Simple RangeThe daily price range is a good proxy to judge an instrument’s volatility. I have combined multiple concepts in this indicator to display information regarding the daily price range & its volatility.
A trading period's range is simply the difference between its high and the low. This script shows the daily high-to-low range of the price as a column chart. It has 3 main components:
1. Narrow-range days (NR7) & Wide-range Days (WR20) - as plot columns
Original concept from Thomas Bulkowski
Modified from "NR4 & NR7 Indicator" script by theapextrader7
Modified from "WR - BC Identifier" script by wrpteam2020
Narrow range days mark price contractions that often precede price expansions. This script uses NR7 (narrow range 7) as a narrow-range day. This value can be changed by the user if, instead of an NR7, he or she wishes to use NR4 or NR21, or any other interval of his or her choice. NR7 is an indecisive trading day in which the range is narrower than any of the previous six days (a total of 7 days). This is a popular concept given by Thomas Bulkowski. A breakout is said to occur when price closes above the top or below the bottom of the NR7. Upside breakout of an NR 7 candle with high volumes indicates bullishness.
Similarly, highs & lows of wide-range bars (on big volumes) are also significant reference levels for price. Wide-range candle are identified by size of the body candle (open - close). The script compares the size of previous 20 candles to identify WR20 candles. This value can also be changed by the user.
The script shows NR7 & WR20 as orange & blue bars, respectively.
The user can also turn on the option to identify a big high-to-low range candle greater than a pre-defined threshold (default is 5%). These show up as green or red bars.
2. TTM Squeeze - as background
Original concept from John Carter's book "Mastering the Trade"
Based on "Squeeze Momentum Indicator" script by LazyBear
John Carter’s TTM Squeeze indicator looks at the relationship between Bollinger Bands and Keltner's Channels to help identify period of volatility contractions. Bollinger Bands being completely enclosed within the Keltner Channels is indicative of a very low volatility. This is a state of volatility contraction known as squeeze. Using different ATR lengths (1.0, 1.5 and 2.0) for Keltner Channels, we can differentiate between levels of squeeze (High, Mid & Low compression, respectively). Greater the compression, higher the potential for explosive moves.
In the script, the High, Mid & Low compression squeezes are depicted via the background color being red, orange, or yellow, respectively.
3. Average Daily Range - as table
Original idea by alpine_trader
Modified from "ADR% - Average Daily Range % by MikeC" script by TheScrutiniser
Average Day Range (ADR) tells how much the price moves between the high and low on a given day. This is the day Range, which is then averaged to create ADR. The script uses an average of the last 20 days to calculate the ADR. Unlike ATR (Average True Range), this excludes Gaps.
The script displays the ADR as a % value in a table.
If you want to find stocks that move a lot on an average on most days, then look for stocks that have ADR% of 5% or more.
If you prefer lower volatility stocks, focus on stocks with lower ADR% values, such as 2% or less.
How it comes together
For a bullish "momentum burst", or a velocity trade:
Select stocks with Average Day Range % (ADR) greater than 5
Identify significant reference price levels via highs & lows of WR20 bars (on big volumes)
Wait for a decent mid-to-high compression squeeze
Look for clusters of NR7 candles in the consolidation
Any breakout from this consolidation should be accompanied by more than average (preferably pocket pivot) volumes
" TABLE "に関するスクリプトを検索
Manage tradeThis indicator is intended to simulate a second entry to adjust the average price.
INPUTS:
Current price || Coins -> Current price, your first entry || Initial amount of coins
Simulate entry || Coins -> New entry, from this entry the average price will be calculated || new amount of coins
Simulate partial % || Coins -> Percentage over current price or average price || Amount of coins withdrawn
* Currency conversion
Value $ || Target price -> amount or coins, example: 25 dolar or 25 busd || Acquisition target price, returns desired coin amount, visible in table.
Table information:
simbol = current symbol
current price = First entry price
total coins = Total coins from first entry
profit or loss = self explanatory
update value = increases or decreases according to profit or loss
Partial profit = partial simulation result,
$ ⮕ ₿ = total amount of currencies in the conversion
Pro Trading Art - Top N Candle's Gainers/Losers(1-40)Top Gainer/Loser Screener.
Explanation :
With the help of this indicator you can filter top Gainer or Loser in comparison with previous selected range. Suppose you select 5 period inside input tab then this indicator will filter top gainer or losers in 5 days.
Input Parameter:
Timeframe: You can change timeframe of chart. Default timeframe is same as chart.
Period: To select range of candle. Default 5. Means how much price changed in previous 5 candle.
Top : Dropdown option to select top Gainer or Losers
Table Location: Where you want to place your table.
Watchlist Group: You can create watchlist for screener.
(Quartile Vol.; Vol. Aggregation; Range US Bars; Gaps) [Kioseff]Hello!
This indicator is a multifaceted tool that's, hopefully, useful for price action and volume analysis.
(This script makes use of the newly introduced "text_font" parameter)
With this script you'll have access to:
Range US Chart
Volume Aggregation Chart
Gaps Chart
Volume by Quartile
Consequently, you'll have access to:
First Quartile Volume Threshold
Second Quartile Volume Threshold
Third Quartile Volume Threshold
90th Percentile Volume Threshold
Fourth Quartile Volume Threshold
Q2 - Q1 Dispersion
Q3 - Q2 Dispersion
Q4 - Q3 Dispersion
Quartile Deviation
Interquartile Range
Avg. "n" bar return following "high" volume
Avg. "n" bar positive return following "high" volume
Avg. "n" bar negative following "high" volume
# of Positive Returns Following a Gap
# of Negative Returns Following a Gap
# of Gaps
# of Up Gaps
# of Down Gaps
Average # of bars to fill Up Gaps
Average # of bars to dill Down Gaps
Average Gap Up % increase
Average Gap Down % decrease
Cumulative % increase of all Up Gaps
Cumulative % decrease of all Down Gaps
Sort gaps by distance from price
Hide gaps that price substantially deviates from (gaps will reappear when price trades near the gap)
Segment Range US bars by date
Manually configure Range US price thresholds
Identify "congestion" areas with Range US bars
Range US Levels that must be exceeded for a new Range US bar to produce
Manually configure cumulative volume threshold for Volume Aggregation bars
Segment Volume Aggregation bars by date
Largest Volume Aggregation bar increases
Largest Volume Aggregation bar decreases
Calculate log returns after "high" volume sessions
Quartile Volume
The Quartile Volume portion of the script segments price/volume intervals by quartile.
The image above shows features of the indicator.
For statistics, the following metrics are recorded:
First Quartile
Second Quartile
Third Quartile
90th Percentile
Fourth Quartile
Q2 - Q1 Dispersion
Q3 - Q2 Dispersion
Q4 - Q3 Dispersion
Quartile Deviation
Interquartile Range
Color-coordinated price bars (by volume quartiles)
The percent rank for the volume of the current bar
Avg. "n" bar return following "high" volume
Avg. "n" bar positive return following "high" volume
Avg. "n" bar negative following "high" volume
The script colors bars via gradient.
By default, bars are colored lime when volume for the interval is "high" (exceeds upper quartile thresholds). The greener the bar, the higher the volume for the interval.
Bars are colored red when volume for the interval is "low" (fails to exceed lower quartile thresholds). The redder the bar, the lower the volume for the interval.
Naturally, brownish-colored bars reflect a volume interval that concluded near the median.
The image above exemplifies the process. This feature might be useful to categorize / objectively define high-volume clusters, low-volume clusters, high-volume price moves, low-volume price moves, etc.
For greater precision, you can select to color bars by volume quartile they belong to.
The image above shows color-coordinated price bars. More details shown in the image.
Additionally, you can select to plot the quartile/percentile that a price bar belongs to on the chart.
The image above shows price bars numbered by the volume quartile they belong to.
The script will distinguish successive 90th percentile violations, superimpose a linear regression channel atop the data sequence, and record pertinent statistics.
The image above shows the process.
Lastly, the user can plot an anchored VWAP using a built-in time function.
The image above shows the anchored VWAP.
Range US Chart
A Range US chart operates irrespective of time and volume - simply - bars produce after a user-defined price move is achieved/exceeded in either direction. A range us chart produces “trend candles” and “reversal candles”. A reversal candle always moves against the most immediate bar; a trend candle always moves in favor of the most immediate bar. The user defines the dollar amount price must travel up/down for a trend candle to fulfill, and for a reversal candle to fulfill.
Note: if a “down reversal” candle (red) Is produced, it’s impossible for the next candle to also be a down reversal candle - for the downside move to continue the criteria for a down trend candle must be fulfilled. Similarly, if an “up reversal” candle (green) Is produced, it’s impossible for the next candle to also be an up reversal candle - for the upside move to continue, the criteria for an uptrend trend candle must be fulfilled. Consequently, Range US bars frequently trade at the same level for extended periods. This is intentional, as this chart type is theorized to “filter noise” (whether Range US charts fulfill this theory is to your discretion).
Lastly, if an up trend candle (green) is produced, the next candle cannot be up a reversal up candle - only a trend up candle or reversal down candle can produce - vice versa for a trend down candle (the subsequent candle cannot be a reversal down candle). In this sense, an uptrend continues on successive trend up candles; a down trend continues on successive trend down candles.
The image above exemplifies Range US chart functionality.
The lower-right stats table shows the requisite price move for a "Trend" candle to produce and for a "Reversal" candle to produce.
The default settings for this chart time automatically calculate the required "Trend" candle price move and the required "Reversal" candle price move. However, both settings are configurable.
The image above shows manually configured parameters for a trend bar and reversal bar to produce. This feature allows the user to replicate the Range US chart hosted on extrinsic charting platforms.
However, please consider that this script does not use tick data; 1-minute OHLC data is used for calculations.
Consequently, configuring the trend bar and reversal bar requirement too low may return inaccurate data. For instance, if you set trend candles to form after a $1 price move then trend candles will form if price moves up $1 from a green Range US bar or down $1 from a red Range US bar. This is sufficient for lower priced assets; however, if you were trading, for instance, Bitcoin - a $1 price move can happen numerous times in one minute. This script can’t plot bars and record data until a 1-minute bar closes and a new 1-minute bar opens. Further, if Bitcoin moves up $1 twenty times and down $1 twenty times in a 1-minute bar - your Range US chart will record such variations as one price move. This data is inaccurate and likely useless.
To counter this quandary, a warning message will appear if you configure trend bar price moves or reversal bar price moves too low.
The image above shows the concealable warning message.
The image above is a flow diagram (made with shaky hands) illustrating the Range US bar formation process.
A google search will return additional information on the Range US chart type.
