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Complexity
Volume 2019, Article ID 7490640, 18 pages
https://doi.org/10.1155/2019/7490640
Research Article

Analyzing Stock Brokers’ Trading Patterns: A Network Decomposition and Spatial Econometrics Approach

1Escuela de Negocios, Universidad Adolfo Ibáñez, Padre Hurtado 750, Viña del Mar, Chile
2Escuela de Negocios, Universidad Adolfo Ibáñez, Diagonal Las Torres 2640, Peñalolén, Santiago, Chile

Correspondence should be addressed to Alejandro Montecinos-Pearce; moc.liamg@lacsapsonicetnoma

Received 22 February 2019; Revised 10 June 2019; Accepted 23 June 2019; Published 25 July 2019

Guest Editor: Ahmet Sensoy

Copyright © 2019 Juan Eberhard et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Using a unique data set with all the daily transactions from the Santiago Stock Exchange, we develop a novel methodology that combines a network decomposition with a spatial econometrics technique to study how brokers’ characteristics and trading decisions may affect the stock market return. We present suggestive evidence of a mechanism by which structural changes of the transaction network between brokers affect the aggregate returns of the stock market. We find that brokers tend to trade with counterparties with dissimilar intraday selling volume when market return significantly increases. Moreover, brokers with a research department tend to sell to brokers without a research department when the market experiences a considerable increase of its return. From the financial perspective, these results highlight new ways in which intermediaries may affect market equilibrium and the efficiency of the market.