Relative Performance Dashboard v. 2This is a smaller and cleaner version of my previous Relative Performance table. It looks at the rate of change over 1M, 3M, 6M, 1YR & YTD and displays those for the current chart's ticker vs. an index/ticker of your choosing (SPX is default). I also have some fields for the ADR of the displayed chart, how far away the displayed chart is from 52-week highs, and a single number that compares the average relative strength of the displayed chart vs. the index. The way this average calculates is customizable by the user.
I like using this table next to an Earnings/Sales/Volume table that already exists by another user in the same pane and I designed this one so it can look just like that one to give a great view of the both fundamental and technical strength of your ticker in the same pane.
Keeping fundamental data independent from performance data allows you to still be able to see performance on things without fundamental data (i.e. ETFs, Indices, Crypto, etc.) as any script that uses fundamental data will not display when a chart that does not have fundamental data is displayed.
Volatility
NET BSP NET BSP derived from Buying & Selling Pressure which is a volatility indicator that monitors average metrics of green and red candles separately.
We could navigate more confidently through market with projected market balance.
BSP allowed us to track and analyze the ongoing performance of bullish and bearish impulsive waves and their corrections.
Due to unintuitive way of measuring decline with SP going up, I decided to remake it into more intuitive version with better precision.
When we encounter the fall it's better to have declining values of tool to be able to cover it visually with ease.
One of the solutions was to create a sense of balance of Buying Pressure against Selling Pressure.
Since we are oriented by growth, it'd be more logical to summarize the market balance with BP - SP
Comparison:
When Buying and Selling Pressure are equal, NET BSP would be at 0.
NETBSP > 0 and NETBSP > NETBSP = 🟢
NETBSP > 0 and NETBSP < NETBSP = 🟡
NETBSP < 0 and NETBSP < NETBSP = 🔴
NETBSP < 0 and NETBSP > NETBSP = 🟡
Hence, we get visualized stages of uptrends and downtrends which allows to evaluate chances and estimations of upcoming counter-waves.
Also, it is worth to note that output clearly shows how one wave is derived from another in terms of sizing.
Feel free to adjust NET BSP arguments to adapt sensitivity to the timeframe you're working on.
LNL Keltner CandlesLNL Keltner Candles
This indicator plots mean reversion (reversal) arrows with custom painted candles based on the price touch or close above or below keltner channel limits (upper & lower bands). This study was created primarily for swing trading & higher time frames such as daily and weekly. Lower time frames might result in more false signals.
Mean Reversal Arrows:
1. Reversal Arrow Up - If the price drops below the lower band extremes, reversal up is the trigger for a bullish mean reversion.
2. Reversal Arrow Down - Once the price reach the higher band extremes, reversal down is the trigger for a bearish mean reversion.
The Concept of Mean Reversion:
There are just two types of moves in any market: The market is either expanding from the mean or retracing back to the mean. These reversions & epxansions are happening across all types of markets. The goal of this study is to catch the powerful mean reversion from extremes back to the mean. Once the candles light up green / red, it is time to look for the reversal (purple) arrow which triggers the mean reversion setup. Mean reversion is not about catching the next big swing turn to new highs or lows. It is all about the base hits = the mean. So the target here is always the average price. The idea here is to catch the average market ebbs & flows, not the next home run.
What Do I Mean by Mean?
Mean is usually the average price from the last 20-30 bars. Basically something like a 20 MA or Keltner Channel or Bollinger Band midline are really good visual representators of the mean (average price).
Hope it helps.
ER-Adaptive ATR Limit Channels w/ States [Loxx]As simple as it gets, channels based on high, low and ATR distances, Shows possible short term support / resistance or can be used as a take profit/stop-loss in some trading systems. It does this by comparing high/low values of price to multiplied by a multiple of ATR to determine when the trend changes. States are included to change the sensitivity to trend changes. 1 is very sensitive, 3 is least sensitive.
This uses Loxx's Expanded Source Types. You can read about them here:
What is ER Adaptive ATR?
