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Embrace the Binary to Capture Trends
Balancing robustness and accuracy in trend measurement involves recognizing the inherently S-shaped nature of many signals, where extremes often exhibit mean-reversion tendencies. Specifically, returns in the highest decile may not be as favorable as those in slightly lower deciles, indicating that strong signals can occasionally mislead predictions. Furthermore, breaking down signals into quartiles reveals minimal statistical difference, reinforcing the value of binary signals. By aggregating various binary signals across different timeframes, it’s possible to derive a distribution that effectively highlights significant predictive capabilities at the extremes, enhancing the forecasting ability for the highest and lowest returning signals while mitigating the flipping behavior of individual binaries.