In this paper, we suggest a deterministic approach for modelling credit risk time series even in distressed periods (including COVID-19). We examine the Moody's Seasoned Aaa Corporate Bond Yield Relative to Yield on 10-Year Treasury Constant Maturity as well as the ICE BofA US High Yield Index Option-Adjusted Spread and we find that the proposed model could fit well the alternation between periods of low and high volatility. This result is compared to the ARIMA-EGARCH model to determine how a chaotic deterministic model stands with respect to a stochastic model expressly designed for handling moving average, autoregression, cointegration and heteroscedastic volatility. According to recent literature, we find that both models give comparable results.

Modelling bursts and chaos regularization in credit risk with a deterministic nonlinear model

Orlando G.
Conceptualization
;
Bufalo M.
2021-01-01

Abstract

In this paper, we suggest a deterministic approach for modelling credit risk time series even in distressed periods (including COVID-19). We examine the Moody's Seasoned Aaa Corporate Bond Yield Relative to Yield on 10-Year Treasury Constant Maturity as well as the ICE BofA US High Yield Index Option-Adjusted Spread and we find that the proposed model could fit well the alternation between periods of low and high volatility. This result is compared to the ARIMA-EGARCH model to determine how a chaotic deterministic model stands with respect to a stochastic model expressly designed for handling moving average, autoregression, cointegration and heteroscedastic volatility. According to recent literature, we find that both models give comparable results.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11586/379396
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