Average True Range (ATR) is widely used indicator in many occasions for technical analysis . It is calculated as the RMA of true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range
Profitable Supertrend v0.1 - AlphaThis a script to try detect the best combination of supertrend parameters in a space of time. Sadly the script is slow. Evaluate all possibilities params is hard for a pinescript and my knowledge too. In some cases, when you want evaluate many time could be the script fails for timeout. Perhaps with time I could enhance. For this problem of speed the calculate of combinatios it's not complete: In factor use a increment of 0.2 in each param (0.1, 0.3, 0.5 ...) in period the increment for each value is 3. The range for factor it's from 3.0 to 12.0. The range of period it's from 10 to 43
My knowledge don't let me go more far. Perhaps with time I can enhance the script.
Open Interest Delta - By LeviathanThis script plots Open Interest Delta (change in OI). It also draws a heatmap and colors chart's candles to help you identify bars with large OI increase or decrease and apply Open Interest analysis concepts to your trading.
Positive OI Delta = net increase in open/unsettled positions
Negative OI Delta = net decrease in open/unsettled positions
Volume Price Balance by serkany88This idea has been in my mind for a while. We all know how important volume is to technical analysis but volume and price itself doesn't mean much when volatility and momentum of the current trend is not taken into account. With this oscillator we try to combine all these factors into one indicator and provide a simplified interpretation of this relationship with spread analysis. This indicator can be used in all timeframes but higher timeframes like 1 hour and above will provide most stable results.
How it works?
This oscillator tries to analyze volume spread along with price spread based on wyckoff methods and attains certain "strength value" for each candle and it's relationship with the volume. After this calculation preferably we remove detected rejection candles from overall calculation and draw them as plots. The multipliers of the strengths can be changed from the settings.
Green Line Above Red Line = Bullish momentum stronger
Red Line Above Green Line = Bearish momentum stronger
Top circles mean possible bullish reversal candle detected. Gray is weak, White is normal and Red top circle means strong possible reversal detected.
Bottom circles mean possible bearish reversal candle detected. Gray is weak, White is normal and Green bottom circle means strong possible reversal detected.
Let's check the example below
As you can see we see a green dot appear in a somewhat weakening bullish momentum, this can mean possible reversal can happen soon and it does.
Below is a bearish example
In this example we see a possible strong reversal signal in a increasing bullish momentum and the price reacts immediately after the candle.
We also have a table that shows the current non-smoothed result of trend strength based on calculated price-volume spread at top right of the oscillator.
RSI TREND FILTERRSI TREND Filter on Chart
RSI scaled to fit on chart instead of oscillator, Trend Analysis is easy and Hidden Divergence is revealed using this indicator. This indicator is an aim to reduce confusing RSI Situations. The Oversold and Overbought lines help to determine the price conditions so its easy to avoid Traps.
Oversold and Overbought conditions are marked on Chart to make it useful to confirm a Buy or Sell Signals.
RSI 50 level is plotted with reference to EMA50 and Oversold and Overbought Conditions are calculated accordingly.
Uptrend: RSI Cloud / Candles above RSI 50 Level
Down Trend: RSI Cloud / Candles below RSI 50 Level
Sideways : Candles in the Gray Area above and below RSI 50 Level
Default RSI (14) : is the Candlestick pattern itself
Disclaimer: Use Solely at your own Risk.
ATR PivotsThe "ATR Pivots" script is a technical analysis tool designed to help traders identify key levels of support and resistance on a chart. The indicator uses various metrics such as the Average True Range (ATR), Daily True Range ( DTR ), Daily True Range Percentage (DTR%), Average Daily Range (ADR), Previous Day High ( PDH ), and Previous Day Low ( PDL ) to provide a comprehensive picture of the volatility and movement of a security. The script also includes an EMA cloud and 200 EMA for trend identification and a 1-minute ATR scalping strategy for traders to make informed trading decisions.
ATR Detail:-
The ATR is a measure of the volatility of a security over a given period of time. It is calculated by taking the average of the true range (the difference between the high and low of a security) over a set number of periods. The user can input the number of periods (ATR length) to be used for the ATR calculation. The script also allows the user to choose whether to use the current close or not for the calculation. The script calculates various levels of support and resistance based on the relationship between the security's range ( high-low ) and the ATR. The levels are calculated by multiplying the ATR by different Fibonacci ratios (0.236, 0.382, 0.5, 0.618, 0.786, 1.000) and then adding or subtracting the result from the previous close. The script plots these levels on the chart, with the -100 level being the most significant level. The user also has an option to choose whether to plot all Fibonacci levels or not.
