The quantitative metrics introduced in this book allow for a rigorous evaluation of moving averages that are believed to offer superior smoothness. This chapter examines whether replacing conventional moving averages with these alternatives enhances the efficiency of trend-following rules. By systematically assessing their impact on key properties—accuracy, responsiveness, and smoothness—we determine whether smoother moving averages provide a meaningful advantage or if their benefits are offset by reduced responsiveness or accuracy. The analysis reveals that while some moving averages achieve high smoothness, they do not necessarily improve overall trend-following efficiency. In many cases, traditional moving averages with carefully chosen parameters perform just as well or even better, underscoring the importance of balancing smoothness with responsiveness and accuracy.