Volume Aggregation Bars
TradingView user and member of the TradingView Discord server @ferreirajames informed me of the Volume Aggregation chart type. The user commented in the "Suggestions" channel for the TradingView Discord server asking for the Volume Aggregation chart type. As an interim fix, I tried my hand at recreating the process, which is available in this script.
Similar to the Range US chart type, Volume Aggregation bars aren’t bound to a time-axis; the bars form after a user-defined, cumulative amount of volume is achieved or exceeded. Consequently, once the cumulative amount of volume is achieved or exceeded - a bar is produced at the corresponding price level.
Underlying theory: The chat type is conducive to identifying price levels where traders are “trapped”. Whether the process adequately distinguishes this circumstance is to your discretion.
The image above exemplifies the Volume Aggregation chart type.
Regardless of the current price, Volume Aggregation bars for after a requisite amount of volume is achieved/exceeded. Tick data isn't used; therefore, remainder values are carry over.
By default, the script automatically calculates a proportional cumulative volume total to dictate the formation of Volume Aggregation bars. However, the cumulative threshold is configurable.
The image above shows Volume Aggregation bars forming subsequent a user-defined cumulative volume total being exceeded.
Note: This chart type uses OHLC data from the timeframe of your chart. Therefore, for instance, setting the volume threshold too low will produce inaccurate, useless data.
A warning message will appear for such occurrence.
Gaps
The indicator incorporates a "Gaps" chart type.
The image above shows accompanying features.
A list of all unfilled gaps is accessible - gaps for this list are sorted by distance from current price.
Partially filled gaps are displayed in the corresponding gap box - the percentage amount the gap was filled is also displayed.
Gap statistics show:
# of Gaps
# of Up Gaps
# of Down Gaps
Average # of bars to fill Up Gaps
Average # of bars to dill Down Gaps
Average Gap Up % increase
Average Gap Down % decrease
Cumulative % increase of all Up Gaps
Cumulative % decrease of all Down Gaps
Naturally, there may be gaps formed thousands of bars ago that aren't close to price. Showing these gaps on the chart will "scrunch" the y-axis and make prices indistinguishable.
I've added a setting that allows the user to hide gaps that are "n" % away from the current price. The gap, if unfilled, will reappear when price trades within the user-defined percentage.
The image above shows an example. There's an unfilled down gap that's "hidden" because the current price is a further % away from price than what I've specified in the settings (1%). When prices trade back within 1% of the gap - it will reappear.
The image above shows the process in action. Prices moved back within 1% (can be any %) of the gap; therefore, it reappeared on the chart.
You can also set the % distance a gap must achieve for it to be considered a gap, recorded and plotted. Additionally, you can select to "visualize" gaps. Similar to the Range US chart and the Volume Aggregation chart, this setting will bars reflecting the most recent sequence of gaps - date and percentage distance of the gap are superimposed atop the bar.
Let me know if there's anything else you'd like included!
Note: The initial compilation time for this script is.... high. However, once the script's compiled, calculation load times are quick and you can sift through assets and timeframes relatively quick.
There's also a setting to "Improve Load Times" in the user-inputs table. This setting only improves the load times for post-compilation calculations and plots. The initial compilation load time is unchanged. Simply, once the indicator has "first loaded", all subsequent loads are quick.
Thank you! (:
Custom Multi-Timeframe IndicatorIt's a pretty simple example of a nice custom screener you can run for multiple timeframes. This is an RSI screener, but you can easily change the function for your own Indicator.
Screener displays:
Last value of the instrument
RSI value for up to 10 instruments / 4 timeframes.
In Parameters you can change:
4 timeframes
10 instruments
Parameters for RSI
Styling parameters for table
If the selected timeframe will be lower than the current one you will receive a warning message in a table.
Thanks to @MUQWISHI to help me code it.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
Weekly Returns with BenchmarkSome time ago I published Monthly returns table. Now It's time for weekly one.
To get it work you need a pretty big screen, but I hope it will be useful for some of you.
Features of this table includes:
Display weekly returns of your strategy, benchmark, and alpha over this benchmark.
Select benchmark to be another instrument
Select the date from which you want to compute monthly returns
Show/hide benchmark and alpha
Choose colors for gradient for gain/loss values
Use it with any type of strategy
Use it with replay
Thanks to @MUQWISHI to help me coding it.
It's not about the strategy itself but the way you display returns on your chart. So pls don't critique my choice of the strategy and its performance 🙂
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting.
This post and the script don’t provide any financial advice.
VIX Cheat SheetHello!
This indicator - "VIX Cheat Sheet" - performs several calculations for $VIX against the asset on your chart. However, using $VIX as a risk proxy or volatility metric often fails beyond large-cap U.S equities. To remedy this, the VixFix indicator is included in the script; you can select whether the script performs calculations for an asset against $VIX or against VixFix (i.e. Forex, Crypto)
Measured are: $VIX correlation to an asset's price fluctuations, the average close-to-close gain/loss subsequent a $VIX/VixFix close above the upper Bollinger Band, the average 5-session gain/loss following the same occurrence in addition to the average 10-session gain/loss, all close-to-close, 5 session, and 10-session gains/losses are stored as tooltips for labels on the chart. The current close-to-close percentage gain/loss for $VIX and VixFix are displayed on the chart.
Displayed in the example image is a box incorporating $VIX price data alongside an upper Bollinger Band and lower Bollinger Band. The data isn't cast to its own price scale but is helpful for quick interpretation of $VIX fluctuations. You can select to plot VixFix data in the box in the user inputs table.
Displayed in the second example image is a semi-transparent blue box encompassing all price moves that occurred when $VIX measured above $40 for at least ten consecutive sessions. The largest percentage close-to-close loss is displayed below the box.
Also illustrated is a red label that appears when $VIX or VixFix closes above the upper Bollinger Band. The indicator will calculate and display the performance of the asset for the subsequent 10 sessions, to which the red label will disappear and all data stored as a tooltip in the blue labels stating "VIX Closed Above Upper Band" or "VixFix Closed Above Upper Band".
To reduce chart clutter, a label and line combination marking all $VIX closes above the upper Bollinger Band was not included. Instead, bar color changes were added. When "$VIX" is selected in the user inputs table the indicator will mark all sessions in which $VIX closed above the upper band as blue, in addition to plotting $VIX price data in the dynamic black box. When "VixFix" is selected, the indicator will mark all sessions where VixFix closed above the upper band as purple; the VixFix indicator will be plotted in the black box.
Be sure to hover over labels to access tooltip information; try the indicator with bar replay!
Financial GrowthThis indicator will acquire the financial data provided by Tradview.
the data is compare between Quarter, Annual and TTM in term of percent of growth.
YoY, QoQ and CAGR is also available by this script (The minimum is 4).
in addition, ploting of data, label and table also available (you can check the mark to toggle on / off).
Data : Revenue, Net Income, EBITDA, EPS, DVPS, Free Cash Flow and Forward PE .
How to use it.
just select the financial data, period and size of data to compare.
you can check the box to toggle the plotting line, label and table.
Enjoy.
40 crypto screener [LUPOWN]// ENGLISH
This indicator shows two tables, with 10 assets each, they can be currencies, stocks or cryptos, the columns can be changed to the information you want to see, among the options are price or change (change in percentage of the candle in the temporality where you are seeing it), TL are buy or sell signals according to the Latin trading strategy (Squeeze momentum combined with ADX) buy if the momentum changes to range or rise and the ADX has a negative slope, sell if the momentum changes to range or fall and The ADX has a negative slope, the signals are not 100% effective, you must support it with price action and market speculation, directionality in the momentum, slope of the ADX, if there is divergence in the momoentum squeeze, lux something and cipher use an indicator of Lazy bear, lux something signals when two wave trends cross and the cipher signals when the wave trend crosses above or below the 0 point.
You can choose between seeing one or two tables, this so that it can be seen on small screens, there is also the option to hide the tables and show the label, which is also an alternative to see it on small screens
i got the main idea from @QuantNomad
//SPANISH
Este indicador muestra dos tablas, con 10 activos cada una, pueden ser divisas, acciones o cryptos, las columnas se pueden cambiar a la información que quieras ver, entre las opciones están precio o cambio (cambio en porcentaje de la vela en la temporalidad donde lo estes viendo), TL son señales de compra o venta según estrategia de trading latino (Squeeze momentum combinado con ADX) compra si el momentum cambia a rango o subida y el ADX tiene pendiente negativa, venta si el momentum cambia a rango o caída y el ADX tiene pendiente negativa, las señales no son 100% efectivas debes apoyarla con la acción del precio y especulación del mercado, direccionalidad en el momentum, pendiente del ADX, si hay divergencia en el squeeze momoentum, lux algo y cipher utilizan un indicador de Lazy bear, lux algo da señal cuando dos wave trend se cruzan y el cipher da señal cuando el wave trend cruza por encima o debajo del punto 0.
Puedes elegir entre ver una o dos tablas, esto para que se pueda ver en pantallas pequeñas, también esta la opción de ocultar las tablas y mostrar el label, que también es una alternativa para verlo en pantallas pequeñas
La idea principal la tome de @QuantNomad
Gann Square of 9Gann's Square's are some of the best known tools created by Gann. His most well known square was his Square of 9.
The reason for this was because of the symmetry 9 had with itself. Gann was able to balance both price and time with this symmetry.
- 9 is the last single-digit and largest number
- You can add anything to 9 and it will give you a natural number
- (9 + 3 = 12); 1 + 2 = 3... (9 + 9 = 18); 1 + 8 = 9... etc.
- Multiplying any number by 9 will have the natural number be 9
- (9 * 6 = 54); 5 + 4 = 9... (9 * 3 = 27); 2 + 7 = 9... etc.
For these reason, Gann claimed that 9 has everything within itself.
Here I have created an on-chart square of 9 including the cardinal and ordinal cross points colored. In the settings you are able to customize the starting value of the table as well as the period movement. In most cases, 81 is not high enough to be useful in charting cases, so I'd recommend printing out your own Gann Square of 9 that goes as high as you need it to go.
THIS IS NOT TRADING ADVICE ; please use your own technical analysis before making any decisions based off of public indicators. Learn more about Gann's Squares before attempting to use them as this script was not meant to give you answers, only the table.
Fast Fourier Transform (FFT) FilterDear friends!
I'm happy to present an implementation of the Fast Fourier Transform (FFT) algorithm. The script uses the FFT procedure to decompose the input time series into its cyclical constituents, in other words, its frequency components , and convert it back to the time domain with modified frequency content, that is, to filter it.
Input Description and Usage
Source and Length :
Indicates where the data comes from and the size of the lookback window used to build the dataset.
