Broker Network Connectivity and the Cross-Section of Expected Returns

53 Pages Posted: 29 Jan 2021

See all articles by Murat Tiniç

Murat Tiniç

Kadir Has University

Ahmet Şensoy

Bilkent University

Muge Demir

Government of the Republic of Turkey - Banking Regulation and Supervision Agency (BDDK)

Duc Khuong Nguyen

IPAG Business School

Date Written: November 2, 2020

Abstract

This paper examines the relationship between broker network connectivity and stock returns in an order-driven market. Considering all stocks traded in Borsa Istanbul between January 2006 and November 2015, we estimate the monthly density, reciprocity and average weighted clustering coefficient as proxies for the broker network connectivity. Accordingly, firm-level cross-sectional regressions indicate a negative and significant predictive relationship between connectivity and one-month ahead stock returns. Specifically, 1% increase in network connectivity reduces the future returns by 2% even after controlling for other systematic factors. Our univariate and multivariate analyses show that stocks in the lowest connectivity quintile earn 1.0% - 1.6% monthly return premiums. We also document that the connectivity premium is stronger in terms of both economic and statistical significance for small size stocks.

Keywords: Stock market,trading networks,broker networks, network connectivity, pricing factors

JEL Classification: G11, G12, G14, G24

Suggested Citation

Tiniç, Murat and Şensoy, Ahmet and Demir, Muge and Nguyen, Duc Khuong, Broker Network Connectivity and the Cross-Section of Expected Returns (November 2, 2020). Available at SSRN: https://ssrn.com/abstract=3745720 or http://dx.doi.org/10.2139/ssrn.3745720

Murat Tiniç (Contact Author)

Kadir Has University ( email )

Istanbul
Turkey

Ahmet Şensoy

Bilkent University ( email )

06533 Bilkent, Ankara
Turkey

Muge Demir

Government of the Republic of Turkey - Banking Regulation and Supervision Agency (BDDK) ( email )

Ataturk Bulvari
No:191
Ankara, Ankara 06680
Turkey

Duc Khuong Nguyen

IPAG Business School ( email )

184 BD Saint Germain
Paris, 75006
France

HOME PAGE: http://www.ipag.fr/en/

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