DTR and DTR% Detail:-
The Daily True Range Percentage (DTR%) is a metric that measures the daily volatility of a security as a percentage of its previous close. It is calculated by dividing the Daily True Range ( DTR ) by the previous close. DTR is the range between the current period's high and low and gives a measure of the volatility of the security on a daily basis. DTR% can be used as an indicator of the percentage of movement of the security on a daily basis. In this script, DTR% is used in combination with other metrics such as the Average True Range (ATR) and Fibonacci ratios to calculate key levels of support and resistance for the security. The idea behind using DTR% is that it can help traders to better understand the daily volatility of the security and make more informed trading decisions.
For example, if a security has a DTR% of 2%, it suggests that the security has a relatively low level of volatility and is less likely to experience significant price movements on a daily basis. On the other hand, if a security has a DTR% of 10%, it suggests that the security has a relatively high level of volatility and is more likely to experience significant price movements on a daily basis.
ADR:-
The script then calculates the ADR (Average Daily Range) which is the average of the daily range of the security, using the formula (Period High - Period Low) / ATR Length. This gives a measure of the average volatility of the security on a daily basis, which can be useful for determining potential levels of support and resistance .
PDH /PDL:-
The script also calculates PDH (Previous Day High) and PDL (Previous Day Low) which are the High and low of the previous day of the security. This gives a measure of the previous day's volatility and movement, which can be useful for determining potential levels of support and resistance .
EMA Cloud and 200 EMA Detail:-
The EMA cloud is a technical analysis tool that helps traders identify the trend of the market by comparing two different exponential moving averages (EMAs) of different lengths. The cloud is created by plotting the fast EMA and the slow EMA on the chart and filling the space between them. The user can input the length of the fast and slow EMA , and the script will calculate and plot these EMAs on the chart. The space between the two EMAs is then filled with a color that represents the trend, with green indicating a bullish trend and red indicating a bearish trend . Additionally, the script also plots a 200 EMA , which is a commonly used long-term trend indicator. When the fast EMA is above the slow EMA and the 200 EMA , it is considered a bullish signal, indicating an uptrend. When the fast EMA is below the slow EMA and the 200 EMA , it is considered a bearish signal, indicating a downtrend. The EMA cloud and 200 EMA can be used together to help traders identify the overall trend of the market and make more informed trading decisions.
1 Minute ATR Scalping Strategy:-
The script also includes a 1-minute ATR scalping strategy that can be used by traders looking for quick profits in the market. The strategy involves using the ATR levels calculated by the script as well as the EMA cloud and 200 EMA to identify potential buy and sell opportunities. For example, if the 1-minute ATR is above 11 in NIFTY and the EMA cloud is bullish , the strategy suggests buying the security. Similarly, if the 1-minute ATR is above 30 in BANKNIFTY and the EMA cloud is bullish , the strategy suggests buying the security.
Inside Candle:-
The Inside Candle is a price action pattern that occurs when the current candle's high and low are entirely within the range of the previous candle's high and low. This pattern indicates indecision or consolidation in the market and can be a potential sign of a trend reversal. When used in the 15-minute chart, traders can look for Inside Candle patterns that occur at key levels of support or resistance. If the Inside Candle pattern occurs at a key level and the price subsequently breaks out of the range of the Inside Candle, it can be a signal to enter a trade in the direction of the breakout. Traders can also use the Inside Candle pattern to trade in a tight range, or to reduce their exposure to a current trend.
Risk Management:-
As with any trading strategy, it is important to practice proper risk management when using the ATR Pivots script and the 1-minute ATR scalping strategy. This may include setting stop-loss orders, using appropriate position sizing, and diversifying your portfolio. It is also important to note that past performance is not indicative of future results and that the script and strategy provided are for educational purposes only.