Standardize Input Dataset :
If enabled, the dataset is preprocessed by subtracting its mean and normalizing the result by the standard deviation, which is sometimes useful when analyzing seasonalities. This procedure is not recommended when using the FFT filter for smoothing (see below), as it will not preserve the average of the dataset.
Show Frequency-Domain Power Spectrum :
When enabled, the results of Fourier analysis (for the last price bar!) are plotted as a frequency-domain power spectrum , where “power” is a measure of the significance of the component in the dataset. In the spectrum, lower frequencies (longer cycles) are on the right, higher frequencies are on the left. The graph does not display the 0th component, which contains only information about the mean value. Frequency components that are allowed to pass through the filter (see below) are highlighted in magenta .
Dominant Cycles, Rows :
If this option is activated, the periods and relative powers of several dominant cyclical components that is, those that have a higher power, are listed in the table. The number of the component in the power spectrum (N) is shown in the first column. The number of rows in the table is defined by the user.
Show Inverse Fourier Transform (Filtered) :
When enabled, the reconstructed and filtered time-domain dataset (for the last price bar!) is displayed.
Apply FFT Filter in a Moving Window :
When enabled, the FFT filter with the same parameters is applied to each bar. The last data point of the reconstructed and filtered dataset is used to build a new time series. For example, by getting rid of high-frequency noise, the FFT filter can make the data smoother. By removing slowly evolving low-frequency components (including non-periodic constituents), one can reveal and analyze shorter cycles. Since filtering is done in real-time in a moving window (similar to the moving average), the modified data can potentially be used as part of a strategy and be subjected to other technical indicators.
Lowest Allowed N :
Indicates the number of the lowest frequency component used in the reconstructed time series.
Highest Allowed N :
Indicates the number of the highest frequency component used in the reconstructed time series.
Filtering Time Range block:
Specifies the time range over which real-time FFT filtering is applied. The reason for the presence of this block is that the FFT procedure is relatively computationally intensive. Therefore, the script execution may encounter the time limit imposed by TradingView when all historical bars are processed.
As always, I look forward to your feedback!
Also, leave a comment if you'd be interested in the tutorial on how to use this tool and/or in seeing the FFT filter in a strategy.
Multi ZigZagI created this as basis for my next scripts. We are just trying to plot multiple zigzags with different length basis here. Input allows you to select different Length , Width , Color and Line Style for each Zigzags.
Max_pivot_size says how many pivots each Zigzag can have. Value 100 means, each zigzag will show 99 lines joining 100 points.
Additional option ShowStatsTable allows you to print pivots in a table. Table only shows selected zigzags.
Chaikin Money Flow + MACD + ATRHere I present you on of Trade Pro's Trading Idea: Chaikin Money Flow + MACD + ATR.
This strategy is not as profitable as it can be seen in one of his videos. In the forex market, the strategy could reach a maximum of 35% profitability.
I have, as some of my followers have requested, created an overview of the current position, risk and leverage settings in the form of a table.
Furthermore, one can again swap between short and long positions.
It is now possible to select or deselect individual indicators.
I have chosen the ATR alone as a take profit stop loss, as in his strategy.
A position is only triggered as soon as all prerequisites have been fulfilled and a command is executed. This prevents false triggering by bots and repainting.
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How does the strategy work?
ENTRY
Long
The MACD indicator must be above the zero line.
Then the K line must cross the D line.
Finally, when this happens, the Money Flow Index must be above the zero line.
Short
Contrary to the premise of long positions.
EXIT
ATR Exit
The value of ATR at the time of buying is multiplied by the value entered in "Profit factor ATR" and "Stop factor ATR". As soon as the price reaches this value, it is closed.
Important
The script must be optimized for each coin or currency pair.
I will publish a guide to the strategy shortly. There I will explain how the table works and how to set the strategy correctly.
The results of the strategy are without commissions and leverage.
If you have any questions or feedback, please let me know in the comments.
MTF Technical Ratings [Anan]█ OVERVIEW
This indicator is a modified version of "Technical Ratings" v5.0 available in the public library to provide a quick overview of Technical Ratings in 6 optional timeframes.
█ FEATURES
- Multi-timeframe Table.
- Display Technical Ratings for "MAs" with a percentage.
- Display Technical Ratings for "Oscillators" with a percentage.
- Display Technical Ratings for "All" with a percentage.
- Full control of displaying any row(MAs / Oscillators / All) or any column(Multi-timeframe)
- Full control of Table position and size.
- Full control of displaying any row or column.
ORIGINAL DESCRIPTION ABOUT TECHNICAL RATING v1.0
█ OVERVIEW
This indicator calculates TradingView's well-known "Strong Buy", "Buy", "Neutral", "Sell" or "Strong Sell" states using the aggregate biases of 26 different technical indicators.
█ CALCULATIONS
The indicator calculates the aggregate value of two groups of indicators: moving averages and oscillators.
The "MAs" group is comprised of 15 different components:
• Six Simple Moving Averages of periods 10, 20, 30, 50, 100 and 200
• Six Exponential Moving Averages of the same periods
• A Hull Moving Average of period 9
• A Volume-weighed Moving Average of period 20
• Ichimoku
The "Oscillators" group includes 11 components:
• RSI
• Stochastic
• CCI
• ADX
• Awesome Oscillator
• Momentum
• MACD
• Stochastic RSI
• Wiliams %R
• Bull Bear Power
• Ultimate Oscillator
The state of each group's components is evaluated to a +1/0/-1 value corresponding to its bull/neutral/bear bias. The resulting value for each of the two groups are then averaged to produce the overall value for the indicator, which oscillates between +1 and -1. The complete conditions used in the calculations are documented in the Help Center.
Relative Growth ScreenBased on the Growth Range indicator published here:
Instead of plotting, they are printed in color coded table. Colors say whether the growth rate of these factors are relatively higher or lower.
Similar to quality screen, table positions can be customized.
If you have big enough screen, you can fit both quality and growth screens this way:
s3.tradingview.com
light_logLight Log - A Defensive Programming Library for Pine Script
Overview
The Light Log library transforms Pine Script development by introducing structured logging and defensive programming patterns typically found in enterprise languages like C#. This library addresses a fundamental challenge in Pine Script: the lack of sophisticated error handling and debugging tools that developers expect when building complex trading systems.
At its core, Light Log provides three transformative capabilities that work together to create more reliable and maintainable code. First, it wraps all native Pine Script types in error-aware containers, allowing values to carry validation state alongside their data. Second, it offers a comprehensive logging system with severity levels and conditional rendering. Third, it includes defensive programming utilities that catch errors early and make code self-documenting.
The Philosophy of Errors as Values
Traditional Pine Script error handling relies on runtime errors that halt execution, making it difficult to build resilient systems that can gracefully handle edge cases. Light Log introduces a paradigm shift by treating errors as first-class values that flow through your program alongside regular data.
When you wrap a value using Light Log's type system, you're not just storing data – you're creating a container that can carry both the value and its validation state. For example, when you call myNumber.INT() , you receive an INT object that contains both the integer value and a Log object that can describe any issues with that value. This approach, inspired by functional programming languages, allows errors to propagate through calculations without causing immediate failures.
Consider how this changes error handling in practice. Instead of a calculation failing catastrophically when it encounters invalid input, it can produce a result object that contains both the computed value (which might be na) and a detailed log explaining what went wrong. Subsequent operations can check has_error() to decide whether to proceed or handle the error condition gracefully.
The Typed Wrapper System
Light Log provides typed wrappers for every native Pine Script type: INT, FLOAT, BOOL, STRING, COLOR, LINE, LABEL, BOX, TABLE, CHART_POINT, POLYLINE, and LINEFILL. These wrappers serve multiple purposes beyond simple value storage.
Each wrapper type contains two fields: the value field v holds the actual data, while the error field e contains a Log object that tracks the value's validation state. This dual nature enables powerful programming patterns. You can perform operations on wrapped values and accumulate error information along the way, creating an audit trail of how values were processed.
The wrapper system includes convenient methods for converting between wrapped and unwrapped values. The extension methods like INT() , FLOAT() , etc., make it easy to wrap existing values, while the from_INT() , from_FLOAT() methods extract the underlying values when needed. The has_error() method provides a consistent interface for checking whether any wrapped value has encountered issues during processing.
The Log Object: Your Debugging Companion
The Log object represents the heart of Light Log's debugging capabilities. Unlike simple string concatenation for error messages, the Log object provides a structured approach to building, modifying, and rendering diagnostic information.
Each Log object carries three essential pieces of information: an error type (info, warning, error, or runtime_error), a message string that can be built incrementally, and an active flag that controls conditional rendering. This structure enables sophisticated logging patterns where you can build up detailed diagnostic information throughout your script's execution and decide later whether and how to display it.
The Log object's methods support fluent chaining, allowing you to build complex messages in a readable way. The write() and write_line() methods append text to the log, while new_line() adds formatting. The clear() method resets the log for reuse, and the rendering methods ( render_now() , render_condition() , and the general render() ) control when and how messages appear.
Defensive Programming Made Easy
Light Log's argument validation functions transform how you write defensive code. Instead of cluttering your functions with verbose validation logic, you can use concise, self-documenting calls that make your intentions clear.
The argument_error() function provides strict validation that halts execution when conditions aren't met – perfect for catching programming errors early. For less critical issues, argument_log_warning() and argument_log_error() record problems without stopping execution, while argument_log_info() provides debug visibility into your function's behavior.
These functions follow a consistent pattern: they take a condition to check, the function name, the argument name, and a descriptive message. This consistency makes error messages predictable and helpful, automatically formatting them to show exactly where problems occurred.
Building Modular, Reusable Code
Light Log encourages a modular approach to Pine Script development by providing tools that make functions more self-contained and reliable. When functions validate their inputs and return wrapped values with error information, they become true black boxes that can be safely composed into larger systems.
The void_return() function addresses Pine Script's requirement that all code paths return a value, even in error handling branches. This utility function provides a clean way to satisfy the compiler while making it clear that a particular code path should never execute.
The static log pattern, initialized with init_static_log() , enables module-wide error tracking. You can create a persistent Log object that accumulates information across multiple function calls, building a comprehensive diagnostic report that helps you understand complex behaviors in your indicators and strategies.
Real-World Applications
In practice, Light Log shines when building sophisticated trading systems. Imagine developing a complex indicator that processes multiple data streams, performs statistical calculations, and generates trading signals. With Light Log, each processing stage can validate its inputs, perform calculations, and pass along both results and diagnostic information.
For example, a moving average calculation might check that the period is positive, that sufficient data exists, and that the input series contains valid values. Instead of failing silently or throwing runtime errors, it can return a FLOAT object that contains either the calculated average or a detailed explanation of why the calculation couldn't be performed.
