Clustering of percentage gross spreads and the avoidance of underwriter switching
PurposeBoth issuing firms and underwriters shall benefit from the associations in underwriting contracts for seasoned equity offerings (SEOs). Issuing firms that are offered underwriting contracts with clustered gross spreads do not have strong incentives to switch away from the firms' prior SE...
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Veröffentlicht in: | International Journal of Managerial Finance 2023-10, Vol.19 (5), p.1002-1023 |
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description | PurposeBoth issuing firms and underwriters shall benefit from the associations in underwriting contracts for seasoned equity offerings (SEOs). Issuing firms that are offered underwriting contracts with clustered gross spreads do not have strong incentives to switch away from the firms' prior SEO underwriters, and thus these existing underwriters are able to maintain or gain greater market share. This study investigates how the clustering of percentage gross spreads affects the likelihood of underwriter switching.Design/methodology/approachUsing the investment bank-underwritten SEOs in Hong Kong, the authors find that the percentage gross spreads of 40% of these SEOs are clustered at 2.5%. The seemingly unrelated bivariate probit model, Weibull survival mixed model and trivariate probit model are applied to analyse this phenomenon.FindingsThe authors' study provides first direct evidence that the clustering of percentage gross spreads lowers the likelihood of underwriter switching. Investment banks as underwriters can explicitly price underwriting contracts at a clustered level, more likely in periods of greater market volatility, and intentionally retain the banks' client firms using pricing arrangements. The authors' finding and approach offer more direct and distinct support that the issuer–underwriter association can be relationship-based.Originality/valueWhilst the clustering of fees is interpreted as a type of anticompetitive price sitting, the authors contribute to literature by providing new empirical evidence on why percentage gross spreads as a price dimension are clustered. On top of contract efficiency and collusion, this study's new evidence provides a third view for the clustering of gross spreads. |
doi_str_mv | 10.1108/IJMF-02-2022-0058 |
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Issuing firms that are offered underwriting contracts with clustered gross spreads do not have strong incentives to switch away from the firms' prior SEO underwriters, and thus these existing underwriters are able to maintain or gain greater market share. This study investigates how the clustering of percentage gross spreads affects the likelihood of underwriter switching.Design/methodology/approachUsing the investment bank-underwritten SEOs in Hong Kong, the authors find that the percentage gross spreads of 40% of these SEOs are clustered at 2.5%. The seemingly unrelated bivariate probit model, Weibull survival mixed model and trivariate probit model are applied to analyse this phenomenon.FindingsThe authors' study provides first direct evidence that the clustering of percentage gross spreads lowers the likelihood of underwriter switching. Investment banks as underwriters can explicitly price underwriting contracts at a clustered level, more likely in periods of greater market volatility, and intentionally retain the banks' client firms using pricing arrangements. The authors' finding and approach offer more direct and distinct support that the issuer–underwriter association can be relationship-based.Originality/valueWhilst the clustering of fees is interpreted as a type of anticompetitive price sitting, the authors contribute to literature by providing new empirical evidence on why percentage gross spreads as a price dimension are clustered. On top of contract efficiency and collusion, this study's new evidence provides a third view for the clustering of gross spreads.</description><identifier>ISSN: 1743-9132</identifier><identifier>EISSN: 1758-6569</identifier><identifier>DOI: 10.1108/IJMF-02-2022-0058</identifier><language>eng</language><publisher>Bradford: Emerald Group Publishing Limited</publisher><subject>Collusion ; Competition ; Equity ; Fees & charges ; Hypotheses ; Initial public offerings ; Investment banking ; Literature reviews ; Reputations ; Underwriting</subject><ispartof>International Journal of Managerial Finance, 2023-10, Vol.19 (5), p.1002-1023</ispartof><rights>Emerald Publishing Limited.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c323t-3cd0ddb8247c419a194aad83935b73aa4c78920f32f82a75dbec89c136dcb10d3</cites><orcidid>0000-0001-8978-4216</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,21694,27923,27924</link.rule.ids></links><search><creatorcontrib>Lee, Chin-Chong</creatorcontrib><title>Clustering of percentage gross spreads and the avoidance of underwriter switching</title><title>International Journal of Managerial Finance</title><description>PurposeBoth issuing firms and underwriters shall benefit from the associations in underwriting contracts for seasoned equity offerings (SEOs). Issuing firms that are offered underwriting contracts with clustered gross spreads do not have strong incentives to switch away from the firms' prior SEO underwriters, and thus these existing underwriters are able to maintain or gain greater market share. This study investigates how the clustering of percentage gross spreads affects the likelihood of underwriter switching.Design/methodology/approachUsing the investment bank-underwritten SEOs in Hong Kong, the authors find that the percentage gross spreads of 40% of these SEOs are clustered at 2.5%. The seemingly unrelated bivariate probit model, Weibull survival mixed model and trivariate probit model are applied to analyse this phenomenon.FindingsThe authors' study provides first direct evidence that the clustering of percentage gross spreads lowers the likelihood of underwriter switching. Investment banks as underwriters can explicitly price underwriting contracts at a clustered level, more likely in periods of greater market volatility, and intentionally retain the banks' client firms using pricing arrangements. The authors' finding and approach offer more direct and distinct support that the issuer–underwriter association can be relationship-based.Originality/valueWhilst the clustering of fees is interpreted as a type of anticompetitive price sitting, the authors contribute to literature by providing new empirical evidence on why percentage gross spreads as a price dimension are clustered. On top of contract efficiency and collusion, this study's new evidence provides a third view for the clustering of gross spreads.