WaveTrend 3D Introduction This is a Python Implementation of the "WaveTrend 3D" oscillator developed in TradingView (2022, Justin Dehorty). It is a great application of modern signal processing techniques to a well-known approach. The "3D" aspect refers to three dimensions that are calculated, each possibly representing a different timeframe. Arguably, it also refers to the three-dimensional visualisation, especially in "mirrored" form. Original description Below is a copy from Justin Dehorty's original implementation: WaveTrend 3D (WT3D) is an alternative implementation of WaveTrend that directly addresses some of the known shortcomings of the indicator, including its unbounded extremes, susceptibility to whipsaw, and lack of insight into other timeframes. In the canonical WT approach, an exponential moving average (EMA) for a given lookback window is used to assess the variability between price and two other EMAs relative to a second lookback window. Since the difference between the average price and its associated EMA is essentially unbounded, an arbitrary scaling factor of 0.015

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