Strategy developers benefit even more from Light Log's capabilities. Complex entry and exit logic often involves multiple conditions that must all be satisfied. With Light Log, each condition check can contribute to a comprehensive log that explains exactly why a trade was or wasn't taken, making strategy debugging and optimization much more straightforward.
Performance Considerations
While Light Log adds a layer of abstraction over raw Pine Script values, its design minimizes performance impact. The wrapper objects are lightweight, containing only two fields. The logging operations only consume resources when actually rendered, and the conditional rendering system ensures that production code can run with logging disabled for maximum performance.
The library follows Pine Script best practices for performance, using appropriate data structures and avoiding unnecessary operations. The var keyword in init_static_log() ensures that persistent logs don't create new objects on every bar, maintaining efficiency even in real-time calculations.
Getting Started
Adopting Light Log in your Pine Script projects is straightforward. Import the library, wrap your critical values, add validation to your functions, and use Log objects to track important events. Start small by adding logging to a single function, then expand as you see the benefits of better error visibility and code organization.
Remember that Light Log is designed to grow with your needs. You can use as much or as little of its functionality as makes sense for your project. Even simple uses, like adding argument validation to key functions, can significantly improve code reliability and debugging ease.
Transform your Pine Script development experience with Light Log – because professional trading systems deserve professional development tools.
Light Log Technical Deep Dive: Advanced Patterns and Architecture
Understanding Errors as Values
The concept of "errors as values" represents a fundamental shift in how we think about error handling in Pine Script. In traditional Pine Script development, errors are events – they happen at a specific moment in time and immediately interrupt program flow. Light Log transforms errors into data – they become information that flows through your program just like any other value.
This transformation has profound implications. When errors are values, they can be stored, passed between functions, accumulated, transformed, and inspected. They become part of your program's data flow rather than exceptions to it. This approach, popularized by languages like Rust with its Result type and Haskell with its Either monad, brings functional programming's elegance to Pine Script.
Consider a practical example. Traditional Pine Script might calculate a momentum indicator like this:
momentum = close - close
If period is invalid or if there isn't enough historical data, this calculation might produce na or cause subtle bugs. With Light Log's approach:
calculate_momentum(src, period)=>
result = src.FLOAT()
if period <= 0
result.e.write("Invalid period: must be positive", true, ErrorType.error)
result.v := na
else if bar_index < period
result.e.write("Insufficient data: need " + str.tostring(period) + " bars", true, ErrorType.warning)
result.v := na
else
result.v := src - src
result.e.write("Momentum calculated successfully", false, ErrorType.info)
result
Now the function returns not just a value but a complete computational result that includes diagnostic information. Calling code can make intelligent decisions based on both the value and its associated metadata.
The Monad Pattern in Pine Script
While Pine Script lacks the type system features to implement true monads, Light Log brings monadic thinking to Pine Script development. The wrapped types (INT, FLOAT, etc.) act as computational contexts that carry both values and metadata through a series of transformations.
The key insight of monadic programming is that you can chain operations while automatically propagating context. In Light Log, this context is the error state. When you have a FLOAT that contains an error, operations on that FLOAT can check the error state and decide whether to proceed or propagate the error.
This pattern enables what functional programmers call "railway-oriented programming" – your code follows a success track when all is well but can switch to an error track when problems occur. Both tracks lead to the same destination (a result with error information), but they take different paths based on the validity of intermediate values.
Composable Error Handling
Light Log's design encourages composition – building complex functionality from simpler, well-tested components. Each component can validate its inputs, perform its calculation, and return a result with appropriate error information. Higher-level functions can then combine these results intelligently.
Consider building a complex trading signal from multiple indicators:
generate_signal(src, fast_period, slow_period, signal_period) =>
log = init_static_log(ErrorType.info)
// Calculate components with error tracking
fast_ma = calculate_ma(src, fast_period)
slow_ma = calculate_ma(src, slow_period)
// Check for errors in components
if fast_ma.has_error()
log.write_line("Fast MA error: " + fast_ma.e.message, true)
if slow_ma.has_error()
log.write_line("Slow MA error: " + slow_ma.e.message, true)
// Proceed with calculation if no errors
signal = 0.0.FLOAT()
if not (fast_ma.has_error() or slow_ma.has_error())
macd_line = fast_ma.v - slow_ma.v
signal_line = calculate_ma(macd_line, signal_period)
if signal_line.has_error()
log.write_line("Signal line error: " + signal_line.e.message, true)
signal.e := log
else
signal.v := macd_line - signal_line.v
log.write("Signal generated successfully")
else
signal.e := log
signal.v := na
signal
This composable approach makes complex calculations more reliable and easier to debug. Each component is responsible for its own validation and error reporting, and the composite function orchestrates these components while maintaining comprehensive error tracking.
The Static Log Pattern
The init_static_log() function introduces a powerful pattern for maintaining state across function calls. In Pine Script, the var keyword creates variables that persist across bars but are initialized only once. Light Log leverages this to create logging objects that can accumulate information throughout a script's execution.
This pattern is particularly valuable for debugging complex strategies where you need to understand behavior across multiple bars. You can create module-level logs that track important events:
// Module-level diagnostic log
diagnostics = init_static_log(ErrorType.info)
// Track strategy decisions across bars
check_entry_conditions() =>
diagnostics.clear() // Start fresh each bar
diagnostics.write_line("Bar " + str.tostring(bar_index) + " analysis:")
if close > sma(close, 20)
diagnostics.write_line("Price above SMA20", false)
else
diagnostics.write_line("Price below SMA20 - no entry", true, ErrorType.warning)
if volume > sma(volume, 20) * 1.5
diagnostics.write_line("Volume surge detected", false)
else
diagnostics.write_line("Normal volume", false)
// Render diagnostics based on verbosity setting
if debug_mode
diagnostics.render_now()
Advanced Validation Patterns
Light Log's argument validation functions enable sophisticated precondition checking that goes beyond simple null checks. You can implement complex validation logic while keeping your code readable:
validate_price_data(open_val, high_val, low_val, close_val) =>
argument_error(na(open_val) or na(high_val) or na(low_val) or na(close_val),
"validate_price_data", "OHLC values", "contain na values")
argument_error(high_val < low_val,
"validate_price_data", "high/low", "high is less than low")
argument_error(close_val > high_val or close_val < low_val,
"validate_price_data", "close", "is outside high/low range")
argument_log_warning(high_val == low_val,
"validate_price_data", "high/low", "are equal (no range)")
This validation function documents its requirements clearly and fails fast with helpful error messages when assumptions are violated. The mix of errors (which halt execution) and warnings (which allow continuation) provides fine-grained control over how strict your validation should be.
Performance Optimization Strategies
While Light Log adds abstraction, careful design minimizes overhead. Understanding Pine Script's execution model helps you use Light Log efficiently.
Pine Script executes once per bar, so operations that seem expensive in traditional programming might have negligible impact. However, when building real-time systems, every optimization matters. Light Log provides several patterns for efficient use:
Lazy Evaluation: Log messages are only built when they'll be rendered. Use conditional logging to avoid string concatenation in production:
if debug_mode
log.write_line("Calculated value: " + str.tostring(complex_calculation))
Selective Wrapping: Not every value needs error tracking. Wrap values at API boundaries and critical calculation points, but use raw values for simple operations:
// Wrap at boundaries
input_price = close.FLOAT()
validated_period = validate_period(input_period).INT()
// Use raw values internally
sum = 0.0
for i = 0 to validated_period.v - 1
sum += close
Error Propagation: When errors occur early, avoid expensive calculations:
process_data(input) =>
validated = validate_input(input)
if validated.has_error()
validated // Return early with error
else
// Expensive processing only if valid
perform_complex_calculation(validated)
Integration Patterns
Light Log integrates smoothly with existing Pine Script code. You can adopt it incrementally, starting with critical functions and expanding coverage as needed.
Boundary Validation: Add Light Log at the boundaries of your system – where user input enters and where final outputs are produced. This catches most errors while minimizing changes to existing code.
Progressive Enhancement: Start by adding argument validation to existing functions. Then wrap return values. Finally, add comprehensive logging. Each step improves reliability without requiring a complete rewrite.
Testing and Debugging: Use Light Log's conditional rendering to create debug modes for your scripts. Production users see clean output while developers get detailed diagnostics:
// User input for debug mode
debug = input.bool(false, "Enable debug logging")
// Conditional diagnostic output
if debug
diagnostics.render_now()
else
diagnostics.render_condition() // Only shows errors/warnings
Future-Proofing Your Code
Light Log's patterns prepare your code for Pine Script's evolution. As Pine Script adds more sophisticated features, code that uses structured error handling and defensive programming will adapt more easily than code that relies on implicit assumptions.
The type wrapper system, in particular, positions your code to take advantage of potential future features or more sophisticated type inference. By thinking in terms of wrapped values and error propagation today, you're building code that will remain maintainable and extensible tomorrow.
Light Log doesn't just make your Pine Script better today – it prepares it for the trading systems you'll need to build tomorrow.
Library "light_log"
A lightweight logging and defensive programming library for Pine Script.
Designed for modular and extensible scripts, this utility provides structured runtime validation,
conditional logging, and reusable `Log` objects for centralized error propagation.
It also introduces a typed wrapping system for all native Pine values (e.g., `INT`, `FLOAT`, `LABEL`),
allowing values to carry errors alongside data. This enables functional-style flows with built-in
validation tracking, error detection (`has_error()`), and fluent chaining.
Inspired by structured logging patterns found in systems like C#, it reduces boilerplate,
enforces argument safety, and encourages clean, maintainable code architecture.
method INT(self, error_type)
Wraps an `int` value into an `INT` struct with an optional log severity.
Namespace types: series int, simple int, input int, const int
Parameters:
self (int) : The raw `int` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: An `INT` object containing the value and a default Log instance.
method FLOAT(self, error_type)
Wraps a `float` value into a `FLOAT` struct with an optional log severity.
Namespace types: series float, simple float, input float, const float
Parameters:
self (float) : The raw `float` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `FLOAT` object containing the value and a default Log instance.
method BOOL(self, error_type)
Wraps a `bool` value into a `BOOL` struct with an optional log severity.
Namespace types: series bool, simple bool, input bool, const bool
Parameters:
self (bool) : The raw `bool` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `BOOL` object containing the value and a default Log instance.
method STRING(self, error_type)
Wraps a `string` value into a `STRING` struct with an optional log severity.
Namespace types: series string, simple string, input string, const string
Parameters:
self (string) : The raw `string` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `STRING` object containing the value and a default Log instance.
method COLOR(self, error_type)
Wraps a `color` value into a `COLOR` struct with an optional log severity.
