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Lorentzian Classification is built around a K-nearest neighbours machine learning model using Lorentzian distance metrics rather than traditional Euclidean measurements, engineered for equity traders operating within D1 to monthly position trading timeframes.
In verified backtesting across a five-year sample, Lorentzian Classification records a 73% win rate and a 2.51 profit factor, with a maximum drawdown of just 10.2%. Equity position traders who want a statistically rigorous classification model will find this tool among the most technically sophisticated options.
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Lorentzian Classification is built around a K-nearest neighbours machine learning model using Lorentzian distance metrics rather than traditional Euclidean measurements, engineered for equity traders operating within D1 to monthly position trading timeframes.
In verified backtesting across a five-year sample, Lorentzian Classification records a 73% win rate and a 2.51 profit factor, with a maximum drawdown of just 10.2%. Equity position traders who want a statistically rigorous classification model will find this tool among the most technically sophisticated options.
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