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Essays in tail risk and asset pricing in credit markets

Fellmann, Reinhard (2021) Essays in tail risk and asset pricing in credit markets. PhD thesis, London School of Economics and Political Science.

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Identification Number: 10.21953/lse.00004404


A measure of tail risk in credit markets is essential to understand the behaviour of credit default swap prices. This thesis presents three tail-risk measures based on dynamic power-law models with multiple time-varying tail parameters. The models use univariate and crosssectional returns of sovereign and corporate credit default swaps to estimate the tail risk at each point of time. The power-law is considered a plausible statistical hypothesis for the tail distribution of returns and measure of tail risk in credit markets. The dynamic power-law exponent is time-varying and persistent. The tail exponent series for 35 European sovereign credit default swaps vary around the mean of 3.0, consistent with the inverse cubic law in other asset classes. Tests show that past exposure to extreme event risk significantly impacts future credit default swap prices and returns. A one-standard-deviation increase in tail risk forecasts an average increase in sovereign credit default swap spreads of 7.6 bps in US credit markets, which is highly significant. These results are robust out-of-sample. The forecasting power of tail risk is also robust to controlling for 25 alternative predictors. Furthermore, tail risk has substantial explanatory power for the cross-section of expected returns in US corporate credit default swaps. Cross-sectionally, firms with high positive loadings on past tail risk earn average expected annual returns 8.1% higher than credit default swaps with low tail risk covariation. Protection sellers increase spreads for credit default swaps bearing high sensitivity to tail risk. This tail risk premium is different from the premiums on market risk, idiosyncratic volatility and coskewness, and robust to considering alternative risk factors. These findings are consistent with asset pricing models that relate tail risk to expected returns and risk premiums.

Item Type: Thesis (PhD)
Additional Information: © 2021 Reinhard Fellmann
Library of Congress subject classification: H Social Sciences > HD Industries. Land use. Labor > HD61 Risk Management
H Social Sciences > HG Finance
Q Science > Q Science (General)
Sets: Departments > Statistics
Supervisor: Baurdoux, Erik and Vedolin, Andrea

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