CINECA IRIS Institutional Research Information System
IRIS è la soluzione IT che facilita la raccolta e la gestione dei dati relativi alle attività e ai prodotti della ricerca. Fornisce a ricercatori, amministratori e valutatori gli strumenti per monitorare i risultati della ricerca, aumentarne la visibilità e allocare in modo efficace le risorse disponibili.
EnglishDefault probability is a fundamental variable determining the credit worthiness of a firm and equity volatility estimation plays a key role in its evaluation. Assuming a structural credit risk modeling approach, we study the effects on the default probability evaluation of choosing different non parametric equity volatility estimators, when market microstructure noise is taken into account. A general stochastic volatility framework with jumps for the underlying assets dynamics is defined by considering a Merton-like structural model with firm's asset evolution described by Bates [8] model. In order to estimate the volatility risk component of a firm, we follow the idea in [28] and use high-frequency equity prices, but differently from [28] we consider a more general framework where microstructure noise is introduced as direct effect of observing noisy high-frequency equity prices. A Monte Carlo simulation analysis is conducted to i) analyze the performance of alternative non-parametric equity volatility estimators in their capability of filtering out the microstructure noise and backing out the true unobservable asset volatility, ii) study the effects of different non-parametric estimation techniques on default probability evaluation.
Firm Volatility Risk and Default Probability Estimation under Market Microstructure Effects, Working Paper / Flavia Barsotti; Maria Elvira Mancino; Simona Sanfelici. - (2014), pp. 1-19.
| Titolo: | Firm Volatility Risk and Default Probability Estimation under Market Microstructure Effects, Working Paper | |
| Autori: | ||
| Data di pubblicazione: | 2014 | |
| Citazione: | Firm Volatility Risk and Default Probability Estimation under Market Microstructure Effects, Working Paper / Flavia Barsotti; Maria Elvira Mancino; Simona Sanfelici. - (2014), pp. 1-19. | |
| Abstract: | Default probability is a fundamental variable determining the credit worthiness of a firm and equity volatility estimation plays a key role in its evaluation. Assuming a structural credit risk modeling approach, we study the effects on the default probability evaluation of choosing different non parametric equity volatility estimators, when market microstructure noise is taken into account. A general stochastic volatility framework with jumps for the underlying assets dynamics is defined by considering a Merton-like structural model with firm's asset evolution described by Bates [8] model. In order to estimate the volatility risk component of a firm, we follow the idea in [28] and use high-frequency equity prices, but differently from [28] we consider a more general framework where microstructure noise is introduced as direct effect of observing noisy high-frequency equity prices. A Monte Carlo simulation analysis is conducted to i) analyze the performance of alternative non-parametric equity volatility estimators in their capability of filtering out the microstructure noise and backing out the true unobservable asset volatility, ii) study the effects of different non-parametric estimation techniques on default probability evaluation. | |
| Handle: | http://hdl.handle.net/11381/2761130 | |
| Appare nelle tipologie: | 7.12 Altro |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| BarsottiMancinoSanfelici_Sept14.pdf | Documento in Pre-print | NON PUBBLICO - Accesso privato/ristretto | Administrator Richiedi una copia |
Copyright © 2021