Abstract
Equity returns and firm’s default probability are strictly interrelated financial measures capturing the credit risk profile of a firm. Following the idea proposed in [20] we use high-frequency equity prices in order to estimate the volatility risk component of a firm within a structural credit risk modeling approach. Differently from [20] we consider a more general framework by introducing market microstructure noise as a direct effect of using noisy high-frequency data and propose the use of non-parametric estimation techniques in order to estimate equity volatility. We conduct a simulation analysis to compare the performance of different non-parametric volatility estimators in their capability of i) filtering out the market microstructure noise, ii) extracting the (unobservable) true underlying asset volatility level, iii) predicting default probabilities deriving from calibrating Merton [17] structural model.
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Barsotti, F., Sanfelici, S. (2014). Firm’s Volatility Risk Under Microstructure Noise. In: Corazza, M., Pizzi, C. (eds) Mathematical and Statistical Methods for Actuarial Sciences and Finance. Springer, Cham. https://doi.org/10.1007/978-3-319-02499-8_5
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DOI: https://doi.org/10.1007/978-3-319-02499-8_5
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02498-1
Online ISBN: 978-3-319-02499-8
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