Namespace types: series color, simple color, input color, const color
Parameters:
self (color) : The raw `color` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `COLOR` object containing the value and a default Log instance.
method LINE(self, error_type)
Wraps a `line` object into a `LINE` struct with an optional log severity.
Namespace types: series line
Parameters:
self (line) : The raw `line` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `LINE` object containing the value and a default Log instance.
method LABEL(self, error_type)
Wraps a `label` object into a `LABEL` struct with an optional log severity.
Namespace types: series label
Parameters:
self (label) : The raw `label` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `LABEL` object containing the value and a default Log instance.
method BOX(self, error_type)
Wraps a `box` object into a `BOX` struct with an optional log severity.
Namespace types: series box
Parameters:
self (box) : The raw `box` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `BOX` object containing the value and a default Log instance.
method TABLE(self, error_type)
Wraps a `table` object into a `TABLE` struct with an optional log severity.
Namespace types: series table
Parameters:
self (table) : The raw `table` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `TABLE` object containing the value and a default Log instance.
method CHART_POINT(self, error_type)
Wraps a `chart.point` value into a `CHART_POINT` struct with an optional log severity.
Namespace types: chart.point
Parameters:
self (chart.point) : The raw `chart.point` value to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `CHART_POINT` object containing the value and a default Log instance.
method POLYLINE(self, error_type)
Wraps a `polyline` object into a `POLYLINE` struct with an optional log severity.
Namespace types: series polyline, series polyline, series polyline, series polyline
Parameters:
self (polyline) : The raw `polyline` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `POLYLINE` object containing the value and a default Log instance.
method LINEFILL(self, error_type)
Wraps a `linefill` object into a `LINEFILL` struct with an optional log severity.
Namespace types: series linefill
Parameters:
self (linefill) : The raw `linefill` object to wrap.
error_type (series ErrorType) : Optional severity level to associate with the log. Default is `ErrorType.error`.
Returns: A `LINEFILL` object containing the value and a default Log instance.
method from_INT(self)
Extracts the integer value from an INT wrapper.
Namespace types: INT
Parameters:
self (INT) : The wrapped INT instance.
Returns: The underlying `int` value.
method from_FLOAT(self)
Extracts the float value from a FLOAT wrapper.
Namespace types: FLOAT
Parameters:
self (FLOAT) : The wrapped FLOAT instance.
Returns: The underlying `float` value.
method from_BOOL(self)
Extracts the boolean value from a BOOL wrapper.
Namespace types: BOOL
Parameters:
self (BOOL) : The wrapped BOOL instance.
Returns: The underlying `bool` value.
method from_STRING(self)
Extracts the string value from a STRING wrapper.
Namespace types: STRING
Parameters:
self (STRING) : The wrapped STRING instance.
Returns: The underlying `string` value.
method from_COLOR(self)
Extracts the color value from a COLOR wrapper.
Namespace types: COLOR
Parameters:
self (COLOR) : The wrapped COLOR instance.
Returns: The underlying `color` value.
method from_LINE(self)
Extracts the line object from a LINE wrapper.
Namespace types: LINE
Parameters:
self (LINE) : The wrapped LINE instance.
Returns: The underlying `line` object.
method from_LABEL(self)
Extracts the label object from a LABEL wrapper.
Namespace types: LABEL
Parameters:
self (LABEL) : The wrapped LABEL instance.
Returns: The underlying `label` object.
method from_BOX(self)
Extracts the box object from a BOX wrapper.
Namespace types: BOX
Parameters:
self (BOX) : The wrapped BOX instance.
Returns: The underlying `box` object.
method from_TABLE(self)
Extracts the table object from a TABLE wrapper.
Namespace types: TABLE
Parameters:
self (TABLE) : The wrapped TABLE instance.
Returns: The underlying `table` object.
method from_CHART_POINT(self)
Extracts the chart.point from a CHART_POINT wrapper.
Namespace types: CHART_POINT
Parameters:
self (CHART_POINT) : The wrapped CHART_POINT instance.
Returns: The underlying `chart.point` value.
method from_POLYLINE(self)
Extracts the polyline object from a POLYLINE wrapper.
Namespace types: POLYLINE
Parameters:
self (POLYLINE) : The wrapped POLYLINE instance.
Returns: The underlying `polyline` object.
method from_LINEFILL(self)
Extracts the linefill object from a LINEFILL wrapper.
Namespace types: LINEFILL
Parameters:
self (LINEFILL) : The wrapped LINEFILL instance.
Returns: The underlying `linefill` object.
method has_error(self)
Returns true if the INT wrapper has an active log entry.
Namespace types: INT
Parameters:
self (INT) : The INT instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the FLOAT wrapper has an active log entry.
Namespace types: FLOAT
Parameters:
self (FLOAT) : The FLOAT instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the BOOL wrapper has an active log entry.
Namespace types: BOOL
Parameters:
self (BOOL) : The BOOL instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the STRING wrapper has an active log entry.
Namespace types: STRING
Parameters:
self (STRING) : The STRING instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the COLOR wrapper has an active log entry.
Namespace types: COLOR
Parameters:
self (COLOR) : The COLOR instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the LINE wrapper has an active log entry.
Namespace types: LINE
Parameters:
self (LINE) : The LINE instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the LABEL wrapper has an active log entry.
Namespace types: LABEL
Parameters:
self (LABEL) : The LABEL instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the BOX wrapper has an active log entry.
Namespace types: BOX
Parameters:
self (BOX) : The BOX instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the TABLE wrapper has an active log entry.
Namespace types: TABLE
Parameters:
self (TABLE) : The TABLE instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the CHART_POINT wrapper has an active log entry.
Namespace types: CHART_POINT
Parameters:
self (CHART_POINT) : The CHART_POINT instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the POLYLINE wrapper has an active log entry.
Namespace types: POLYLINE
Parameters:
self (POLYLINE) : The POLYLINE instance to check.
Returns: True if an error or message is active in the log.
method has_error(self)
Returns true if the LINEFILL wrapper has an active log entry.
Namespace types: LINEFILL
Parameters:
self (LINEFILL) : The LINEFILL instance to check.
Returns: True if an error or message is active in the log.
void_return()
Utility function used when a return is syntactically required but functionally unnecessary.
Returns: Nothing. Function never executes its body.
argument_error(condition, function, argument, message)
Throws a runtime error when a condition is met. Used for strict argument validation.
Parameters:
condition (bool) : Boolean expression that triggers the runtime error.
function (string) : Name of the calling function (for formatting).
argument (string) : Name of the problematic argument.
message (string) : Description of the error cause.
Returns: Never returns. Halts execution if the condition is true.
argument_log_info(condition, function, argument, message)
Logs an informational message when a condition is met. Used for optional debug visibility.
Parameters:
condition (bool) : Boolean expression that triggers the log.
function (string) : Name of the calling function.
argument (string) : Argument name being referenced.
message (string) : Informational message to log.
Returns: Nothing. Logs if the condition is true.
argument_log_warning(condition, function, argument, message)
Logs a warning when a condition is met. Non-fatal but highlights potential issues.
Parameters:
condition (bool) : Boolean expression that triggers the warning.
function (string) : Name of the calling function.
argument (string) : Argument name being referenced.
message (string) : Warning message to log.
Returns: Nothing. Logs if the condition is true.
argument_log_error(condition, function, argument, message)
Logs an error message when a condition is met. Does not halt execution.
Parameters:
condition (bool) : Boolean expression that triggers the error log.
function (string) : Name of the calling function.
argument (string) : Argument name being referenced.
message (string) : Error message to log.
Returns: Nothing. Logs if the condition is true.
init_static_log(error_type, message, active)
Initializes a persistent (var) Log object. Ideal for global logging in scripts or modules.
Parameters:
error_type (series ErrorType) : Initial severity level (required).
message (string) : Optional starting message string. Default value of ("").
active (bool) : Whether the log should be flagged active on initialization. Default value of (false).
Returns: A static Log object with the given parameters.
method new_line(self)
Appends a newline character to the Log message. Useful for separating entries during chained writes.
Namespace types: Log
Parameters:
self (Log) : The Log instance to modify.
Returns: The updated Log object with a newline appended.
method write(self, message, flag_active, error_type)
Appends a message to a Log object without a newline. Updates severity and active state if specified.
Namespace types: Log
Parameters:
self (Log) : The Log instance being modified.
message (string) : The text to append to the log.
flag_active (bool) : Whether to activate the log for conditional rendering. Default value of (false).
error_type (series ErrorType) : Optional override for the severity level. Default value of (na).
Returns: The updated Log object.
method write_line(self, message, flag_active, error_type)
Appends a message to a Log object, prefixed with a newline for clarity.
Namespace types: Log
Parameters:
self (Log) : The Log instance being modified.
message (string) : The text to append to the log.
flag_active (bool) : Whether to activate the log for conditional rendering. Default value of (false).
error_type (series ErrorType) : Optional override for the severity level. Default value of (na).
Returns: The updated Log object.
method clear(self, flag_active, error_type)
Clears a Log object’s message and optionally reactivates it. Can also update the error type.
Namespace types: Log
Parameters:
self (Log) : The Log instance being cleared.
flag_active (bool) : Whether to activate the log after clearing. Default value of (false).
error_type (series ErrorType) : Optional new error type to assign. If not provided, the previous type is retained. Default value of (na).
Returns: The cleared Log object.
method render_condition(self, flag_active, error_type)
Conditionally renders the log if it is active. Allows overriding error type and controlling active state afterward.
Namespace types: Log
Parameters:
self (Log) : The Log instance to evaluate and render.
flag_active (bool) : Whether to activate the log after rendering. Default value of (false).
error_type (series ErrorType) : Optional error type override. Useful for contextual formatting just before rendering. Default value of (na).
Returns: The updated Log object.
method render_now(self, flag_active, error_type)
Immediately renders the log regardless of `active` state. Allows overriding error type and active flag.
Namespace types: Log
Parameters:
self (Log) : The Log instance to render.
flag_active (bool) : Whether to activate the log after rendering. Default value of (false).
error_type (series ErrorType) : Optional error type override. Allows dynamic severity adjustment at render time. Default value of (na).
Returns: The updated Log object.
render(self, condition, flag_active, error_type)
Renders the log conditionally or unconditionally. Allows full control over render behavior.
Parameters:
self (Log) : The Log instance to render.
condition (bool) : If true, renders only if the log is active. If false, always renders. Default value of (false).
flag_active (bool) : Whether to activate the log after rendering. Default value of (false).
error_type (series ErrorType) : Optional error type override passed to the render methods. Default value of (na).
