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Quantifying Key Properties of Trend-Following Rules

In: The Ultimate Moving Average Handbook

Author

Listed:
  • Valeriy Zakamulin

    (University of Agder, Norway)

  • Javier Giner

    (University of La Laguna)

Abstract

This chapter argues that an effective trading rule must exhibit three fundamental properties: accuracy, responsiveness, and smoothness. To quantify these properties, we introduce three objective measures derived from the weighting function of return lags in the trading indicator. These measures rely on a key assumption: market returns randomly alternate between bull and bear states. However, unlike traditional approaches based on parametric regime-switching models, our framework does not require estimating transition probabilities or state-dependent parameters. Instead, it directly utilizes the return weights inherent in the trading rule. This approach allows for a model-independent evaluation, enabling a precise comparison of different trend-following rules. The proposed measures provide a transparent and systematic way to analyze the tradeoffs between signal precision, reaction speed to trend reversals, and stability of trading signals. This framework offers traders and researchers a robust method for evaluating the effectiveness of trend-following strategies beyond subjective visual comparisons.

Suggested Citation

  • Valeriy Zakamulin & Javier Giner, 2025. "Quantifying Key Properties of Trend-Following Rules," Springer Books, in: The Ultimate Moving Average Handbook, chapter 0, pages 111-159, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-90907-8_4
    DOI: 10.1007/978-3-031-90907-8_4
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