as transients and bursts.
The uniform window is sometimes called a transient or boxcar window.
For sine waves that are exactly periodic within a time record, using the uniform window allows you to measure the amplitude exactly (to within hardware specifications) from the Spectrum trace.
Hanning Window
The Hanning window attenuates the input signal at both ends of the time record to zero. This forces the signal to appear periodic. The Hanning window offers good frequency resolution at the expense of some amplitude accuracy.
This window is typically used for broadband signals such as random noise. This window should not be used for burst or chirp source types or other strictly periodic signals. The Hanning window is sometimes called the Hann window or random window.
Hamming Window
Computers can't do computations with an infinite number of data points, so all signals are "cut off" at either end. This causes the ripple on either side of the peak that you see. The hamming window reduces this ripple, giving you a more accurate idea of the original signal's frequency spectrum.
Blackman
The Blackman window is a taper formed by using the first three terms of a summation of cosines. It was designed to have close to the minimal leakage possible. It is close to optimal, only slightly worse than a Kaiser window.
Blackman-Harris
This is the original "Minimum 4-sample Blackman-Harris" window, as given in the classic window paper by Fredric Harris "On the Use of Windows for Harmonic Analysis with the Discrete Fourier Transform", Proceedings of the IEEE, vol 66, no. 1, pp. 51-83, January 1978. The maximum side-lobe level is -92.00974072 dB.
Linear Weighted
A Weighted Moving Average puts more weight on recent data and less on past data. This is done by multiplying each bar’s price by a weighting factor. Because of its unique calculation, WMA will follow prices more closely than a corresponding Simple Moving Average.
Triangular Weighted
Triangular windowing is known for very smooth results. The weights in the triangular moving average are adding more weight to central values of the averaged data. Hence the coefficients are specifically distributed. Some of the examples that can give a clear picture of the coefficients progression:
period 1 : 1
period 2 : 1 1
period 3 : 1 2 1
period 4 : 1 2 2 1
period 5 : 1 2 3 2 1
period 6 : 1 2 3 3 2 1
period 7 : 1 2 3 4 3 2 1
period 8 : 1 2 3 4 4 3 2 1
Read here to read about how each of these filters compare with each other: Windowing
What is a Finite Impulse Response Filter?
In signal processing, a finite impulse response (FIR) filter is a filter whose impulse response (or response to any finite length input) is of finite duration, because it settles to zero in finite time. This is in contrast to infinite impulse response (IIR) filters, which may have internal feedback and may continue to respond indefinitely (usually decaying).
The impulse response (that is, the output in response to a Kronecker delta input) of an Nth-order discrete-time FIR filter lasts exactly {\displaystyle N+1}N+1 samples (from first nonzero element through last nonzero element) before it then settles to zero.
FIR filters can be discrete-time or continuous-time, and digital or analog.
A FIR filter is (similar to, or) just a weighted moving average filter, where (unlike a typical equally weighted moving average filter) the weights of each delay tap are not constrained to be identical or even of the same sign. By changing various values in the array of weights (the impulse response, or time shifted and sampled version of the same), the frequency response of a FIR filter can be completely changed.
An FIR filter simply CONVOLVES the input time series (price data) with its IMPULSE RESPONSE. The impulse response is just a set of weights (or "coefficients") that multiply each data point. Then you just add up all the products and divide by the sum of the weights and that is it; e.g., for a 10-bar SMA you just add up 10 bars of price data (each multiplied by 1) and divide by 10. For a weighted-MA you add up the product of the price data with triangular-number weights and divide by the total weight.
Ultra Low Lag Moving Average's weights are designed to have MAXIMUM possible smoothing and MINIMUM possible lag compatible with as-flat-as-possible phase response.
What is a Clutter Filter?
For our purposes here, this is a filter that compares the slope of the trading filter output to a threshold to determine whether to shift trends. If the slope is up but the slope doesn't exceed the threshold, then the color is gray and this indicates a chop zone. If the slope is down but the slope doesn't exceed the threshold, then the color is gray and this indicates a chop zone. Alternatively if either up or down slope exceeds the threshold then the trend turns green for up and red for down. Fro demonstration purposes, an EMA is used as the moving average. This acts to reduce the noise in the signal.
