Electronic Theses and Dissertations

Wei Sun

Date

2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Business Administration

Committee Chair

Ronald Spahr

Committee Member

Mark Sunderman

Committee Member

Pankaj Jain

Committee Member

David Kemme

Committee Member

Sabatino Silveri

Abstract

Essay 1: We introduce and analyze a new intraday measure of trade-time clustering which we demonstrate to be superior to volume and duration at detecting periodic grouping of trades. In stable markets, both elevated information flow and lower trading costs lead to greater trade-time clustering, while in volatile markets only lower trading costs lead to greater time clustering. Trade-time clustering is positively associated with contemporaneous price impact, price volatility, and negatively associated with variance ratios, suggesting that trade clustering contributes to price discovery. Following increased time clustering, we observe more aggressive orders from informed traders, but less HFT in stable markets.Essay 2: We investigate the impact of inter-firm connections on alliances. We find that both professional connections and social connections, borne out of board interlocks, employment ties and educational ties, increase the likelihood of alliance formation. In addition, the market reacts more favorably to alliance announcements in the presence of such connections and this positive valuation effect increases with the degree of information asymmetry between the partner firms. Our findings are consistent with inter-firm connections creating value because they facilitate the flow of information between partner firms, thereby reducing moral hazard concerns and the risk of ex-post opportunistic behavior.Essay 3: We identify real and social costs associated with neighborhood blight by creating unique neighborhood blight indices based on average individual property blight scores in Memphis, Tennessee. Both individual property blight scores and neighborhood blight indices negatively impact single-family sale prices and assessed valuations. We validate the data accuracy of a 2016 blight survey, finding that supplemental information collected for each property accurately predicts its assigned blight score. We apply factor analysis, Shapley-Owen decomposition, and hedonic regressions to identify blight drivers that include neighborhood demographic and economic factors associated with both individual property and neighborhood blight. A comparative residual test finds that blight scores provide informational value in addition to county assessor and data for each property and census data for each neighborhood. We quantify neighborhood characteristics and demographic factors impacting both individual property and neighborhood blight effects on neighborhood esthetics and property values that helps identify blight resolution alternatives.

Comments

Data is provided by the student.

Library Comment

Dissertation or thesis originally submitted to ProQuest

Notes

Open Access

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