This is part of a new series we are calling "Strategy Myth-Busting" where we take open public manual trading strategies and automate them. The goal is to not only validate the authenticity of the claims but to provide an automated version for traders who wish to trade autonomously.
Our fourth one we are automating is one of the strategies from " I Found The Best...
An almost zero lag version of the LSMA (Least Squares Moving Average)
Gives instant linear regression of current price action.
This line works with the same rules as its "laggy" counterpart the LSMA:
When price crosses over it signals a bull trend.
When price crosses under it signals bear trend.
When price stays close or on the line sideways action is to be...
This indicator returns the average of stochastic oscillators with periods ranging from 4 to length . This allows for a slightly more reactive oscillator as well as having information regarding the position of the price relative to rolling maximums/minimums of different periods.
We introduce settings that allow for pre and post-smoothing, with selectable...
Elder-Ray Bear and Bull Power
Dr. Alexander Elder cleverly named his first indicator Elder-Ray because of its function, which is designed to see through the market like an X-ray machine. Developed in 1989, the Elder-Ray indicator can be applied to the chart of any security and helps traders determine the strength of competing groups of bulls and bears by gazing...
This script calculates the performance of any asset following a golden cross of two moving averages of any length!
The calculated moving averages are: SMA, EMA, HMA, VWMA, WMA, LSMA, and ALMA
The best performing moving average for the selected data series is listed first, followed by a descending order.
The indicator works on any timeframe, any asset, and...
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...
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...
This indicator uses the Least Squares Moving Average (LSMA) in tandem with the Arnaud Legoux Moving Average (ALMA) and Hull Moving Average (HMA) to generate buy-sell signals, represented by the light blue and orange crosses respectively.
The yellow lines produced by the indicator show periods of market uncertainty and possible reversal, and a modified,...
This script calculates the average percentage gain/loss following a price crossover of a moving of any length, up until prices cross back under the MA.
The script calculates the average number of candles that the source (i.e. close, open, low, ohlc4) remains above the moving average until crossing back under, in addition to the number of crosses....
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...
This is an experimental study designed using data from Bollinger Bands to determine price squeeze ranges and active levels of support and resistance.
First, a set of Bollinger Bands using a Coefficient of Variation weighted moving average as the basis is calculated.
Then, the relative percentage of current bandwidth to maximum bandwidth over the specified sampling...
This is a simple script designed to help filter out bad trades. LSMA is a trend king and by using the 21,200 and 1000 length lines traders can get a clear view of where price action is travelling. This indicator is the perfect companion to the LSMA Wave Rider indicator. Once a pullback is discovered (price action crosses under blue or white line) Traders can use...
Estimating the LSMA Without Classics Parameters
I already mentioned various methods in order to estimate the LSMA in the idea i published. The parameter who still appeared on both the previous estimation and the classic LSMA was the sample correlation coefficient. This indicator will use an estimate of the correlation coefficient using the standard score thus...
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 ...
This is a variation of Gerald Appel's MACD with seven moving average source types to choose from.
The MA types I've included in this script are:
- Kaufman's Adaptive Moving Average
- Geometric Moving Average
- Hull Moving Average
- Volume Weighted Moving Average
- Least Squares Moving Average
- Arnaud Legoux Moving Average
The "AC-P" version of Jaggedsoft's RSX Divergence and Everget's RSX script is my personal customized version of RSX with the following additions and modifications:
LSMA-D line that averages in three LSMA components to form a composite, the LSMA-D line. Offset for the LSMA-D line is set to -2 to offset latency from averaging togther the LSMA components to form...
The ratings algo is my discount version of the many paid-for algorithms put out by numerous different companies. A technical "rating" (by default between -10 and 10) is produced for each candle, telling the user when to buy, sell, or hold. I took 11 of my personal favorite indicators to develop a rating system. They are:
50/200 SMA crossover
Moving averages are filters on price data. This moving average creates a filter which factors in:
- the price RSI or it's Momentum
- the volume RSI
- the RVI or Volatility
Each factor is put through a least squares filter to smooth them first.
Then the factors are used to build a coefficient for an exponentially weighted average.
The chart above shows a...