Due to popular demand, I'm pusblishing Fourier Extrapolator of Price w/ Projection Forecast.. As stated in it's twin indicator, this one is also multi-harmonic (or multi-tone) trigonometric model of a price series xi, i=1..n, is given by: xi = m + Sum( a*Cos(w*i) + b*Sin(w*i), h=1..H ) Where: xi - past price at i-th bar, total n past prices; m - bias; ...

1888

This is the Exit-Willy indicator. It issues Buy and Sell signals based on exit data from different moving averages and the Williams Percent R. It also has a LSMA filter. All values are adjustable. I like to use it with a higher Exit value being as it filters some of the false signals. There are multiple different settings to change and alter.

135

This is an experimental study designed to calculate polynomial regression for any order polynomial that TV is able to support. This study aims to educate users on polynomial curve fitting, and the derivation process of Least Squares Moving Averages (LSMAs). I also designed this study with the intent of showcasing some of the capabilities and potential applications...

1552

Rᴀꜰꜰ Rᴇɢʀᴇꜱꜱɪᴏɴ Cʜᴀɴɴᴇʟ (RRC) This study aims to automate Raff Regression Channel drawing either based on ZigZag Indicator or optionally User Preference The Raff Regression Channel , developed by Gilbert Raff, is based on a linear regression, which is the least-squares line-of-best-fit for a price series, with evenly spaced trend lines above and below . The...

2385

This is my Channel Surfing indicator. It fires Buy and Sell signals based on multiple conditions. You can use EMAs or LSMAs. You will have to check the box of which moving averages to use once you add it to the chart. It plots EMAs or LSMAs using the different sources Close, Low, and High as the channel to surf. It fires a Buy signal if price crosses the...

81

This is the Olympus Mons indicator. It uses Braid Filter, LSMA, and Hawkeye Volume to fire Buy and Sell signals. I use this on the 5 Min. SPY chart to play 1 point scalp targets with options. I have been able to get a pretty consistent win rate using it like this. The default settings are what I use. Hope it helps any of you guys. Let me know if you see any...

48

Introduction At the start of 2019 i published my first post "Approximating A Least Square Moving Average In Pine", who aimed to provide alternatives calculation of the least squares moving average (LSMA), a moving average who aim to estimate the underlying trend in the price without excessive lag. The LSMA has the form of a linear regression ax + b where x ...

449

Introduction The ability of the least squares moving average to provide a great low lag filter is something i always liked, however the least squares moving average can have other uses, one of them is using it with the z-score to provide a fast smoothing oscillator. The Indicator The indicator aim to provide fast and smooth results. length control the...

162

Quick script made by reusing some functions written for other projects. This is a variation on the least squares moving average, but with custom weights on the linear regression. This gives higher weights to recent values and values with high volume. Behaves very similarly to my volume weighted Hull moving average, especially with the hull smoothing option turned on.

104

Introduction I already mentioned various problems associated with the lsma, one of them being overshoots, so here i propose to use an lsma using a developed and adaptive form of 1st order polynomial to provide several improvements to the lsma. This indicator will adapt to various coefficient of determinations while also using various recursions. More In Depth ...

129

This is an experimental study which calculates a linear regression channel over a specified period or interval using custom moving average types for its calculations. Linear regression is a linear approach to modeling the relationship between a dependent variable and one or more independent variables. In linear regression, the relationships are modeled using...

2695

Introduction Forecasting is a blurry science that deal with lot of uncertainty. Most of the time forecasting is made with the assumption that past values can be used to forecast a time series, the accuracy of the forecast depend on the type of time series, the pre-processing applied to it, the forecast model and the parameters of the model. In tradingview we...

1074

Double RSI uses a Slow RSI combined with a Fast RSI to generate Buy and Sell signals. Least Squares Moving Average is only here for filtering signals. It is very good on certain stocks or ETFs on longer timeframes for swing trading. If you get a Buy signal look at the LSMA trend and if the candle is above the LSMA. It works great for me on lower timeframes...

279

Fourier Extrapolator of Price is a multi-harmonic (or multi-tone) trigonometric model of a price series xi, i=1..n, is given by: xi = m + Sum( a *Cos(w *i) + b *Sin(w *i), h=1..H ) Where: xi - past price at i-th bar, total n past prices; m - bias; a and b - scaling coefficients of harmonics; w - frequency of a harmonic; h - harmonic number; H -...

151

This is based on a video I watched while searching for good indicators to use for scanning pumps across the crypto market. You can probably find the video by searching for "Pump Finder On 15 Minute Chart With Best Trading Indicators". The approach presented uses LSMA and BB B% to detect pumps. Results: It does detect many pumps, it also detects many...

145

Introduction The trend step indicator family has produced much interest in the community, those indicators showed in certain cases robustness and reactivity. Their ease of use/interpretation is also a major advantage. Although those indicators have a relatively good fit with the input price, they can still be improved by introducing least-squares fitting on...

715

Introduction The estimation of a least squares moving average of any degree isn't an interesting goal, this is due to the fact that lsma of high degrees would highly overshoot as well as overfit the closing price, which wouldn't really appear smooth. However i proposed an estimate of an lsma of any degree using convolution and a new sine wave series, all the...

186

This is an example of what can be done by combining Legendre polynomials and analytic signals. I get a way of determining a smooth period and relative adaptive strength indicator without adding time lag. This indicator displays the following: The Least Squares fit of a polynomial to a DC subtracted time series - a best fit to a cycle. The normalized...

85