In conclusion, the "ATR Pivots" script is a powerful tool that can help traders identify key levels of support and resistance , as well as trend direction. The additional metrics such as DTR , DTR%, ADR, PDH , and PDL provide a more comprehensive picture of the volatility and movement of the security, making it easier for traders to make better trading decisions. The inclusion of the EMA cloud and 200 EMA for trend identification, and the 1-minute ATR scalping strategy for quick profits can further enhance a trader's decision-making process. However, it is important to practice proper risk management and understand that past performance is not indicative of future results.
Special thanks to satymahajan for the idea of clubbing Average True Range with Fibonacci levels.
Fair value bands / quantifytools— Overview
Fair value bands, like other band tools, depict dynamic points in price where price behaviour is normal or abnormal, i.e. trading at/around mean (price at fair value) or deviating from mean (price outside fair value). Unlike constantly readjusting standard deviation based bands, fair value bands are designed to be smooth and constant, based on typical historical deviations. The script calculates pivots that take place above/below fair value basis and forms median deviation bands based on this information. These points are then multiplied up to 3, representing more extreme deviations.
By default, the script uses OHLC4 and SMA 20 as basis for the bands. Users can form their preferred fair value basis using following options:
Price source
- Standard OHLC values
- HL2 (High + low / 2)
- OHLC4 (Open + high + low + close / 4)
- HLC3 (High + low + close / 3)
- HLCC4 (High + low + close + close / 4)
Smoothing
- SMA
- EMA
- HMA
- RMA
- WMA
- VWMA
- Median
Once fair value basis is established, some additional customization options can be employed:
Trend mode
Direction based
Cross based
Trend modes affect fair value basis color that indicates trend direction. Direction based trend considers only the direction of the defined fair value basis, i.e. pointing up is considered an uptrend, vice versa for downtrend. Cross based trends activate when selected source (same options as price source) crosses fair value basis. These sources can be set individually for uptrend/downtrend cross conditions. By default, the script uses cross based trend mode with low and high as sources.
Cross based (downtrend not triggered) vs. direction based (downtrend triggered):
Threshold band
Threshold band is calculated using typical deviations when price is trading at fair value basis. In other words, a little bit of "wiggle room" is added around the mean based on expected deviation. This feature is useful for cross based trends, as it allows filtering insignificant crosses that are more likely just noise. By default, threshold band is calculated based on 1x median deviation from mean. Users can increase/decrease threshold band width via input menu for more/less noise filtering, e.g. 2x threshold band width would require price to cross wiggle room that is 2x wider than typical, 0x erases threshold band altogether.
Deviation bands
Width of deviation bands by default is based on 1x median deviations and can be increased/decreased in a similar manner to threshold bands.
Each combination of customization options produces varying behaviour in the bands. To measure the behaviour and finding fairest representation of fair and unfair value, some data is gathered.
— Fair value metrics
Space between each band is considered a lot, named +3, +2, +1, -1, -2, -3. For each lot, time spent and volume relative to volume moving average (SMA 20) is recorded each time price is trading in a given lot:
Depending on the asset, timeframe and chosen fair value basis, shape of the distributions vary. However, practically always time is distributed in a normal bell curve shape, being highest at lots +1 to -1, gradually decreasing the further price is from the mean. This is hardly surprising, but it allows accurately determining dynamic areas of normal and abnormal price behaviour (i.e. low risk area between +1 and -1, high risk area between +-2 to +-3). Volume on the other hand is typically distributed the other way around, being lowest at lots +1 to -1 and highest at +-2 to +-3. When time and volume are distributed like so, we can conclude that 1) price being outside fair value is a rare event and 2) the more price is outside fair value, the more anomaly behaviour in volume we tend to find.
Viewing metric calculations
Metric calculation highlights can be enabled from the input menu, resulting in a lot based coloring and visibility of each lot counter (time, cumulative relative volume and average relative volume) in data window:
— Alerts
Available alerts are the following:
Individual
- High crossing deviation band (bands +1 to +3 )
- Low crossing deviation band (bands -1 to -3 )
- Low at threshold band in an uptrend
- High at threshold band in a downtrend
- New uptrend
- New downtrend
Grouped
- New uptrend or downtrend
- Deviation band cross (+1 or -1)
- Deviation band cross (+2 or -2)
- Deviation band cross (+3 or -3)
— Practical guide
Example #1 : Risk on/risk off trend following
Ideal trend stays inside fair value and provides sufficient cool offs between the moves. When this is the case, fair value bands can be used for sensible entry/exit levels within the trend.