Returns: The updated Log object.
Log
A structured object used to store and render logging messages.
Fields:
error_type (series ErrorType) : The severity level of the message (from the ErrorType enum).
message (series string) : The text of the log message.
active (series bool) : Whether the log should trigger rendering when conditionally evaluated.
INT
A wrapped integer type with attached logging for validation or tracing.
Fields:
v (series int) : The underlying `int` value.
e (Log) : Optional log object describing validation status or error context.
FLOAT
A wrapped float type with attached logging for validation or tracing.
Fields:
v (series float) : The underlying `float` value.
e (Log) : Optional log object describing validation status or error context.
BOOL
A wrapped boolean type with attached logging for validation or tracing.
Fields:
v (series bool) : The underlying `bool` value.
e (Log) : Optional log object describing validation status or error context.
STRING
A wrapped string type with attached logging for validation or tracing.
Fields:
v (series string) : The underlying `string` value.
e (Log) : Optional log object describing validation status or error context.
COLOR
A wrapped color type with attached logging for validation or tracing.
Fields:
v (series color) : The underlying `color` value.
e (Log) : Optional log object describing validation status or error context.
LINE
A wrapped line object with attached logging for validation or tracing.
Fields:
v (series line) : The underlying `line` value.
e (Log) : Optional log object describing validation status or error context.
LABEL
A wrapped label object with attached logging for validation or tracing.
Fields:
v (series label) : The underlying `label` value.
e (Log) : Optional log object describing validation status or error context.
BOX
A wrapped box object with attached logging for validation or tracing.
Fields:
v (series box) : The underlying `box` value.
e (Log) : Optional log object describing validation status or error context.
TABLE
A wrapped table object with attached logging for validation or tracing.
Fields:
v (series table) : The underlying `table` value.
e (Log) : Optional log object describing validation status or error context.
CHART_POINT
A wrapped chart point with attached logging for validation or tracing.
Fields:
v (chart.point) : The underlying `chart.point` value.
e (Log) : Optional log object describing validation status or error context.
POLYLINE
A wrapped polyline object with attached logging for validation or tracing.
Fields:
v (series polyline) : The underlying `polyline` value.
e (Log) : Optional log object describing validation status or error context.
LINEFILL
A wrapped linefill object with attached logging for validation or tracing.
Fields:
v (series linefill) : The underlying `linefill` value.
e (Log) : Optional log object describing validation status or error context.
_matrixLibrary "_matrix"
Library helps visualize matrix as array of arrays and enables users to use array methods such as push, pop, shift, unshift etc along with cleanup activities on drawing objects wherever required
method delete(mtx, rowNumber)
deletes row from a matrix
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of objects
rowNumber (int) : row index to be deleted
Returns: void
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method delete(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
remove row from a matrix and returns them to caller
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of objects
rowNumber (int) : row index to be deleted
Returns: type
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method remove(mtx, rowNumber)
Namespace types: matrix
Parameters:
mtx (matrix)
rowNumber (int)
method unshift(mtx, row, maxItems)
unshift array of lines to first row of the matrix
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines
row (array) : array of lines to be inserted in row
maxItems (simple int)
Returns: resulting matrix of type
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method unshift(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
push array of lines to end of the matrix row
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines
row (array) : array of lines to be inserted in row
maxItems (simple int)
Returns: resulting matrix of lines
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method push(mtx, row, maxItems)
Namespace types: matrix
Parameters:
mtx (matrix)
row (array)
maxItems (simple int)
method shift(mtx)
shift removes first row from matrix of lines
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines from which the shift operation need to be performed
Returns: void
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method shift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
rshift removes first row from matrix of lines and returns them as array
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines from which the rshift operation need to be performed
Returns: type
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rshift(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
pop removes last row from matrix of lines
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines from which the pop operation need to be performed
Returns: void
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method pop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
rpop removes last row from matrix of lines and reutnrs the array to caller
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines from which the rpop operation need to be performed
Returns: void
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method rpop(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
clear clears the matrix
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines which needs to be cleared
Returns: void
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method clear(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
clear clears the matrix but retains the drawing objects
Namespace types: matrix
Parameters:
mtx (matrix) : matrix of lines which needs to be cleared
Returns: void
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
method flush(mtx)
Namespace types: matrix
Parameters:
mtx (matrix)
PSv5 Color Magic and Chart Theme SimulatorKEEP YOUR COINS FOLKS! I DON'T NEED THEM, DON'T WANT THEM. Many other talented authors on TV deserve them.
INTRODUCTION:
This is my "PSv5 Color Magic and Chart Theme Simulator" displayed using Pine Script version 5.0. The purpose of this PSv5 colorcator is to show vivid colors that are most suitable in my opinion for modifying or developing Pine scripts. Whether you are new to Pine or an experienced Pine poet, this should aid you in developing indicators with stunning color from the provided color list that is easily copied and pasted into any novel script you should possess. Whichever colors you choose, and how, is up to your imagination's capacity.
COMMENTARY:
I have a thesis. Pine essentially is a gigantor calculator with a lot of programmable bells and whistles to perform intense analytics. Zillions of numbers per day are blended up into another cornucopia of numbers to analyze. The thing is, ALL of those numbers are moot unless we can informatively portray them in various colorized forms with unique methods to point out significant numeric events. By graphically displaying them with specific modes of operation, only then do these numbers truly make any sense to us and become quantitatively beneficial.
I have to admit... I hate numbers. I never really liked them, even before I knew what an ema() was. Some days I almost can't stand them, and on occasion I feel they deserve to be flushed down the toilet at times. However, I'm a stickler for a proper gauge of measurements. Numbers are a mental burden, but they do have "purpose and meaning". That's where COLOR comes in! By applying color in specific ways in varying dynamic forms, we can generate smarter visual aids from these numerics. Numbers can be "transformed" into something colorful it wasn't before, into a tool, like a hammer. But we don't need a hammer, we need an impressive jack hammer for BIG problem solving that we could never achieve in the not to distant past.
As time goes on, we analytically measure more, and more, and more each year. It's necessary to our continual evolution. That's one significant difference between us and cave men, and the pertinent reason why we are quickly evolving as a species, while animals haven't. Humankind is gifted to enumerate very well AND blessed to see in color. We use it for innumerable things in the technological present for purpose and pleasure. Day in and day out, we take color for granted, because it's every where we can look. The fact is, color is the most important apparatus in humankind's existence EVER. We wouldn't have survived this far without it.
By utilizing color to it's grand potential, greater advancements can be attained while simultaneously being enjoyed visually. Once color is transformed from it's numeric origins into applicable tools, we can enjoy the style, elegance, and QUALITATIVE nature of the indication that can be forged. Quantities can't reveal all. Color on the other hand has a handy "quality" factor to it, often revealing things we can't ordinarily recognize. When high quality tools provide us with obtained goals, that's when we will realize how magical color truly is, always has been, and shall always be.
The future emerging economies and future financial vessels of people around the globe are going to be dependent on the secured construction of intelligent applications with a rock solid color foundation, not just math alone. I have no doubt about that. I can envision that with my eyes closed. To make an informed choice, it should be charted or graphed somehow prior to a final executive decision to trade. Going back to abysmal black and white with double decimal points placed next to cartoons within extinction doomed newspapers is not a viable option any more.
OBSERVATIONS AND UTILITY:
One thing you will notice is the code is very dense. Looks almost hideous right? Well, the variable naming is lengthy, but it's purpose is to be self explanatory, even for those who don't know how to program, YET. I'm simply not a notation enthusiast. My main intention was to provide clearly identifiable variables from their origin of assignment to their intended destination of use, clearly visible for anyone visiting. The empowerment of well versed words that are easier to understand, is a close rival to the prominent influence color has.
Secondly, I'm displaying hline() and label.new() as prime candidates to exemplify by demonstration how the "Power of Color" can be embraced with the "Power of Pine". Color in Pine has been extensively upgraded to serve novel purposes to accomplish next generation indicators that do and WILL come to exist. New functions included with PSv5 are color.rgb(), color.from_gradient(), color.r(), color.g(), color.b(), and color.t() to accompany color.new() in our mutual TV adventures. Keep in mind, the extreme agility of color also extends to line.new(), the "entirely new" linefill.new(), table.new(), bgcolor() and every other function that may utilize color.
There's a wide range of adjustability in Settings to make selections to see how they perform on different backgrounds, with their size and form. As you curiously toy with those, you're going to notice how some jump out like laser beams while others don't. Things that aren't visually appealing, still have very viable purposes, even if they don't stand out in the crowd. Often, that's preferable. The important thing is that when pertinent information relative to indication is crucial, you can program it with distinction from an assortment of a potential 1.67 million colors that can be created in Pine. "These" are my chosen favorite few, and I hope you adopt them.
PURPOSES:
For those of you who are new to Pine Script, this also may help you understand color hex/rgb and how it is utilized in Pine in a most effective manner. The most skilled of programmers can garner perks as well. There is countless examples of code diversity present here that are applicable in other scripts with adequate mutation. Any member has the freedom use any of this code in this script any way they see fit. It's specifically intended for all. There is absolutely no need for accreditation for any of this code reuse ever, in the present case. Don't worry about, I'm not.
The color_tostring() will be most valuable in troubleshooting color when using color.rgb() and becoming adept with it. I'm not going to be able to use color.rgb() without it. Chameleon indicators of the polychromatic variety are most likely going to be fine tuned with color_tostring() divulging it's results to label.new() or even table.new() maybe. One the best virtues of this script in chart, is when you hover over the generated labels, there's a hidden gift for those who truly wish to learn the intricate mechanics of diverse color in Pine. Settings has informative tooltips too.
AFTERTHOUGHTS:
Colors are most vibrant on the "Black Chart" which is the default, but it doesn't currently exist as a chart theme. With the extreme luminous intensity of LCDs in millicandela( mcd ), you may notice "Light" charts may saturate the colors making charts challenging to analyze. Because of this, I personally use "Dark Charts" and design my indicators specifically for these. I hope this provides inspiration for the future developers who are contemplating the creation of next generation indicators and how color may enhance their usefulness.
When available time provides itself, I will consider your inquiries, thoughts, and concepts presented below in the comments section, should you have any questions or comments regarding this indicator. When my indicators achieve more prevalent use by TV members , I may implement more ideas when they present themselves as worthy additions. Have a profitable future everyone!
NAS100 Component Sentiment Scanner# NAS100 Component Sentiment Scanner
## 🎯 Overview
The NAS100 Component Sentiment Scanner analyzes the top-weighted stocks in the NASDAQ-100 index to provide real-time bullish/bearish sentiment signals that can help predict NAS100 price movements. This indicator combines multiple technical analysis methods to give traders a comprehensive view of underlying market sentiment.
