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Studies in debt valuation adjustments

Research output: ThesisDoctoral Thesis

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Studies in debt valuation adjustments. / Lin, Wen.

Lancaster University, 2021. 147 p.

Research output: ThesisDoctoral Thesis

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Lin, Wen. / Studies in debt valuation adjustments. Lancaster University, 2021. 147 p.

Bibtex

@phdthesis{896658036c4044359c23858a6ccfef28,
title = "Studies in debt valuation adjustments",
abstract = "This thesis consists of two self-contained studies in Debt Valuation Adjustments(DVAs). The first study is motivated by the debate about the introduction of theFair Value Option for financial Liabilities (FVOL) and the requirement to recognize and separately disclose DVAs in financial statements. This study investigates what we can learn regarding own credit risk from DVAs. Using a sample of U.S. bank holding companies that adopt the FVOL, we show that DVAs generally cannot be explained by the same factors that explain contemporaneous changes in the credit quality of these institutions. These results may be driven by the opportunistic use of the FVOL or the superior ability of managers to estimate own credit risk. Further tests indicate that DVAs for fair value Level 3 reporters can explain future changes in credit risk, providing support for the latter explanation.The second study compares the reported Debt Valuation Adjustments provided by managers with the estimated DVAs based on market information. To obtain the estimated DVAs we use two structural credit risk models: the Merton (1974) model and the Leland (1994) model. We find that the private information contained in the reported DVAs causes a significant deviation of the estimated DVAs from the reported DVAs. This deviation is more pronounced for the banks with high volatile creditworthiness and gets better for the banks with stable credit standing. Findings suggest that the reported DVAs reflect more private information on credit risk when the economy is volatile rather than stable. In addition, the comparison of estimation errors shows that the Merton model outperforms the Leland model with regard to the estimation of DVAs over the sample period, suggesting that the incorporation of additional information in structural models does not improve the performance of pricing DVAs.",
author = "Wen Lin",
year = "2021",
doi = "10.17635/lancaster/thesis/1336",
language = "English",
publisher = "Lancaster University",
school = "Lancaster University",

}

RIS

TY - THES

T1 - Studies in debt valuation adjustments

AU - Lin, Wen

PY - 2021

Y1 - 2021

N2 - This thesis consists of two self-contained studies in Debt Valuation Adjustments(DVAs). The first study is motivated by the debate about the introduction of theFair Value Option for financial Liabilities (FVOL) and the requirement to recognize and separately disclose DVAs in financial statements. This study investigates what we can learn regarding own credit risk from DVAs. Using a sample of U.S. bank holding companies that adopt the FVOL, we show that DVAs generally cannot be explained by the same factors that explain contemporaneous changes in the credit quality of these institutions. These results may be driven by the opportunistic use of the FVOL or the superior ability of managers to estimate own credit risk. Further tests indicate that DVAs for fair value Level 3 reporters can explain future changes in credit risk, providing support for the latter explanation.The second study compares the reported Debt Valuation Adjustments provided by managers with the estimated DVAs based on market information. To obtain the estimated DVAs we use two structural credit risk models: the Merton (1974) model and the Leland (1994) model. We find that the private information contained in the reported DVAs causes a significant deviation of the estimated DVAs from the reported DVAs. This deviation is more pronounced for the banks with high volatile creditworthiness and gets better for the banks with stable credit standing. Findings suggest that the reported DVAs reflect more private information on credit risk when the economy is volatile rather than stable. In addition, the comparison of estimation errors shows that the Merton model outperforms the Leland model with regard to the estimation of DVAs over the sample period, suggesting that the incorporation of additional information in structural models does not improve the performance of pricing DVAs.

AB - This thesis consists of two self-contained studies in Debt Valuation Adjustments(DVAs). The first study is motivated by the debate about the introduction of theFair Value Option for financial Liabilities (FVOL) and the requirement to recognize and separately disclose DVAs in financial statements. This study investigates what we can learn regarding own credit risk from DVAs. Using a sample of U.S. bank holding companies that adopt the FVOL, we show that DVAs generally cannot be explained by the same factors that explain contemporaneous changes in the credit quality of these institutions. These results may be driven by the opportunistic use of the FVOL or the superior ability of managers to estimate own credit risk. Further tests indicate that DVAs for fair value Level 3 reporters can explain future changes in credit risk, providing support for the latter explanation.The second study compares the reported Debt Valuation Adjustments provided by managers with the estimated DVAs based on market information. To obtain the estimated DVAs we use two structural credit risk models: the Merton (1974) model and the Leland (1994) model. We find that the private information contained in the reported DVAs causes a significant deviation of the estimated DVAs from the reported DVAs. This deviation is more pronounced for the banks with high volatile creditworthiness and gets better for the banks with stable credit standing. Findings suggest that the reported DVAs reflect more private information on credit risk when the economy is volatile rather than stable. In addition, the comparison of estimation errors shows that the Merton model outperforms the Leland model with regard to the estimation of DVAs over the sample period, suggesting that the incorporation of additional information in structural models does not improve the performance of pricing DVAs.

U2 - 10.17635/lancaster/thesis/1336

DO - 10.17635/lancaster/thesis/1336

M3 - Doctoral Thesis

PB - Lancaster University

ER -