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Political Connection, Corruption, and Demand-Driven Stock Returns

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Abstract

I examine how firm-level political connections impact stock returns through institutional demand. I find that demand shifts by mutual funds significantly contribute to the decline in concurrent stock returns: mutual funds generally reduce holdings of stocks with higher political connections, especially those headquartered in provinces with elevated corruption indices, following the 2012 Chinese anti-corruption campaign announcement. Overall, while political connections have an insignificant direct effect on stock returns as an additional pricing factor, they significantly and negatively impact stock returns through the fund demand channel. Under a characteristic-based demand asset pricing framework, I further investigate the aggregate price impact for stocks with different political connections. I show that stocks with stronger political connections experience greater price impacts, particularly among the least liquid stocks and around the announcement of the 2012 anti-corruption campaign. This demand-based approach offers a novel perspective to understand the decrease in stock returns, isolates the effects of political connections from those of corruption, and emphasizes the demand-side effects on increased volatility during periods marked by unexpected political events.

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  • Chunxiao Lu, 2025. "Political Connection, Corruption, and Demand-Driven Stock Returns," Working Papers in Economics 25/15, University of Canterbury, Department of Economics and Finance.
    • Handle: RePEc:cbt:econwp:25/15
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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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