## 📊 How It Works
The indicator calculates sentiment scores for major NASDAQ-100 components (AAPL, MSFT, NVDA, GOOGL, AMZN, META, TSLA, AVGO, COST, NFLX) using:
- **RSI Analysis**: Identifies overbought/oversold conditions
- **Moving Average Trends**: Compares fast vs slow MA positioning
- **Volume Confirmation**: Validates moves with volume thresholds
- **Price Momentum**: Analyzes recent price direction
- **Market Cap Weighting**: Uses actual NASDAQ-100 weightings for accuracy
## 🚀 Key Features
### Real-Time Sentiment Analysis
- Weighted composite score based on individual stock analysis
- Color-coded sentiment line (Green = Bullish, Red = Bearish)
- Dynamic background coloring for strong signals
### Interactive Data Table
- Shows individual stock scores and signals
- Bullish/Bearish stock count summary
- Customizable position and size
### Smart Signal System
- **Bullish Signals**: Green triangle up when sentiment crosses threshold
- **Bearish Signals**: Red triangle down when sentiment falls below threshold
- **Alert Conditions**: Automatic notifications for signal changes
## ⚙️ Customization Options
### Technical Analysis Settings
- **RSI Period**: Adjust lookback period (default: 14)
- **RSI Levels**: Set overbought/oversold thresholds
- **Moving Averages**: Configure fast/slow MA periods
- **Volume Threshold**: Set volume confirmation multiplier
### Signal Thresholds
- **Bullish/Bearish Levels**: Customize trigger points
- **Strong Signal Levels**: Set extreme sentiment thresholds
- Fine-tune sensitivity to market conditions
### Display Options
- **Toggle Table**: Show/hide sentiment data table
- **Table Position**: 6 position options (Top/Bottom/Middle + Left/Right)
- **Table Size**: Choose from Tiny, Small, Normal, or Large
- **Background Colors**: Enable/disable signal backgrounds
- **Signal Arrows**: Show/hide buy/sell indicators
### Stock Selection
- **Individual Control**: Enable/disable any of the 10 major stocks
- **Dynamic Weighting**: Automatically adjusts calculations based on selected stocks
- **Flexible Analysis**: Focus on specific sectors or market leaders
## 📈 How to Use
### 1. Basic Setup
1. Add the indicator to your NAS100 chart
2. Default settings work well for most traders
3. Observe the sentiment line and signals
### 2. Signal Interpretation
- **Score > 30**: Bullish bias for NAS100
- **Score > 50**: Strong bullish signal
- **Score -30 to 30**: Neutral/consolidation
- **Score < -30**: Bearish bias for NAS100
- **Score < -50**: Strong bearish signal
### 3. Trading Strategies
**Trend Following:**
- Buy NAS100 when bullish signals appear
- Sell/short when bearish signals trigger
- Use background colors for quick visual confirmation
**Divergence Trading:**
- Watch for sentiment/price divergences
- Strong sentiment with weak NAS100 price = potential breakout
- Weak sentiment with strong NAS100 price = potential reversal
**Consensus Trading:**
- Monitor bullish/bearish stock counts in table
- 8+ stocks aligned = strong directional bias
- Mixed signals = wait for clearer consensus
### 4. Advanced Usage
- Combine with your existing NAS100 trading strategy
- Use multiple timeframes for confirmation
- Adjust thresholds based on market volatility
- Focus on specific stocks by disabling others
## 🔔 Alert Setup
The indicator includes built-in alert conditions:
1. Go to TradingView Alerts
2. Select "NAS100 Component Sentiment Scanner"
3. Choose from available alert types:
- NAS100 Bullish Signal
- NAS100 Bearish Signal
- Strong Bullish Consensus
- Strong Bearish Consensus
## 💡 Pro Tips
### Optimization
- **High Volatility**: Increase signal thresholds (±40, ±60)
- **Low Volatility**: Decrease thresholds (±20, ±40)
- **Day Trading**: Use smaller table, focus on real-time signals
- **Swing Trading**: Enable background colors, larger thresholds
### Best Practices
- Don't use as a standalone system - combine with price action
- Check individual stock table for context
- Monitor during market open for most reliable signals
- Consider earnings seasons for individual stock impacts
### Market Conditions
- **Trending Markets**: Higher accuracy, use with trend following
- **Ranging Markets**: Watch for false signals, increase thresholds
- **News Events**: Individual stock news can skew sentiment temporarily
## 🎨 Visual Guide
- **Green Line Above Zero**: Bullish sentiment building
- **Red Line Below Zero**: Bearish sentiment building
- **Background Color Changes**: Strong signal confirmation
- **Triangle Arrows**: Entry/exit signal points
- **Table Colors**: Quick sentiment overview
## ⚠️ Important Notes
- This indicator analyzes component stocks, not NAS100 directly
- Market cap weightings approximate real NASDAQ-100 weightings
- Sentiment can change rapidly during volatile periods
- Always use proper risk management
- Combine with other technical analysis tools
## 🔧 Troubleshooting
- **No signals**: Check if thresholds are too extreme
- **Too many signals**: Increase threshold sensitivity
- **Table not showing**: Ensure "Show Sentiment Table" is enabled
- **Missing stocks**: Verify individual stock toggles in settings
---
**Suitable for**: Day traders, swing traders, NAS100 specialists, index traders
**Best Timeframes**: 5min, 15min, 1H, 4H
**Market Sessions**: US market hours for highest accuracy
Portfolio Tracker ARJO (V-01)Portfolio Tracker ARJO (V-01)
This indicator is a user-friendly portfolio tracking tool designed for TradingView charts. It overlays a customizable table on your chart to monitor up to 15 stocks or symbols in your portfolio. It calculates real-time metrics like current market price (CMP), gains/losses, and stoploss breaches, helping you stay on top of your investments without switching between multiple charts. The table uses color-coding for quick visual insights: green for profits, red for losses, and highlights breached stoplosses in red for alerts. It also shows portfolio-wide totals for overall performance.
Key Features
Supports up to 15 Symbols: Enter stock tickers (e.g., NSE:RELIANCE or BSE:TCS) with details like buy price, date, units, and stoploss.
Symbol: The stock ticker and description.
Buy Date: When you purchased it.
Units: Number of shares/units held.
Buy Price: Your entry price.
Stop Loss: Your set stoploss level (highlighted in red if breached by CMP).
CMP: Current market price (fetched from the chart's timeframe).
% Gain/Loss: Percentage change from buy price (color-coded: green for positive, red for negative).
Gain/Loss: Total monetary gain/loss based on units.
Optional Timeframe Columns: Toggle to show % change over 1 Week (1W), 1 Month (1M), 3 Months (3M), and 6 Months (6M) for historical performance.
Portfolio Summary: At the top of the table, see total % gain/loss and absolute gain/loss for your entire portfolio.
Visual Customizations: Adjust table position (e.g., Top Right), size, colors for positive/negative values, and intensity cutoff for gradients.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
Benchmark Index-Based Header: The title row's background color reflects NIFTY's weekly trend (green if above 10-week SMA, red if below) for market context.
How to Use It: Step-by-Step Guide
Add the Indicator to Your Chart: Search for "Portfolio Tracker ARJO (V-01)" in TradingView's indicator library and add it to any chart (preferably Daily timeframe for accuracy).
Input Your Portfolio Symbols:
Open the indicator settings (gear icon).
In the "Symbol 1" to "Symbol 15" groups, fill in:
Symbol: Enter the ticker (e.g., NSE:INFY).
Year/Month/Day: Select your buy date (e.g., 2024-07-01).
Buy Price: Your purchase price per unit.
Stoploss: Your exit price if things go south.
Units: How many shares you own.
Only fill what you need—leave extras blank. The table auto-adjusts to show only entered symbols.
Customize the Table (Optional):
In "Table settings":
Choose position (e.g., Top Right) and size (% of chart).
Toggle "Show Timeframe Columns" to add 1W/1M/3M/6M performance.
In "Color settings":
Pick colors for positive (green) and negative (red) cells.
Set "Color intensity cutoff (%)" to control how strong the colors get (e.g., 10% means changes above 10% max out the color).
Interpret the Table on Your Chart:
The table appears overlaid—scan rows for each symbol's stats.
Look at colors: Greener = better gains; redder = bigger losses.
Check CMP cell: Red means stoploss breached—consider selling!
Portfolio Gain/Loss at the top gives a quick overall health check.
For Best Results:
Use on a Daily chart to avoid CMP errors (the script will warn if on Weekly/Monthly).
Refresh the chart or wait for a new bar if data doesn't update immediately.
For Indian stocks, prefix with NSE: or BSE: (e.g., BSE:RELIANCE).
This is for tracking only—not trading signals. Combine with your strategy.
If no symbols show, ensure inputs are valid (e.g., buy price > 0, valid date).
Finally, this tool makes it quite easy for beginners to track their portfolios, while also giving advanced traders powerful and customizable insights. I'd love to hear your feedback—happy trading!
Multi SMA AnalyzerMulti SMA Analyzer with Custom SMA Table & Advanced Session Logic
A feature-rich SMA analysis suite for traders, offering up to 7 configurable SMAs, in-depth trend detection, real-time table, and true session-aware calculations.
Ideal for those who want to combine intraday, swing, and higher-timeframe trend analysis with maximum chart flexibility.
Key Features
📊 Multi-SMA Overlay
- 7 SMAs (default: 5, 20, 50, 100, 200, 21, 34)—individually configurable (period, source, color, line style)
- Show/hide each SMA, custom line style (solid, stepline, circles), and color logic
- Dynamic color: full opacity above SMA, reduced when below
⏰ Session-Aware SMAs
- Each SMA can be calculated using only user-defined session hours/days/timezone
- “Ignore extended hours” option for accurate intraday trend
📋 Smart Data Table
- Live SMA values, % distance from price, and directional arrows (↑/↓/→)
- Bull/Bear/Sideways trend classification
- Custom table position, size, colors, transparency
- Table can run on chart or custom (higher) timeframe for multi-TF analysis
🎯 Golden/Death Cross Detection
- Flexible crossover engine: select any two from (5, 10, 20, 50, 100, 200) for fast/slow SMA cross signals
- Plots icons (★ Golden, 💀 Death), optional crossover labels with custom size/colors
🏷️ SMA Labels
- Optional on-chart SMA period labels
- Custom placement (above/below/on line), size, color, offset
🚨 Signal & Trend Engine
- Bull/Bear/Sideways logic: price vs. multiple SMAs (not just one pair)
- Volume spike detection (2x 20-period SMA)
- Bullish engulfing candlestick detection
- All signals can use chart or custom table timeframe
🎨 Visual Customization
- Dynamic background color (Bull: green, Bear: red, Neutral: gray)
- Every visual aspect is customizable: label/table colors, transparency, size, position
🔔 Built-in Alerts
- Crossovers (SMA20/50, Golden/Death)
- Bull trend, volume spikes, engulfing pattern—all alert-ready
How It Works
- Session Filtering:
- SMAs can be set to count only bars from your chosen market session, for true intraday/trading-hour signals
Dynamic Table & Signals:
- Table and all signal logic run on your selected chart or custom timeframe
Flexible Crossover:
- Choose any pair (5, 10, 20, 50, 100, 200) for cross detection—SMA 10 is available for crossover even if not shown as an SMA line
Everything is modular:
- Toggle features, set visuals, and alerts to your workflow
🚨 How to Use Alerts
- All key signals (crossovers, trend shifts, volume spikes, engulfing patterns) are available as alert conditions.
