Founder of [MESA software](https://mesasoftware.com/). Considers best article was "[[A Technical Description of Market Data for Traders]]" Thinks volatility is Orthogonal to market timing signals. In finance, volatility refers to the degree of variation in the price of a financial asset over time, while market timing signals refer to indicators or signals that are used to determine the best time to buy or sell an asset. Therefore, if volatility is considered orthogonal to market timing signals, it means that changes in the level of volatility in the market do not have a direct impact on the timing of buy or sell decisions. In other words, the level of volatility does not provide any meaningful insight into when to buy or sell an asset, and market timing signals should be based on other factors such as price trends, economic indicators, or fundamental analysis. In short - avoid volatility when trying to improve market timing. Things like Bollinger bands and moving averages suffer too much [[Computational Lag]]. His primary thinking is that signal information in data is analogous to [[Frequency and Phase Modulation]] of a radio wave. He believes [[Band Limiting Filters]] can be used to recover trading information. He believes price action is [[Fractal]] and the statistical shape of market spectrum is [[Pink Noise]]. His theory relates to swing, or [[Mean Reversion]], style of trading. "Swing trade timing rules should be solely dependent on the position of the phasor". This is different to trend following, if you apply [[Digital Signal Processing]] (DSP) techniques to the latter, all you achieve are smoothing filters.