Filter impulse & step responsesA simple utility tool to examine a filter's step & impulse responses.
By default you can see LSMA's responses.
How to use:
1. Insert your filter to "f(input)" function inside the code;
2. Let this tool help you to make your own filters.
I been seeing people dropping snaps with this stuff but NEVER, NO1 actually dropped the tool itself (4 real?).
Well here is it, for you.
Almost forgot, adjust "Position" parameter to make plots seen. Try to zoom out, and +-100
Su Pine
How To Identify Argument Type Of Number Using OverloadsExample overload functions accept loading of _value for types float, int, or string, then positively identifies the actual argument type of that specific loaded _value.
How To Identify Type Of NumberExample function accepts loading of _value for types float, int, or string, then identifies whether the loaded _value is a string number, string, or number.
How To Count DecimalsCustom f_nDecimals() function returns precision of decimal numbers of the following forms:
const, input, simple, and series of the following types: float, integer, and string.
Error checking is performed for valid numbers and invalid values return NaN.
NOTICE: This is an example script and not meant to be used as an actual strategy. By using this script or any portion thereof, you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script!
Auxiliary Equity Configurator (AXE)Auxiliary Equity Configurator (AXE) is a whole new level money management auxiliary that calculates statistically preferable lot based on the Account balance, Winning rate, Risk reward ratio, and Kelly multiplier configured a priori in the input panel.
On the chart, RR visualization bands, Expected balance history matrix in the worst successive trading loss (for displaying how many times you can trade with a given lot at simple/compound interest), and Info-table for the calculation details are shown.
Regarding RR visualization bands, whenever the Tolerable drawback input changes, the proper lot is calculated based on the given data. You can easily access how many lots you should possess and the take-profit/stop-loss price to set. A tolerable drawback can be placed in the quoted currency rate of the displayed chart, except the forex and part of CFD symbols (Gold, Silver, Platinum, WTI oil, Brent oil, Natural gas, and more in the future!) that is valued in Pips. Parameters are configurable in suit with the broker you are using. Also, RR visualization bands are brilliantly interactive, thanks to pine v5 interactive scripts.
The currency for Account balance and Tolerable drawback is automatically converted to USD for internal calculation; therefore, no mess-ups around thinking currency value conversion whatsoever! The design for each tool is highly customizable, too.
Unleash yourself from consuming the colossal amount of time thinking of money management with AXE!
Oscillator EdgesAnother simple script to be added on top of other indicators. Simply provides a symbol of varying color depending on the value of the oscillator. Allows up to 4 different colors in each direction. Includes alerts conditions. Demonstration is the indicator being applied to the RSI (purple) included in Market Cipher B.
To use, simply add it to your indicator, and choose and oscillator of your choice in the Input Settings. Alternatively, you can just keep it on 'close' and use the built in RSI. Or, you can use the RSI formula on top of something else (if that's your thing).
The names are silly, so I hope this is okay with all of you.
Let me know what you think, and if there are any problems, questions, or concerns!
Kitti-Playbook :MAGNIFY // MAGNIFY
// Feature : Display Current price into chart by chart in one tab , More comfortable for market monitoring
//
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1 Can Display both Symbol and Exchange or Symbol only
2 Show last Price
3 Show price difference from close of previous bar
4 Color definition : Green --> price > previous bar close , Red --> price < previous bar close , Yellow --> price = previous bar close
5 Can Magnify 2 level : LARGE and HUGE
6 Can adjust Vertical Position for Label
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Percentile Nearest Rank Using Arrays [LuxAlgo]The new array feature is extremely powerful, as it will allow pinescript users to do more complex things, or compute existing calculations more efficiently, it will also be possible to shine some light to some already existing functions, one of them being percentile_nearest_rank .
We have been working on this new feature with our pal alexgrover, and made this script which computes a rolling percentile using the nearest rank method.
Settings
Length: Window of the rolling percentile, determine the number of past data to be used.
Percentage: Return the current value if Percentage % of the data fall below that value, the setting is in a range (0,100).
Src: Input source of the indicator.
Usage
A rolling percentile can have many usages when it comes to technical analysis, this is due to its ability to return the value of three common rolling statistics, the rolling median, which can be obtained using a percentage equal to 50, the rolling maximum, obtained with a percentage equal to 100, and the rolling minimum, obtained with a percentage equal to 0.
When we use our rolling percentile as a rolling median, we can obtain a robust estimation of the underlying trend in the price, while using it as a rolling maximum/minimum can allow us to determine if the market is trending, and at which direction. The rolling maximum/minimum is a rolling statistic used to calculate the well known stochastic oscillator and Donchian channel indicator.
We can also compute rolling quartiles, which can be obtained using a percentage of 25 or 75, with one of 25 returning the lower quartile and 75 the upper quartile.
In blue the upper rolling quartile (%75), in orange the lower rolling quartile (%25), both using a window size of 100.
Details
In order to compute a rolling percentile nearest rank, we must first take the most recent length closing prices, then order them in ascending order, we then return the value of the ordered observations at index (percentage/100*length) - 1 (we use - 1 because our array index starts at 0).