Included
Bar coloring
Loxx's Expanded Source Types
Signals
Alerts
Related Indicators
STD/Clutter-Filtered, Kaiser Window FIR Digital Filter
STD- and Clutter-Filtered, Non-Lag Moving Average
Clutter-Filtered, D-Lag Reducer, Spec. Ops FIR Filter
STD-Filtered, Ultra Low Lag Moving Average
[Old] TL with K/K and CustomizationThe old version of Trap Light before the most recent update. In order to facilitate the table functionality that is currently available for Trap Light, I had to make some values that are used in calculations hard-coded. By request, I'm quickly making this version available.
Trap Light
Description
Trap Light is an indicator that uses the K value of the Stochastic RSI to indicate potential long or short entries. It was designed to operate like a traffic stop light that is displayed near the current candle so that you don't have to look away from the candlesticks while trading.
Kriss/Kross is simply a cross over/under strategy that utilizes the 10 EMA and the 50 EMA .
Signals and Available Alerts:
1. Max Sell (Red Sell Label)
When K is equal to 100.00.
This is the strongest sell signal, remember that you only need to make sure that the trend is reversing before you make an entry, because several of these signals can appear in a row if a strong trend hasn't yet reversed.
2. Sell (Red Sell Label)
When K is equal to or greater than 99.50.
A sell signal.
3. Close to Sell (Red Down Arrow)
When K is equal to or greater than 95.00.
A sell signal may be produced soon.
4. Not Ready (Yellow Circle)
When K is less than 95 and greater than 5.00.
This indicates that neither a sell nor buy signal are close to being produced.
5. Close to Buy (Green Up Arrow)
When K is equal to or less than 5.00.
A buy signal may be produced soon.
6. Buy (Green Buy Label)
When K is equal to or less than 0.50 and greater than 0.00.
A buy signal.
7. Max Buy (Green Buy Label)
When K is equal to 0.00.
Strongest buy signal, remember to make sure that the trend is reversing before making an entry.
8. Kriss (Buy)
A buy signal when the 10 EMA (Blue) crosses above the 50 EMA (Yellow). This is also illustrated by the triggering candle being colored blue.
9. Kross (Sell)
A sell signal when the 10 EMA (Blue) crosses below the 50 EMA (Yellow). This is also illustrated by the triggering candle being colored yellow.
Customization of many different options is available, and the code is open-source for your reference, etc.
Remember to do you own due diligence and feel free to leave a comment with questions, etc.
Ehlers Two-Pole Predictor [Loxx]Ehlers Two-Pole Predictor is a new indicator by John Ehlers . The translation of this indicator into PineScript™ is a collaborative effort between @cheatcountry and I.
The following is an excerpt from "PREDICTION" , by John Ehlers
Niels Bohr said “Prediction is very difficult, especially if it’s about the future.”. Actually, prediction is pretty easy in the context of technical analysis . All you have to do is to assume the market will behave in the immediate future just as it has behaved in the immediate past. In this article we will explore several different techniques that put the philosophy into practice.
LINEAR EXTRAPOLATION
Linear extrapolation takes the philosophical approach quite literally. Linear extrapolation simply takes the difference of the last two bars and adds that difference to the value of the last bar to form the prediction for the next bar. The prediction is extended further into the future by taking the last predicted value as real data and repeating the process of adding the most recent difference to it. The process can be repeated over and over to extend the prediction even further.
Linear extrapolation is an FIR filter, meaning it depends only on the data input rather than on a previously computed value. Since the output of an FIR filter depends only on delayed input data, the resulting lag is somewhat like the delay of water coming out the end of a hose after it supplied at the input. Linear extrapolation has a negative group delay at the longer cycle periods of the spectrum, which means water comes out the end of the hose before it is applied at the input. Of course the analogy breaks down, but it is fun to think of it that way. As shown in Figure 1, the actual group delay varies across the spectrum. For frequency components less than .167 (i.e. a period of 6 bars) the group delay is negative, meaning the filter is predictive. However, the filter has a positive group delay for cycle components whose periods are shorter than 6 bars.
Figure 1
Here’s the practical ramification of the group delay: Suppose we are projecting the prediction 5 bars into the future. This is fine as long as the market is continued to trend up in the same direction. But, when we get a reversal, the prediction continues upward for 5 bars after the reversal. That is, the prediction fails just when you need it the most. An interesting phenomenon is that, regardless of how far the extrapolation extends into the future, the prediction will always cross the signal at the same spot along the time axis. The result is that the prediction will have an overshoot. The amplitude of the overshoot is a function of how far the extrapolation has been carried into the future.
