Quantifying Key Properties of Trend-Following Rules

Valeriy Zakamulin () and Javier Giner ()
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Valeriy Zakamulin: University of Agder, Norway
Javier Giner: University of La Laguna

Chapter Chapter 4 in The Ultimate Moving Average Handbook, 2025, pp 111-159 from Springer

Abstract: 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.

Date: 2025
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DOI: 10.1007/978-3-031-90907-8_4

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