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.

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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...

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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...

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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; ...

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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 -...

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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...

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This is the Stochastic/LSMA Buy and Sell indicator. The Buy signal is generated when the %K line crosses up above the %D line from the stochastics while the signal candle is green and has come after a red candle. The Sell signal is generated when the %K line crosses down below the %D line from the stochastics while the signal candle is red and has come after a...

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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...

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Bollinger Bands with user selection options to calculate the moving average basis and bands from a variety of different moving averages. The user selects their choice of moving average, and the bands automatically adjust. The user may select a MA that reacts faster to volatility or slower/smoother. Added additional options to color the bands or basis based on...

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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...

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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...

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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...

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Channel uses @KivancOzbilgic's VIDYA script as a basis and the maximum distance between Least Square Moving Average (14) over a specified number of periods (80) as size. This combination is good as it uses one very slow MA and one highly overlapping one. Can be combined with ATR channels where Triumph will represent extreme in relevance to the previous days and...

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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 ...

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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.

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Similar to Bollinger Bands but adjusted for momentum. Instead of having the centerline be a simply moving average and the bands showing the rolling variance, this does a linear regression, and shows the LSMA at the center, while the band width is the average deviation from the regression line instead of from the SMA. This means that unlike for normal Bollinger...

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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...

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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...

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