This is an FTLM digital filter with a smoothing algorithm, also it shows candle formations in the histogram. The candles help to spot turning points as they get squeezed.
This is an RSI with Dynamic zones with a Smoothing algorithm. It was translated from an MT4 indicator written and shared by Mladen, and now we can use it in Multicharts.
If you Download the Indicator and like please click on the thanks button.
Here is the Velocity OrderFlow for Multicharts. It's meant to be used with Footprint charts.
It provides the bid volume, ask volume, delta, and duration of the bar in seconds.
If the duration of the bar is beneath a certain threshold it will plot an arrow over or under the bar
depending on if the signal is bearish or bullish. This is the Velocity arrow. I use Volume charts or contract charts. But it could be used with tick charts as well. I included an indicator called TaiChi it's a good indicator. It's a modified supertrend with no extremes just the middle line.
Test it out, I just coded it in a day so it could have some bugs.
This is a Grid trading algo that sets levels based on the tick size, grid step, and grid size. This algo may be profitable with different settings depending on the instrument. I have released it here so it can be tested, modified, or improved into something better. It's very simple the code is simple and clear. I also will include a Grid Levels indicator so you can see where the levels are at.
What follows is a function that normalizes an indicator value between a max and min value of +50/-50. This is a derivation of the normalization function as described in the section "Historical Adjustment to Improve Stationarity" within the book Statistically Sound Machine Learning for Algorithmic Trading of Financial Instruments by David Aronson and Timothy Masters.
The goal of normalization is to retain any predictive value of an indicator that gains its importance from its current value relative to recent values. This normalization process imparts stationarity on the indicator. From the text, "In most case, stationarity improves the accuracy of predictive models. (Recall that, roughly speaking, stationarity means that the statistical properties of an indicator do not change over time.)".
The attached function is in easylanguage syntax. It should be able to take any raw indicator value and normalize it by both centering and scaling it within a range of +50/-50.
Attached is a text file of the easy language code.
I hope you find this useful.
Updates:
08/15/2021 v001 - corrected the function name return value to the name of the text file