</description><subject>Collusion</subject><subject>Competition</subject><subject>Equity</subject><subject>Fees & charges</subject><subject>Hypotheses</subject><subject>Initial public offerings</subject><subject>Investment banking</subject><subject>Literature reviews</subject><subject>Reputations</subject><subject>Underwriting</subject><issn>1743-9132</issn><issn>1758-6569</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpFkM1KAzEURoMoWKsP4C7gOpq_mSRLKVYriggK7kImybRTamZMZiy-vQkVXN27-M53uQeAS4KvCcHyZvX4vESYIoopRRhX8gjMiKgkqqtaHZedM6QIo6fgLKUtxpzVHM_A62I3pdHHLqxh38LBR-vDaNYermOfEkxD9MYlaIKD48ZD8913zgTrS3oKzsd97DIP074b7SbXnIOT1uySv_ibc_C-vHtbPKCnl_vV4vYJWUbZiJh12LlGUi4sJ8oQxY1xkilWNYIZw62QiuKW0VZSIyrXeCuVJax2tiHYsTm4OvQOsf-afBr1tp9iyCc1lSK_KrmSOUUOKVveib7VQ-w-TfzRBOtiThdzGlNdzOliLjPwwHjbhy79E1KQqs7dH-wXjBdsmg</recordid><startdate>20231024</startdate><enddate>20231024</enddate><creator>Lee, Chin-Chong</creator><general>Emerald Group Publishing Limited</general><scope>OQ6</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>AFKRA</scope><scope>ANIOZ</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F~G</scope><scope>K6~</scope><scope>L.-</scope><scope>M0C</scope><scope>M1F</scope><scope>PQBIZ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0001-8978-4216</orcidid></search><sort><creationdate>20231024</creationdate><title>Clustering of percentage gross spreads and the avoidance of underwriter switching</title><author>Lee, Chin-Chong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c323t-3cd0ddb8247c419a194aad83935b73aa4c78920f32f82a75dbec89c136dcb10d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Collusion</topic><topic>Competition</topic><topic>Equity</topic><topic>Fees & charges</topic><topic>Hypotheses</topic><topic>Initial public offerings</topic><topic>Investment banking</topic><topic>Literature reviews</topic><topic>Reputations</topic><topic>Underwriting</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Chin-Chong</creatorcontrib><collection>ECONIS</collection><collection>CrossRef</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Accounting, Tax & Banking Collection</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Business Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Banking Information Database</collection><collection>ProQuest One Business</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>International Journal of Managerial Finance</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Chin-Chong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Clustering of percentage gross spreads and the avoidance of underwriter switching</atitle><jtitle>International Journal of Managerial Finance</jtitle><date>2023-10-24</date><risdate>2023</risdate><volume>19</volume><issue>5</issue><spage>1002</spage><epage>1023</epage><pages>1002-1023</pages><issn>1743-9132</issn><eissn>1758-6569</eissn><abstract>PurposeBoth issuing firms and underwriters shall benefit from the associations in underwriting contracts for seasoned equity offerings (SEOs). Issuing firms that are offered underwriting contracts with clustered gross spreads do not have strong incentives to switch away from the firms' prior SEO underwriters, and thus these existing underwriters are able to maintain or gain greater market share. This study investigates how the clustering of percentage gross spreads affects the likelihood of underwriter switching.Design/methodology/approachUsing the investment bank-underwritten SEOs in Hong Kong, the authors find that the percentage gross spreads of 40% of these SEOs are clustered at 2.5%. The seemingly unrelated bivariate probit model, Weibull survival mixed model and trivariate probit model are applied to analyse this phenomenon.FindingsThe authors' study provides first direct evidence that the clustering of percentage gross spreads lowers the likelihood of underwriter switching. Investment banks as underwriters can explicitly price underwriting contracts at a clustered level, more likely in periods of greater market volatility, and intentionally retain the banks' client firms using pricing arrangements. The authors' finding and approach offer more direct and distinct support that the issuer–underwriter association can be relationship-based.Originality/valueWhilst the clustering of fees is interpreted as a type of anticompetitive price sitting, the authors contribute to literature by providing new empirical evidence on why percentage gross spreads as a price dimension are clustered. On top of contract efficiency and collusion, this study's new evidence provides a third view for the clustering of gross spreads.</abstract><cop>Bradford</cop><pub>Emerald Group Publishing Limited</pub><doi>10.1108/IJMF-02-2022-0058</doi><tpages>22</tpages><orcidid>https://orcid.org/0000-0001-8978-4216</orcidid></addata></record> |
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subjects | Collusion Competition Equity Fees & charges Hypotheses Initial public offerings Investment banking Literature reviews Reputations Underwriting |
title | Clustering of percentage gross spreads and the avoidance of underwriter switching |
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