But the overshoot gives us an opportunity to make a useful prediction at the cyclic turning point of band limited signals (i.e. oscillators having a zero mean). If we reduce the overshoot by reducing the gain of the prediction, we then also move the crossing of the prediction and the original signal into the future. Since the group delay varies across the spectrum, the effect will be less effective for the shorter cycles in the data. Nonetheless, the technique is effective for both discretionary trading and automated trading in the majority of cases.
EXPLORING THE CODE
Before we predict, we need to create a band limited indicator from which to make the prediction. I have selected a “roofing filter” consisting of a High Pass Filter followed by a Low Pass Filter. The tunable parameter of the High Pass Filter is HPPeriod. Think of it as a “stone wall filter” where cycle period components longer than HPPeriod are completely rejected and cycle period components shorter than HPPeriod are passed without attenuation. If HPPeriod is set to be a large number (e.g. 250) the indicator will tend to look more like a trending indicator. If HPPeriod is set to be a smaller number (e.g. 20) the indicator will look more like a cycling indicator. The Low Pass Filter is a Hann Windowed FIR filter whose tunable parameter is LPPeriod. Think of it as a “stone wall filter” where cycle period components shorter than LPPeriod are completely rejected and cycle period components longer than LPPeriod are passed without attenuation. The purpose of the Low Pass filter is to smooth the signal. Thus, the combination of these two filters forms a “roofing filter”, named Filt, that passes spectrum components between LPPeriod and HPPeriod.
Since working into the future is not allowed in EasyLanguage variables, we need to convert the Filt variable to the data array XX. The data array is first filled with real data out to “Length”. I selected Length = 10 simply to have a convenient starting point for the prediction. The next block of code is the prediction into the future. It is easiest to understand if we consider the case where count = 0. Then, in English, the next value of the data array is equal to the current value of the data array plus the difference between the current value and the previous value. That makes the prediction one bar into the future. The process is repeated for each value of count until predictions up to 10 bars in the future are contained in the data array. Next, the selected prediction is converted from the data array to the variable “Prediction”. Filt is plotted in Red and Prediction is plotted in yellow.
The Predict Extrapolation indicator is shown below for the Emini S&P Futures contract using the default input parameters. Filt is plotted in red and Predict is plotted in yellow. The crossings of the Predict and Filt lines provide reliable buy and sell timing signals. There is some overshoot for the shorter cycle periods, for example in February and March 2021, but the only effect is a late timing signal. Further reducing the gain and/or reducing the BarsFwd inputs would provide better timing signals during this period.
Figure 2. Predict Extrapolation Provides Reliable Timing Signals
I have experimented with other FIR filters for predictions, but found none that had a significant advantage over linear extrapolation.
MESA
MESA is an acronym for Maximum Entropy Spectral Analysis. Conceptually, it removes spectral components until the residual is left with maximum entropy. It does this by forming an all-pole filter whose order is determined by the selected number of coefficients. It maximally addresses the data within the selected window and ignores all other data. Its resolution is determined only by the number of filter coefficients selected. Since the resulting filter is an IIR filter, a prediction can be formed simply by convolving the filter coefficients with the data. MESA is one of the few, if not the only way to practically determine the coefficients of a higher order IIR filter. Discussion of MESA is beyond the scope of this article.
TWO POLE IIR FILTER
While the coefficients of a higher order IIR filter are difficult to compute without MESA, it is a relatively simple matter to compute the coefficients of a two pole IIR filter.
(Skip this paragraph if you don’t care about DSP) We can locate the conjugate pole positions parametrically in the Z plane in polar coordinates. Let the radius be QQ and the principal angle be 360 / P2Period. The first order component is 2*QQ*Cosine(360 / P2Period) and the second order component is just QQ2. Therefore, the transfer response becomes:
H(z) = 1 / (1 - 2*QQ*Cosine(360 / P2Period)*Z-1 + QQ2*Z-2)
By mixing notation we can easily convert the transfer response to code.
