{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:28:20Z","timestamp":1760236100881,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T00:00:00Z","timestamp":1635292800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>We investigated a comprehensive analysis of the mutual exciting mechanism for the dynamic of stock price trends. A multi-dimensional Hawkes-model-based approach was proposed to capture the mutual exciting activities, which take the form of point processes induced by dual moving average crossovers. We first performed statistical measurements for the crossover event sequence, introducing the distribution of the inter-event times of dual moving average crossovers and the correlations of local variation (LV), which is often used in spike train analysis. It was demonstrated that the crossover dynamics in most stock sectors are generally more regular than a standard Poisson process, and the correlation between variations is ubiquitous. In this sense, the proposed model allowed us to identify some asymmetric cross-excitations, and a mutually exciting structure of stock sectors could be characterized by mutual excitation correlations obtained from the kernel matrix of our model. Using simulations, we were able to substantiate that a burst of the dual moving average crossovers in one sector increases the intensity of burst both in the same sector (self-excitation) as well as in other sectors (cross-excitation), generating episodes of highly clustered burst across the market. Furthermore, based on our finding, an algorithmic pair trading strategy was developed and backtesting results on real market data showed that the mutual excitation mechanism might be profitable for stock trading.<\/jats:p>","DOI":"10.3390\/e23111411","type":"journal-article","created":{"date-parts":[[2021,10,27]],"date-time":"2021-10-27T22:00:23Z","timestamp":1635372023000},"page":"1411","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Detection of Mutual Exciting Structure in Stock Price Trend Dynamics"],"prefix":"10.3390","volume":"23","author":[{"given":"Shangzhe","family":"Li","sequence":"first","affiliation":[{"name":"School of Mathematical Science and LMIB, Beihang University, Beijing 100191, China"},{"name":"School of Computer Science and Engineering and NLSDE, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Mathematical Science and LMIB, Beihang University, Beijing 100191, China"},{"name":"Zhengzhou Aerotropolis Institute of Artificial Intelligence, Zhengzhou 451162, China"},{"name":"Pengcheng Laboratory, Shenzhen 518052, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Junran","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering and NLSDE, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lin","family":"Tong","sequence":"additional","affiliation":[{"name":"Gabelli School of Business, Fordham University, New York, NY 10023, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ke","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering and NLSDE, Beihang University, Beijing 100191, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,10,27]]},"reference":[{"key":"ref_1","first-page":"454","article-title":"Cluster models for earthquakes-regional comparisons","volume":"45","author":"Hawkes","year":"1973","journal-title":"Bull. 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