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Priyank Gandhi

Researcher at Rutgers University

Publications -  30
Citations -  1054

Priyank Gandhi is an academic researcher from Rutgers University. The author has contributed to research in topics: Stock (geology) & Tail risk. The author has an hindex of 10, co-authored 27 publications receiving 914 citations. Previous affiliations of Priyank Gandhi include University of Notre Dame & University of California, Los Angeles.

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Journal ArticleDOI

Counterparty Credit Risk and the Credit Default Swap Market

TL;DR: In this paper, the authors examined how counterparty credit risk is actually priced in the CDS market and found that the magnitude of the effect is vanishingly small and is consistent with a market structure in which participants require collateralization of swap liabilities by counterparties.
Journal ArticleDOI

Counterparty credit risk and the credit default swap market

TL;DR: In this article, the authors examined how counterparty credit risk is actually priced in the CDS market and found that the effect of counterparty risk is vanishingly small and consistent with a market structure in which participants require collateralization of swap liabilities by counterparties.
Journal ArticleDOI

Size Anomalies in U.S. Bank Stock Returns

TL;DR: In this paper, the authors uncover a size factor in the component of bank returns that is orthogonal to the standard risk factors, including small minus big, which has the right covariance with bank returns to explain the average risk-adjusted returns.
Journal ArticleDOI

Size Anomalies in U.S. Bank Stock Returns

TL;DR: In this paper, the authors uncover a size factor in the component of bank returns that is orthogonal to the standard risk factors, including small-minus-big, which has the right covariance with bank returns to explain the average risk-adjusted returns.
Journal ArticleDOI

Using Annual Report Sentiment as a Proxy for Financial Distress in U.S. Banks

TL;DR: In this article, the authors argue that current measures of bank distress find marginal value in predictive variables beyond a capital adequacy ratio and tend to miss extreme events impacting the entire sector.