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

Giuseppe Orlando and Michele Bufalo

Finance Research Letters, 2022, vol. 47, issue PA

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.

Keywords: Rulkov map; Credit risk; Chaos; COVID-19; ARIMA; GARCH (search for similar items in EconPapers)
JEL-codes: C01 C02 C6 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finlet:v:47:y:2022:i:pa:s1544612321004888

DOI: 10.1016/j.frl.2021.102599

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