This chapter presents analytical results for the accuracy, responsiveness, and smoothness measures of trend-following rules based on standard moving averages. The findings highlight a fundamental tradeoff in trading rule design: improving one property, such as accuracy or smoothness, often comes at the cost of another, such as responsiveness. Using these quantitative measures, the chapter systematically compares different trading rules, revealing distinct performance patterns. Some rules excel in responsiveness and accuracy, reacting swiftly to trend changes while maintaining precision, whereas others offer a more balanced tradeoff between responsiveness and smoothness, reducing noise and minimizing whipsaw effects. By providing a rigorous, model-independent framework for evaluating trend-following strategies, this analysis moves beyond subjective visual assessments and offers a transparent basis for comparing trading rules. The results demonstrate that no single rule optimally balances all three properties, underscoring the importance of selecting a strategy that aligns with specific market conditions and trading objectives.