Example #2 : Mean reversions
When price shows exuberance into an extreme deviation, followed by a stall and signs of exhaustion (wicks), an opportunity for mean reversion emerges. The higher the deviation, the more volatility in the move, the more signalling of exhaustion, the better.
Example #3 : Tweaking bands for desired behaviour
The faster the length of fair value basis, the more momentum price needs to hit extreme deviation levels, as bands too are moving faster alongside price. Decreasing fair value basis length typically leads to more quick and aggressive deviations and less steady trends outside fair value.
ROC (Rate of Change) Refurbished▮ Introduction
The Rate of Change indicator (ROC) is a momentum oscillator.
It was first introduced in the early 1970s by the American technical analyst Welles Wilder.
It calculates the percentage change in price between periods.
ROC takes the current price and compares it to a price 'n' periods (user defined) ago.
The calculated value is then plotted and fluctuates above and below a Zero Line.
A technical analyst may use ROC for:
- trend identification;
- identifying overbought and oversold conditions.
Even though ROC is an oscillator, it is not bounded to a set range.
The reason for this is that there is no limit to how far a security can advance in price but of course there is a limit to how far it can decline.
If price goes to $0, then it obviously will not decline any further.
Because of this, ROC can sometimes appear to be unbalanced.
(TradingView)
▮ Improvements
The following features were added:
1. Eight moving averages for the indicator;
2. Dynamic Zones;
3. Rules for coloring bars/candles.
▮ Motivation
Averages have been added to improve trend identification.
For finer tuning, you can choose the type of averages.
You can hide them if you don't need them.
The Dynamic Zones has been added to make it easier to identify overbought/oversold regions.
Unlike other oscillators like the RSI for example, the ROC does not have a predetermined range of oscillations.
Therefore, a fixed line that defines an overbought/oversold range becomes unfeasible.
It is in this matter that the Dynamic Zone helps.
It dynamically adjusts as the indicator oscillates.
▮ About Dynamic Zones
'Most indicators use a fixed zone for buy and sell signals.
Here's a concept based on zones that are responsive to the past levels of the indicator.'
The concept of Dynamic Zones was described by Leo Zamansky (Ph.D.) and David Stendahl, in the magazine of Stocks & Commodities V15:7 (306-310).
Basically, a statistical calculation is made to define the extreme levels, delimiting a possible overbought/oversold region.
Given user-defined probabilities, the percentile is calculated using the method of Nearest Rank.
It is calculated by taking the difference between the data point and the number of data points below it, then dividing by the total number of data points in the set.
The result is expressed as a percentage.
This provides a measure of how a particular value compares to other values in a data set, identifying outliers or values that are significantly higher or lower than the rest of the data.
▮ Thanks and Credits
- TradingView: for ROC and Moving Averages
- allanster: for Dynamic Zones
Squeeze Range: Bollinger Bands / Keltner Channels [Whvntr]Presenting Squeeze Range: Bollinger Bands / Keltner Channels
TTMSqueeze method is a volatility and momentum indicator introduced by John Carter of Simpler Trading, which capitalizes on the tendency for price to break out strongly after consolidating in a tight trading range.
How did I make this indicator? The Bollinger Bands & Keltner Channels base scripts are from the standard indicators of their class in the Technicals section... I made this indicator first then noticed there were 3 others with a similar concept, but this differs in it's unique features and application of the TTMSqueeze strategy. This indicator plots the True Range of the Keltner Channel (Customizable in 'Bands Style" in the Inputs Menu) the instances the Bollinger Bands are within the range of the Keltner channel (the market just entered a squeeze).
Featuring: customizable Moving Averages
1. Exponential (Default for both BB & KC)
2. Simple
3. RMA (MA used in RSI )
Keltner channels have a multiplier of 2 & 3 on the Chart (3 being the outer).