Output / Input = 1 / (1 - 2*QQ*Cosine(360 / P2Period)* + QQ2* )
Output - 2*QQ*Cosine(360 / P2Period)*Output + QQ2*Output = Input
Output = Input + 2*QQ*Cosine(360 / P2Period)*Output - QQ2*Output
The Two Pole Predictor starts by computing the same “roofing filter” design as described for the Linear Extrapolation Predictor. The HPPeriod and LPPeriod inputs adjust the roofing filter to obtain the desired appearance of an indicator. Since EasyLanguage variables cannot be extended into the future, the prediction process starts by loading the XX data array with indicator data up to the value of Length. I selected Length = 10 simply to have a convenient place from which to start the prediction. The coefficients are computed parametrically from the conjugate pole positions and are normalized to their sum so the IIR filter will have unity gain at zero frequency.
The prediction is formed by convolving the IIR filter coefficients with the historical data. It is easiest to see for the case where count = 0. This is the initial prediction. In this case the new value of the XX array is formed by successively summing the product of each filter coefficient with its respective historical data sample. This process is significantly different from linear extrapolation because second order curvature is introduced into the prediction rather than being strictly linear. Further, the prediction is adaptive to market conditions because the degree of curvature depends on recent historical data. The prediction in the data array is converted to a variable by selecting the BarsFwd value. The prediction is then plotted in yellow, and is compared to the indicator plotted in red.
The Predict 2 Pole indicator is shown above being applied to the Emini S&P Futures contract for most of 2021. The default parameters for the roofing filter and predictor were used. By comparison to the Linear Extrapolation prediction of Figure 2, the Predict 2 Pole indicator has a more consistent prediction. For example, there is little or no overshoot in February or March while still giving good predictions in April and May.
Input parameters can be varied to adjust the appearance of the prediction. You will find that the indicator is relatively insensitive to the BarsFwd input. The P2Period parameter primarily controls the gain of the prediction and the QQ parameter primarily controls the amount of prediction lead during trending sections of the indicator.
TAKEAWAYS
1. A more or less universal band limited “roofing filter” indicator was used to demonstrate the predictors. The HPPeriod input parameter is used to control whether the indicator looks more like a trend indicator or more like a cycle indicator. The LPPeriod input parameter is used to control the smoothness of the indicator.
2. A linear extrapolation predictor is formed by adding the difference of the two most recent data bars to the value of the last data bar. The result is considered to be a real data point and the process is repeated to extend the prediction into the future. This is an FIR filter having a one bar negative group delay at zero frequency, but the group delay is not constant across the spectrum. This variable group delay causes the linear extrapolation prediction to be inconsistent across a range of market conditions.
3. The degree of prediction by linear extrapolation can be controlled by varying the gain of the prediction to reduce the overshoot to be about the same amplitude as the peak swing of the indicator.
4. I was unable to experimentally derive a higher order FIR filter predictor that had advantages over the simple linear extrapolation predictor.
5. A Two Pole IIR predictor can be created by parametrically locating the conjugate pole positions.
6. The Two Pole predictor is a second order filter, which allows curvature into the prediction, thus mitigating overshoot. Further, the curvature is adaptive because the prediction depends on previously computed prediction values.
7. The Two Pole predictor is more consistent over a range of market conditions.
ADDITIONS
Loxx's Expanded source types:
Library for expanded source types:
Explanation for expanded source types:
Three different signal types: 1) Prediction/Filter crosses; 2) Prediction middle crosses; and, 3) Filter middle crosses.
Bar coloring to color trend.
Signals, both Long and Short.
Alerts, both Long and Short.
Dynamic Relative StrengthMainly this indicator is a Relative strength indicator which tells us about the strength of a scrip as compared to an index . That is it outperforming the index or underperforming . Outperformance signifies Strength and Under performance signifies Weakness .Inspired from Bharat trader's Relative Strength of a stock , but changing the period for all time frames is a hassle so i have set 10 period for Monthly and 52 period for Weekly. As for monthly we need around 10 months data or we can use 12 as 1 year has 12 months but 10 works best . used 52 period for Weekly time frame because there are 52 weeks in a year. These values are by default dynamically applied to the indicator when weekly or monthly timeframes are chosen . Daily Period can be chosen as per anyone's need . As can be seen in provided screenshot , that the stock has recently started gaining strength on weekly a compared to Small cap100 index . So we can conclude that it has more strength than the overall index it is representing so more chances of outperformance will be there.
