Cosearch Attention and Stock Return Predictability in Supply-Chains

Ashish Agarwal, Alvin Chung Man Leung, Prabhudev Konana, Alok Kumar (2017) Cosearch Attention and Stock Return Predictability in Supply Chains, Information Systems Research, DOI: doi/10.1287/isre.2016.0656 (Forthcoming)

60 Pages Posted: 30 Mar 2017

See all articles by Ashish Agarwal

Ashish Agarwal

University of Texas at Austin - Red McCombs School of Business

Alvin Leung

City University of Hong Kong (CityUHK) - Department of Information Systems

Prabhudev Konana

University of Texas at Austin - Department of Information, Risk and Operations Management

Alok Kumar

University of Miami - School of Business Administration

Date Written: March 1, 2016

Abstract

The ability to make predictions based on online searches in various contexts is gaining substantial interest in both research and practice. This study investigates a novel application of correlated online searches in predicting stock performance across supply chain partners. If two firms are economically dependent through a supply chain relationship and if information related to both firms diffuses in the market slowly or rapidly, then our ability to predict stock returns increases or decreases, respectively. We use online cosearches of stock as a proxy for the extent of information diffusion across supply chain-related firms. We identify publicly traded supply chain partners using Bloomberg data and construct cosearch networks of supply chain partners based on the weekly coviewing pattern of these firms on Yahoo! Finance. Our analyses show that the cosearch intensity across supply chain partners helps determine cross-return predictability. When investors of a focal stock pay less attention to its supply chain partners, we can use lagged partner returns to predict the future return of the focal stock. When investors’ coattention to focal and partner stocks is high, the predictability is low. Our simulated trading strategy using returns of supply chain partners with low coattention generates a significant and positive return above the market returns and performs better than the previously established trading strategy using returns of all supply chain partners.

Keywords: online search, correlated search, user attention, network analysis, stock returns, supply chain

Suggested Citation

Agarwal, Ashish and Leung, Alvin and Konana, Prabhudev and Kumar, Alok, Cosearch Attention and Stock Return Predictability in Supply-Chains (March 1, 2016). Ashish Agarwal, Alvin Chung Man Leung, Prabhudev Konana, Alok Kumar (2017) Cosearch Attention and Stock Return Predictability in Supply Chains, Information Systems Research, DOI: doi/10.1287/isre.2016.0656 (Forthcoming). Available at SSRN: https://ssrn.com/abstract=2941930

Ashish Agarwal

University of Texas at Austin - Red McCombs School of Business ( email )

Austin, TX 78712
United States

Alvin Leung (Contact Author)

City University of Hong Kong (CityUHK) - Department of Information Systems ( email )

83 Tat Chee Avenue
Kowloon
Hong Kong

Prabhudev Konana

University of Texas at Austin - Department of Information, Risk and Operations Management ( email )

CBA 5.202
Austin, TX 78712
United States

Alok Kumar

University of Miami - School of Business Administration ( email )

514 Jenkins Building
Department of Finance
Coral Gables, FL 33124-6552
United States
305-284-1882 (Phone)

HOME PAGE: http://moya.bus.miami.edu/~akumar

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