To enable:
- Click the “Alerts” (clock) icon at the top of TradingView.
- Select your desired signal (e.g., “Golden Cross”) from the condition dropdown.
- Set your alert preferences and create the alert.
- Now, you’ll get notified automatically whenever a signal occurs!
Perfect For
- Multi-timeframe and swing traders seeking higher timeframe SMA confirmation
- Intraday traders who want to ignore pre/post-market data
- Anyone wanting a modern, powerful, fully customizable multi-SMA overlay
// P.S: Experiment with Golden Cross where Fast SMA is 5 and Slow SMA is 20.
// Set custom timeframe for 4 hr while monitoring your chart on 15 min time frame.
// Enable Background Color and Use Table Timeframe for Background.
// Uncheck Pine labels in Style tab.
Clean, open-source, and loaded with pro features—enjoy!
Like, share, and let me know if you'd like any new features added.
RifleShooterLibLibrary "RifleShooterLib"
Provides a collection of helper functions in support of the Rifle Shooter Indicators.
Functions support the key components of the Rifle Trade algorithm including
* measuring momentum
* identifying paraboloic price action (to disable the algorthim during such time)
* determine the lookback criteria of X point movement in last N minutes
* processing and navigating between the 23/43/73 levels
* maintaining a status table of algorithm progress
toStrRnd(val, digits)
Parameters:
val (float)
digits (int)
_isValidTimeRange(startTimeInput, endTimeInput)
Parameters:
startTimeInput (string)
endTimeInput (string)
_normalize(_src, _min, _max)
_normalize Normalizes series with unknown min/max using historical min/max.
Parameters:
_src (float) : Source series to normalize
_min (float) : minimum value of the rescaled series
_max (float) : maximum value of the rescaled series
Returns: The series scaled with values between min and max
arrayToSeries(arrayInput)
arrayToSeries Return an array from the provided series.
Parameters:
arrayInput (array) : Source array to convert to a series
Returns: The array as a series datatype
f_parabolicFiltering(_activeCount, long, shooterRsi, shooterRsiLongThreshold, shooterRsiShortThreshold, fiveMinuteRsi, fiveMinRsiLongThreshold, fiveMinRsiShortThreshold, shooterRsiRoc, shooterRsiRocLongThreshold, shooterRsiRocShortThreshold, quickChangeLookbackBars, quckChangeThreshold, curBarChangeThreshold, changeFromPrevBarThreshold, maxBarsToholdParabolicMoveActive, generateLabels)
f_parabolicFiltering Return true when price action indicates a parabolic active movement based on the provided inputs and thresholds.
Parameters:
_activeCount (int)
long (bool)
shooterRsi (float)
shooterRsiLongThreshold (float)
shooterRsiShortThreshold (float)
fiveMinuteRsi (float)
fiveMinRsiLongThreshold (float)
fiveMinRsiShortThreshold (float)
shooterRsiRoc (float)
shooterRsiRocLongThreshold (float)
shooterRsiRocShortThreshold (float)
quickChangeLookbackBars (int)
quckChangeThreshold (int)
curBarChangeThreshold (int)
changeFromPrevBarThreshold (int)
maxBarsToholdParabolicMoveActive (int)
generateLabels (bool)
rsiValid(rsi, buyThreshold, sellThreshold)
rsiValid Returns true if the provided RSI value is withing the associated threshold. For the unused threshold set it to na
Parameters:
rsi (float)
buyThreshold (float)
sellThreshold (float)
squezeBands(source, length)
squezeBands Returns the squeeze bands momentum color of current source series input
Parameters:
source (float)
length (int)
f_momentumOscilator(source, length, transperency)
f_momentumOscilator Returns the squeeze pro momentum value and bar color states of the series input
Parameters:
source (float)
length (int)
transperency (int)
f_getLookbackExtreme(lowSeries, highSeries, lbBars, long)
f_getLookbackExtreme Return the highest high or lowest low over the look back window
Parameters:
lowSeries (float)
highSeries (float)
lbBars (int)
long (bool)
f_getInitialMoveTarget(lbExtreme, priveMoveOffset, long)
f_getInitialMoveTarget Return the point delta required to achieve an initial rifle move (X points over Y lookback)
Parameters:
lbExtreme (float)
priveMoveOffset (int)
long (bool)
isSymbolSupported(sym)
isSymbolSupported Return true if provided symbol is one of the supported DOW Rifle Indicator symbols
Parameters:
sym (string)
getBasePrice(price)
getBasePrice Returns integer portion of provided float
Parameters:
price (float)
getLastTwoDigitsOfPrice(price)
getBasePrice Returns last two integer numerals of provided float value
Parameters:
price (float)
getNextLevelDown(price, lowestLevel, middleLevel, highestLevel)
getNextLevelDown Returns the next level above the provided price value
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
getNextLevelUp(price, lowestLevel, middleLevel, highestLevel)
getNextLevelUp Returns the next level below the provided price value
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
isALevel(price, lowestLevel, middleLevel, highestLevel)
isALevel Returns true if the provided price is onve of the specified levels
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
getClosestLevel(price, lowestLevel, middleLevel, highestLevel)
getClosestLevel Returns the level closest to the price value provided
Parameters:
price (float)
lowestLevel (float)
middleLevel (float)
highestLevel (float)
f_fillSetupTableCell(_table, _col, _row, _text, _bgcolor, _txtcolor, _text_size)
f_fillSetupTableCell Helper function to fill a setup table celll
Parameters:
_table (table)
_col (int)
_row (int)
_text (string)
_bgcolor (color)
_txtcolor (color)
_text_size (string)
f_fillSetupTableRow(_table, _row, _col0Str, _col1Str, _col2Str, _bgcolor, _textColor, _textSize)
f_fillSetupTableRow Helper function to fill a setup table row
Parameters:
_table (table)
_row (int)
_col0Str (string)
_col1Str (string)
_col2Str (string)
_bgcolor (color)
_textColor (color)
_textSize (string)
f_addBlankRow(_table, _row)
f_addBlankRow Helper function to fill a setup table row with empty values
Parameters:
_table (table)
_row (int)
f_updateVersionTable(versionTable, versionStr, versionDateStr)
f_updateVersionTable Helper function to fill the version table with provided values
Parameters:
versionTable (table)
versionStr (string)
versionDateStr (string)
f_updateSetupTable(_table, parabolicMoveActive, initialMoveTargetOffset, initialMoveAchieved, shooterRsi, shooterRsiValid, rsiRocEnterThreshold, shooterRsiRoc, fiveMinuteRsi, fiveMinuteRsiValid, requireValid5MinuteRsiForEntry, stallLevelOffset, stallLevelExceeded, stallTargetOffset, recoverStallLevelValid, curBarChangeValid, volumeRoc, volumeRocThreshold, enableVolumeRocForTrigger, tradeActive, entryPrice, curCloseOffset, curSymCashDelta, djiCashDelta, showDjiDelta, longIndicator, fontSize)
f_updateSetupTable Manages writing current data to the setup table
Parameters:
_table (table)
parabolicMoveActive (bool)
initialMoveTargetOffset (float)
initialMoveAchieved (bool)
shooterRsi (float)
shooterRsiValid (bool)
rsiRocEnterThreshold (float)
shooterRsiRoc (float)
fiveMinuteRsi (float)
fiveMinuteRsiValid (bool)
requireValid5MinuteRsiForEntry (bool)
stallLevelOffset (float)
stallLevelExceeded (bool)
stallTargetOffset (float)
recoverStallLevelValid (bool)
curBarChangeValid (bool)
volumeRoc (float)
volumeRocThreshold (float)
enableVolumeRocForTrigger (bool)
tradeActive (bool)
entryPrice (float)
curCloseOffset (float)
curSymCashDelta (float)
djiCashDelta (float)
showDjiDelta (bool)
longIndicator (bool)
fontSize (string)
FA Dashboard: Valuation, Profitability & SolvencyFundamental Analysis Dashboard: A Multi-Dimensional View of Company Quality
This script presents a structured and customizable dashboard for evaluating a company’s fundamentals across three key dimensions: Valuation, Profitability, and Solvency & Liquidity.
Unlike basic fundamental overlays, this dashboard consolidates multiple financial indicators into visual tables that update dynamically and are grouped by category. Each ratio is compared against configurable thresholds, helping traders quickly assess whether a company meets certain value investing criteria. The tables use color-coded checkmarks and fail marks (✔️ / ❌) to visually signal pass/fail evaluations.
▶️ Key Features
Valuation Ratios:
Earnings Yield: EBIT / EV
EV / EBIT and EV / FCF: Enterprise value metrics for profitability
Price-to-Book, Free Cash Flow Yield, PEG Ratio
Profitability Ratios:
Return on Invested Capital (ROIC), ROE, Operating, Net & Gross Margins, Revenue Growth
Solvency & Liquidity Ratios:
Debt to Equity, Debt to EBITDA, Current Ratio, Quick Ratio, Altman Z-Score
Each of these metrics is calculated using request.financial() and can be viewed using either annual (FY) or quarterly (FQ) data, depending on user preference.
🧠 How to Use
Add the script to any stock chart.
Select your preferred data period (FY or FQ).
Adjust thresholds if desired to match your personal investing strategy.
Review the visual dashboard to see which metrics the company passes or fails.
💡 Why It’s Useful
This tool is ideal for traders or long-term investors looking to filter stocks using fundamental criteria. It draws inspiration from principles used by Benjamin Graham, Warren Buffett, and Joel Greenblatt, offering a fast and informative way to screen quality businesses.
This is not a repackaged built-in or autogenerated script. It’s a custom-built, interactive tool tailored for fundamental analysis using official financial data provided via Pine Script’s request.financial().
