Essays in Applied Financial Econometrics

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Date

2015

Authors

Liu, Lily Yanli

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Patton, Andrew J

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Abstract

This dissertation studies applied econometric problems in volatility estimation and CDS pricing. The first chapter studies estimation of loss given default from CDS spreads for U.S. corporates. This paper combines a term structure model of credit default swaps (CDS) with weak-identification robust methods to jointly estimate the probability of default and the loss given default of the underlying firm. The model is not globally identified because it forgoes parametric time series restrictions that have ensured identification in previous studies, but that are also difficult to verify in the data. The empirical results show that informative (small) confidence sets for loss given default are estimated for half of the firm-months in the sample, and most of these do not include the conventional value of 0.60. In addition, risk-neutral default probabilities, and hence risk premia on default probabilities, are underestimated when loss given default is exogenously fixed at the conventional value instead of estimated from the data.

The second chapter, which is joint work with Andrew Patton and Kevin Sheppard, studies the accuracy of a wide variety of estimators of asset price

variation constructed from high-frequency data (so-called "realized measures"), and compare them with a simple "realized variance" (RV) estimator. In total, we consider over 400 different estimators, applied to 11 years of data on 31 different financial assets spanning five asset classes, including equities, equity indices, exchange rates and interest rates. We apply data-based ranking methods to the realized measures and to forecasts based on these measures. When 5-minute RV is taken as the benchmark realized measure, we find little evidence that it is outperformed by any of the other measures. When using inference methods that do not require specifying a benchmark, we find some evidence that more sophisticated realized measures significantly outperform 5-minute RV. In forecasting applications, we find that a low frequency "truncated" RV

outperforms most other realized measures. Overall, we conclude that it is

difficult to significantly beat 5-minute RV for these assets.

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Citation

Liu, Lily Yanli (2015). Essays in Applied Financial Econometrics. Dissertation, Duke University. Retrieved from https://hdl.handle.net/10161/9837.

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