N-Degree Moment-Based Adaptive Detection🙏🏻 N-Degree Moment-Based Adaptive Detection (NDMBAD) method is a generalization of MBAD since the horizontal line fit passing through the data's mean can be simply treated as zero-degree polynomial regression. We can extend the MBAD logic to higher-degree polynomial regression.
I don't think I need to talk a lot about the thing there; the logic is really the same as in MBAD, just hit the link above and read if you want. The only difference is now we can gather cumulants not only from the horizontal mean fit (degree = 0) but also from higher-order polynomial regression fit, including linear regression (degree = 1).
Why?
Simply because residuals from the 0-degree model don't contain trend information, and while in some cases that's exactly what you need, in other cases, you want to model your trend explicitly. Imagine your underlying process trends in a steady manner, and you want to control the extreme deviations from the process's core. If you're going to use 0-degree, you'll be treating this beautiful steady trend as a residual itself, which "constantly deviates from the process mean." It doesn't make much sense.
How?
First, if you set the length to 0, you will end up with the function incrementally applied to all your data starting from bar_index 0. This can be called the expanding window mode. That's the functionality I include in all my scripts lately (where it makes sense). As I said in the MBAD description, choosing length is a matter of doing business & applied use of my work, but I think I'm open to talk about it.
I don't see much sense in using degree > 1 though (still in research on it). If you have dem curves, you can use Fourier transform -> spectral filtering / harmonic regression (regression with Fourier terms). The job of a degree > 0 is to model the direction in data, and degree 1 gets it done. In mean reversion strategies, it means that you don't wanna put 0-degree polynomial regression (i.e., the mean) on non-stationary trending data in moving window mode because, this way, your residuals will be contaminated with the trend component.
By the way, you can send thanks to @aaron294c , he said like mane MBAD is dope, and it's gonna really complement his work, so I decided to drop NDMBAD now, gonna be more useful since it covers more types of data.
I wanned to call it N-Order Moment Adaptive Detection because it abbreviates to NOMAD, which sounds cool and suits me well, because when I perform as a fire dancer, nomad style is one of my outfits. Burning Man stuff vibe, you know. But the problem is degree and order really mean two different things in the polynomial context, so gotta stay right & precise—that's the priority.
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Papercuts Time Sampled Higher Timeframe EMA Without SecurityThis EMA uses a higher time sampled method instead of using security to gather higher timeframe data.
Its quite fast and worked well with the timeframes prescribed, up to 8hrs, after 8hrs, the formatting gets more complicated and i probably wouldn't use it anyway.
You can use this as a guide to avoid security and even f_security with this method.
NOTE: This includes the non repainting f_security call so that i woudl be able to check my results against what it does, thats not nessecary to keep at all.
There is some minor differences in data, but its so minor it doesnt bother me, though it would be interesting to know what the difference actually is. If anyone figures that out, leave a comment and let me know!
This is meant to be an example for others to build and learn and play with.. so enjoy!
2nd 3rd 4th Order PivotsThis indicator calculates pivots of 2nd, 3rd and 4th order in the current timeframe.
The idea is borrowed from the book "The Art and Science of Technical Trading" by Adam Grimes:
"A pivot high is a bar that has a higher high than the bar that came before it and the bar that comes after it"
"Second-order pivot highs are first-order pivot highs that are preceded and followed by lower first-order pivot highs.
The type of picot calculation can be found as well in script "Higher Order Pivots" by rumpypumpydumpy. However, this script is different in the following ways:
1. Shows pivots of order 2, 3 and 4
2. The chart timeframe can be different than the pivot timeframe, allowing e.g. to map daily pivots to intraday charts via lines
3. Labels and/or lines can be used to show pivot points
4. Use of extended session data can be enabled/disabled, independently from the current chart settings
5. To disable older pivots, a starting time for the pivot calculation can be set
Please consider following limitations:
1. Maximum of 500 drawing objects per chart. Use Notification option to keep track of when running out of chart objects.
2. Lookback history: The max lookback history is limited by the currently selected timeframe. E.g. on a 5min timeframe, 20000 bars (Premium Plan) result in approx. 5 months of lookback period, meaning you may want to verify with a 30 min or higher chart to get a complete picture of pivots.
Higher and lower close indicatorSome strategies depend on a higher or lower close than the previous bar's close. With lower time frames and small bars, this can be time consuming. The indicator reduces the time for such decisions by colour indicating the condition. A higher close than the previous bar is denoted by a green dot at the bottom of the screen, red for a lower close and blue for an equal close.
HTF High/LowThis simple script draws the previous higher timeframe candle high/low to your chart.
You can also make the script paint the zone between the low/open and the high/close.
Higher Timeframe EMAThis script plots a higher timeframe EMA to your chart.
You can specify the timeframe and the length of the EMA in the settings.
This chart demonstrates the 5-minute 50EMA (black) combined with the 1-hour 50EMA (colored) on the 1 minute timeframe.