How do I use this indicator? Once the teal dots are inside the solid red lines this would indicate that TTMperiod of low market volatility (the market is preparing itself for an explosive move up or down). Do some research and study how to use the TTMSqueeze method by John Carter. Disclaimer: not a guarantee of future favorable results.
DTR/ATR Scanner v1.0This indicator allows you to view DTR vs. ATR % for multiple instruments. When colors are Red the instrument is near 90% of its daily ATR.
MAD - Mean Absolute Deviation purpose :implementation of MAD Mean Absolute Deviation in pinescript
implementation by : patmaba
type : measures of spread
Mean absolute deviation
The mean absolute deviation of a dataset is the average distance between each data point and the mean. It gives us an idea about the variability in a dataset.
Here's how to calculate the median absolute deviation.
Step 1: Calculate the mean.
Step 2: Calculate how far away each data point is from the mean using positive distances. These are called absolute deviations.
Step 3: Add those deviations together.
Step 4: Divide the sum by the number of data points.
Source of MAD:
www.khanacademy.org
Formula :
MAD = ( ∑ |xi−µ| ) / n
where
xi = the value of a data point
|xi − µ| = absolute deviation
µ = mean
n = sample size
Exponential Bollinger Bands (EBB)This script is a variation of the popular Bollinger Bands indicator, which uses exponential moving averages (EMA) instead of simple moving averages (SMA) as its core calculation. The indicator is designed to provide a visual representation of volatility, with the distance between the upper and lower bands being determined by the standard deviation of the underlying data.
The script starts by defining a number of helper functions that are used to calculate the moving averages and standard deviations required for the indicator. The first helper function is sma(), which calculates the simple moving average of the input data over a specified length. This function uses linear interpolation to smooth the data when the length is not an integer. The stdev() function calculates the standard deviation of the input data using the simple moving average calculated by the sma() function.
The bes() function calculates the exponential moving average of the input data over a specified length. The estdev() function calculates the standard deviation of the input data using the exponential moving average calculated by the bes() function.
The estdev function calculates the standard deviation using an exponential moving average method, rather than the traditional simple moving average method used by the stdev function. The exponential moving average method gives more weight to recent data, which can make the estdev more responsive to recent changes in volatility. This can make it more useful in certain types of analysis, such as identifying trends in volatility. Additionally, it also uses the same EMA algorithm to calculate the average value of the data set, which can help to keep the output of the estdev and average functions consistent.
The script also defines two more helper functions, average() and standard_deviation(), which allow the user to switch between using simple moving averages (SMA) and exponential moving averages (EMA) as the basis for the indicator. These functions take three arguments, the input data, the length of the moving average, and a string that specifies whether to use SMA or EMA.
The script then defines the input parameters for the indicator. The user can choose whether to use SMA or EMA as the basis for the indicator using the select parameter. The user can also specify the length of the moving average and the multiplier for the standard deviation using the length and multiplier parameters, respectively.
Finally, the script calculates the average and standard deviation of the input data using the selected method (SMA or EMA), and plots the upper and lower bands of the indicator. The upper band is calculated as the average plus the standard deviation multiplied by the specified multiplier, while the lower band is calculated as the average minus the standard deviation multiplied by the specified multiplier.
Up Down VolatilityThis is just experimental. I wanted the flexibility in looking at volatility and this indicator gives you several ways to do so.
I haven't figured out the best way to use this yet but I suspect that as a form of entry confirmation indicator would be best.
If you find a way this works well for you please drop me a note. It would nice know someone found a way to use it successfully!
The options available are:
* Your source can be price or the ATR.
* It allows you to separate the volatility of the bearish and bullish candles and even allows you to produce differential.
* You can choose to run the result through any one of many smoothers.
With the above options you can look at:
* The normal volatility. That is not split into bearish and bullish components.
* The bearish and bullish volatility and the difference between them.
* The relative bearish and bullish volatility and the difference between them.
The "The relative bearish and bullish" is each one divided into the source before it was split into Up and Down or low/high divided by close which should make the max value roughly around 1.
The code is structured to easily drop into a bigger system so use it as a lone indicator or add the code to some bigger project you are creating. If you do integrate it into something else then send me a note as it would be nice to know it's being well used.
Enjoy and good luck!
