Optimal Allocation of Trend‐Following Rules: An Application Case of Theoretical Results

Lequeux, Pierre

doi:10.1002/0470013265.ch11

Cited by 3 publications

(2 citation statements)

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“…In a continuous-time setting, price persistence is typically modeled using the Ornstein-Uhlenbeck process for returns (see Zhu and Zhou 2009, Han et al 2016, Ayed et al 2017. In discrete time, the price trend is commonly modeled by an AR(1) process, which is the discrete-time analogue of the continuous Ornstein-Uhlenbeck process (examples are Acar 1998, Lequeux 2005, Hong and Satchell 2015. In our paper, the return process incorporates higher order autoregressive lags that are often needed to capture the complex dynamics of real markets.…”

Section: Return Processmentioning

confidence: 99%

“…† However, despite the enormous current interest in trend following and a series of publications in academic journals, there is still a dearth of theoretical results on the properties of trend-following rules. A few exceptions are the studies by Acar (1998), Lequeux (2005), Zhu and Zhou (2009), and Hong and Satchell (2015). In addition, very little research has been conducted on contrasting the MOM and MA rules.…”

Section: Introductionmentioning

confidence: 99%

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Trend following with momentum versus moving averages: a tale of differences

Zakamulin

Giner

2020

Quantitative Finance

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Despite the ever-growing interest in trend following and a series of publications in academic journals, there is a dearth of theoretical results on the properties of trend-following rules. Our paper fills this gap by comparing and contrasting the two most popular trend-following rules, the momentum (MOM) and moving average (MA) rules, from a theoretical perspective. We provide theoretical results on the similarity between different trend-following rules and the forecast accuracy of trading rules. Our results show that the similarity between the MOM and MA rules is high and increases with the strength of the trend. However, compared to the MOM rule, the MA rules exhibit more robust forecast accuracy for the future direction of price trends. In this paper, we also develop a hypothesis about uncertain market dynamics. We show that this hypothesis, coupled with our analytical results, has far-reaching practical implications and can explain a number of empirical observations. Among other things, our hypothesis explains why the empirical performance of the MA rules is better than that of the MOM rule. We broaden the appeal and practical importance of our theoretical results by offering various illustrations and real-world examples.

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