This type of moving average was originally developed by Bruno Pio in 2010. I just ported the original code from MetaTrader 5.
The weights of this moving average are powers of the weights of the standard weighted moving average WMA . Remember: When parameter Power = 0, you will get SMA . When parameter Power = 1, you will get WMA . Good luck!
Adapt To The Right Situation There are already some Adaptive Stochastic scripts out there, but i didn't see the concept of using different periods highest/lowest for their calculations. What we want for such oscillator is to be active when price is trending and silent during range periods. Like that the information we will see will be clear and easy to...
Another Adaptive Filter This indicator share the same structure as a classic adaptive filter using an exponential window with a smoothing constant. However the smoothing constant used is different than any previously made (Kalman Gain, Efficiency ratio, Scaled Fractal Dimension Index) , here the smoothing constant is inspired by the different formulations for...
This is a sample script I coded during one of my mentoring videos about my methodology, the goal of that video is to teach my students how they can do their R&D !
Hey there! This tool will help you to choose a moving average/filter that has the lowest lag throughout the whole history for the specified period. What does it do? It calculates the mean absolute errors for each moving average or filter and shows histogram with results. The lower error the lower lag of the moving average. So, the best average will be at the...
Trading The Movements That Matters Inspired by the Price Volume Trend indicator the Efficient Price aim to create a better version of the price containing only the information a trend trader must need. Calculation This indicator use the Efficiency Ratio as a smoothing constant, it is calculated as follow : ER =...
The Self Referencing Stochastic Oscillator The stochastic oscillator bring values in range of (0,100). This process is called Feature scaling or Unity-Based Normalization When a function use recursion you can highlights cycles or create smoother results depending on various factors, this is the goal of a recursive stochastic. For example : k =...
Developed by Emily Karobein, the Karobein oscillator is an oscillator that aim to rescale smoothed values with more reactivity in a range of (0,1) Calculation The scaling method is similar to the one used in a kalman filter for the kalman gain. We first average the up/downs x, those calculations are similar to the ones used for calculating the average...
A One Dimensional Kalman Filter, the particularity of Kalman Filtering is the constant recalculation of the Error between the measurements and the estimate.This version is modified to allow more/less filtering using an alternative calculation of the error measurement. Camparison of the Kalman filter Red with a moving average Black of both period 50 Can...
🆓 Smoothed Chande Trend Score w/ Signal Line by Cryptorhythms 👀Did not see this one in the public library yet, so here you go! I added an ema signal line that you can configure the length on. Also dressed it up a little with OB/OS zones and some purdy colors. Here are long + short charts: 👍Enjoying this indicator or find it useful? Please give me a like...
Mean Reversion and Momentum Interpretation: - Divergence means trend reversal - Parallel movement means trend continuation Squares above serve as a confirming signal
A quadratic regression is the process of finding the equation that best fits a set of data.This form of regression is mainly used for smoothing data shaped like a parabola. Because we can use short/midterm/longterm periods we can say that we use a Quadratic Least Squares Moving Average or a Moving Quadratic Regression. Like the Linear Regression (LSMA) a...
Applying a window to the filter weights provides sometimes extra control over the characteristics of the filter.In this script an hamming window is applied to the volume before being used as a weight.In general this process smooth the frequency response of a filter. Lets compare the classic vwma with hamming windowed vwma Something i noticed is that windowed...
When i was in Japan with some traders colleagues we talked about traditional charting tools from this country and how they changed the way we look at our charts today. Then suddenly one of the japanese traders i have met earlier said "Why not making another charting tool ? Smoother than Heikin-Ashi and including all the information a trader may need but easier to...
Logistic Correlation is a correlation oscillator using a logistic function. A Logistic Function is a Sigmoid Function who stabilize the variance of data.The logistic function have the same function as the inverse fisher transform but with an advantage over it, the k constant can control the steepness of the curve, lowers k's will preserve the original form of...
Single Exponential Smoothing ( ema ) does not excel in following the data when there is a trend. This situation can be improved by the introduction of a second equation with a second constant gamma . The gamma constant cant be lower than 0 and cant be greater than 1, higher values of gamma create less lag while preserving smoothness.Higher values of length ...
The Sawada Masu Moving Average is a filtering technique invented by the japan engineer Sawada Masu with the help of the french trader Alex pierrefeu. This filter have 2 input, a lenght input, who modify the sensibility of the filter to market movement, and a alpha input who just smooth the filter. The recommended inputs are : a length of 90 and a alpha of...